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Diagnostics and Therapeutic Advances in GI Malignancies
Series Editor: Ganji Purnachandra Nagaraju
Ramakrishna Vadde
Ganji Purnachandra Nagaraju Editors
Immunotherapy
for
Gastrointestinal
Malignancies
Diagnostics and Therapeutic Advances
in GI Malignancies
Series Editor
Ganji Purnachandra Nagaraju, Emory University School of Medicine, Atlanta, GA,
USA
Editorial Board Members

Sarfraz Ahmad, Advent Health Cancer Institute, Orlando, FL, USA
Dinakara Rao Ampasala, Centre for Bioinformatics, Pondicherry University,
Puducherry, Pondicherry, India
Sujatha Peela, Collège of Science, Dr. B.R. Ambdekar University, Srikakulam,
Andhra Pradesh, India
Riyaz Basha, University of North Texas Health Science, Fort Worth, TX, USA
Ramakrishna Vadde, Dept Biotechnology & Bioinformatics, Yogi Vemana Univer-
sity, Kadapa, Andhra Pradesh, India
Bindu Madhava Reddy Aramati, School of Life Sciences, University of Hyderabad,
Hyderabad, Telangana, India
This series will highlight the recent innovations in the diagnostics and therapeutic
strategies for different Gastrointestinal (GI) cancers.
Gastrointestinal cancers are a group of cancers that affect the digestive system and
include gastric cancer, colorectal cancer, liver cancer, esophageal cancer, and pan-
creatic cancer. GI cancers are the leading health problem in the world and their
burden is increasing in many countries. This heavy burden is due to the lack of
effective early detection methods and to the emergence of chemoradioresistance.
Attempts at improving the outcome of GI cancers by incorporating cytotoxic agents
such as chemo drugs have been so far disappointing. These results indicate that the
main challenge remains in the primary resistance of GI cancer cells to chemotherapy
in the majority of patients. Therefore, improvement in the outcomes of these
malignancies is dependent on the introduction of new agents that can modulate the
intrinsic and acquired mechanisms of resistance.
The increased understanding of the biology, metabolism, genetic, epigenetic, and
molecular pathways dysregulated in GI cancers has revealed the complexity of the
mechanisms implicated in tumor development. These include alterations in the
expression of key oncogenic or tumor suppressive miRNAs, modifications in meth-
ylation patterns, the upregulation of key oncogenic kinases, etc.
The individual books in this series will focus on the genetic basis of each
gastrointestinal cancers, molecular pathophysiology, and different biomarkers to
estimate cancer risk, detection of cancer at microscopic dimensions, and suitable
and effectiveness of the therapies. In addition, the volumes will discuss the role of
various signaling molecules/pathways and transcriptional factors in the regulation of
the tumor microenvironment and effect on the tumor growth.
Lastly, it will elaborate the use of molecularly targeted drugs that have been
proven to be effective for the treatment of GI cancers, with a focus on the emerging
strategies.
This edition will provide researchers and physicians with novel ideas and per-
spectives for future research that translates the bench to the bedside.
More information about this series at http://www.springer.com/series/16343

Ramakrishna Vadde •
Ganji Purnachandra Nagaraju
Editors
Immunotherapy for
Gastrointestinal Malignancies
Editors
Ramakrishna Vadde Ganji Purnachandra Nagaraju
Department Biotechnology & Winship Cancer Institute
Bioinformatics Emory University School of Medicine
Yogi Vemana University Atlanta, GA, USA
Kadapa, Andhra Pradesh, India
ISSN 2662-2688 ISSN 2662-2696 (electronic)

Diagnostics and Therapeutic Advances in GI Malignancies
ISBN 978-981-15-6486-4 ISBN 978-981-15-6487-1 (eBook)
https://doi.org/10.1007/978-981-15-6487-1
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore
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Preface
Gastrointestinal malignancies are the most common cancers diagnosed worldwide,

with increasing incidence and mortality rate every year. The traditional therapeutic
strategies that include surgery, chemotherapy, and radiotherapy are found effective.
However, the prognosis percentage always remains poor. Therefore, novel
approaches for gastrointestinal malignancies therapy are essential. Immunotherapy
is a novel therapeutic strategy at present and it could be a better therapeutic option
for cancer.
Immunological therapy was carried out for the first time by Coley in the year
1891, against a malignant patient using a bacterial immunotoxin. Burnet in the year
1970, presented the concept of immunological surveillance and van der Bruggen
et al. in the year 1991 finally reported cytolytic T lymphocytes recognizing antigen
on human melanoma. This field of immunology progressed highly with the discov-
ery of novel immune-based targets that are based on understanding the tumor
microenvironment and tumor immunology. Varied types of immunomodulatory
treatments including dendritic cell vaccines, IL-2 activated lymphocytes, tumor-
associated antigen-derived peptides, and tumor-specific reactive CD8+ T lympho-
cytes are demonstrated for the therapy of gastrointestinal malignancies. However,
the confidence of immunotherapy is built only with the initiation of immune
checkpoint inhibitors and was widely encouraged as the “Breakthrough of the year
2013” by Science. Thus, immunotherapy is the current mainstream for gastrointes-
tinal malignancies.
This book focuses on the novel immunotherapeutic strategies including immune
checkpoint inhibitors, peptide vaccines, and adoptive cell transfer therapy against
gastrointestinal malignancies including esophageal cancer, gastric cancer, and colo-
rectal cancer. The authors in the book summarized types and drivers for heteroge-
neity in respect to their biological and clinical importance with respect to tumor
evolution. This knowledge will allow to understand heterogeneity in determining the
cause for cancer patients not responding to the therapy. The book also clarifies about
the cytokines involved in gastrointestinal malignancy therapy and application with
the review of meta-analysis to determine the association between gene
vii
viii Preface
polymorphism and predicting the risk for the cause of cancer. It will also focus on the
immunomarkers that play a crucial role in predicting the malignant behavior of the
cancer cells and help clinicians for early diagnosis and employing them as thera-
peutic targets for therapy of gastrointestinal malignancies. Lastly, the book explores
the diverse facts of computational biology for the diagnosis and therapy of gastro-
intestinal malignancies. Finally, it explores how these novel advances integrate into
a precision and personalized medicine approach that eventually enhances
patient care.
It is our pleasure to present this comprehensive summary of novel fields to the
science community for a better understanding of the future advances in the field of
immunotherapeutic application toward gastrointestinal malignancies. We hope this
book reflects the novel research ideas for better innovation and ultimate benefit to
patients and their families.
Kadapa, Andhra Pradesh, India Ramakrishna Vadde

Atlanta, GA, USA Ganji Purnachandra Nagaraju
Contents
1 Tumor Heterogeneity: Challenges and Perspectives for

Gastrointestinal Cancer Therapy . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Manoj Kumar Gupta, Gayatri Gouda, Ravindra Donde,
and Ramakrishna Vadde
2 Immunocomposition of Gastrointestinal Tract of Gut . . . . . . . . . . . 17
Mekapogu Madakka, Nambi Rajesh, and Jinka Rajeswari
3 Immunomarkers for Detection of GI Malignancies . . . . . . . . . . . . . 41
Ravikiran Tekupalli, Santosh Anand, Sowbhagya Ramachandregowda,
Anupama Sindhghatta Kariyappa, and Bhagyalakshmi Dundaiah
4 Immunotherapeutics of Gastrointestinal Malignancies . . . . . . . . . . 51
Nakka Venkata Prasuja
5 Immune Cell Therapy Against Gastrointestinal Tract Cancers . . . . 61
Ravindra Donde, Manoj Kumar Gupta, Gayatri Gouda,
Sushanta Kumar Dash, Lambodar Behera, and Ramakrishna Vadde
6 Immune Checkpoint Inhibitors in Gastrointestinal Malignancies . . . 79
Padmaraju Vasudevaraju and Malla Rama Rao
7 Monoclonal Antibody Therapy Against Gastrointestinal Tract
Cancers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
Gayatri Gouda, Manoj Kumar Gupta, Ravindra Donde,
Lambodar Behera, and Ramakrishna Vadde
8 Therapeutic Vaccines for Gastrointestinal Malignancies . . . . . . . . . 113
Bonala Sabeerabi, Venkat R. Arva Tatireddygari,
9 Immuno-Oncology of Oesophageal Cancer . . . . . . . . . . . . . . . . . . . 159
Bindu Prasuna Aloor and Senthilkumar Rajagopal
ix
x Contents
10 Association Between IL6 Gene Polymorphisms and Gastric Cancer

Risk: A Meta-Analysis of Case-Control Studies . . . . . . . . . . . . . . . . 171
Henu Kumar Verma, Neha Merchant, and L. V. K. S. Bhaskar
11 Immuno-Oncology of Colorectal Cancer . . . . . . . . . . . . . . . . . . . . . 183
Ramachandra Reddy Pamuru, K. V. Sucharitha,
12 Immune Targets in Colorectal Cancer . . . . . . . . . . . . . . . . . . . . . . . 205
Begum Dariya and Ganji Purnachandra Nagaraju
13 Applications of Computational Biology in Gastrointestinal
Malignancies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231
Manoj Kumar Gupta and Ramakrishna Vadde
About the Editors
Ramakrishna Vadde is an Assistant Professor at the

Department of Biotechnology and Bioinformatics, Yogi
Vemana University, India. He obtained his MSc and
PhD, both in Biochemistry, from Sri Krishnadevaraya
University, Anantapur, India, and subsequently received
a DBT CREST Award to pursue advanced training in
cancer research at Pennsylvania State University and
Colorado State University, USA. He is currently using
in vitro, in vivo and in silico models to explore the role
of dietary bioactive compounds in both the development
and prevention of cancer through a ‘polypharmacology’
approach. He has published over 80 research papers in
prominent international journals and has presented more
than 50 papers at national and international conferences.
He serves as an editorial board member for several
international journals, and is an Associate Fellow of
Andhra Pradesh Akademi of Sciences.
Ganji Purnachandra Nagaraju is a faculty member at

the Department of Hematology and Medical Oncology,
Winship Cancer Institute, Emory University School of
Medicine. Holding a DSc from Berhampur University in
Berhampur, India, his research focuses on translational
projects concerning gastrointestinal malignancies. He
has published over 100 research papers in prominent
international journals and has presented more than
50 papers at national and international conferences. Dr
Nagaraju is the author and editor of several books and
xi
xii About the Editors
serves as an editorial board member for numerous aca-

demic journals. He is an associate member of the Dis-
covery and Developmental Therapeutics Research
Program at Winship Cancer Institute, and has received
several international awards for his contributions.
Chapter 1
Tumor Heterogeneity: Challenges
and Perspectives for Gastrointestinal
Cancer Therapy
Manoj Kumar Gupta, Gayatri Gouda, Ravindra Donde,

Abstract Cancer is clinically characterized via the uncontrolled proliferation of

cells. Several studies have reported that tumor heterogeneity is the main reason for
the low treatment response rate in cancer patients. Thus, there is always a quest to
understand the tumor heterogeneity in any cancer type. In this chapter, the authors
attempted to understand the types and drivers for tumor heterogeneity, especially in
gastrointestinal cancers, and discussed their biological as well as clinical importance
with respect to tumor evolution. Obtained information revealed that tumor hetero-
geneity can be either at inter- (amongst diverse tumors from diverse patients or
within the same patients) or intra- (amongst diverse cells in the same tumor) level.
Nevertheless, the main reason for inter-tumor heterogeneity is the intra-tumor
heterogeneity. To understand this heterogeneity various high throughput sequencing
approaches, for instance, single-cell RNA sequencing, and models, for instance, the
“Clonal evolution” model and “big bang” model, have been developed to date.
However, the complete mechanism associated with tumor heterogeneity remains
elusive to date. Authors believe that by integrating information obtained from
various disciplines, including pathology, clinical-radiology, genetic and molecular
biology, we can unravel the mechanism comprehensively associated with tumor
heterogeneity. In the near future, the information present in this chapter will be
highly useful for the early detection and prevention of gastrointestinal cancer in
humans.
Keywords Cancer · Heterogeneity · Clonal evolution model · Cancer stem cell

model · Tumor
M. K. Gupta · R. Vadde (*)

Department of Biotechnology and Bioinformatics, Yogi Vemana University, Kadapa, Andhra
Pradesh, India
G. Gouda · R. Donde
ICAR-National Rice Research Institute, Cuttack, Odisha, India
© The Editor(s) (if applicable) and The Author(s), under exclusive license to 1
Springer Nature Singapore Pte Ltd. 2020
R. Vadde, G. P. Nagaraju (eds.), Immunotherapy for Gastrointestinal Malignancies,
Diagnostics and Therapeutic Advances in GI Malignancies,
https://doi.org/10.1007/978-981-15-6487-1_1
2 M. K. Gupta et al.
1.1 Introduction
Recent advancements in high throughput sequencing technologies have provided us

an extraordinary insight into the cancer genome and its evolution (Jamal-Hanjani
et al. 2015; Gupta et al. 2017, 2019a; Gupta and Vadde 2019a). Cancer is clinically
characterized via the uncontrolled proliferation of cells, which is often referred to as
a tumor. As cancer can develop from any cell type, there are more than 100 cancer
forms, including gastrointestinal (GI) cancer (Cooper 2000). A tumor may be either
benign or malignant. A benign tumor remains restrained to its site of origin and
neither invades nearby normal tissue nor disperses to distal body sites. On the
contrary, malignant tumor invades nearby normal tissue as well as dispersed
throughout the body either via the lymphatic or via circulatory systems. While
benign tumors can be removed surgically; malignant tumors are often hard for
treatment due to their metastatic nature (Cooper 2000; Gupta et al. 2017, 2019b).
Earlier studies have suggested that benign tumor converts into malignant form
through series of events, i.e., avoidance of cell death and growth suppression related
signals and angiogenesis stimulation, which in turn activates nearby tissue invasion
as well as metastasis. Thus, the stochastic nature of cancer suggests that cancer
initiation and formation do not follow a fixed path but rather a complex mechanism
comprised of numerous critical cellular process. Even after attaining the metastatic
phase, it remains active and evolves continuously. This ongoing evolution might
produce heterogeneous tumors composed of distinct cancer cells with a unique
molecular signature which respond distinctly with anti-cancer therapies (Dagogo-
Jack and Shaw 2018). Thus, tumor heterogeneity is the main reason for the low
treatment response rate in cancer patients. Additionally, the presence of specific
traits, for instance, point mutations responsible for enhancing drug resistance, is
high. Thus, intra-tumor heterogeneity is like an “arsenal” that shields cancer against
cancer therapies. Nevertheless, the environment of this arsenal changes continuously
due to the aggregation of novel mutations. Besides this, the non-cancerous cell in
tumor and nearby tissue is also changing continuously, which augments diversifica-
tion in the arsenal, thereby making the situation more tough for anti-cancer therapies
(Janiszewska 2020). Thus, it is highly required to exploit and understand the tumor
at the cellular level. Considering this, in this chapter, we summarized the types and
drivers for tumor heterogeneity especially in gastrointestinal cancer and discussed
their biological as well as clinical importance with respect to tumor evolution. In the
near future, the information present in this chapter will be highly useful for the early
detection and prevention of gastrointestinal cancer in humans.
1 Tumor Heterogeneity: Challenges and Perspectives for Gastrointestinal Cancer. . . 3
1.2 Heterogeneity Type
Heterogeneity is a Greek word, which means “different kinds,” thereby representing

a dissimilar mass composition instead of a uniform mass. Tumor heterogeneity may
be either inter-tumor (amongst diverse tumors from diverse patients or within the
same patients) or intra-tumor (amongst diverse cells in the same tumor) (Liu et al.
2018; Lin and Lin 2019).
1.2.1 Inter-Tumor Heterogeneity
Inter-tumor heterogeneity refers to the alteration in the phenotype as well as geno-

type within different or same cancer patients that are induced via various environ-
mental as well as etiological factors (Liu et al. 2018). In 2003, Ribic and the team
suggested that fluorouracil-based adjuvant chemotherapy enables early detection of
stage II and stage III colon carcinoma with microsatellite-stable tumors and tumors
displaying low-frequency microsatellite instability, respectively. However, it fails to
detect tumors displaying high-frequency microsatellite instability (Ribic et al. 2003).
This was plausibly the first inter-tumor heterogeneity that was clearly applicable to
clinicians in practice (Liu et al. 2018). Since then, cancer has been classified into
numerous subtypes using different markers, for instance, in lung cancer (e.g., ALK
fusion+ and EGFR+), gastric cancer (e.g., microsatellite unstable and Epstein–Barr
virus+), and breast cancer (e.g., basal-like, luminal, and Her2+). Irrespective of all
significant findings, detailed insight into inter-tumoral heterogeneity in several
cancer forms remains elusive to date (Liu et al. 2018).
Recently, in 2017, The Cancer Genome Atlas (TCGA) consortium categorized
90 esophageal squamous cell carcinoma (ESCC) specimens into three subgroups,
namely, ESCC1–3 (Cancer Genome Atlas Research Network et al. 2017). ESCC1
and ESCC3 mainly belong to Asian and North America samples, respectively.
ESCC2 belongs to Eastern European and South American samples. ESCC1 harbors
modification in the NRF2 pathway (KEAP1, NFE2L2, ATG7, and CUL3) and SOX2
and/or TP63 amplification. ESCC2 is clinically characterized via enhanced rates of
ZNF750N and NOTCH1 mutations, KDM2D, PIK3R1, KDM6A, and PTEN inacti-
vation, and CDK6 amplification. Because of the small population size, no definitive
clinical features have been established with ESCC3 (Liu et al. 2018). In the same
study, it was stated that gastric cancer (GC) heterogeneity has a negative impact on
the response to therapies directed to FGFR, EGFR, and HER2, and possibly to
CCND1 and MYC. It also proposed four GC subtypes with (1) microsatellite insta-
bility (MSI-high), (2) chromosomal instability (CIN), (3) Epstein–Barr infection
(EBV+), and (4) genomic stability (GS). EBV + GC (EBVaGC) demonstrates a
distinct profile recognized in various studies and well established in Asian and
Western populations. The key feature of this subtype is the proximal location,
male predominance, CDKN2A (p16) promoter hyper-methylation, and extreme
CpG island methylator phenotype, mutation of PIK3CA, ARID1A, and BCOR, and
PD-L1, JAK2, and PD-L2 amplification (Alsina et al. 2017). Another study reported
that mutations in ARID1A are more common in the Epstein–Barr virus-infected and
microsatellite instability types of gastric cancer (Wang et al. 2011). In 2012, Zang
and the team observed recurrent mutations in PIK3CA, TP53, and ARID1A within
15 gastric cancer samples. They also reported genetic abnormalities within the
chromatin remodeling genes, namely, MLL3, MLL, and ARID1A, and the
E-cadherin family gene, namely, FAT4, amongst 110 gastric cancer samples. Inac-
tivation of ARID1A and FAT4 was found to be associated with malignant character-
istics of gastric cancer, for instance, cellular proliferation, migration, and invasion
(Zang et al. 2012).
Cases reporting both intra- and inter-tumoral heterogeneity in colorectal cancer
are very less (Jeantet et al. 2016). To date, numerous mutations in BRAF, NRAS, and
KRAS that are responsible for causing colorectal cancer have been detected. How-
ever, as most of these previous studies employed sequencing methods with low
sensitivity, no significant inter-heterogeneity between a primary and metastatic
lesion in metastatic colorectal cancer was detected. Moreover, the concordance
between BRAF and KRAS status is found to be above 95% (Santini et al. 2008;
Baldus et al. 2010; Brannon et al. 2014). In 2016, Jeantet and the team investigated
the intra- and inter-tumoral heterogeneity of BRAF and RAS mutations within
60 tumor regions from 18 colorectal cancer cases employing pyrosequencing
(Jeantet et al. 2016). Results obtained revealed that, in the primary tumors, intra-
tumor heterogeneity associated with RAS mutation was detected in 33% of the cases.
However, inter-tumor heterogeneity associated with RAS mutation amongst meta-
static lymph nodes and primary tumors was detected in 36% of the cases (Jeantet
et al. 2016). However, in 2015, Sanborn and the team reveal that the main reason for
inter-tumor heterogeneity is intra-tumor heterogeneity (Sanborn et al. 2015).
1.2.2 Intra-Heterogeneity
Intra-tumor heterogeneity denotes the intrinsic temporal–spatial variances amongst

distinct tumor cells sub-populations in the same tumor at both epigenetic and genetic
levels (Welch 2016). Recently developed high throughput sequencing technologies
enable detection of various regions with distinct epigenetic and genetic characteris-
tics features within the same tumor (Gerlinger et al. 2012). Additionally,
non-cancerous cells, namely, infiltrating immune cells, stromal cells, etc., interact
with nearby cancer cells and form a distinct microenvironment. Subsequently,
factors associated with each microenvironment respond distinctly to chemothera-
peutics, which in turn make the system complex and, hence, more difficult for
treatment (Gao et al. 2018). To date, four important models, namely, the clonal
evolution model, the cancer stem cell, the plasticity model, and the big bang model
have been proposed to understand the intra-tumor heterogeneity in cancer (Fig. 1.1).
Fig. 1.1 Depicting the hypothesis associated with (a) the clonal evolution model, (b) the cancer
stem cell, (c) the plasticity model to understand the intra-tumor heterogeneity in cancer
1.2.2.1 The Clonal Evolution Model
This model hypothesizes that a normal cell undergoes “neoplastic proliferation” after
experiencing either spontaneous or induced genetic modification (Nowell 1976).
Consequently, random genetic modifications in these neoplastic cells generate novel
mutant cells with flexible fitness, and the cellular population endures selection. The
majority of these genetic variants are deleterious and thus are eliminated through the
immune system cells of the host. Few of these are advantageous to a tumor cell and
may generate dominant sub-population (Ding et al. 2013). This works similarly to
natural selection (Gupta and Vadde 2019b). The successive selection and diversifi-
cation make the tumor malignancy more severe (Ding et al. 2013).
Since four decades several studies supporting this theory in numerous cancer
types have been conducted by employing cytogenetic tools, molecular genetics, and
high throughput sequencing approaches (Navin et al. 2010; Snuderl et al. 2011; Xu
et al. 2012; Gerlinger et al. 2012; Welch et al. 2012). In 2011, Snuderl and the team
reported amplification of three distinct receptor tyrosine kinases, namely, EGFR,

PDGFRA, and MET, within different cells of a single tumor in a mutually exclusive
manner. Each distinct sub-population was actively dividing, and co-existing sub--
population experiences mutual primary genetic modification, thereby suggesting
their origin from individual precursor cells (Snuderl et al. 2011). In the same year,
another study examined the clonal makeup of gastric glands in the stomach of
humans. Results obtained revealed that metaplastic organs originate from the same
clone and all lineages shared a mutual mtDNA mutation. They also reported that
dysplasia originates from metaplasia (Gutierrez–Gonzalez et al. 2011).
As it is widely accepted that cancer is a micro-evolutionary process and develops
from a single cell, recognizing cancer phylogeny may help us in identifying muta-
tions associated with the branch, trunk, as well as a private branch (Hanahan and
Weinberg 2011; Vormehr et al. 2016). Since trunk mutations denote the genomic
variation amongst normal and the cancer cells, they serve as an essential biomarker
toward early cancer detection. In 2017, Zhou and the team reported that non-trunk
mutations have lower variant allele frequencies (VAFs) in comparison to trunk
mutations. Trunk mutation present in the protein-coding regions may produce
mutant proteins that are plausibly tumor-causing neo-antigens within cancer cells
(Zhou et al. 2017). Yachida and the team observed two distinct categories of
mutations in pancreatic cancer and their associated metastases. Trunk mutation,
which denotes early tumorigenesis, was found to be present in a large amount
(64%) in both primary and secondary metastatic tumors (Yachida et al. 2010).
Zhou and the team have reported that small-scale multiregional sampling and
subsequent screening of low VAF somatic mutations might be a cost-effective
approach for identifying the majority of trunk mutations in gastric carcinoma
(Zhou et al. 2017). Other studies have also reported about the clonal evolution
concept in colorectal cancer as well as a few breast cancer (Navin et al. 2010; Kim
et al. 2015).
1.2.2.2 The Cancer Stem Cell Model
Amongst the early studies on heterogeneity in cancer, for the first time, Virchow and
Cohnheim hypothesized the involvement of cancer stem cells in tumor development.
They believed that these cancer stem cells originate from “activation of dormant
embryonic tissue remnants” (Huntly and Gilliland 2005). For the first time, cancer
stem cells were isolated from acute myeloid leukemia by Bonnet and Dick (Bonnet
and Dick 1997). However, information about their definitive properties and func-
tions in various tumors remains elusive to date. Unlike the clonal evolution model,
the cancer stem cells model hypothesizes that few stem cells present in the tumor are
capable of self-renew as well as differentiation into a various cell types with distinct
capabilities as well as phenotypes (Michor and Polyak 2010; Gerdes et al. 2014;
Plaks et al. 2015). Few other studies have also proposed that development process
associated with normal tissue organization, to a certain extent, may also be associ-
ated with cancer initiation in small cell lung carcinoma (Baylin et al. 1978),
mammary carcinoma (Hager et al. 1981), and teratocarcinoma (Pierce et al. 1960).
These studies reported that various differentiated cells of tumors originate from
tumor “stem” cells, as like normal differentiated tissues that develop from normal
tissue stem cells. Hence, tumors can be considered as a caricature of normal tissue
renewal or embryogenesis (Pierce and Speers 1988). Like normal tissue-specific
stem cells, there are also quiescent sub-population of “cancer stem cells.” Addition-
ally, in these cancer stem cells, anti-apoptotic proteins and cellular efflux pumps are
highly expressed and reactive oxygen species are suppressed. These cancer stem
cells also play key role in DNA damage repair. Thus, cancer stem cells are more
resistant to radio- and chemo-therapies and, are the main reason for cancer
reoccurrence (Allan et al. 2006; Bao et al. 2006; Todaro et al. 2007; Li and Clevers
2010).
Earlier several studies have also reported that most of the leukemia blasts are
post-mitotic and required replacement via a small amount of highly proliferative
cells (Kreso and Dick 2014). In pancreatic cancer of humans, the CXCR4 portion of
the CD133+ cancer stem cells is only capable of metastasis (Hermann et al. 2007). In
colorectal cancer, CD26+ sub-population of cancer stem cells is only capable of
metastasis and their presence indicates successive metastasis within the liver of
primary colon cancer patients. Recently, several studies have suggested the presence
of cancer stem cells in gastric cancer. Since cancer stem cells are generally produced
from tissue-specific stem cells, there is always a debate if gastric cancer develops
from cancerous gastric stem cells (Zhao et al. 2015).
For the first time, villins were detected as a biomarker for gastric stem cells.
Villins are calcium-modulated actin-binding protein present on epithelial cell and are
associated with regulating the re-organization of microvillar actin filaments (Nomura
et al. 1998). Unlike extremely proliferative putative gastric stem cells present within
the isthmus, the villin promoter-marked gastric stem cells (V-GSCs) are quiescent
and situated nearby the lower-third of the antral glands (Qiao et al. 2007). As
V-GSCs are mostly present in the antrum’s lesser curvature (Qiao et al. 2007), the
primary site of origin of human gastric cancer (Odze 2005), numerous studies have
hypothesized that V-GSCs modification may cause gastric cancer. Another study has
also reported that the down-regulation of Klf4 is responsible for developing gastric
cancer in humans (Wei et al. 2005). Klf4 can also restrict cell proliferation via
activating the cyclin-dependent kinase-inhibitors’ expression (Katz et al. 2005; Wei
et al. 2008). Klf4 deletion may also enhance expression of the FoxM1,
pro-proliferative factor, in the gastric tissue (LI et al. 2012), which in turn may
modify V-GSCs, thereby causing gastric cancer. Few researchers have also reported
that the Lgr5+ stem cells present within the intestine and stomach could be respon-
sible for initiating tumors (Zhao et al. 2015).
1.2.2.3 The Plasticity Model
The plasticity model hypothesizes that the processes and stimuli associated with
inherent tumor cells may cause them to behave like normal stem cells. On the
contrary, these processes may also influence cancer stem cells to differentiate into
non-stem cancer cells. In general, cancer cells experience higher plasticity than
normal cells and this plasticity is associated with modulation of the epithelial–
mesenchymal transition process (Rich 2016). Studies have suggested that various
form of T cells, including Th17, Th1 and Th1, shows the outstanding amount of
developmental plasticity via epigenetic mechanisms that are essential for preserving
homeostasis specifically within the gastrointestinal region (Rezalotfi et al. 2019).
Few studies have also reported that, under certain inflammatory conditions, normal
function of FOXP3+ Treg cells may become disrupted and behave like an effector
CD4+ T cells (Sakaguchi et al. 2013). Additionally, loss of FoxP3 expression may
cause Treg cells to behave like an IL-17-secreting cell. Furthermore, in response to
IL-12 under in vitro condition, Treg cells can also generate IFN-γ (Muranski and
Restifo 2013).
1.2.2.4 The Big Bang Model
Sottoriva and the team proposed the temporal aspect of tumor mutations that may
lead to heterogeneity during cancer (Sottoriva et al. 2015). The “big bang model”
proposes that the mutations associated with tumor development as well as progres-
sion occur at early stage of colorectal cancer. Hence, the tumor behavior is deter-
mined at an early stage of cancer. That is why some tumor metastasize at any early
stage while some never metastasize. To understand this model, single gland inves-
tigation in diverse tumor regions was employed for mapping the regional spreading
of genetic modifications in colorectal cancer. Obtained result revealed that merging
sub-clones are the characteristic of invasive carcinomas. Separated sub-clones are
the characteristic of adenomas. This temporal and spatial analysis would support a
“single clonal expansion” concept. Instead of dominant sub-clones spatially over-
growing others, Sottoriva and the team also detected large amount of mixed
sub-clones that are driven by bystander mutations instead of Darwinian selection
of the “fittest” sub-clone that causes spatial dominance (Sottoriva et al. 2015; Blank
et al. 2018).
1.3 Approaches to Explore Tumor Heterogeneity
In recent years, genomic studies have suggested that tumor heterogeneity is the main
reason for ineffective cancer treatment as well as personalized medicine. Hence,
there is an urgent need to understand tumor heterogeneity in the early onset of any
cancer, which in turn may improvise the outcomes of this killer disease. To date,
several experimental approaches, for instance, “next-generation sequencing”
approaches, have been developed to elucidate tumor heterogeneity, which may
provide biomarkers in the prevention or curing of any cancer type. After employing
“next-generation sequencing” approaches, in 2016, Clavé and the team suggested
that ROS1 deletions and amplifications are heterogeneous in non-small-cell lung

cancer but have no impact on overall survival of the patient (Clavé et al. 2016). Other
studies have reported about LRP2, ATM, and APC deletion during gastric cancer.
This finding is in accordance with the Cancer Genome Atlas (Cai et al. 2019). Zehir
and the team investigated the mutational landscape of ~10,000 pan-cancer patients
employing a hybridization capture-based NGS panel, namely, “MSK-IMPACT”
(Zehir et al. 2017). In another study, Chen and the team did whole-exome sequenc-
ing on 78 gastric cancer patients within the Northern Province of China, namely,
Tianjin, and differentiated gastric cancer into two subtypes, namely, high-clonality
or low-clonality (Chen et al. 2015).
Though “next-generation sequencing” approaches enable somatic mutation iden-
tification in cancer, they are incapable of detecting rare mutations because of the
errors that generate during library preparation as well as genome amplification at the
time of the sequencing process (Etchings 2017). To overcome these problems, two
approaches, namely, safe sequencing and duplex sequencing, have been developed
(Gupta and Somer 2017). Though these two technologies effectively detect
sub-clonal mutations, they are only beneficial for investigating small genomic sub-
jects because of their low genome coverage and short read lengths problems (Gupta
and Somer 2017). To overcome this problem, another technology, namely, circle-
sequencing technology has been developed. In circle sequencing, genomic DNA is
fragmented and subsequently circularized via ligating terminal region of the frag-
ment, and amplified employing a rolling-circle polymerase (Lou et al. 2013). Later
analyzing blood-based solid tumors employing intact circulating tumor cells, as well
as cell-free ctDNA, provided a unique way of investigating temporal intra-tumor
heterogeneity. However, these techniques are limited to analysis of structural
rearrangements, DNA methylation changes, single-nucleotide variants, and copy
number alterations (Gupta and Somer 2017).
However, most of these approaches to study tumor heterogeneity in cancer were
mainly designed upon bulk-cell analysis, which in turn provides little information
about the population of cells. For the first time, in 2009, transcriptomic data was
estimated at the single-cell level by Tang and the team (Tang et al. 2009). Since then,
the technique of single-cell RNA sequencing (scRNA-seq) has experienced an
explosive development in the past 10 years. In comparison to bulk-based techniques,
scRNA-seq provides more detailed insights into cellular heterogeneity and brings
important discoveries in biology (Tang et al. 2011; Zeisel et al. 2015). For instance,
Deng and the team identified the stochastic expression of monoallelic genes in
mammalian cells (Deng et al. 2014). Earlier Xin and team (Xin et al. 2016) and
Segerstolpe and team (Segerstolpe et al. 2016) reported the expression heterogeneity
of human islet cells (for instance, β-cells, α-cells, and δ-cells). They also investigated
the modifications in patterns of gene expression and the enriched signaling pathways
in T2D in comparison with healthy people. Hence, the single-cell RNA-sequencing
technology can provide detailed insight about the molecular mechanisms associated
with any disease or trait, including gastrointestinal cancer, by capturing gene
expression at the inter-cell level.
Bockerstett and the team employed scRNA-seq and identified a population of

“Mucin 6 (Muc6)+gastric intrinsic factor (Gif)+ cells” within the healthy tissue.
However, these cells do not play important role in “spasmolytic polypeptide-
expressing metaplasia” in gastric mucosa, the regenerative lesion that is the plausible
precursor for “intestinal metaplasia/gastric adenocarcinoma” (Bockerstett et al.
2019). In another study, Yang and the team performed analysis on 218 scRNA-seq
libraries and identified the wide range of gene expression in “esophageal squamous
cell carcinoma” cells. Additionally, they also reported that genes, namely, ITGB4,
LAMA5, SDC4, CFLAR, and ITGA6, and pathways, namely, cell differentiation and
proliferation pathways tumor cell migration, PI3K-AKT pathway, invasion path-
ways, pathways evading apoptosis, are responsible for radio-resistance development
(Yang et al. 2019). Chen and the team analyzed ~30,000 single cells retrieved from
eight gastric tumors and identified heterogeneous fibroblasts (COLA1+, THY1+, and
ACTA2+), endothelial cells (PECAM1+ and VWF+), epithelial cells (TFF1+,
CDH1+, PGC+, EPCAM+, and MUC5AC+), and various immune cells including
CD4 T cells (CD4D+ and CD3+), M1 and M2 macrophages (IL1B+, CD68+,
MARCO+, TNF+, IL1A+, and MSR1+), Gamma Delta T cells (TRDC+ and
TRGC2+), B cells (CD79+), CD8 T cells (CD8A+), and plasma cells (CD20+,
CD19+, and IgG+) (Chen et al. 2019). Component of both non-immune, namely,
CD45-, and immune, namely, CD45+, cell is found to be highly heterogeneous in
human gastric cancers (82). Irrespective of the benefits of the scRNA-seq technol-
ogies over technologies, information about tumor heterogeneity remain a topic of
debate to date. Thus, there is always a scope for developing more effective strategies
and approaches that may help to understand the complete mechanism associated
with tumor heterogeneity in a more comprehensive way.
1.4 Conclusion
In conclusion, tumor heterogeneity is the main reason for the low treatment response
rate in cancer patients. Tumor heterogeneity can be either at inter- or intra-level.
Though to date, several approaches have been developed, there is still scope for
development for more effective strategies and approaches towards understanding
tumor heterogeneity in cancer. Authors believe that tumor heterogeneity can be
investigated effectively by integrating information obtained from various disci-
plines, including pathology, clinical-radiology, genetic and molecular biology.
Authors also believe that employing deep learning techniques, for instance, Tensor
Flow (https://www.tensorflow.org/), in clinical-pathological diagnostic cases may
help in developing various algorithms that may aid in early detection of cancer. In
the near future, the information present in this chapter will be highly useful for the
early detection and prevention of gastrointestinal cancer in humans.
Conflict of Interests None.
References
Allan AL, Vantyghem SA, Tuck AB, Chambers AF (2006) Tumor dormancy and cancer stem cells:
implications for the biology and treatment of breast cancer metastasis. Breast Dis 26:87–98.
https://doi.org/10.3233/bd-2007-26108
Alsina M, Gullo I, Carneiro F (2017) Intratumoral heterogeneity in gastric cancer: a new challenge
to face. Ann Oncol 28:912–913. https://doi.org/10.1093/annonc/mdx134
Baldus SE, Schaefer K-L, Engers R et al (2010) Prevalence and heterogeneity of KRAS, BRAF,
and PIK3CA mutations in primary colorectal adenocarcinomas and their corresponding metas-
tases. Clin Cancer Res 16:790–799. https://doi.org/10.1158/1078-0432.CCR-09-2446
Bao S, Wu Q, McLendon RE et al (2006) Glioma stem cells promote radioresistance by preferential
activation of the DNA damage response. Nature 444:756–760. https://doi.org/10.1038/
nature05236
Baylin SB, Weisburger WR, Eggleston JC et al (1978) Variable content of histaminase, L-dopa
decarboxylase and calcitonin in small-cell carcinoma of the lung. N Engl J Med 299:105–110.
https://doi.org/10.1056/NEJM197807202990301
Blank A, Roberts DE, Dawson H et al (2018) Tumor heterogeneity in primary colorectal cancer and
corresponding metastases. Does the apple fall far from the tree? Front Med (Lausanne) 5:234.
https://doi.org/10.3389/fmed.2018.00234
Bockerstett KA, Lewis SA, Wolf KJ et al (2019) Single-cell transcriptional analyses of spasmolytic
polypeptide-expressing metaplasia arising from acute drug injury and chronic inflammation in
the stomach. Gut 69(6):1027–1038. https://doi.org/10.1136/gutjnl-2019-318930
Bonnet D, Dick JE (1997) Human acute myeloid leukemia is organized as a hierarchy that
originates from a primitive hematopoietic cell. Nat Med 3:730–737. https://doi.org/10.1038/
nm0797-730
Brannon AR, Vakiani E, Sylvester BE et al (2014) Comparative sequencing analysis reveals high
genomic concordance between matched primary and metastatic colorectal cancer lesions.
Genome Biol 15:454. https://doi.org/10.1186/s13059-014-0454-7
Cai H, Jing C, Chang X et al (2019) Mutational landscape of gastric cancer and clinical application
of genomic profiling based on target next-generation sequencing. J Transl Med 17:189. https://
doi.org/10.1186/s12967-019-1941-0
Cancer Genome Atlas Research Network, Analysis Working Group: Asan University, BC Cancer
Agency et al (2017) Integrated genomic characterization of oesophageal carcinoma. Nature
541:169–175. https://doi.org/10.1038/nature20805
Chen K, Yang D, Li X et al (2015) Mutational landscape of gastric adenocarcinoma in Chinese:
implications for prognosis and therapy. PNAS 112:1107–1112. https://doi.org/10.1073/pnas.
1422640112
Chen J, Sathe A, Grimes S et al (2019) Abstract 151: comprehensive characterization of gastric
cancer at single-cell resolution. Cancer Res 79:151–151. https://doi.org/10.1158/1538-7445.
AM2019-151
Clavé S, Gimeno J, Muñoz-Mármol AM et al (2016) ROS1 copy number alterations are frequent in
non-small cell lung cancer. Oncotarget 7:8019–8028. https://doi.org/10.18632/oncotarget.6921
Cooper GM (2000) The development and causes of cancer. The cell: a molecular approach, 2nd
edn. Sinauer Associates, Sunderland, MA
Dagogo-Jack I, Shaw AT (2018) Tumour heterogeneity and resistance to cancer therapies. Nat Rev
Clin Oncol 15:81–94. https://doi.org/10.1038/nrclinonc.2017.166
Deng Q, Ramsköld D, Reinius B, Sandberg R (2014) Single-cell RNA-seq reveals dynamic,

random monoallelic gene expression in mammalian cells. Science 343:193–196. https://doi.
org/10.1126/science.1245316
Ding L, Raphael BJ, Chen F, Wendl MC (2013) Advances for studying clonal evolution in cancer.
Cancer Lett 340:212–219. https://doi.org/10.1016/j.canlet.2012.12.028
Etchings JA (2017) Strategies in biomedical data science: driving force for innovation. Wiley,
Hoboken
Gao J-P, Xu W, Liu W-T et al (2018) Tumor heterogeneity of gastric cancer: from the perspective of
tumor-initiating cell. World J Gastroenterol 24:2567–2581. https://doi.org/10.3748/wjg.v24.
i24.2567
Gerdes MJ, Sood A, Sevinsky C et al (2014) Emerging understanding of multiscale tumor
heterogeneity. Front Oncol 4:366. https://doi.org/10.3389/fonc.2014.00366
Gerlinger M, Rowan AJ, Horswell S et al (2012) Intratumor heterogeneity and branched evolution
revealed by multiregion sequencing. N Engl J Med 366:883–892. https://doi.org/10.1056/
NEJMoa1113205
Gupta RG, Somer RA (2017) Intratumor heterogeneity: novel approaches for resolving genomic
architecture and clonal evolution. Mol Cancer Res 15:1127–1137. https://doi.org/10.1158/
1541-7786.MCR-17-0070
Gupta MK, Vadde R (2019a) Identification and characterization of differentially expressed genes in
type 2 diabetes using in silico approach. Comput Biol Chem 79:24–35. https://doi.org/10.1016/
j.compbiolchem.2019.01.010
Gupta MK, Vadde R (2019b) Genetic basis of adaptation and maladaptation via balancing selection.
Zoology 136:125693. https://doi.org/10.1016/j.zool.2019.125693
Gupta MK, Behara SK, Vadde R (2017) In silico analysis of differential gene expressions in biliary
stricture and hepatic carcinoma. Gene 597:49–58
Gupta MK, Sarojamma V, Reddy MR et al (2019a) Computational biology: toward early detection
of pancreatic cancer. Crit Rev Oncog 24:191–198. https://doi.org/10.1615/CritRevOncog.
2019031335
Gupta MK, Vadde R, Sarojamma V (2019b) Curcumin - a novel therapeutic agent in the prevention
of colorectal cancer. Curr Drug Metab 20(12):977–987. https://doi.org/10.2174/
1389200220666191007153238
Gutierrez–Gonzalez L, Graham TA, Rodriguez–Justo M et al (2011) The clonal origins of dysplasia
from intestinal metaplasia in the human stomach. Gastroenterology 140:1251–1260.e6. https://
doi.org/10.1053/j.gastro.2010.12.051
Hager JC, Fligiel S, Stanley W et al (1981) Characterization of a variant-producing tumor cell line
from a heterogeneous strain BALB/cfC3H mouse mammary tumor. Cancer Res 41:1293–1300
Hanahan D, Weinberg RA (2011) Hallmarks of cancer: the next generation. Cell 144:646–674.
https://doi.org/10.1016/j.cell.2011.02.013
Hermann PC, Huber SL, Herrler T et al (2007) Distinct populations of cancer stem cells determine
tumor growth and metastatic activity in human pancreatic cancer. Cell Stem Cell 1:313–323.
https://doi.org/10.1016/j.stem.2007.06.002
Huntly BJP, Gilliland DG (2005) Leukaemia stem cells and the evolution of cancer-stem-cell
research. Nat Rev Cancer 5:311–321. https://doi.org/10.1038/nrc1592
Jamal-Hanjani M, Quezada SA, Larkin J, Swanton C (2015) Translational implications of tumor
heterogeneity. Clin Cancer Res 21:1258–1266. https://doi.org/10.1158/1078-0432.CCR-14-
1429
Janiszewska M (2020) The microcosmos of intratumor heterogeneity: the space-time of cancer
evolution. Oncogene 39(10):2031–2039. https://doi.org/10.1038/s41388-019-1127-5
Jeantet M, Tougeron D, Tachon G et al (2016) High intra- and inter-tumoral heterogeneity of
RAS mutations in colorectal cancer. Int J Mol Sci 17:2015. https://doi.org/10.3390/
ijms17122015
Katz JP, Perreault N, Goldstein BG et al (2005) Loss of Klf4 in mice causes altered proliferation and
differentiation and precancerous changes in the adult stomach. Gastroenterology 128:935–945.
https://doi.org/10.1053/j.gastro.2005.02.022
Kim T-M, Jung S-H, An CH et al (2015) Subclonal genomic architectures of primary and metastatic
colorectal cancer based on intratumoral genetic heterogeneity. Clin Cancer Res 21:4461–4472.
https://doi.org/10.1158/1078-0432.CCR-14-2413
Kreso A, Dick JE (2014) Evolution of the cancer stem cell model. Cell Stem Cell 14:275–291.
https://doi.org/10.1016/j.stem.2014.02.006
Li L, Clevers H (2010) Coexistence of quiescent and active adult stem cells in mammals. Science
327:542–545. https://doi.org/10.1126/science.1180794
Li Q, Jia Z, Wang L et al (2012) Disruption of Klf4 in villin-positive gastric progenitor cells
promotes formation and progression of tumors of the antrum in mice. Gastroenterology
142:531–542. https://doi.org/10.1053/j.gastro.2011.11.034
Lin L, Lin D-C (2019) Biological significance of tumor heterogeneity in esophageal squamous cell
carcinoma. Cancers (Basel) 11:1156. https://doi.org/10.3390/cancers11081156
Liu J, Dang H, Wang XW (2018) The significance of intertumor and intratumor heterogeneity in
liver cancer. Exp Mol Med 50:e416–e416. https://doi.org/10.1038/emm.2017.165
Lou DI, Hussmann JA, McBee RM et al (2013) High-throughput DNA sequencing errors are
reduced by orders of magnitude using circle sequencing. Proc Natl Acad Sci U S A
110:19872–19877. https://doi.org/10.1073/pnas.1319590110
Michor F, Polyak K (2010) The origins and implications of intratumor heterogeneity. Cancer Prev
Res (Phila) 3:1361–1364. https://doi.org/10.1158/1940-6207.CAPR-10-0234
Muranski P, Restifo NP (2013) Essentials of Th17 cell commitment and plasticity. Blood
121:2402–2414. https://doi.org/10.1182/blood-2012-09-378653
Navin N, Krasnitz A, Rodgers L et al (2010) Inferring tumor progression from genomic heteroge-
neity. Genome Res 20:68–80. https://doi.org/10.1101/gr.099622.109
Nomura S, Esumi H, Job C, Tan S-S (1998) Lineage and clonal development of gastric glands. Dev
Biol 204:124–135. https://doi.org/10.1006/dbio.1998.9055
Nowell PC (1976) The clonal evolution of tumor cell populations. Science 194:23–28. https://doi.
org/10.1126/science.959840
Odze RD (2005) Unraveling the mystery of the gastroesophageal junction: a pathologist’s perspec-
tive. Am J Gastroenterol 100:1853–1867. https://doi.org/10.1111/j.1572-0241.2005.50096.x
Pierce GB, Speers WC (1988) Tumors as caricatures of the process of tissue renewal: prospects for
therapy by directing differentiation. Cancer Res 48:1996–2004
Pierce GB, Dixon FJ, Verney EL (1960) Teratocarcinogenic and tissue-forming potentials of the
cell types comprising neoplastic embryoid bodies. Lab Investig 9:583–602
Plaks V, Kong N, Werb Z (2015) The cancer stem cell niche: how essential is the niche in regulating
stemness of tumor cells? Cell Stem Cell 16:225–238. https://doi.org/10.1016/j.stem.2015.02.
015
Qiao XT, Ziel JW, McKimpson W et al (2007) Prospective identification of a multilineage
progenitor in murine stomach epithelium. Gastroenterology 133:1989–1998. https://doi.org/
10.1053/j.gastro.2007.09.031
Rezalotfi A, Ahmadian E, Aazami H et al (2019) Gastric cancer stem cells effect on Th17/Treg
balance; a bench to beside perspective. Front Oncol 9:226. https://doi.org/10.3389/fonc.2019.
00226
Ribic CM, Sargent DJ, Moore MJ et al (2003) Tumor microsatellite-instability status as a predictor
of benefit from fluorouracil-based adjuvant chemotherapy for colon cancer. N Engl J Med
349:247–257. https://doi.org/10.1056/NEJMoa022289
Rich JN (2016) Cancer stem cells: understanding tumor hierarchy and heterogeneity. Medicine
(Baltimore) 95:S2–S7. https://doi.org/10.1097/MD.0000000000004764
Sakaguchi S, Vignali DAA, Rudensky AY et al (2013) The plasticity and stability of regulatory T
cells. Nat Rev Immunol 13:461–467. https://doi.org/10.1038/nri3464
Sanborn JZ, Chung J, Purdom E et al (2015) Phylogenetic analyses of melanoma reveal complex
patterns of metastatic dissemination. Proc Natl Acad Sci U S A 112:10995–11000. https://doi.
org/10.1073/pnas.1508074112
Santini D, Loupakis F, Vincenzi B et al (2008) High concordance of KRAS status between primary
colorectal tumors and related metastatic sites: implications for clinical practice. Oncologist
13:1270–1275. https://doi.org/10.1634/theoncologist.2008-0181
Segerstolpe Å, Palasantza A, Eliasson P et al (2016) Single-cell transcriptome profiling of human
pancreatic islets in health and type 2 diabetes. Cell Metab 24:593–607. https://doi.org/10.1016/j.
cmet.2016.08.020
Snuderl M, Fazlollahi L, Le LP et al (2011) Mosaic amplification of multiple receptor tyrosine
kinase genes in glioblastoma. Cancer Cell 20:810–817. https://doi.org/10.1016/j.ccr.2011.11.
005
Sottoriva A, Kang H, Ma Z et al (2015) A big bang model of human colorectal tumor growth. Nat
Genet 47:209–216. https://doi.org/10.1038/ng.3214
Tang F, Barbacioru C, Wang Y et al (2009) mRNA-Seq whole-transcriptome analysis of a single
cell. Nat Methods 6:377–382. https://doi.org/10.1038/nmeth.1315
Tang F, Lao K, Surani MA (2011) Development and applications of single-cell transcriptome
analysis. Nat Methods 8:S6–S11. https://doi.org/10.1038/nmeth.1557
Todaro M, Alea MP, Di Stefano AB et al (2007) Colon cancer stem cells dictate tumor growth and
resist cell death by production of interleukin-4. Cell Stem Cell 1:389–402. https://doi.org/10.
1016/j.stem.2007.08.001
Vormehr M, Diken M, Boegel S et al (2016) Mutanome directed cancer immunotherapy. Curr Opin
Immunol 39:14–22. https://doi.org/10.1016/j.coi.2015.12.001
Wang K, Kan J, Yuen ST et al (2011) Exome sequencing identifies frequent mutation of ARID1A
in molecular subtypes of gastric cancer. Nat Genet 43:1219–1223. https://doi.org/10.1038/ng.
982
Wei D, Gong W, Kanai M et al (2005) Drastic down-regulation of Krüppel-like factor 4 expression
is critical in human gastric cancer development and progression. Cancer Res 65:2746–2754.
https://doi.org/10.1158/0008-5472.CAN-04-3619
Wei D, Kanai M, Jia Z et al (2008) Krüppel-like factor 4 induces p27Kip1 expression in and
suppresses the growth and metastasis of human pancreatic cancer cells. Cancer Res
68:4631–4639. https://doi.org/10.1158/0008-5472.CAN-07-5953
Welch DR (2016) Tumor heterogeneity--a “contemporary concept” founded on historical insights
and predictions. Cancer Res 76:4–6. https://doi.org/10.1158/0008-5472.CAN-15-3024
Welch JS, Ley TJ, Link DC et al (2012) The origin and evolution of mutations in acute myeloid
leukemia. Cell 150:264–278. https://doi.org/10.1016/j.cell.2012.06.023
Xin Y, Kim J, Okamoto H et al (2016) RNA sequencing of single human islet cells reveals type
2 diabetes genes. Cell Metab 24:608–615. https://doi.org/10.1016/j.cmet.2016.08.018
Xu X, Hou Y, Yin X et al (2012) Single-cell exome sequencing reveals single-nucleotide mutation
characteristics of a kidney tumor. Cell 148:886–895. https://doi.org/10.1016/j.cell.2012.02.025
Yachida S, Jones S, Bozic I et al (2010) Distant metastasis occurs late during the genetic evolution
of pancreatic cancer. Nature 467:1114–1117. https://doi.org/10.1038/nature09515
Yang L, Zhang X, Hou Q et al (2019) Single-cell RNA-seq of esophageal squamous cell carcinoma
cell line with fractionated irradiation reveals radioresistant gene expression patterns. BMC
Genomics 20:611. https://doi.org/10.1186/s12864-019-5970-0
Zang ZJ, Cutcutache I, Poon SL et al (2012) Exome sequencing of gastric adenocarcinoma
identifies recurrent somatic mutations in cell adhesion and chromatin remodeling genes. Nat
Genet 44:570–574. https://doi.org/10.1038/ng.2246
Zehir A, Benayed R, Shah RH et al (2017) Mutational landscape of metastatic cancer revealed from
prospective clinical sequencing of 10,000 patients. Nat Med 23:703–713. https://doi.org/10.
1038/nm.4333
Zeisel A, Muñoz-Manchado AB, Codeluppi S et al (2015) Brain structure. Cell types in the mouse
cortex and hippocampus revealed by single-cell RNA-seq. Science 347:1138–1142. https://doi.
org/10.1126/science.aaa1934
Zhao Y, Feng F, Zhou Y-N (2015) Stem cells in gastric cancer. World J Gastroenterol 21:112–123.
https://doi.org/10.3748/wjg.v21.i1.112
Zhou Z, Wu S, Lai J et al (2017) Identification of trunk mutations in gastric carcinoma: a case study.
BMC Med Genet 10:49. https://doi.org/10.1186/s12920-017-0285-y
Chapter 2
Immunocomposition of Gastrointestinal
Tract of Gut
Mekapogu Madakka, Nambi Rajesh, and Jinka Rajeswari
Abstract The human gastrointestinal tract (GI tract) is a distinctive organ occupied
by a series of commensal microorganisms, while also being showed to an over-
whelming load of antigens in the form of dietary antigens on a daily basis. The GI
tract has played dual role in the body, in that it performs uptake of nutrients and
digestion while also performing out the complex and principal task of maintaining
immune homeostasis, i.e., maintaining the balance between the good and the bad. It
is equally important that we protect ourselves from reacting against the good,
meaning that we reside tolerant to harmless food, commensal bacteria and self-
antigens, as well as react with force against the bad, meaning induction of immune
responses against harmful microorganisms. This complex task is achieved through
the presence of a highly efficient mucosal barrier and a specialised multifaceted
immune system, made up of a large population of scattered immune cells and
organised lymphoid tissues termed the gut-associated lymphoid tissue (GALT).
This book chapter provides an overview of the primary components of the human
mucosal immune system and how the immune responses in the GI tract are coordi-
nated and induced.
Keywords Lamina propria · GALT · Mucosal immunity · Mucosal tolerance ·

Immune homeostasis · Gut microbiota
M. Madakka (*) · N. Rajesh

Pradesh, India
J. Rajeswari
Department of Biochemistry, Acharya Nagarjuna University, Guntur, Andhra Pradesh, India
https://doi.org/10.1007/978-981-15-6487-1_2
18 M. Madakka et al.
2.1 Introduction
2.1.1 Gastrointestinal Tract Architecture
Gastrointestinal (GI) tract plays an important role in uptaking nutrients, digestion. GI

tract has large surface area due to multiple folds which allows absorbing nutrients,
and gastrointestinal tract facilitates dual roles i.e., uptake of nutrients and defence
against potentially pathogenic organisms (PPOs) (O’Leary and Sweeney 1987)
followed by maintaining immune homeostasis. GI tract has several levels of invag-
inations at the tissue (Kerckring folds), cellular (villi) and membrane levels (micro-
villi). At the cellular level, intestinal epithelial cells (IECs) lined up the villi region
which has microvilli to absorb nutrients released during digestion and housing for
large number of immune cells in the body. Filamentous brush border glycocalyx
(FBBG) present at the tip of microvillus is composed of a layer of membrane
anchored glycoproteins that allows nutrients to cross, while restricting entry of
whole bacteria. Antimicrobial peptides, mucins and trefoil peptides also act to
restrict pathogen access to mucosal surfaces (Mestecky 2005; Brown et al. 1990).
2.2 Immune System of Gut
Immune system of mucosal gut comprises intestinal epithelial barrier, lamina propria
and GALT—Gut-associated lymphoid tissue. The components of mucosal immune
system of gut includes intestinal epithelial barrier, the lamina propria and the gut
(GALT). GALT is the leading organ further categorised into Peyer’s patches (PP),
isolated lymphoid follicles (ILF) and mesenteric lymph nodes (MLN) (Mestecky
2005; O’Leary and Sweeney 1987) (Fig. 2.1).
GALT is again differentiated into Peyer’s patches (PP), both form the biggest
lymphatic organ. Defence function, carried out by two sites includes inductive and
effector sites. Antigens from the mucosal surface, in the inductive sites activate naive
and memory T and B lymphocytes, consist of PP, ILF and MLN which are organised
nodes of lymphoid follicles (Mestecky 2005; Bhide et al. 2001; Heel et al. 1997).
Effector sites include epithelium and lamina propria, site of lymphatic scattered
(Mestecky 2005; O’Leary and Sweeney 1987; Bhide et al. 2001; Heel et al. 1997).
The mucosa-associated lymphoid tissue (MALT) is the largest immune organ in
the body containing more plasma B cells than the lymphoid nodes, spleen and bone
marrow combined, its role is to defend the mucosal surfaces from pathogenic
organisms. The MALT can be divided into two morphologically distinct regions:
(1) diffuse lymphoid tissue, where loosely ordered clusters of lymphoid cells are
scattered in the lamina propria of the mucosae and (2) well-organised lymphoid
tissue, where lymphoid cells are grouped together forming aggregates in the sub-
mucosa (Mestecky 2005).
2 Immunocomposition of Gastrointestinal Tract of Gut
Fig. 2.1 Representation of mucosal immune system of gastrointestinal tract. Intestinal epithelial cells and the mucous layer form a biochemical and physical
barrier that maintains segregation between the gut lumen and the mucosal immune system
19
The mucosal membrane of the GIT comprised of single layer of absorptive

epithelial cells enterocytes. Enterocytes not only allow for the absorption of nutrients
from the lumen but they also function as a protective barrier preventing the adher-
ence and entry of microorganisms. Gut-associated lymphoid tissue (GALT) provides
immunological defence for the GIT. The GALT must discriminate pathogens where
a protective immune response is induced from commensals and dietary antigens,
where homeostasis is preserved by maintaining a state of non-responsiveness.
Johannes Conrad Peyer, a Swiss anatomist is credited with identifying PPs in 1673
(and first publishing his observations in 1677). PPs are mainly located on the anti-
mesenteric wall of the ileum but can also be found in the duodenum and jejunum. In
humans, the greatest number of individual follicles are found in the large intestine
and in the appendix and caecum where there is a high number of commensals
(O’Leary and Sweeney 1987). Human PPs develop in association with the ileum,
where PPs are first seen at the 15th week of gestation (Bhide et al. 2001). However,
the typical PP structure is not seen until after birth, where the germinal centre
develops rapidly following antigenic stimulation by the gut luminal bacteria (Heel
et al. 1997). Morphologically, the PP is divided into four main domains: the
lymphoid follicle, the interfollicular region (IFR), the sub-epithelium dome (SED)
and the follicle-associated epithelium. The lymphoid follicle contains a germinal
centre consisting of proliferating B cells with a small population of CD4+ T cells and
follicular dendritic cells that present antigens to B cells. The germinal centre contains
a large B cell population with a small population of CD4+ T cells and follicular
dendritic cells. The IFR is a T cell-rich area containing mainly CD4+ T cells,
macrophages, dendritic cells and high endothelial venules. The SED lies above the
follicle and contains B cells, T cells, dendritic cells and macrophages. M cells are
found in the follicle-associated epithelium overlaying the PP (Neutra and Kozlowski
2006).
2.3 Intestinal Epithelial Barrier
Intestinal epithelium consists of intestinal epithelial cells (IECs) further modified

into crypts and villi. Hence this is the body’s largest mucosal surface, intestinal
epithelium comprised of specialised cells includes immune response and defence
antigens, toxins, pathogens and enteric microbiota and absorbs selectively by nutri-
ents, electrolytes and water (Bevins 2006; Frey et al. 1996). Inductive site consists of
lymphoid follicle nodes, PP, ILF and MLN, where antigens from mucosal surface
activate naïve and memory T and B lymphocytes, effector site consists of epithelium
and lamina propria. The lymphocytes are scattered throughout the tissue in which
effector cells after extravasation, retention and differentiation perform this action.
Crypts contain pluripotent epithelial stem cells at the base, which are renewed
continually in the epithelium. IECs forms the segregates the gut lumen and its
contents from the cells in lamina propria found underneath tight junctions, seals
the intercellular spaces by linking adjacent epithelial cells, by forming physical and
2 Immunocomposition of Gastrointestinal Tract of Gut 21
biochemical barrier (Brown et al. 1990; Owen and Bhalla 1983). To maintain
integrity and permeability the expression of the junctional proteins was highly
regulated. If any alterations in intestinal permeability and mucosal defect barriers
leads to inflammatory bowel disease and irritable bowel syndrome (Bevins 2006;
Frey et al. 1996).
2.4 Specialised Secretory IECs
Goblet cells and Paneth cells are specialised cells that secrete mucins and antimi-
crobial proteins (AMPs) to establish barrier functions (Kraehenbuhl and Neutra
1992) and the organisation of the intestinal mucous layer (Kraehenbuhl and Neutra
1992; Bjerke and Brandtzaeg 1988). The Paneth cells secrete AMPs, which include
defensins, cathelicidins, secretory phospholipase A2 and lysosomes, further form the
barrier and selectively descriptive cell wall and surface membranes of bacteria
(Kraehenbuhl and Neutra 1992; Neutra et al. 1996; Giannasca et al. 1994).
2.5 Lamina Propria
Lamina propria is the layer of loosely packed connective tissue that lies below the
epithelium (Mestecky 2005; Sharma et al. 1996). It majorly consists of intestinal
immune cells, the blood supply, the lymphatic drainage system and the nervous
supply for the mucosa (Jang et al. 2004) and the major site of intestinal immune
response. Its role is to prevent the entry, spread and destruction of pathogens across
the gut mucosa (Sharma et al. 1996; Mooseker 1985).
2.6 Peyer’s Patches
Peyer’s patches are well organised and primary inductive site for mucosal immune
response usually found in the distal ileum. It consists of large B cell follicles with
intervening smaller T cell areas known as subepithelial dome (SED) due to its dome
shape and single layered follicle-associated epithelium (FAE) separates the intestinal
lumen (Heel et al. 1997; Iwasaki and Kelsall 2000). The FAE contains M cells
(specialised IECs), mediates primary step in initiating a mucosal immune response
by attacking luminal antigens and intact microbes by transporting to DCs, lying
within the SED (Sharma et al. 1996; Regoli et al. 1995). PPs contain B cells, CD4þ T
cells and CD8þT cells (Wolf et al. 1983), dendritic cells and macrophages (Jepson
et al. 1993).
2.7 Follicle-Associated Epithelium (FAE)
The FAE of the PP differs greatly from the surrounding villus epithelium. The
majority of the villus epithelium consists of absorptive enterocytes that are formed
in the crypts of Lieberkuhn from stem cells. Enterocytes migrate out of the crypts
into the villi, where they differentiate into mature absorptive cells that take up
nutrients and aid indigestion. Stem cells in the crypts can also give rise to goblet
cells, enteroendocrine cells and Paneth cells (Mestecky 2005). They provide defence
against microbes by secreting a number of antimicrobial molecules such as
defensins, lysozyme and phospholipase A2 in response to microbial stimulation
(Bevins 2006) In contrast to the villus epithelium, the FAE contains enterocytes
and specialised antigen sampling M cells, but there are few or no enteroendocrine or
goblet cells (Mestecky 2005) Therefore, there is less mucin produced by the FAE
allowing greater access for luminal antigens to the FAE. Enterocytes of the FAE are
morphologically similar to villus enterocytes; they are polarised columnar cells with
a well-defined brush border with a thick glycocalyx (Frey et al. 1996). However,
enterocytes of the FAE express less membrane (apical) bound digestive enzymes
such as sucrase, isomaltase and alkaline phosphatase (Brown et al. 1990; Owen and
Bhalla 1983; Smith 1985). Polymeric immunoglobulin receptor (p IgR) that medi-
ates the basolateral to apical transport, and secretion of immunoglobulin A (IgA) is
absent from the basolateral membrane of the FAE (Bjerke and Brandtzaeg 1988;
Pappo and Owen 1988). The glycosylation patterns of the FAE differ from the villus,
even within the FAE, the glycosylation pattern of the follicle enterocytes differs from
the patterns seen on the M cells (Clark et al. 1995; Giannasca et al. 1994; Sharma
et al. 1996). The FAE lacks subepithelial myofibroblasts found in the villus. One
the most notable differences between the FAE and the villus epithelium is seen in the
basement membrane composition. Perlecan and laminin a2 are absent from the
basement membrane of the FAE (Sierro et al. 2000). The difference in basement
membrane composition is thought to influence the proliferation and differentiation of
the FAE as well as forming a more porous basal lamina, thus allowing for easier
migration of lymphocytes and dendritic cells from the antigenic sampling M cells to
the SED (Mc Clugage et al. 1996). M cells were once believed to be a unique feature
of FAE; however, recent studies have shown that M cells may also be found on the
intestinal villi (Jang et al. 2004; Nochi et al. 2007; Terahara et al. 2008). Villus M
cells are found at a higher density towards the end of the ileum than throughout the
small intestine. Villus M cells share all the features and functions of PP M cells;
however, they exist independent of the PP (Jang et al. 2004).
It should be noted that the villus M cells were induced with cholera toxin.
Therefore, the villus M cells may more readily represent an intermediate state in
the conversion of M cells from villus enterocytes (discussed in the development of M
cells). M cells are specialised polarised epithelial cells that are found in the FAE. M
cells were first described in 1965 by Schmedtje who, using immune histochemistry,
noted the presence of lymphoepithelial cells in the appendix of rabbits. The involve-
ment of M cells in the transport of antigens was reported in 1977 when Owen
showed that M cells transport horseradish peroxidase (Owen 1977). The thick
glycocalyx that overlays the microvilli of enterocytes is much reduced over M
cells (Frey et al. 1996). M cells lack membrane hydrolytic enzymes such as alkaline
phosphatase and sucrase isomaltase (Brown et al. 1990; Smith 1985). Brush border
assembly requires the recruitment of actin binding proteins such as villin to the
apical membrane (Mooseker 1985). In M cells, villin is not associated with the apical
membrane and is instead found in the cytoplasm (Kanaya et al. 2007; Kerneis et al.
1996). The apical cytoplasm is rich in mitochondria and vesicles involved in
transcytosis (Wolf et al. 1983). The M cell cytoplasm generally contains fewer
lysosomes. The reduction in lysosomes suggests that the M cell delivers antigenic
material unchanged to the lymphoid follicle (Owen et al. 1986a). Similar to
enterocytes, the Golgi apparatus and the endoplasmic reticulum (ER) are located
above the nucleus. The nucleus of the M cell is displaced basally because the
basolateral membrane of the M cells is invaginated and forms a pocket that contains
lymphocytes and dendritic cells (Mestecky 2005; Iwasaki and Kelsall 2000; Regoli
et al. 1995). The primary function of M cells is to sample antigens in the lumen, to
take them up and deliver them to the underlying follicle. The structure of M cells
allows for the effective uptake and swift delivery of antigens. The lack of tightly
packed microvilli and a thick glycocalyx enables, the deep invagination of the
basolateral contained in the M cell pocket (Jepson et al. 1993).
M cells take up bacteria and large molecules by phagocytosis, where the M cell is
seen to engulf the bacteria. Although studies have reported on the adherence and
transcytosis of many microbes, there is still much to be investigated. Many of the
studies with M cells are done in mice and it is known that M cells differ greatly
between species. Therefore, M cells in mice differ greatly from M cells in humans.
The development of the in vitro M cell model by Kerneis and the subsequent
modification by Gullberg have provided a human M cell model to allow a greater
understanding of “human” M cells to be elucidated (Gullberg et al. 2000; Kerneis
et al. 1997). The model has been used to study the morphology, interaction with
commensal and pathogenic organisms, expression of cell-specific apical receptors,
drug absorption and novel vaccine targeting of M cells. Although the in vitro M cell
model has allowed us to generate a greater understanding of humanised M cells, it is
a simplified system, where the interaction of signalling factors from other immune
cells, especially those needed for proper PP function (T cells and dendritic cells), is
not taken into account.
The in vitro M cell model was designed by Kerneis and adapted by Gullberg et al.
(Gullberg et al. 2000) and Kerneis et al. (Kerneis et al. 1997). Caco-2 cells are seeded
on to a semi-permeable membrane and cultured until fully polarised (21 days). Either
PP lymphocytes or Raji lymphocytes (B cells) are added to the basolateral chamber.
Cells are cultured for 3 days to allow phenotypic M cells (M-like cells) to develop
within the polarised Caco-2 monolayer.
2.8 Mesenteric Lymph Nodes
Mesenteric lymph nodes are the largest lymph nodes in the body comprised of
paracortex, the cortex and the medulla with more number of lymphocytes (Jensen
et al. 1998; Neutra et al. 1987). Its main role is to filter intestine lymph and attack
incoming antigens and initiate immune responses in either in free form nor bring
them to MLN by DCs. MLNs also consist of macrophages and APCs and are an
efficient location for the interaction of naive or primed lymphocytes with APCs to
undergo further differentiation (Jensen et al. 1998; Neutra et al. 1987).
2.9 Antigen Sampling by M Cells
The ability of M cells to take up antigens from the lumen and transport them across
the epithelial barrier to the underlying follicle is enhanced by the structural charac-
teristics of the M cells. The reduced brush border, glycocalyx and amount of
hydrolytic enzymes on the apical membrane allow for greater interaction between
lumen antigens and the M cells. The deep invagination of the basolateral pocket
means that the distance from the apical membrane to the basolateral membrane is
shortened allowing endocytosed antigens to be delivered to the pocket lymphocytes
in as little as 15 min (Neutra et al. 1987; Ouzilou et al. 2002). Many pathogens, both
bacteria and viruses, survive the transcytosis process mediated by M cells, even
though the endosomal vesicles are acidified and can proceed to cause infection of the
mucosae (Allan and Trier 1991; Phalipon and Sansonetti 1999). M cells have been
shown to transcytose a diverse array of infectious agents across the epithelial barrier,
including bacteria, viruses, parasites and prions (Ouzilou et al. 2002; Heppner et al.
2001; Owen et al. 1986b). This surveillance function can be exploited by invasive
pathogens to yield an entry route into the underlying tissue.
Infection with poliovirus (PV), a member of picornaviridae and the causative
agent of poliomyelitis, occurs by ingestion of contaminated material via the gastro-
intestinal mucosal surfaces. Initial viral replication occurs in the FAE of PPs (Bodian
1955, 1956). PV has been shown to adhere to, and be transcytosed by M cells from
the lumen to the underlying lymphoid tissue (Ouzilou et al. 2002; Sicinski et al.
1990). Following replication of PV in the PPs, most PV infections result in asymp-
tomatic transient viraemia with 4–8% of cases developing major viraemia and <1%
develop neurological symptoms (Melnick 1996; Nathanson and Martin 1979; Sabin
1956). Members of the Retroviridae family, in particular human immunodeficiency
virus (HIV) and mouse mammary tumour virus (MMTV), have been shown to be
transcytosed by M cells. HIV-1 has been shown to adhere to M cells in rabbits and
mice and was transcytosed by M cells to the underling lymphoid follicle to infect
CD4+ T cells (Amerongen et al. 1991). Further studies showed that transcytosis of
HIV-1 by M cells was receptor mediated (Fotopoulos et al. 2002). Using the in vitro
M cell model, a lymphotropic strain of HIV-1 was transcytosed by M cells, mediated
by lactosyl cerebroside and CXCR4 receptors that are expressed on the apical
surface of Caco-2 and M cells50. A monotropic HIV-1 strain is unable to cross
in vitro M cell monolayers.
However, transfection of the Caco-2 cells with CCR5 resulted in transcytosis of
the virus50 MMTV is transmitted vertically via milk from mother to pup. The virus
is transcytosed by M cells, where it infects the pup’s macrophages and then
lymphocytes (Moore et al. 1979; Weltzin et al. 1989). Reovirus type 1, known to
be a cause of systemic and intestinal disease in mice, is transmitted via the faecal,
oral route. Reovirus type 1 has been shown to selectively adhere to and be
transcytosed by M cells in the PP where replication occurs (Wolf et al. 1981).
During cell entry, the reovirus capsid undergoes a series of disassembly steps (native
virions to ISVPs-intermediate sub-viral particles) to activate its membrane-
penetration machinery for delivery of particles into the cytoplasm (Bodkin et al.
1989). Studies have shown that conversion of native reovirus to ISVPs is a prereq-
uisite for M cell adherence, where either sigma 1 or mu 1 (capsid proteins) mediate
interaction of virus with M cell apical membranes (Amerongen et al. 1994). The
transport of reovirus has been shown to be receptor mediated, where reovirus sigma
1 protein (of ISVP) binds to glycoconjugates containing a(2-3) sialic acid that are
accessible to viral particles only on M cell apical surfaces (Helander et al. 2003).
Various bacteria are transcytosed by M cells such as Vibrio cholerae, Yersinia spp,
Salmonella spp, Shigella spp, Listeria monocytogenes, Mycobacterium tuberculosis,
Escherichia coli, Brucella abortus, Haemophilus influenzae, Streptococcus
pyogenes and Campylobacter jejuni (Jensen et al. 1998; Owen et al. 1986b;
Ackermann et al. 1988; Walker et al. 1988). Pathogenic bacteria such as Salmonella
spp, Yersinia spp and Shigella spp can cause direct infection of M cells, damaging
the M cells and spreading to neighbouring enterocytes (Jones et al. 1994). For
example, Salmonella typhimurium is selectively transcytosed by M cells, where it
is associated with extensive ruffling of the apical surface of the M cells and damage
to the FAE (Jensen et al. 1998; Sansonetti and Phalipon 1999). S. typhimurium
infection in mice is used as a model for S. typhi (the causative agent of typhoid fever)
in humans. S. typhimurium adhesion to M cells induces cytoskeleton rearrangement
with ruffling of the apical membrane and actin polymerisation resulting in engulf-
ment of the bacteria (Jones et al. 1994). In calves, S. typhimurium was taken up by M
cells within 5 min of exposure (Frost et al. 1997). Thirty minutes after infection, the
majority of M cells infected in the FAE have been sloughed off, after 1 h the cells
had been destroyed (Frost et al. 1997; Watson et al. 1995). The destruction allows
entry of the bacteria into the host and infection of neighbouring enterocytes
(Phalipon and Sansonetti 1999). Studies have identified both Salmonella pathoge-
nicity island (SPI) and the long polar fimbria (LFP) operon as having a role in the
adherence of Salmonella to M cells as both SPI and LFP mutants show reduced
virulence (Baumler et al. 1996, 1997; Clark et al. 1998). Recently, a study by Lim
and colleagues has shown that S. typhimurium associates with caveolae in the apical
membrane in the in vitro M cell model and that expression of caveolin-1 (a marker
for caveolae) mediates transcytosis of S. typhimurium (Lim et al. 2009). In vitro M
cells in which the expression of caveolin-1 had been down-regulated by siRNA did
not transcytose S. typhimurium (Lim et al. 2009). Caveolae (a type of lipid raft) are
flask-shaped invaginations in the plasma membrane that are cholesterol and
sphingolipid rich (Brown and London 1998). Caveolin-1 was not expressed by
Caco-2 cells but was expressed in M-like cells and was seen to localise with sialyl
Lewis A antigen (Lim et al. 2009). This also suggests that M cells may be identified/
isolated from the surrounding FAE and enterocytes based on lipid rafts present in the
apical membrane. Hase and colleagues have recently found that glycoprotein 2 that
is preferentially expressed by M cells binds FimH (component of type-I-pili) and
mediates transcytosis of the bacteria as glycoprotein 2 was also present in the
endocytosed vesicles containing the bacteria (Hase et al. 2009) S. typhimurium,
S. enteritidis and E. coli all express type-I-pili and their transcytosis by M cells was
mediated by glycoprotein 2 (Hase et al. 2009). Enteropathogenic E. coli are
non-invasive but cause disease by colonising the mucosal surface. M cells have
been shown to transcytose enteropathogenic E. coli that leads to the production of
secretory Ig A that limits the duration and severity of the disease (Levine et al. 1987).
Early studies identified expression of AF/R1 pili as necessary for attachment to M
cells (Inman and Cantey 1983; Sansonetti et al. 1996). Hase and colleagues have
now shown that the FimH sub-unit of the type-I-pili mediates transcytosis of E. coli
by binding glycoprotein 2 (Hase et al. 2009). V. cholerae a non-invasive pathogen
adheres to M cells inducing actin rearrangement and phagocytosis of the bacteria by
extensions of the plasma membrane fusing around the bacteria to form a phagosome
(Owen et al. 1986b). A recent study by Blanco and DiRita reported that transcytosis
of V. cholerae by M cells is mediated by bacteria-associated cholera toxin-binding
ganglioside receptor GM1 (Blanco and Dirita 2006b). Transcytosis of V. cholerae by
M cells stimulates the production and secretion of s IgA (Apter et al. 1993; Winner
3rd et al. 1991). V. Cholerae-bound s IgA promotes M cell-mediated transcytosis of
V. cholerae (Blanco and Dirita 2006).
2.10 Mucosal Vaccination
There is great interest in exploiting the transcytotic activity of M cells in the

development of oral mucosal vaccines and oral drug therapies. The lack of a
universal M cell marker or a human M cell marker has impeded M cell character-
isation and targeting for vaccine development. Oral vaccination offers advantages
over parenteral routes of vaccination. Mucosal vaccination induces both mucosal
and systemic immune responses (Belyakov et al. 1998). The mucosal immune
system is a critical part of the defence against infectious disease, as to first cause
infection many pathogens must gain access to the host by crossing the mucosae and
thus many infections are initiated at mucosal sites. The induction of specific immune
responses (both humoral and cellular) at the mucosal sites of entry could limit
infections at the point of entry. Oral vaccination does not require trained medical
personnel to administer the vaccine, thus making vaccination campaigns in the
developing world easier, where access to medical staff is often limited. Oral vaccines
are easier and safer to administer as they do not require sterile needles and syringes.
There are a limited number of oral vaccines that have been approved for use. Oral
polio vaccine (OPV) or Sabin vaccine was the most successful oral vaccine. Its use
has resulted in a dramatic reduction in paralytic poliomyelitis (Kimman and Boot
2006). However, polio vaccination strategies have changed as the attenuated oral
vaccine was found to revert to the wild-type virus giving rise to vaccine-derived
poliovirus and persistence of the virus within populations (Fine and Carneiro 1999).
Successful oral vaccines must overcome the innate immune barriers such as peri-
stalsis, mucus, secreted antibodies, stomach acid, proteases, nucleases and
the epithelia glycocalyx in the GIT. Mucosal pathogens themselves are one of the
most obvious choices for vaccine design as they have evolved to overcome the
mucosal barriers to cause disease. Currently, the most successful oral vaccines are
live attenuated S. typhi Ty21a and the previously mentioned OPV both of which are
known to target M cells through selective binding and are transcytosed by M cells to
the underlying lymphoid tissue (Sicinski et al. 1990; Jones et al. 1994; Hase et al.
2009). Currently, recombinant or attenuated strains of V. cholerae, Salmonella,
Shigella, E. coli, Yersinia and L. monocytogenes are being investigated as oral
vaccine vectors to deliver antigens to the mucosal immune system as they have
been shown to be preferentially transcytosed by M cells in the follicle of the PP
(Bowe et al. 2003; Liang et al. 2009). The use of live attenuated microbes as vaccine
vectors offers a number of advantages, they specifically bind to and are transcytosed
by M cells, they are stable in the GIT, dose size is low due to replication and they are
commercially cheaper to produce. However, pre-existing immunity to these attenu-
ated organisms may prevent them acting as vaccines. It is estimated that one out of
ten million epithelial cells in the intestinal tract is an M cell (Bye et al. 1984; Kuolee
and Chen 2008). Due to the low numbers of M cells present, it is necessary to target
vaccines to M cells to ensure that they are transcytosed. The transcriptome of the
FAE and M cells has been investigated using DNA microarrays in order to determine
novel M cells markers and the elusive universal M cell marker (Terahara et al. 2008;
Hase et al. 2005; Verbrugghe et al. 2006). Terahara and colleagues produced the first
study that isolated M cells from the surrounding FAE and isolated villus M cells
from the surrounding villus epithelium in mice. They used the selective binding of
UEA-1 and NKM 16-2-4 mAb (a newly proposed M cell-specific antibody) to M
cells to sort the labelled population (M cells) using flow cytometry (Terahara et al.
2008). They reported the preferential expression of both glycoprotein 2 and
myristoylated alanine-rich C kinase substrate (MARCKS)-like protein by M cells
in the PP (Terahara et al. 2008). Glycoprotein 2 has been shown to preferentially
bind type-I-pili and mediate transcytosis of the bacteria suggesting that designing
oral vaccines to glycoprotein 2 may aid M cell targeting (Hase et al. 2009). A recent
study by Nakato and colleagues reported that PrPC is highly expressed on the apical
surface of murine M cells (Nakato et al. 2009). PrPC is highly expressed not only by
M cells but also by follicular DCs, mature myeloid cells and activated T cells
(Thielen et al. 2001). This cellular distribution suggests that PrPC may be of interest
as a target for future vaccine design. M cells have been shown to not only transcytose
microorganisms but also to transcytose particles (up to 1 mm in size) that adhere to
their apical surface (Frey et al. 1996; Frey and Neutra 1997). This has led to the
development of vaccine strategies based on attachment of antigens to latex or poly-
DL-lactide-co-glycolide (PLG) microspheres. The microspheres are not degraded in
the GIT and are preferentially transcytosed by M cells (Jepson et al. 1993; Foster
et al. 1998; Pappo and Ermak 1989). However, targeting of the microspheres to M
cells results in greater induction of an immune response UEA-1-coated PLG micro-
particles expressing HIV peptides were found to preferentially adhere to M cells and
generate both a mucosal and systemic immune response in mice (Manocha et al.
2005). The vaccine was found to be more immunogenic when administered
mucosally than when it was administered systemically (Manocha et al. 2005).
UEA-1 has also been used to target killed Helicobacter pylori and C. jejuni
(inactivated vaccines) to M cells to induce immune responses against challenge
with the live bacteria (Chionh et al. 2009). PLG microspheres containing a surface
antigen from enterotoxigenic E. coli were used in a human trial where a modest
increase in sIgA and IgG serum levels was observed (Katz et al. 2003) Although the
vaccine itself was not overly effective, the method of vaccination did not produce
any adverse effects in the five human test subjects (Katz et al. 2003). The size of the
microspheres used in M cell targeting is an important factor for particle uptake and
thus for initiation of an immune response. Reovirus adhesion protein sigma 1 that
has been shown to mediate adherence of reovirus to apical membranes of M cells has
also been used to target M cells to induce uptake of vaccines such as an HIV DNA
vaccine (Amerongen et al. 1994; Wang et al. 2003). PV is also being investigated as
a potential vaccine vector (Andino et al. 1994). Studies have shown that PV vectors
induce both humoral and cell-specific immune responses (Mandl et al. 1998). A
great deal of recent vaccine research has been targeted towards stimulation of pattern
recognition receptors (PRR), in particular Toll-like receptors (TLR).
2.11 Pattern Recognition Receptors
PRR play a central role in the innate immune response by recognising conserved
PAMPs in microorganisms. A class of PRR called the TLR family has the ability to
recognise pathogens and pathogen-derived products and initiate signalling events
that lead to the activation of the innate immune system.
After the discovery of TLRs, several classes of cytoplasmic PRRs, including
retinoic acid-inducible gene I (RIG-I)*like helicases (RLH) and nucleotide-binding
oligomerisation domain (Nod), were identified. Nod proteins have been shown to
play a pivotal role in the detection of bacterial cell wall components within epithelial
cells. Nod1 and Nod2 recognise peptides derived from the degradation of peptido-
glycan (PGN) and when stimulated produce pro-inflammatory cytokines through the
recruitment of NFkB (Girardin et al. 2003a, b). The RLR family consists of three
members, RIG-I, melanoma differentiation-associated gene 5 (MDA5) and labora-
tory of genetics and physiology 2 (Lgp2) that are involved in the detection of viral
RNA (Kang et al. 2002; Yoneyama et al. 2004). Detection of viral RNA by RLH
leads to the production of type 1 interferons (IFNa/b) that are essential for the
development of an anti-viral immune response (Kawai et al. 2005). Viral RNA can
also be detected by RNA dependent protein kinase R that is a cytoplasmic serine
kinase which recognises short-stem loop structures within RNA in a RLH indepen-
dent manner (Jacobs and Langland 1996). Recently, several groups identified
another cytoplasmic PRR family, PYHIN proteins (pyrin an HIN domain containing
protein) that detect dsDNA (Burckstummer et al. 2009; Schroder et al. 2009).
2.12 Toll-Like Receptors
TLRs are evolutionarily conserved type 1 transmembrane proteins with leucine-rich

repeats responsible for binding various PAMP and an intracellular Toll/interleukin
1 domain responsible for initializing signalling. TLRs have been shown to be
expressed on cells of the innate immune system, such as dendritic cells, macro-
phages and antigen-presenting cells, and have been shown to be involved in phago-
cytosis and in the development of a pro-inflammatory immune response (Blander
and Medzhitov 2004).
Stimulation of the Toll/Interleukin 1 domain of the TLR by its PAMP is respon-
sible for initialising signalling, leading to dimerisation and activation of a signalling
cascade through recruitment of adaptor molecules such as MyD88 (Myeloid differ-
entiation primary response gene 88), TRIF (TIR-domain-containing adapter-
inducing interferon-b), TRAM (TICAM1) (Toll-like receptor adaptor molecule 1)
and TIRAP (Toll-interleukin 1 receptor (TIR) domain containing adaptor protein).
Early studies showed that signalling through TLR3 and TLR4 generated both type I
interferon and inflammatory cytokine responses, whereas stimulation of TLR1/
TLR2, TLR2/TLR6 and TLR5 mainly generated inflammatory cytokines that lead
to the realisation that TLRs activated distinct signalling events through adaptor
proteins mediating specific immune responses. The TLR signalling pathways can
be broadly divided into two, one the MyD88-dependent pathway that drives the
induction of inflammatory cytokines in early phase activation of NFkB via the
IL-1R-associated kinase (IRAK) pathway, and two, the TRIF-dependent pathway
that induces type I interferon as well as inflammatory cytokines through the inter-
feron regulatory factor (IRF) three pathway that results in a later phase activation of
NFkB. MyD88 is used by all TLRs bar TLR3 to activate the MyD88-dependent
pathway (Brikos and O’Neill 2008). TRIF is used by TLR3 and TLR4 and induces
the TRIF-dependent pathway. TLR4 is the only TLR molecule that can use all four
adaptor molecules and can activate either the MyD88-dependent or the TRIF-
dependent pathways. TRAM recruits TRIF to TLR4 and TIRAP recruits MyD88
to TLR2 and TLR4 to initiate signalling (Doyle and ONeill 2006). When the
MyD88-dependent signalling pathway is stimulated, MyD88 recruits members of
the IRAK family. IRAK4 is initially activated and it in turn activates IRAK1 and
IRAK2 (Kawagoe et al. 2008).
2.13 Nod1 and Nod2
The Nod-like receptors (NLR) proteins are structurally similar to R proteins that are
found in plants and are involved in disease resistance (Jones and Dangl 2006). NLRs
represent a large family (over 20 members) of PRRs that respond to various stimuli
that include PAMPs and cellular stresses (Brodsky and Monack 2009). NLRs
recognise microbial products, thereby initiating host defence pathways through the
activation of the NFkB (Brodsky and Monack 2009). Activation of NLRs has also
been shown to have a role in the activation of autophagy and cell death (Suzuki et al.
2007; Willingham et al. 2007). Nod1 and Nod2 are the best studied members of the
NLR family; they represent an intracellular pathogen-sensing system (Harton et al.
2002). The Nod1 and Nod2 proteins can structurally be divided into three regions,
the first, a carboxy terminal ligand recognition domain containing leucine-rich
repeats, and the second a central nucleotide-binding domain (also known as a
NACHT domain). Nod1 and Nod2 differ from each other in the third domain, the
amino terminal. Nod1 contains one caspase activating and recruitment domain
(CARD), whereas Nod2 contains two CARD domains. Studies have found that
Nod1 is stimulated by g-D-glutamyl-meso-diamino-pimelic acid (iE-DAP) that is
mainly derived from the PGN of Gram-negative bacteria (Chamaillard et al. 2003).
Nod2 senses muramyl dipeptide (MDP), another PGN derivative present in both
Gram-positive and Gram-negative PGN (Mc Clugage et al. 1996). Stimulation of
Nod by its ligand results in homo oligomerisation of Nod proteins, resulting in the
recruitment of adaptor protein Rip2 that mediates both Nod1- and Nod2-dependent
activation of NFkB and MAPK signalling. Although a cytosolic protein, studies
have shown that for Nod2 to be stimulated by MDP, it is necessary for Nod2 and
Rip2 to localise to the plasma membrane (Barnich et al. 2005; Lecine et al. 2007).
Nod2 is crucial for PP homeostasis (Barreau et al. 2007). Nod2 knockout mice have
an increased number of larger PPs. These PPs also had an increased number of M
cells present within the FAE. An increase in the translocation/permeability of
bacteria across the FAE was observed. However, it is unclear whether this increase
was, as a result of the increased number of M cells or, through the loss of epithelial
integrity by the loss of tight junctions within the PP or through some as of yet
undefined action of Nod2. Stimulation by the normal gut microflora of the PP in
Nod2 knockout mice leads to an increase in the production of Th1 pro-inflammatory
cytokines. Mutations in CARD15, the gene that encodes Nod2, have been associated
with the development of Crohn’s disease and Blau’s syndrome (Inohara et al. 2003;
Rose et al. 2005). Mutations in CARD4 (the gene that encodes Nod1) have been
associated with an increased risk of developing asthma and atopic eczema (Hysi
et al. 2005; Weidinger et al. 2005).
2.14 RIG-Like Helicases
RLH are a family of cytoplasmic sensors that detect viral nucleic acids. To date,
three members of the RHL family have been identified, RIG-1, MDA5 and Lgp2
(Kang et al. 2002; Yoneyama et al. 2004). Detection of viral RNA by RLH leads to
the production of type 1 IFNs that are essential for the development of an anti-viral
immune response (Kawai et al. 2005). Structurally, they contain two CARD domains
at the amino terminal and a central ATPase and helicase domain (Yoneyama et al.
2005). RIG-I contains a repressor/regulatory domain at the carboxyl terminal that
inhibits signalling (Saito et al. 2007). MDA5 contains a carboxyl terminal that is
similar to RIG-I; however, it is not known if it acts as a repressor domain (Yoneyama
et al. 2005). Lgp2 lacks a CARD domain but has a helicase and repressor domain. It
was originally suggested that Lgp2 was a negative regulatory of RIG-1 as the Lgp2
repressor domain binds the RIG-I repressor domain and thus suppresses
(Rothenfusser et al. 2005). However, a recent study has shown that Lgp2 was
required for both RIG-I and MDA5 signalling. It was also reported that Lgp2
knockout mice were more susceptible to infection with encephalomyocarditis virus
(a picornavirus) as plasmacytoid dendritic cells showed impaired production of type
I IFN (Satoh et al. 2010). Originally, it was thought that both RIG-I and MDA5 were
functionally redundant and detected poly I:C (Kang et al. 2002; Brikos and O’Neill
2008). However, the development of RIG-1 and MDA5 knockout mice allowed the
individual function of each RLH to be elucidated. In RIG-I knockout mice, the
production of IFN was reduced in dendritic cells infected with virus and vesicular
stomatitis virus (Kato et al. 2005). The same study also reported that IFN production
in plasmacytoid dendritic cells was not dependent on RIG-1 but on TLRs. Studies in
MDA5 knockout mice have shown that MDA5 mediates IFN responses to picorna-
viruses and poly I:C (Gitlin et al. 2006; Kato et al. 2006). RIG-I and MDA5 have
been shown to detect different lengths of dsRNA. In virus-infected cells, long
dsRNA (I1 kb) induces IFN via MDA5, whereas short dsRNA (B1 kb) induces
IFN via RIG-I (Kato et al. 2008). RIG-I has also been shown to detect
50 -triphosphate RNA that is generated during the replication of some viruses, this
50 modification also allows RIG-I to distinguish cellular RNA from viral RNA
(Hornung et al. 2009; Pichlmair et al. 2006). A recent in vitro assay has shown
that a recombinant RIG-I protein bound to short (25 bp) dsRNA with a 50 or 30
phosphate group as well as ssRNA with a 50 -triphosphate group (Kawai et al. 2005;
Takahasi et al. 2008). IPS-1 consists of an amino terminal CARD domain, a central
region that is proline rich and a carboxyl terminal containing a transmembrane
domain that anchors IPS-1 to the mitochondrial membrane. IPS-1 activates IKKi
and TBK1 (Seth et al. 2005). These kinases phosphorylate NFkB, IRF3 and inflam-
matory cytokines that RIG-I associates with the actin cytoskeleton through the
CARD domain, where its expression is localised to membrane ruffles in
non-polarised Caco-2 cells. In polarised cells, RIG-I expression was localised to
the apico-lateral cell junctions (Mukherjee et al. 2009). Actin depolymerisation
resulted in RIG-1 activation and the induction of IRF3 and NFkB (Mukherjee
et al. 2009). MDA5 was expressed in the cytoplasm and was not found to associate
with actin (Mukherjee et al. 2009).
2.15 Gastrointestinal Immune System and Inflammatory

Bowel Disease
Inflammatory bowel diseases (both Crohn’s disease and Ulcerative Colitis) are
chronic idiopathic, inflammatory, immune-mediated disorders of the intestine
characterised by diarrhoea, rectal bleeding, abdominal pain, fever and weight loss.
The average age of onset is late teens to early twenties. Lesions are characterised
histologically as immune-mediated pathology with large numbers of infiltrating
polymorphonuclear leukocytes, monocytes and activated lymphocytes. It is gener-
ally believed that the gut inflammation is driven through a dysregulated immune
response to commensal or “normal” (non-pathogenic) flora (Blumberg 2006; Kaser
et al. 2010). What triggers this dysregulated immune response after 20 years of
normal regulation? We cannot rule out a de novo gastrointestinal infection as a
trigger. It is clear that the maintenance of the integrity of the mucosal barrier is
essential for the prevention of dissemination of gastrointestinal pathogens and
normal commensal flora to systemic sites. Several subsets of T cells in the gut
have an important barrier-promoting role. These include gamma delta T cells, Th17,
T cells, natural killer NK and NK T cells. These cells produce a range of cytokines,
including IL17A, IL17F, IL22 and IL26 that induce antimicrobial proteins, e.g.,
defensins and chemokines strengthening the mucosal barrier (Blaschitz and
Raffatellu 2010). However, when intra-vascular T cells are induced to traffic to the
GALT or mesenteric lymph nodes subsequent to invasive infection, they undergo
antigen priming and activation. They become polarised and expand yielding effector
cells to destroy invading microorganisms in an inflammatory milieu. Critically, this
response must be effectively down-regulated on elimination of the infection to
prevent these antigen induced effector T cells from maintaining and promoting
chronic intestinal inflammation. Once naive-T cells are polarised to their
Th1/Th17 phenotype in the absence of down-regulation, they are capable of perpet-
uating inflammatory bowel disease (Koboziev et al. 2010). Probiotics have been
shown to engage both the innate and adaptive immune responses in in vitro and in
animal models in a strain-specific manner (Petrof 2009; OMahony et al. 2001) and
link this effect to cytokine balance (Mc Carthy et al. 2003). Lactobacillus UCC118
was also shown to attenuate arthritis in a murine model (Sheil et al. 2004). Feeding
mice with the probiotic Bifidobacterium infantis 35624 mediated profound inhibi-
tion of salmonella infection and LPS-induced NFkB activity. B. infantis increased
CH4+ CD25+ Foxp3+ regulatory T cell numbers in the mucosa and spleen of
conventionally colonised mice (O’Mahony et al. 2008). Mazmanian also demon-
strated the ability of a commensal B. fragilis to induce Treys in germ-free mice. This
finding demonstrates the ability of a highly selected probiotic when consumed orally
to engage and modify both the mucosal and systemic immune system (spleen) in a
fully immunocompetent animal. In human trials, probiotic consumption has also
been shown to modulate both the mucosal and systemic immune systems. Humans
consuming L. salivarius UCC118 showed significantly increased granulocyte
phagocytic activity when compared to baseline levels and placebo-fed controls.
Subjects also produced an increase in mucosal IgA antibodies to the Lactobacillus
UCC118 strain (Dunne et al. 1999). Other probiotic preparations, e.g., VSLH3
E. coli Nissle 1917 and Lactobacillus reuteri, have also been shown to attenuate
colitis in humans and in murine models (Petrof 2009). It is clear that oral consump-
tion of highly selected probiotic strains can engage even in the presence of a normal
microbiota. How could oral probiotic consumption be immunologically perceived in
the presence of the overwhelming numbers of the commensal microbiota. Oral
consumption of a bolus of 1010 probiotic bacteria that can survive gastric acid and
bile would provide a dominant microbiota in the almost sterile small bowel that
houses a significant amount of the human immune system with multiple sampling
sites.
References
Ackermann MR, Cheville NF, Deyoe BL (1988) Bovine ileal dome lymphoepithelial cells:
endocytosis and transport of Brucella abortus strain 19. Vet Pathol 25:28–35
Allan CH, Trier JS (1991) Structure and permeability differ in subepithelial villus and Peyer’s patch
follicle capillaries. Gastroenterology 100:1172–1179
Amerongen HM, Weltzin R, Farnet CM, Michetti P, Haseltine WA, Neutra MR (1991)
Transepithelial transport of HIV-1 by intestinal M cells: a mechanism for transmission of
AIDS. J Acquir Immune Defic Syndr 4:760–765
Amerongen HM, Wilson GA, Fields BN, Neutra MR (1994) Proteolytic processing of reovirus is
required for adherence to intestinal M cells. J Virol 68:8428–8432
Andino R, Silvera D, Suggett SD et al (1994) Engineering poliovirus as a vaccine vector for the
expression of diverse antigens. Science 265:1448–1451
Apter FM, Lencer WI, Finkelstein RA, Mekalanos JJ, Neutra MR (1993) Monoclonal immuno-
globulin A antibodies directed against cholera toxin prevent the toxin-induced chloride secre-
tory response and block toxin binding to intestinal epithelial cells in vitro. Infect Immun
61:5271–5278
Barnich N, Aguirre JE, Reinecker HC, Xavier R, Podolsky DK (2005) Membrane recruitment of
NOD2 in intestinal epithelial cells is essential for nuclear factor-{kappa}B activation in
muramyl dipeptide recognition. J Cell Biol 170:21–26
Barreau F, Meinzer U, Chareyre F et al (2007) CARD15/NOD2 is required for Peyer’s patches
homeostasis in mice. PLoS One 2:e523
Baumler AJ, Tsolis RM, Heffron F (1996) The lpf fimbrial operon mediates adhesion of Salmonella
typhimurium to murine Peyer’s patches. Proc Natl Acad Sci U S A 93:279–283
Baumler AJ, Tsolis RM, Valentine PJ, Ficht TA, Heffron F (1997) Synergistic effect of mutations in
invA and lpfC on the ability of Salmonella typhimurium to cause murine typhoid. Infect Immun
65:2254–2259
Belyakov IM, Derby MA, Ahlers JD et al (1998) Mucosal immunization with HIV-1 peptide
vaccine induces mucosal and systemic cytotoxic T lymphocytes and protective immunity in
mice against intrarectal recombinant HIV-vaccinia challenge. Proc Natl Acad Sci U S A
95:1709–1714
Bevins CL (2006) Paneth cell defensins: key effector molecules of innate immunity. Biochem Soc
Trans 34:263–266
Bhide SA, Wadekar KV, Koushik SA (2001) Peyer’s patches are precocious to the appendix in
human development. Dev Immunol 8:159–166
Bjerke K, Brandtzaeg P (1988) Lack of relation between expression of HLA-DR and secretory
component (SC) in follicle-associated epithelium of human Peyer’s patches. Clin Exp Immunol
71:502–507
Blanco LP, Dirita VJ (2006) Antibodies enhance interaction of Vibrio cholera with intestinal M-like
cells. Infect Immun 74:6957–6964
Blanco LP, Dirita VJ (2006b) Bacterial-associated cholera toxin and GM1 binding are required for
transcytosis of classical biotype Vibrio cholera through an in vitro M cell model system. Cell
Microbiol 8:982–998
Blander JM, Medzhitov R (2004) Regulation of phagosome maturation by signals from toll-like
receptors. Science 304:1014–1018
Blaschitz C, Raffatellu M (2010) Th17 cytokines and the gut mucosal barrier. J Clin Immunol
30:196–203
Blumberg RS (2006) Inflammation in the intestinal tract: pathogenesis and treatment. Dig Dis
27:455–464
Bodian D (1955) Viremia, invasiveness, and the influence of injections. Ann N Y Acad Sci
61:877–882
Bodian D (1956) Poliovirus in chimpanzee tissues after virus feeding. Am J Hyg 64:181–197
Bodkin DK, Nibert ML, Fields BN (1989) Proteolytic digestion of reovirus in the intestinal lumens
of neonatal mice. J Virol 63:4676–4681
Bowe F, Pickard DJ, Anderson RJ, Londono-Arcila P, Dougan G (2003) Development of attenu-
ated Salmonella strains that express heterologous antigens. Methods Mol Med 87:83–100
Brikos C, O’Neill LA (2008) Signalling of toll-like receptors. Handb Exp Pharmacol 183:21–50
Brodsky IE, Monack D (2009) NLR-mediated control of inflammasome assembly in the host
response against bacterial pathogens. Semin Immunol 21:199–207
Brown DA, London E (1998) Functions of lipid rafts in biological membranes. Annu Rev Cell Dev
Biol 14:111–136
Brown D, Cremaschi D, James PS, Rossetti C, Smith MW (1990) Brush-border membrane alkaline
phosphatase activity in mouse Peyer’s patch follicle-associated enterocytes. J Physiol
427:81–88
Burckstummer T, Baumann C, Bluml S et al (2009) An orthogonal proteomic-genomic screen
identifies AIM2 as a cytoplasmic DNA sensor for the inflammasome. Nat Immunol 10:266–272
Bye WA, Allan CH, Trier JS (1984) Structure, distribution, and origin of M cells in Peyer’s patches
of mouse ileum. Gastroenterology 86:789–801
Chamaillard M, Hashimoto M, Horie Y et al (2003) An essential role for NOD1 in host recognition
of bacterial peptidoglycan containing diaminopimelic acid. Nat Immunol 4:702–707
Chionh YT, Wee JL, Every AL, Ng GZ, Sutton P (2009) M-cell targeting of whole killed bacteria
induces protective immunity against gastrointestinal pathogens. Infect Immun 77:2962–2970
Clark MA, Jepson MA, Simmons NL, Hirst BH (1995) Selective binding and transcytosis of Ulex
europaeus 1 lectin by mouse Peyer’s patch M-cells in vivo. Cell Tissue Res 282:455–461
Clark MA, Hirst BH, Jepson MA (1998) Inoculum composition and Salmonella pathogenicity
island 1 regulate M-cell invasion and epithelial destruction by Salmonella typhimurium. Infect
Immun 66:724–731
Doyle SL, ONeill LA (2006) Toll-like receptors: from the discovery of NFkappaB to new insights
into transcriptional regulations in innate immunity. Biochem Pharmacol 72:1102–1113
Dunne C, Murphy L, Flynn S, O’Mahony L et al (1999) Probiotics: from myth to reality.
Demonstration of functionality in animal models of disease and in human clinical trials. Antonie
van Leeuwenhoek 76:279–292
Fine PE, Carneiro IA (1999) Transmissibility and persistence of oral polio vaccine viruses:
implications for the global poliomyelitis eradication initiative. Am J Epidemiol 150:1001–1021
Foster N, Clark MA, Jepson MA, Hirst BH (1998) Ulex europaeus 1 lectin targets microspheres to
mouse Peyer’s patch M-cells in vivo. Vaccine 16:536–541
Fotopoulos G, Harari A, Michetti P, Trono D, Pantaleo G, Kraehenbuhl JP (2002) Transepithelial
transport of HIV-1 by M cells is receptor-mediated. Proc Natl Acad Sci U S A 99:9410–9414
Frey A, Neutra MR (1997) Targeting of mucosal vaccines to Peyer’s patch M cells. Behring Inst
Mitt 98:376–389
Frey A, Giannasca KT, Weltzin R et al (1996) Role of the glycocalyx in regulating access of
microparticles to apical plasma membranes of intestinal epithelial cells: implications for micro-
bial attachment and oral vaccine targeting. J Exp Med 184:1045–1059
Frost AJ, Bland AP, Wallis TS (1997) The early dynamic response of the calf ileal epithelium to
Salmonella typhimurium. Vet Pathol 34:369–386
Giannasca PJ, Giannasca KT, Falk P, Gordon JI, Neutra MR (1994) Regional differences in
glycoconjugates of intestinal M cells in mice: potential targets for mucosal vaccines. Am J
Phys 267:G1108–G1121
Girardin SE, Boneca IG, Carneiro LA et al (2003a) Nod1 detects a unique muropeptide from gram-
negative bacterial peptidoglycan. Science 300:1584–1587
Girardin SE, Travassos LH, Herve M et al (2003b) Peptidoglycan molecular requirements allowing
detection by Nod1 and Nod2. J Biol Chem 278:41702–41708
Gitlin L, Barchet W, Gilfillan S et al (2006) Essential role of mda-5 in type I IFN responses to
polyriboinosinic:polyribocytidylic acid and encephalomyocarditis picornavirus. Proc Natl Acad
Sci U S A 103:8459–8464
Gullberg E, Leonard M, Karlsson J et al (2000) Expression of specific markers and particle transport
in a new human intestinal M-cell model. Biochem Biophys Res Commun 279:808–813
Harton JA, Linhoff MW, Zhang J, Ting JP (2002) Cutting edge: CATERPILLER: a large family of
mammalian genes containing CARD, pyrin, nucleotide-binding, and leucine-rich repeat
domains. J Immunol 169:4088–4093
Hase K, Ohshima S, Kawano K et al (2005) Distinct gene expression profiles characterize cellular
phenotypes of follicle-associated epithelium and M cells. DNA Res 12:127–137
Hase K, Kawano K, Nochi T et al (2009) Uptake through glycoprotein 2 of FimH(+) bacteria by M
cells initiates mucosal immune response. Nature 462:226–230
Heel KA, McCauley RD, Papadimitriou JM, Hall JC (1997) Review: Peyer’s patches. J
Gastroenterol Hepatol 12:122–136
Helander A, Silvey KJ, Mantis NJ et al (2003) The viral sigma1 protein and glycoconjugates
containing alpha2-3-linked sialic acid are involved in type 1 reovirus adherence to M cell apical
surfaces. J Virol 77:7964–7977
Heppner FL, Christ AD, Klein MA et al (2001) Transepithelial prion transport by M cells. Nat Med
7:976–977
Hornung V, Ablasser A, Charrel-Dennis M et al (2009) AIM2 recognizes cytosolic dsDNA and
forms a caspase-1-activating inflammasome with ASC. Nature 458:514–518
Hysi P, Kabesch M, Moffatt MF et al (2005) NOD1 variation, immunoglobulin E and asthma. Hum
Mol Genet 14:935–941
Inman LR, Cantey JR (1983) Specific adherence of Escherichia coli (strain RDEC-1) to membra-
nous (M) cells of the Peyer’s patch in Escherichia coli diarrhea in the rabbit. J Clin Invest 71:1–8
Inohara N, Ogura Y, Fontalba A et al (2003) Host recognition of bacterial muramyl dipeptide
mediated through NOD2. Implications for Crohn’s disease. J Biol Chem 278:5509–5512
Iwasaki A, Kelsall BL (2000) Localization of distinct Peyer’s patch dendritic cell subsets and their
recruitment by chemokines macrophage inflammatory protein (MIP)-3alpha, MIP-3beta, and
secondary lymphoid organ chemokine. J Exp Med 191:1381–1394
Jacobs BL, Langland JO (1996) When two strands are better than one: the mediators and modu-
lators of the cellular responses to double-stranded RNA. Virology 219:339–349
Jang MH, Kweon MN, Iwatani K et al (2004) Intestinal villous M cells: an antigen entry site in the
mucosal epithelium. Proc Natl Acad Sci U S A 101:6110–6115
Jensen VB, Harty JT, Jones BD (1998) Interactions of the invasive pathogens Salmonella
typhimurium, Listeria monocytogenes, and Shigella flexneri with M cells and murine Peyer’s
patches. Infect Immun 66:3758–3766
Jepson MA, Simmons NL, Savidge TC, James PS, Hirst BH (1993) Selective binding and
transcytosis of latex microspheres by rabbit intestinal M cells. Cell Tissue Res 271:399–405
Jones JD, Dangl JL (2006) The plant immune system. Nature 444:323–329
Jones BD, Ghori N, Falkow S (1994) Salmonella typhimurium initiates murine infection by
penetrating and destroying the specialized epithelial M cells of the Peyer’s patches. J Exp
Med 180:15–23
Kanaya T, Aso H, Miyazawa K et al (2007) Staining patterns for actin and villin distinguish M cells
in bovine follicle-associated epithelium. Res Vet Sci 82:141–149
Kang DC, Gopalkrishnan RV, Wu Q, Jankowsky E, Pyle AM, Fisher PB (2002) mda-5: an
interferon-inducible putative RNA helicase with double-stranded RNA-dependent ATPase
activity and melanoma growth-suppressive properties. Proc Natl Acad Sci U S A 99:637–642
Kaser A, Zeissig S, Blumberg RS (2010) Inflammatory bowel disease. Annu Rev Immunol
28:573–621
Kato H, Sato S, Yoneyama M et al (2005) Cell type-specific involvement of RIG-I in antiviral
response. Immunity 23:19–28
Kato H, Takeuchi O, Sato S et al (2006) Differential roles of MDA5 and RIG-I helicases in the
recognition of RNA viruses. Nature 441:101–105
Kato H, Takeuchi O, Mikamo-Satoh E, Hirai R, Kawai T, Matsushita K et al (2008) Length-
dependent recognition of double-stranded ribonucleic acids by retinoic acid–inducible gene-I
and melanoma differentiation–associated gene 5. J Exp Med 205:1601–1610
Katz DE, DeLorimier AJ, Wolf MK et al (2003) Oral immunization of adult volunteers with
microencapsulated enterotoxigenic Escherichia coli (ETEC) CS6 antigen. Vaccine 21:341–346
Kawagoe T, Sato S, Matsushita K et al (2008) Sequential control of toll-like receptor dependent
responses by IRAK1 and IRAK2. Nat Immunol 9:684–691
Kawai T, Takahashi K, Sato S et al (2005) IPS-1, an adaptor triggering RIG-I and Mda5-mediated
type I interferon induction. Nat Immunol 6:981–988
Kerneis S, Bogdanova A, Colucci-Guyon E, Kraehenbuhl JP, Pringault E (1996) Cytosolic
distribution of villin in M cells from mouse Peyer’s patches correlates with the absence of a
brush border. Gastroenterology 110:515–521
Kerneis S, Bogdanova A, Kraehenbuhl JP, Pringault E (1997) Conversion by Peyer’s patch
lymphocytes of human enterocytes into M cells that transport bacteria. Science 277:949–952
Kimman TG, Boot H (2006) The polio eradication effort has been a great success–let’s finish it and
replace it with something even better. Lancet Infect Dis 6:675–678
Koboziev I, Karrlson F, Grisham MB (2010) Gut-associated lymphoid tissue, T cell trafficking, and
chronic intestinal inflammation. Ann N Y Acad Sci 1207:E86–E93
Kraehenbuhl JP, Neutra MR (1992) Transepithelial transport and mucosal defence II: secretion of
IgA. Trends Cell Biol 2:170–174
Kuolee R, Chen W (2008) M cell-targeted delivery of vaccines and therapeutics. Expert Opin Drug
Deliv 5:693–702
Lecine P, Esmiol S, Metais JY et al (2007) The NOD2-RICK complex signals from the plasma
membrane. J Biol Chem 282:15197–15207
Levine MM, Herrington D, Murphy JR et al (1987) Safety, infectivity, immunogenicity, and in vivo
stability of two attenuated auxotrophic mutant strains of Salmonella typhi, 541Ty and 543Ty, as
live oral vaccines in humans. J Clin Invest 79:888–902
Liang S, Hosur KB, Nawar HF, Russell MW, Connell TD, Hajishengallis G (2009) In vivo and
in vitro adjuvant activities of the B subunit of type IIb heat-labile enterotoxin (LT-IIb-B5) from
Escherichia coli. Vaccine 27:4302–4308
Lim JS, Na HS, Lee HC et al (2009) Caveolae-mediated entry of Salmonella typhimurium in a

human M-cell model. Biochem Biophys Res Commun 390:1322–1327
Mandl S, Sigal LJ, Rock KL, Andino R (1998) Poliovirus vaccine vectors elicit antigen specific
cytotoxic T cells and protect mice against lethal challenge with malignant melanoma cells
expressing a model antigen. Proc Natl Acad Sci U S A 95:8216–8221
Manocha M, Pal PC, Chitralekha KT et al (2005) Enhanced mucosal and systemic immune
response with intranasal immunization of mice with HIV peptides entrapped in PLG micropar-
ticles in combination with Ulex Europaeus-I lectin as M cell target. Vaccine 23:5599–5617
Mc Carthy J, O’Mahony L, O’Callaghan L, Sheil B, Vaughan EE et al (2003) Double blind placebo
controlled trial of two probiotic strains in interleukin 10 knockout mice and mechanistic link
with cytokine balance. Gut 52:975–980
Mc Clugage SG, Low FN, Zimny ML (1996) Porosity of the basement membrane overlying Peyer’s
patches in rats and monkeys. Gastroenterology 91:1128–1133
Melnick JL (1996) Current status of poliovirus infections. Clin Microbiol Rev 9:293–300
Mestecky J (2005) Mucosal immunology. Elsevier Academic Press, Amsterdam
Moore DH, Long CA, Vaidya AB, Sheffield JB, Dion AS, Lasfargues EY (1979) Mammary tumor
viruses. Adv Cancer Res 29:347–418
Mooseker MS (1985) Organization, chemistry, and assembly of the cytoskeletal apparatus of the
intestinal brush border. Annu Rev Cell Biol 1:209–241
Mukherjee A, Morosky SA, Shen L et al (2009) Retinoic acid-induced gene-1 (RIG-I) associates
with the actin cytoskeleton via caspase activation and recruitment domain dependent interac-
tions. J Biol Chem 284:6486–6494
Nakato G, Fukuda S, Hase K, Goitsuka R, Cooper MD, Ohno H (2009) New approach for m-cell-
specific molecules screening by comprehensive transcriptome analysis. DNA Res 16:227–235
Nathanson N, Martin JR (1979) The epidemiology of poliomyelitis: enigmas surrounding its
appearance, epidemicity, and disappearance. Am J Epidemiol 110:672–692
Neutra MR, Kozlowski PA (2006) Mucosal vaccines: the promise and the challenge. Nat Rev
Immunol 6:148–158
Neutra MR, Phillips TL, Mayer EL, Fishkind DJ (1987) Transport of membrane-bound macromol-
ecules by M cells in follicle-associated epithelium of rabbit Peyer’s patch. Cell Tissue Res
247:537–546
Neutra MR, Pringault E, Kraehenbuhl JP (1996) Antigen sampling across epithelial barriers and
induction of mucosal immune responses. Annu Rev Immunol 14:275–300
Nochi T, Yuki Y, Matsumura A et al (2007) A novel M cell-specific carbohydrate targeted mucosal
vaccine effectively induces antigen-specific immune responses. J Exp Med 204:2789–2796
O’Leary AD, Sweeney EC (1987) Lymphoglandular complexes in the diseased colon. Ir J Med Sci
156:353–360
O’Mahony C, Scully P, O’Mahony D, Murphy S et al (2008) Commensal-induced regulatory T
cells mediate protection against pathogen-stimulated NF-kB activation. PLoS Pathog 4(8):1–10
OMahony L, Feeney M, O’Halloran S, Murphy L, Kiely B et al (2001) Probiotic impact on
microbial flora, inflammation and tumour development in IL-10 knockout mice. Aliment
Pharmacol Ther 15:1219–1225
Ouzilou L, Caliot E, Pelletier I, Prevost MC, Pringault E, Colbere-Garapin F (2002) Poliovirus
transcytosis through M-like cells. J Gen Virol 83:2177–2182
Owen RL (1977) Sequential uptake of horseradish peroxidase by lymphoid follicle epithelium of
Peyer’s patches in the normal unobstructed mouse intestine: an ultrastructural study. Gastroen-
terology 72:440–451
Owen RL, Bhalla DK (1983) Cytochemical analysis of alkaline phosphatase and esterase activities
and of lectin-binding and anionic sites in rat and mouse Peyer’s patch M cells. Am J Anat
168:199–212
Owen RL, Apple RT, Bhalla DK (1986a) Morphometric and cytochemical analysis of lysosomes in
rat Peyer’s patch follicle epithelium: their reduction in volume fraction and acid phosphatase
content in M cells compared to adjacent enterocytes. Anat Rec 216:521–527
Owen RL, Pierce NF, Apple RT, Cray WC Jr (1986b) M cell transport of Vibrio cholera from the
intestinal lumen into Peyer’s patches: a mechanism for antigen sampling and for microbial
transepithelial migration. J Infect Dis 153:1108–1118
Pappo J, Ermak TH (1989) Uptake and translocation of fluorescent latex particles by rabbit Peyer’s
patch follicle epithelium: a quantitative model for M cell uptake. Clin Exp Immunol 76:144–148
Pappo J, Owen RL (1988) Absence of secretory component expression by epithelial cells overlying
rabbit gut-associated lymphoid tissue. Gastroenterology 95:1173–1177
Petrof EO (2009) Anti-inflamm anti-allergy agents. Med Chem 8(3):260–269
Phalipon A, Sansonetti PJ (1999) Microbial-host interactions at mucosal sites. Host response to
pathogenic bacteria at mucosal sites. Curr Top Microbiol Immunol 236:163–189
Pichlmair A, Schulz O, Tan CP et al (2006) RIG-I-mediated antiviral responses to single-stranded
RNA bearing 50 -phosphates. Science 314:997–1001
Regoli M, Bertelli E, Borghesi C, Nicoletti C (1995) Three-dimensional (3D-) reconstruction of M
cells in rabbit Peyer’s patches: definition of the intraepithelial compartment of the follicle-
associated epithelium. Anat Rec 243:19–26
Rose CD, Doyle TM, McIlvain-Simpson G et al (2005) Blau syndrome mutation of CARD15/
NOD2 in sporadic early onset granulomatous arthritis. J Rheumatol 32:373–375
Rothenfusser S, Goutagny N, DiPerna G et al (2005) The RNA helicase Lgp2 inhibits
TLR-independent sensing of viral replication by retinoic acid-inducible gene-I. J Immunol
175:5260–5268
Sabin AB (1956) Pathogenesis of poliomyelitis; reappraisal in the light of new data. Science
123:1151–1157
Saito T, Hirai R, Loo YM et al (2007) Regulation of innate antiviral defences through a shared
repressor domain in RIG-I and LGP2. Proc Natl Acad Sci U S A 104:582–587
Sansonetti PJ, Phalipon A (1999) M cells as ports of entry for enteroinvasive pathogens: mecha-
nisms of interaction, consequences for the disease process. Semin Immunol 11:193–203
Sansonetti PJ, Arondel J, Cantey JR, Prevost MC, Huerre M (1996) Infection of rabbit Peyer’s
patches by Shigella flexneri: effect of adhesive or invasive bacterial phenotypes on follicle-
associated epithelium. Infect Immun 64:2752–2764
Satoh T, Kato H, Kumagai Y et al (2010) LGP2 is a positive regulator of RIG-I and MDA5-
mediated antiviral responses. Proc Natl Acad Sci U S A 107:1512–1517
Schroder K, Muruve DA, Tschopp J (2009) Innate immunity: cytoplasmic DNA sensing by the
AIM2 inflammasome. Curr Biol 19:R262–R265
Seth RB, Sun L, Ea CK, Chen ZJ (2005) Identification and characterization of MAVS, a mito-
chondrial antiviral signaling protein that activates NFkappaB and IRF 3. Cell 122:669–682
Sharma R, van Damme EJ, Peumans WJ, Sarsfield P, Schumacher U (1996) Lectin binding reveals
divergent carbohydrate expression in human and mouse Peyer’s patches. Histochem Cell Biol
105:459–465
Sheil B, McCarthy J, OMahony L, Bennett MW, Ryan P et al (2004) Is the mucosal route of
administration essential for probiotic function? Subcutaneous administration is associated with
attenuation of murine colitis and arthritis. Gut 53:694–700
Sicinski P, Rowinski J, Warchol JB et al (1990) Poliovirus type 1 enters the human host through
intestinal M cells. Gastroenterology 98:56–58
Sierro F, Pringault E, Assman PS, Kraehenbuhl JP, Debard N (2000) Transient expression of M-cell
phenotype by enterocyte-like cells of the follicleassociated epithelium of mouse Peyer’s
patches. Gastroenterology 119:734–743
Smith MW (1985) Selective expression of brush border hydrolases by mouse Peyer’s patch and
jejunal villus enterocytes. J Cell Physiol 124:219–225
Suzuki T, Franchi L, Toma C et al (2007) Differential regulation of caspase-1 activation, pyroptosis,
and autophagy via Ipaf and ASC in Shigella-infected macrophages. PLoS Pathog 3:e111
Takahasi K, Yoneyama M, Nishihori T et al (2008) Nonself RNA-sensing mechanism of RIG-I
helicase and activation of antiviral immune responses. Mol Cell 29:428–440
Terahara K, Yoshida M, Igarashi O et al (2008) Comprehensive gene expression profiling of

Peyer’s patch M cells, villous M-like cells, and intestinal epithelial cells. J Immunol
180:7840–7846
Thielen C, Antoine N, Melot F, Cesbron JY, Heinen E, Tsunoda R (2001) Human FDC express
PrPc in vivo and in vitro. Dev Immunol 8:259–266
Verbrugghe P, Waelput W, Dieriks B, Waeytens A, Vandesompele J, Cuvelier CA, Murine M
(2006) Murine M cells express annexin V specifically. J Pathol 209:240–249
Walker RI, Schmauder-Chock EA, Parker JL, Burr D (1988) Selective association and transport of
Campylobacter jejuni through M cells of rabbit Peyer’s patches. Can J Microbiol 34:1142–1147
Wang X, Hone DM, Haddad A, Shata MT, Pascual DW (2003) M cell DNA vaccination for CTL
immunity to HIV. J Immunol 171:4717–4725
Watson PR, Paulin SM, Bland AP, Jones PW, Wallis TS (1995) Characterization of intestinal
invasion by Salmonella typhimurium and Salmonella dublin and effect of a mutation in the invH
gene. Infect Immun 63:2743–2754
Weidinger S, Klopp N, Rummler L et al (2005) Association of NOD1 polymorphisms with atopic
eczema and related phenotypes. J Allergy Clin Immunol 116:177–184
Weltzin R, Lucia-Jandris P, Michetti P, Fields BN, Kraehenbuhl JP, Neutra MR (1989) Binding and
transepithelial transport of immunoglobulins by intestinal M cells: demonstration using mono-
clonal IgA antibodies against enteric viral proteins. J Cell Biol 108:1673–1685
Willingham SB, Bergstralh DT, O’Connor W et al (2007) Microbial pathogen-induced necrotic cell
death mediated by the inflammasome components CIAS1/cryopyrin/NLRP3 and ASC. Cell
Host Microbe 2:147–159
Winner L 3rd, Mack J, Weltzin R, Mekalanos JJ, Kraehenbuhl JP, Neutra MR (1991) New model
for analysis of mucosal immunity: intestinal secretion of specific monoclonal immunoglobulin
A from hybridoma tumors protects against Vibrio cholerae infection. Infect Immun 59:977–982
Wolf JL, Rubin DH, Finberg R et al (1981) Intestinal M cells: a pathway for entry of reovirus into
the host. Science 212:471–472
Wolf JL, Kauffman RS, Finberg R, Dambrauskas R, Fields BN, Trier JS (1983) Determinants of
reovirus interaction with the intestinal M cells and absorptive cells of murine intestine. Gastro-
enterology 85:291–300
Yoneyama M, Kikuchi M, Natsukawa T et al (2004) The RNA helicase RIG-I has an essential
function in double-stranded RNA-induced innate antiviral responses. Nat Immunol 5:730–737
Yoneyama M, Kikuchi M, Matsumoto K et al (2005) Shared and unique functions of the DExD/H-
box helicases RIG-I, MDA5, and LGP2 in antiviral innate immunity. J Immunol
175:2851–2858
Chapter 3
Immunomarkers for Detection of GI
Malignancies
Ravikiran Tekupalli, Santosh Anand, Sowbhagya Ramachandregowda,

Anupama Sindhghatta Kariyappa, and Bhagyalakshmi Dundaiah
Abstract Gastrointestinal (GI) cancers are related to several diseases of the GI tract
including adenocarcinomas of the esophagus, stomach, colon, and rectum, which are
among the leading cause of morality worldwide. In spite of rapid development in
molecular and genomic techniques, prognosis of the malignant potential of GI
cancers is challenging. Immunomarkers may play an important role in the prediction
of malignant behavior of these cancers. In this chapter, we have made an attempt to
provide a comprehensive review on immunomarkers which are discovered recently
and used in the detection of GI malignancies. These immunomarkers can help
clinicians in the early diagnosis and as therapeutic targets to treat GI cancers.
Keywords Immunomarkers · Esophageal cancer · Gastric cancer · Colorectal

cancer · Carcinoembryonic antigen · Vascular endothelial growth factor
3.1 Introduction
Gastrointestinal (GI) cancers are considered to be an overwhelming global health

issue, and are among the principal cause of morbidity and deaths worldwide. GI
cancers are associated with malignancies emerging in the esophagus, stomach,
intestine, colon, and rectum. The two primary GI malignancies are gastric and
colorectal cancers, which affect around 1.4 million and 9.5 lakh deaths, respectively,
per year (Vedeld et al. 2018). Epigenetic alterations are found to be responsible for
cancer initiation and progression in GI cancers. DNA methylation is the most
R. Tekupalli (*) · A. S. Kariyappa · B. Dundaiah

Department of Biotechnology, Bangalore University, Bengaluru, India
e-mail: ravikiran@bub.ernet.in
S. Anand · S. Ramachandregowda
Department of Biotechnology, Ramaiah College of Arts, Science and Commerce, Bengaluru,
India
https://doi.org/10.1007/978-981-15-6487-1_3
42 R. Tekupalli et al.
common unusual epigenetic change involved in these tumors (Portela and Esteller
2010). They include both benign as well as malignant forms and represent an array
of malignant potential projected primarily by the size and mitotic activity. Computed
tomography, endoscopy, and colonoscopy are the gold standards for early detection
of these cancers. However, these methods are invasive, inconvenient, expensive, and
are hindered by low compliance rates (Taylor et al. 2011). Non-invasive diagnostics
such as blood-dependent assays have the ability to improvise the patient amenability
in relation to invasive methods. Immunomarkers are disease-specific and biologi-
cally related to the pathophysiological development process of the disease. Further,
exclusive diagnostic molecular techniques and skilled labor are avoided, and there is
no need for tissue processing when compared to genetic markers. In this chapter, we
have emphasized the significance of promising immunomarkers for the initial
detection and prevention of GI malignancies, as represented in Table 3.1.
3.2 Esophageal Cancer Immunomarkers
Esophageal cancer (EC) is the fourth most evident cancer in males with a high
mortality rate worldwide (Chava et al. 2012). The histological subtypes of EC found
globally are adenocarcinoma and squamous cell carcinoma, which may vary
depending on lifestyle, genetic susceptibility, and various environmental factors
(Di Pardo et al. 2016). EC is normally diagnosed in the middle-late situation, thereby
extending treatment duration resulting in reduced survival rate. Recent evidence
suggests that EC tissues abnormally express different molecules that help in the
detection, diagnosis, and treatment of EC.
Epidermal growth factor receptor (EGFR) is a membrane protein exhibiting
tyrosine kinase activity. Enhanced EGFR levels have been reported in EC, which
is associated with disease progression, tumor metastases, and can be used to forecast
patient prognosis. HER2, belonging to the EGFR family, also performs a crucial role
in the treatment of EC. Chan et al. (2012) reported a decreased survival rate with
positive expression of HER2. Besides these receptors, E-cadherin (cell adhesion
molecule), α-catenin, and β-catenin (cytoskeleton linking molecules) are the three
important proteins having promising prognostic importance in EC. Increased expres-
sion of these proteins is directly proportional to the increased survival of patients.
The ACTN-4 (α-actinins) are actin-binding proteins that contribute a significant role
in cell–cell adhesion, fiber formation, and maintaining cell structure. Laminin is a
glycoprotein of the basement membrane, which mediates several biological func-
tions that are facilitated via interaction with cell-specific membrane receptors.
67 kDa laminin receptor has been reported to be overexpressed by cytokines,
extracellular matrix proteins, and inflammatory agents. Fu et al. (2007) demonstrated
that the upregulation of these two proteins could be employed for predicting the
stage of tumor and patient prognosis in esophageal squamous cell carcinomas
(ESCC).
3 Immunomarkers for Detection of GI Malignancies 43
Table 3.1 Immunomarkers for gastrointestinal cancers

Cancer type Biomarkers Specimen Methodology
Esophageal cancer EGFR Tissue IHC
ACTN-4 Tissue 2-DE
Cox-2 Tissue IHC
VEGF Tissue IHC
Laminin Tissue 2-DE
TGF-β receptors Tissue IHC
Cyclin D1 Tissue IHC
Cyclin E1 Tissue IHC
MCM4 Tissue IHC
MCM7 Tissue IHC
Gastric cancer HER Tissue IHC
VEGF Tissue IHC
YB-1 Tissue IHC
SAT-B2 Tissue WB
IL-1b, IL-8, and TFF-α Blood sample ELISA
CEA, CA19-9, and CA72-4 Tissue IHC
bcl-2 and bax Tissue IHC
DKK3 Tissue IHC
Colorectal cancer CEA Tissue RT-PCR
CYRA 21-1 Serum ELISA
Osteoprotegerin Tissue IHC
TIMP Serum ELISA
ER-β Tissue IHC
IGF Tissue IHC
P53 Tissue IHC
Ki 67 Tissue IHC
Cyclin D1 Tissue IHC
IL6 Serum ELISA
IHC Immunohistochemistry, 2-DE Two-Dimensional Gel Electrophoresis, WB Western Blotting
Angiogenic factors, like vascular endothelial growth factor (VEGF), and

cyclooxygenase-2 (Cox-2) are potential prognostic indicators in patients with
EC. Studies have reported an association between enhanced VEGF and COX-2
expression with patient survival and cancer stage (Kulke et al. 2004; Prins et al.
2012).
Besides these two angiogenic factors, TGF-β receptors also perform a vital
function in the progression of tumor by inhibiting epithelial cell proliferation.
Decreased expression of these receptors in ESCC is related to enhanced tumor
growth, metastasis of lymph node, and poor prediction (Fukai et al. 2003).
The p53 protein is a DNA-binding protein which plays a vital role in tumorigen-
esis as it regulates cell growth, apoptosis, and angiogenesis. The reduced expression
of p53 protein is linked with a better prognosis, as reported by Ikeguchi et al. (2000).
Survivin, an inhibitor of apoptosis, is proven as an efficient marker for the detection

of cancer, its diagnosis and prediction of outcome. Studies by Rosato et al. (2006)
discovered that the expression of surviving could be a predictive factor only
in ESCC.
Cyclin D1 and E1 are vital proteins that play a major function in cell cycle, and
the increased levels of these two proteins have been reported in various tumor tissues
(Zhao et al. 2015). The upregulation of cyclin D1 protein may offer vital prognostic
evidence and for determining the optimal therapeutic approach for EC (Nagasawa
et al. 2001).
The minichromosomal maintenance (MCM) protein family comprises six pro-
teins playing a vital part in DNA replication (Frigola et al. 2013). Findings of Choy
et al. (2016) showed increased expression of MCM4 and MCM7 in EC. These two
proteins serve as significant proliferation markers for the assessment of EC.
3.3 Gastric Cancer Immunomarkers
Gastric cancer (GC), a global health issue, is one of the prominent causes of cancer-
associated death globally (Wu et al. 2015). Presently, the tumor staging system and
histologic cataloging are used for routine prognosis and treatment among GC
patients but lacks substantial prognostic value (Jiang et al. 2018).
The human epidermal growth factor receptor (HER) family includes four differ-
ent receptors, HER 1,2,3, and 4. HER2 is a well-established marker for GC, and
these receptors work together in the maintenance of various functions like cell
division, differentiation, and survival. This receptor family is involved in the pro-
gression of diverse tumor types and is documented targets for multiple cancers
therapy (Lastraioli et al. 2012).
The vascular endothelial growth factor (VEGF) family serves a pivotal role in
processes including inflammation, vascular regeneration, and angiogenesis. This
family comprises of VEGF-A, B, C, D and E, among which VEGF-A has long
been recognized as an important regulator in tumor angiogenesis (Ferrara et al.
2007). Although this family has been regarded to effect tumor-linked angiogenesis,
the prognostic implication of VEGF expression is still debatable in GC.
Y-box binding protein-1 (YB-1) is a versatile protein associated with angiogen-
esis, proliferation, and aggressiveness of cancer cells. Its upregulation in different
cancers was connected with adverse patient diagnosis. Studies have demonstrated
that YB-1 might be an essential biomarker for the management of GC patients
(Wu et al. 2015).
Special AT-rich sequence-binding protein 2 (SATB2) is a nuclear transcription
factor involved in transcription and chromatin remodeling. Wu et al. (2016) reported
that SATB2 expression was reduced in GC tissues. The decreased expression of
SATB2 is correlated with a shortened lifespan of GC patients.
The most widely used serum-based tumor markers in GC are carcinoembryonic
antigen (CEA), CA 72-4, and cancer-related antigen 19-9 (CA 19-9). Majority of the
studies suggested that CA 72-4, a glycoprotein present on the tumor cell surface, is
the most potential marker for detecting GC. Other important serum markers for GC
detection are alpha-fetoprotein, CA125, and sialyl Tn antigens (Shimada et al. 2014).
Apart from traditional serum markers, studies have shown that interleukin 1b
(IL-1b), IL-8 and tumor necrosis factor-α (TNF-α), may be regarded as reliable
markers in screening and prognostic assessment of gastric carcinoma (Macrì et al.
2006).
Cyclooxygenase-2 (COX-2) performs an essential function in carcinogenesis and
inflammation. Studies suggest that they are involved in angiogenesis, metastasis,
invasion, proliferation, and apoptosis (Wang and Du Bois 2006). Mrena et al. (2010)
reported that COX-2 expression could be used as a valuable indicator for aggressive
tumor growth in GC.
bcl-2 family comprises bcl-2 and bax that play a remarkable role in apoptotic
regulatory mechanism. The bcl-2 expression can serve as one of the important
biomarkers for predicting the prognosis of GC patients and may be a candidate for
detecting the different stages of cancer apart from conventional sources (Liu et al.
2011).
Dickkopf-related protein 3 (DKK3) may act as a tumor inhibitor, and its expres-
sion is reduced in different cancer types. Park et al. (2015) reported decreased DKK3
protein level in GC patients, which can be employed as a prognostic indicator.
3.4 Colorectal Cancer Immunomarkers
Colorectal cancer (CRC) is a common cancer worldwide affecting both men and
women, accounting for around 700,000 deaths annually (Arnold et al. 2017; Guo
et al. 2018). It is a heterogeneous disease varying in clinical presentation and
molecular characteristics (Linnekamp et al. 2018). The well-established tools for
screening include colonoscopy, flexible sigmoidoscopy, and fecal occult blood
analysis (Kolligs 2016). Biochemical indicators for CRC are potentially helpful in
screening, diagnosis, and prognosis of the disease. Although numerous markers have
been defined for CRC, confusion persists with regard to the usefulness of these
markers (Duffy et al. 2003).
Carcinoembryonic antigen (CEA) has been regularly employed as a serum-based
marker to identify CRC metastasis/recurrences. Moreover, its detection as a marker
in tumor samples with prognostic evidence has not been well established. Apart from
CEA, sialyl Lewis antigen (sLex), a glycoprotein found on the cell surface may act
as a ligand for endothelial leucocyte adhesion protein facilitating the interaction
between tumor cells and endothelial cells. The upregulation of this glycoprotein is
related to augmented tumor cell progression (McLeod and Murray 1999; Crawford
et al. 2003). Cytokeratin 19 fragment (CYRA 21-1) is also an established marker that
exhibited a better sensitivity in stage IV when compared to the early stages of CRC
(Wild et al. 2010).
Tissue inhibitor of metalloproteinase 1 (TIMP-1), a glycoprotein that triggers cell

growth, inhibits apoptosis, and suppresses metalloprotease activity (Duffy et al.
2003). The TIMP-1 content was found to be elevated significantly in CRC
(Holten-Andersen et al. 2002). Studies by Birgisson et al. (2018) analyzed 92 plasma
proteins in CRC patients, among which osteoprotegerin was found to be a potent
predictive marker and can be a possible target for disease management.
The level of estrogen receptor β (ER-β) is related to patient prognosis and as an
important marker of tumor development and a possible target for chemoprevention
in CRC patients (Filho et al. 2018). Insulin-like growth factor (IGF), 1, 2, and 1R
regulate cell metabolism and play a remarkable role in apoptosis and proliferation.
Recent evidence revealed enhanced levels of IGF-1 and 2 in the initial identification
of CRC pathogenesis (Peters et al. 2003).
Interleukin-6 (IL-6) is a pro-inflammatory cytokine involved in many biological
functions. It is synthesized by various cell types and performs a principal role in
immunity, metabolism, hematopoiesis, angiogenesis, neuronal development and
inflammation. Xu et al. (2016) reported the prognostic and diagnostic significance
of serum IL-6 in CRC and reported that IL-6 could be used as a valuable biomarker
that could distinguish the CRC patients from healthy persons (Vainer et al. 2018).
p53, a tumor suppressor gene, codes for a transcription factor that governs the
expression of regulatory genes related to angiogenesis, apoptosis, and cell cycle. It
has been extensively used as an indicative and prognostic therapeutic marker for
CRC (Duffy et al. 2007). bcl-2 is an antiapoptotic protein that arrests cell death in
normal and tumor cells. Many investigators have found a strong correlation between
bcl-2 expression and CRC prognosis (Bosari et al. 1995). Ki-67 and Cyclin D1 are
the critical proteins associated with cell cycle regulation. However, there is no
correlation between the upregulation of these proteins with prognosis in CRC
(Hilska et al. 2005).
Transforming growth factor (TGF) family comprises α and β subgroups, which
promotes the growth and proliferation of colon cancer cells. In addition to TGF,
EGFR expression also has a prognostic significance in CRC.
Apart from above-discussed markers, recent evidence has suggested that hor-
mones also act as an important biomarker for cancer detection. Adipocytokines, such
as resistin, visfatin, leptin, and adiponectin are adipocyte-secreted hormones asso-
ciated with colorectal malignancies. Studies by Nakajima et al. (2010) documented
that resistin, visfatin, and adiponectin levels may be good indicators of CRC stage
progression. Glycoprotein hormone hCG beta upregulation has been documented in
CRC patients (Lundin et al. 2000). Studies by Pressler et al. (2011) reported that
organic anion-transporting proteins are significantly elevated in colon cancer and can
be used as a biomarker for chemotherapy management. Prolactin, a pituitary gland
hormone, is overexpressed in CRC. Soroush et al. (2004) demonstrated that prolactin
could be a better tumor indicator than CEA in CRC patients.
3.5 Concluding Remarks
In conclusion, the identification of novel tumor markers is one of the thrust areas of
cancer research. The overall review of the biomarkers in this chapter could throw
light on the recognition of efficient biomarkers for GI cancers, at different stages of
developmental and extent of malignancy. Further, it is essential to know about
clinical aspects of these biomarkers to have a better understanding of their physio-
logical, pathophysiological, and biochemical aspects. However, knowledge in rela-
tion to tumor markers has to be constantly updated with respect to advances in
clinical manifestation and medicine.
Acknowledgement We thank the Department of Microbiology and Biotechnology, Bangalore

University, Bengaluru, India, for providing essential support.
Conflicts of Interest The authors declare no conflict of interest.
References
Arnold M, Sierra MS, Laversanne M, Soerjomataram I, Jemal A, Bray F (2017) Global patterns and
trends in colorectal cancer incidence and mortality. Gut 66:683–691
Birgisson H, Tsimogiannis K, Freyhult E, Kamali-Moghaddam M (2018) Plasma protein profiling
reveal osteoprotegerin as a marker of prognostic impact for colorectal cancer. Transl Oncol
11:1034–1043
Bosari S, Moneghini L, Graziani D, Lee AKC, Murray JJ, Coggi G, Viale G (1995) Bcl-2
oncoprotein in colorectal hyperplastic polyps, adenomas, and adenocarcinomas. Hum Pathol
26(5):534–540
Chan DSY, Twine CP, Lewis WG (2012) Systematic review and meta-analysis of the influence of
HER2 expression and amplification in operable oesophageal cancer. J Gastrointest Surg
16:1821–1829
Chava S, Mohan V, Shetty PJ, Manolla ML, Vaidya S, Khan IA, Waseem GL, Boddala P, Ahuja
YR, Hasan Q (2012) Immunohistochemical evaluation of p53, FHIT, and IGF2 gene expression
in esophageal cancer. Dis Esophagus 25(1):81–87
Choy B, LaLonde A, Que JW, Wu TT, Zhou ZR (2016) MCM4 and MCM7, potential novel
proliferation markers, significantly correlated with Ki-67, Bmil, and cyclin E expression in
esophageal adenocarcinoma, squamous cell carcinoma, and precancerous lesions. Hum Pathol
57:126–135
Crawford NPS, Colliver DW, Galandiuk S (2003) Tumor markers and colorectal cancer: utility in
management. J Surg Oncol 84:239–248
Di Pardo BJ, Bronson NW, Diggs BS, Thomas CR Jr, Hunter JG, Dolan JP (2016) The global
burden of esophageal cancer: a disability-adjusted life-year approach. World J Surg 40:395–401
Duffy MJ, van Dalen A, Haglund C, Hansson L, Klapdor R, Lamerz R, Nilsson O, Sturgeon C,
Topolcan O (2003) Clinical utility of biochemical markers in colorectal cancer: European Group
on Tumour Markers (EGTM) guidelines. Eur J Cancer 39:718–727
Duffy MJ, van Dalen A, Haglund C, Hansson L, Holinski-Feder E, Klapdor R, Lamerz R,
Peltomaki P, Sturgeon C, Topolcan O (2007) Tumour markers in colorectal cancer: European
Group on Tumour Markers (EGTM) guidelines for clinical use. Eur J Cancer 43:1348–1360
Ferrara N, Mass RD, Campa C, Kim R (2007) Targeting VEGF-A to treat cancer and age-related
macular degeneration. Annu Rev Med 58:491–504
Filho PRS, Junior SA, Begnami MD, Ferreira FO, Nakagawa WT, Spencer RMSB, Bezzera TS,
Boggiss PE, Lopes A (2018) Estrogen receptor β as a prognostic marker of tumor progression in
colorectal cancer with familial adenomatous polyposis and sporadic polyps. Pathol Oncol Res
24:533–540
Frigola J, Remus D, Mehanna A, Diffley FX (2013) ATPase-dependent quality control of DNA
replication origin licensing. Nature 495:339–343
Fu L, Qin YR, Xie D, Chow HY, Ngai SM, Kwong DLW, Li Y, Guan XY (2007) Identification of
alpha-actinin 4 and 67 kDa laminin receptor as stage-specific markers in esophageal cancer via
proteomic approaches. Cancer 110:2672–2681
Fukai Y, Fukuchi M, Masuda N, Osawa H, Kato H, Nakajima T, Kuwano H (2003) Reduced
expression of transforming growth factor-beta receptors is an unfavorable prognostic factor in
human esophageal squamous cell carcinoma. Int J Cancer 104:161–166
Guo PD, Sun ZW, Lai HJ, Yang J, Wu PP, Guo YD, Sun J (2018) Clinicopathological analysis of
PD-L2 expression in colorectal cancer. Onco Targets Ther 11:7635–7642
Hilska M, Collan YU, Laine VJO, Kossi J, Hirsimaki P, Laato M, Roberts PJ (2005) The
significance of tumor markers for proliferation and apoptosis in predicting survival in colorectal
cancer. Dis Colon Rectum 48:2197–2208
Holten-Andersen MN, Christensen IJ, Nielsen HJ, Stephens RW, Jensen V, Nielsen OH,
Sorensen S, Overgaard J, Lilja H, Harris A, Murphy G, Brunner N (2002) Total levels of tissue
inhibitor of metalloproteinases 1 in plasma yield high diagnostic sensitivity and specificity in
patients with colon cancer. Clin Cancer Res 8:156–164
Ikeguchi M, Oka S, Gomyo Y, Tsjujitani S, Maeta M, Kaibara N (2000) Combined analysis of p53
and retinoblastoma protein expressions in esophageal cancer. Ann Thorac Surg 70:913–917
Jiang Y, Zhang Q, Hu Y, Li T, Yu J, Zhao L, Ye G, Deng H, Mou T, Cai S, Zhou Z, Liu H, Chen G,
Li G, Qi X (2018) Immuno score signature: a prognostic and predictive tool in gastric cancer.
Ann Surg 267:504–513
Kolligs FT (2016) Diagnostics and epidemiology of colorectal cancer. Visc Med 32:158–164
Kulke MH, Odze RD, Mueller JD, Wang H, Redston M, Bertagnolli MM (2004) Prognostic
significance of vascular endothelial growth factor and cyclooxygenase 2 expression in patients
receiving preoperative chemoradiation for esophageal cancer. J Thorac Cardiovasc Surg
127:1579–1586
Lastraioli E, Romoli MR, Arcangeli A (2012) Immunohistochemical biomarkers in gastric cancer
research and management. Int J Surg Oncol 2012:868645
Linnekamp JF, Hooff SRV, Prasetyanti PR, Kandimalla R, Buikhuisen JY, Fessler E, Ramesh P,
Lee KAST, Bochove GGW, de Jong JH, Cameron K, van Leersum R, Rodermond HM,
Franitza M, Nurnberg P, Mangiapane LR, Wang X, Clevers H, Vermeulen L, Stassi G, Medema
JP (2018) Consensus molecular subtypes of colorectal cancer are recapitulated in in vitro and
in vivo models. Cell Death Differ 25:616–633
Liu X, Cai H, Huang H, Long Z, Shi Y, Wang Y (2011) The prognostic significance of apoptosis-
related biological markers in Chinese gastric cancer patients. PLoS One 6:e29670
Lundin M, Nordling S, Carpelan-Holmstrom M, Louhimo J, Alfthan H, Stenman UH, Haglund C
(2000) A comparison of serum and tissue hCG beta as prognostic markers in colorectal cancer.
Anticancer Res 20(6D):4949–4951
Macrì A, Versaci A, Loddo S, Scuderi G, Travagliante M, Trimarchi G, Teti D, Famulari C (2006)
Serum levels of interleukin 1beta, interleukin 8 and tumour necrosis factor alpha as markers of
gastric cancer. Biomarkers 11:184–193
McLeod HL, Murray GI (1999) Tumour markers of prognosis in colorectal cancer. Br J Cancer
79:191–203
Mrena J, Wiksten JP, Kokkola A, Nordling S, Ristimaki A, Haglund C (2010) COX-2 is associated
with proliferation and apoptosis markers and serves as an independent prognostic factor in
gastric cancer. Tumor Biol 31:1–7
Nagasawa S, Onda M, Sasajima K, Makino H, Yamashita K, Takubo K, Miyashita M (2001) Cyclin

D1 overexpression as a prognostic factor in patients with esophageal carcinoma. J Surg Oncol
78:208–214
Nakajima TE, Yamada Y, Hamano T, Furuta K, Matsuda T, Fujita S, Kato K, Hamaguchi T,
Shimada Y (2010) Adipocytokines as new promising markers of colorectal tumors: adiponectin
for colorectal adenoma, and resistin and visfatin for colorectal cancer. Cancer Sci
101:1286–1291
Park JM, Kim MK, Chi KC, Kim JH, Lee SH, Lee EJ (2015) Aberrant loss of dickkopf-3 in gastric
cancer: can it predict lymph node metastasis preoperatively? World J Surg 39:1018–1025
Peters G, Gongoll S, Langner C, Mengel M, Piso P, Klempnauer J, Ruschoff J, Kreipe H, von
Wasielewski R (2003) IGF-1R, IGF-1 and IGF-2 expression as potential prognostic and
predictive markers in colorectal-cancer. Virchows Arch 443:139–145
Portela A, Esteller M (2010) Epigenetic modifications and human disease. Nat Biotech
28:1057–1068
Pressler H, Sissung TM, Venzon D, Price DK, Figg WD (2011) Expression of OATP family
members in hormone-related cancers: potential markers of progression. PLoS One 6(5):e20372
Prins MJD, Verhage RJJ, Ten Kate FJW, Van Hillegersberg R (2012) Cyclooxygenase isoenzyme-
2 and vascular endothelial growth factor are associated with poor prognosis in esophageal
adenocarcinoma. J Gastrointest Surg 16:956–966
Rosato A, Pivetta M, Parenti A, Iaderosa GA, Zoso A, Milan G, Mandruzzato S, Del Bianco P,
Ruol A, Zaninotto G, Zanovello P (2006) Survivin in esophageal cancer: an accurate prognostic
marker for squamous cell carcinoma but not adenocarcinoma. Int J Cancer 119:1717–1722
Shimada H, Noie T, Ohashi M, Oba K, Takahashi Y (2014) Clinical significance of serum tumor
markers for gastric cancer: a systematic review of literature by the task force of the Japanese
Gastric Cancer Association. Gastric Cancer 17:26–33
Soroush AR, Zadeh HM, Moemeni M, Shakiba B, Elmi S (2004) Plasma prolactin in patients with
colorectal cancer. BMC Cancer 4:97
Taylor FGM, Quirke P, Heald RJ, Moran B, Blomqvist L, Swift I, Sebag-Montefiore DJ, Tekkis P,
Brown G (2011) Preoperative high-resolution magnetic resonance imaging can identify good
prognosis stage I, II, and III rectal cancer best managed by surgery alone: a prospective,
multicenter, European study. Ann Surg 253:711–719
Vainer N, Dehlendorff C, Johansen JS (2018) Systematic literature review of IL-6 as a biomarker or
treatment target in patients with gastric, bile duct, pancreatic and colorectal cancer. Oncotarget 9
(51):29820–29841
Vedeld HM, Goel A, Lind GE (2018) Epigenetic biomarkers in gastrointestinal cancers: the current
state and clinical perspectives. Semin Cancer Biol 51:36–49
Wang D, Du Bois RN (2006) Prostaglandins and cancer. Gut 55(1):115–122
Wild N, Andres H, Rollinger W, Krause F, Dilba P, Tacke M, Karl J (2010) A combination of
serum markers for the early detection of colorectal cancer. Clin Cancer Res 16:6111–6121
Wu MH, Lee WJ, Hua KT, Kuo ML, Lin MT (2015) Macrophage infiltration induces gastric cancer
invasiveness by activating the beta-catenin pathway. PLoS One 10(7):e0134122
Wu L, Chen J, Qin Y, Mo X, Huang M, Ru H, Yang Y, Liu J, Lin Y (2016) SATB2 suppresses
gastric cancer cell proliferation and migration. Tumour Biol 37:4597–4602
Xu J, Ye Y, Zhang H, Szmitkowski M, Makinen MJ, Li P, Xia D, Yang J, Wu Y, Wu H (2016)
Diagnostic and prognostic value of serum interleukin-6 in colorectal cancer. Medicine (Balti-
more) 95(2):e2502
Zhao S, Yi M, Yuan Y, Zhuang W, Zhang D, Yu X, Chen X, Teng B, Guan Z, Zhang Y (2015)
Expression of AKAP95, Cx43, CyclinE1 and CyclinD1 in esophageal cancer and their associ-
ation with the clinical and pathological parameters. Intr J Clin Exp Med 8(5):7324–7332
Chapter 4
Immunotherapeutics of Gastrointestinal
Malignancies
Nakka Venkata Prasuja
Abstract Gastrointestinal (GI) malignancies in humans are the most widespread

cancers worldwide. Surgical resection and radio or chemotherapy offer the primary
line of the treatment strategy for patients suffering from GI malignancies. However,
the majority of the patient population receives only palliative care due to a lack of
poor or timely diagnosis. Thus it is imperative to establish novel treatment strategies
for patients suffering from advanced metastasis or GI malignancies. Immunotherapy
evolved as one of the most efficient strategies for the treatment of various cancers
including GI malignancies. This chapter discusses the critical checkpoints of tumor
escape from the immune system with an emphasis on novel immunotherapeutic
strategies and potential drug target markers of the immune system for GI
malignancies.
Keywords Gastrointestinal cancers · Immune checkpoint inhibitors · Humanized

antibodies · Vaccines · Adoptive T-cell transfer · Clinical trials · Immunotherapy
Abbreviations
ACT Adoptive T-cell transfer

APCs Antigen-presenting cells
CAF Cancer-associated fibroblast
CAR T-cells Chimeric antigen receptor expressing T-cells
CD Cluster differentiation
CRC Colorectal cancer
CRISPR/Cas9 (Clustered regularly interspaced short palindromic repeats/
CRISPR associated protein 9)
CTLA4 Cytotoxic T-lymphocyte associated protein-4
N. Venkata Prasuja (*)

Department of Biochemistry, Acharya Nagarjuna University, Guntur, Andhra Pradesh, India
e-mail: prasujanv@anu.ac.in
https://doi.org/10.1007/978-981-15-6487-1_4
52 N. Venkata Prasuja
DCs Dendritic cells

dMMR DNA mismatch repair deficient
FDA Food and Drug Administration, USA
GC Gastric cancer
GEJC Gastroesophageal junction cancer
GI Gastrointestinal
HCC Hepatocellular carcinoma
HLA Human leukocyte antigen
IL-2 Interleukin-2
kg Kilogram
MAb Monoclonal antibody
MDSC Myeloid-derived suppressor cell
mg Milligram
MHC Major histocompatibility complex
mRNA Messenger ribonucleic acid
NK cells Natural killer cells
ORR Objective response rate
PD-1 Programmed cell death receptor-1
PD-L1 Programmed cell death receptor-1 ligand
TCR T-cell receptor
TGF Transforming growth factor
TILs Tumor-infiltrating lymphocytes
VEGF Vascular endothelial growth factor
4.1 Background
4.1.1 Tumor Escape: A Rate Limiting Step in GI

Malignancies
Certain molecules of the immune system serve as critical checkpoints or biomarkers

for tumor microenvironment. Increased expression of immune checkpoint markers
such as receptor for programmed cell death protein-1 (PD-1) or its ligand PD-L1/2
(CD274/CD273), and cytotoxic T-lymphocyte associated protein-4 (CTLA4) either
suppresses the immune system or induces tolerance that results in cancer cells to be
recognized as self and to escape from the host immune system (Yaghoubi et al.
2019). Thus tumors develop various strategies to invade the host immune system. A
precise understanding of the molecular mechanisms underlying tumor escape may
help to identify potential targets for developing immune therapy against GI malig-
nancies. Usually, foreign antigen peptides are presented on the T-cell surface by
4 Immunotherapeutics of Gastrointestinal Malignancies 53
antigen-presenting cells (APCs) with the help of major histocompatibility complex

to discriminate self vs. non-self. Of note, this phenomenon is negatively regulated by
co-inhibitor molecules such as PD-1 and CTLA4 in the case of cancer tumors
(Yaghoubi et al. 2019; Harris and Drake 2013; Goode and Smyth 2016).
CTLA-4 binds a cluster of differentiation (CD) 80/86 on APCs by competing
with CD28 to inhibit the activation of T-cells (Harris and Drake 2013). Specific
expression of PD-1 on activated CD8+T-cells interacts with PDL-1/2 on the APCs,
for example, dendritic cells (DCs) and macrophages of tumor targets. An increase in
PD-1 expression results in exhaustion of T-cell that curtails the primary line of
defense mechanism against tumors (Kamphorst et al. 2017). Therefore, pharmaco-
logical inhibition of the PD-1 receptor might help to provoke the second line of
immune response beyond the lymphoid tissue. Overall, CTLA-4 serves as a key
checkpoint inhibitor in lymphoid tissue, whereas PD-1/PDL-1 as a peripheral check-
point (Yaghoubi et al. 2019).
4.2 Immunotherapy Against GI Malignancies
4.2.1 Pharmacological Manipulation of PD-1 and CTLA-4

and Its Clinical Significance
The efficacy of immune therapy by targeting pathways such as CTLA4, PD-1/PD-L1

in various cancers extensively investigated in clinical settings (Myint and Goel 2017;
Pardoll 2012). For example, in patients subjected to PD-1 therapy (sample size about
300), the tumor size reduced significantly in melanoma, kidney, and lung cancers by
31%, 29%, and 17%, respectively (Topalian et al. 2012). In the current chapter, we
highlighted some of the important outcomes of clinical studies aiming for PD-1 and
CTLA4 pathway in various GI malignancies (Table 4.1). Colorectal cancer (CRC)
stands the fourth leading cause of cancer deaths worldwide (Dekker et al. 2019;
Overman et al. 2017). Dysfunction of DNA mismatch repair (dMMR) system
associated with microsatellite instability serves as a good biomarker for prognosis
of early CRC but not in patients with advanced or metastatic CRC (Overman et al.
2017; Zhao et al. 2019). Of note, blocking PD-1 in such patients with a monoclonal
antibody (MAb) nivolumab (pretreatment@3 mg/kg) provides robust disease control
against metastatic CRC and dMMR (Overman et al. 2017). Combination treatment
with nivolumab and ipilimumab (dosage at 1 and 3 mg/kg respectively) in gastric
cancers (GC) showed a good response (~24%), particularly in PDL-1 negative
patients (Checkmate 032 study) (Janjigian et al. 2016). Further, humanized MAbs
against PDL-1 such as avelumab showed durability of response condition when
administered as primary therapy in the advanced stage and as supportive treatment
followed by first-line chemotherapy in GC (Chung et al. 2016). Consistent with the
Table 4.1 Approved immune checkpoint and other inhibitors for clinical use in GI cancers
Drug Type of GI Clinical Outcome/ Current
target Drug used malignancy Trial Reference status
PD-1 Pembrolizumab GCs; solid Manageable toxic- Le et al. FDA
(MAb) tumors with ity; Antitumor (2017), approved
dMMR associ- activity (KEY- Fuchs et al.
ated microsatel- NOTE-059) (2017)
lite instability-
high
PD-1 Nivolumab HCC; CRC Manageable safety Overman FDA
(MAb) with dMMR profile; durable et al. approved
associated ORR and disease (2017),
microsatellite control (Check- Khoueiry
instability-high Mate 142; 040) et al.
(2017)
PD-1 Nivolumab GC or GEJC Survival benefits in Kang et al. JAPAN
(MAb) patients previously (2017) approved
undergone heavy
chemotherapy
(ONO-4538-12,
ATTRACTION-2)
VEGF Bevacizumab CRC Survival in combi- Hurwitz FDA
(MAb) nation with et al. approved
chemotherapy (2004),
Nienhüser
and
Schmidt
(2017)
Multi- Sorafenib HCC Longer survival Lang FDA
kinase (Nexavar) (unresectable) (REFLECT for (2008), approved
inhibitors Lenvatinib Lenvatinib) Personeni
et al.
(2019)
VEGF Ramucirumab GC Second line of Nienhüser FDA
receptor (MAb) treatment for and approved
2 advanced GC Schmidt
(REGARD and (2017)
RAINBOW)
up-regulation of PDL-1, a phase 1b clinical trial (KEYNOTE-012) reported the

efficacy and safety of pembrolizumab (anti-PD-1 MAb) that showed antitumor
activity and improved outcome in PDL-1 positive patients with recurrent/metastatic
adenocarcinoma of the gastroesophageal junction (Muro et al. 2016; Joshi et al.
2018). The overall response of PD-1 MAb treatment seems promising when com-
pared to PDL1 MAb therapy in patients with GC.
Sorafenib, a multi-kinase inhibitor is the only drug of choice approved for treating
advanced hepatocellular carcinoma (HCC), however with poor outcomes in clinical
settings (Llovet et al. 2008; Khoueiry et al. 2017). CheckMate 040 (phase 1/2
clinical trial) evaluated the efficacy of nivolumab (MAb that blocks PD-1 activity)
in advanced HCC patients (Khoueiry et al. 2017). Administration of

nivolumab@3 mg/kg showed promising results in terms of safety and the addition
of new complications in patients with advanced HCC. Durable objective responses
conferred the potential of nivolumab for the treatment of HCC (Khoueiry et al.
2017). Of note, the use of nivolumab has been approved by the FDA for clinical use
in patients with HCC subjected to sorafenib treatment earlier (Hazama et al. 2018).
Thus PD-1 appears as a potential drug target to establish novel therapeutic strategies
for GI malignancies.
Further, tremelimumab (MAb that blocks CTLA-4) assessed for its efficacy in a
clinical trial (phase-II) that included patients (n ¼ 18) with metastatic gastric and
esophageal adenocarcinomas (Ralph et al. 2010). Tremelimumab administered as a
secondary treatment once every three months until the disease progression, but only
one individual who benefited from the treatment group with significant durability.
Thus it suggests further studies are required to establish CTLA-4 targeted immuno-
therapy, perhaps in combination with other drugs. Targeting immune checkpoints
leads to immune suppression by secreting cytokines, e.g., transforming growth
factor β, interleukin-6, prostaglandins, and regulatory T-cells that induce T-cells
with antitumor activity in the lymph node. Thus altering tumor microenvironment
helps to establish successful immunotherapy against GI malignancies (Hazama et al.
2018). Tumors with massive infiltration of CTLs (known as “hot tumors”) may have
a very good response against immune checkpoint inhibitors alone, without any
immune suppression. While tumors with high immunogenicity and suppressive
immunity (known as “dark tumors”) and tumors with low immunogenicity with
suppressive immunity and immune exhaustion (known as “cold tumors”) require a
combinatorial therapeutic approach to regulate immunosuppressive mechanism and
to augment the immunogenicity of the tumor microenvironment.
4.3 Adoptive T-cell Transfer (ACT)
Earlier, in 1984 Mule et al. suggested that administration of lymphokine-activated

killer cells in the combination of recombinant interleukin-2 at higher dose resulted in
the poor outcome against metastatic GI cancer (Mule et al. 1984). Later the concept
of ACT has become a promising immunotherapy approach for cancer treatment. The
ACT includes TILs (tumor-infiltrating lymphocytes), TCRs (T-cell receptor T-cells),
and CAR T-cells (chimeric antigen receptor expressing T-cells), which are now
being commercialized by some pharmaceutical and biotechnology companies (June
et al. 2018).
Both the TILs and natural killer (NK) cells have got prognostic relevance in GC
(Dolcetti et al. 2018). Treatment with TILs isolated from a metastatic lymph node in
combination with recombinant interleukin-2 in unresectable advanced GC patients
(n ¼ 23) showed a complete reduction of tumor focus in three patients (i.e., 13.0%)
and partial reduction in five patients (i.e., 21.7%), while the others with no response
to the treatment (Xu et al. 1995). The expansion of NK cells in combination with
OK432 (produced from Streptococcus pyogenes of human origin) and IL-2 showed
a better outcome in advanced GC and unresectable patients (Dolcetti et al. 2018). In
the case of TCRs, the infiltrating capacity of TCR repertoires of gastric pancreatic
lesions gradually increased during gastric malignant transformation (Kuang et al.
2017).
The role of CAR T-cells demonstrated in chronic lymphoid leukemia (CLL),
which has shown durable effects. Targeting CD19 elicited a specific immune
response in the bone marrow through cytokine release, ablation of CLL cells with
concomitant infiltration of CAR T-cells (Porter et al. 2011). To date, very limited
clinical data is available on the role of CAR-T therapy related to GI cancers. The
phase I clinical trial (dose escalation) of CAR-T therapy showed better tolerance in
patients with metastatic CRC administered in high doses (Zhang et al. 2017).
Similarly, a phase I clinical trial on CAR-T immunotherapy has a promising
outcome in biliary tract and pancreatic cancer patients positive for human epidermal
growth factor receptor 2 (Feng et al. 2018). Thus CAR-T immunotherapy empha-
sizes that there is an emerging need for precise investigation on the clinical efficacy
of CAR-T immunotherapy aiming GI malignancies including other solid tumors.
4.4 Vaccines
Conventional chemotherapy and radiotherapy show partial efficacy and high toxicity
in cancer patients. Therefore, alternative therapeutic strategies such as immunother-
apy have been explored, which showed good efficacy and tolerance against various
cancers including GI malignancies. Increased understanding of the molecular basis
of tumor biology in the recent past has prompted the development of vaccines
against GI cancers (Hazama et al. 2018).
Cancer vaccines stimulate humoral (antibody-mediated) or cell-mediated
immune responses against tumor cells. The tumor antigens must be processed and
presented in the form of peptides by the APCs to induce T-cell response (Rahma and
Khleif 2011). Therefore, antigens can be administered by vector-mediated (viruses
and nucleic acids) in the form of peptides, whole proteins, and recombinant proteins.
DCs are potent APCs in generating specific primary T-cell responses that can be
used as adoptive immunotherapy. As combination therapy for pancreatic cancer,
adoptive T-cell therapy tested using matured DCs transfected with either mucin-1
mRNA or peptide and CTLs along with gemcitabine (promotes antitumor activity)
drug treatment proved to be effective clinical settings (Shindo et al. 2014). Further,
treating HCC patients (viral infection-related) with heat shock protein 70 mRNA
transfected DCs showed better efficacy without any significant side effects (Maeda
et al. 2015).
Peptide-based vaccines seem to play a critical role in modulating advanced GCs.
For instance, the OTSGC-A24 peptide vaccine clinically tested in GC patients
particularly in those positive for HLA-A*24:02 haplotype (Sundar et al. 2018).
Administration of OTSGC-A24 combined vaccine (sub-cutaneous @1 mg dose
every 2 weeks) showed significant CTL responses and better tolerance (Sundar et al.
2018). Existing clinical data suggests that blockade of immune checkpoints may
have beneficial outcomes based on immunogenicity and inflammatory responses.
Thus, combination treatment with cancer vaccine and immune checkpoint inhibitors
helps to develop novel effective therapeutics for GI cancers.
4.5 Conclusions and Future Perspective
Immunotherapeutic strategies emerged as most promising in the treatment of various

cancers including GI malignancies (Fig. 4.1). The possible basis for successful
immunotherapy is based on the fact, i.e., not to include patients with poor responses
subjected to immunotherapy. Both the PD-1 and CTLA-4 negatively regulate
immune response that helps tumor antigens escape from the host line defense
mechanism and causes immune tolerance. So far, monotherapy with the humanized
antibody pembrolizumab (targets PD-1 receptor) showed the most promising result
in patients with advanced GC. Similarly, nivolumab plus ipilimumab combination
Combination Immunotherapy
Hot/Dark/Cold tumor
microenvironment
Adoptive Immunotherapy Immune check point

inhibitors (PD-1, CTLA4)
VACCINES
GI MALIGNANCIES Humanized antibodies
(GCs, HCC, CRC, GEJC
etc.)
DC based vaccines, peptide vaccines Pembrolizumab, Nivolumab etc.
and recombinant virus/cell based
CAR T-cells Clinical out come:
Clinical out come: Prevents receptor ligand binding
Humoral and cell mediated immune Promotes anti-tumor response
response against tumor cells (T-cell mediated)
Anti-tumor activity
Durable ORR
Manageable toxicity
Fig. 4.1 Illustrate strategies of immunotherapy for various GI malignancies. Immune checkpoint
inhibitors help to curtail tumor evasion from the host line of immunity and to recognize non-self-
antigens. However, a combinatorial immunotherapeutic strategy seems to be instrumental
depending on the tumor microenvironment. Adoptive cell immunotherapy (passive immunization
with tumor-specific T-cells), DC-based vaccines for proper presentation of tumor antigens, enhanc-
ing NK cell activation, etc. are very promising for developing newer and effective therapeutic
strategies for GI malignancies
also demonstrated a good response against CRC in clinical settings. Thus pharma-
cological regulation of immune checkpoint inhibitors seems promising drug targets
to develop immune therapies against GI malignancies. However, some early phase
clinical trials showed unsatisfactory results possibly due to tumor heterogeneity or
the lack of effective host immune response. Altering the tumor microenvironment by
inducing CTL (CD8+) infiltration without suppressing the immune system might
respond well to immune checkpoint inhibitors. Suppressing the host immune
response makes the tumors low immunogenic that eventually promotes tumor
survival. Thus the cautious use of immune-suppressive drugs is warranted for
developing immunotherapy against GI cancers. The partial improvement observed
even after using immune checkpoint inhibitors in individuals with dMMR associated
microsatellite instability-high possibly influenced by several factors within the tumor
microenvironment such as insufficient newly formed antigens, increased burden of
tumors, suppressed immune system, etc. The suppressive immunity caused by
regulatory T-cells, IL-6, TGF-β, MDSC, and CAF can be regulated by using specific
inhibitors (Hazama et al. 2018). Nonetheless, in-depth sequencing analysis of whole-
exome/protein-coding regions would be helpful to develop precise immunothera-
peutics for GI malignancies. A recent report suggests that TCR recognizes and kills
most of the cancer cells via class I MHC related protein (Crowther et al. 2020). Thus
future studies to establish novel immunotherapies for GI malignancies should also
aim towards screening CRISPR/Cas9 based genome-wide screening.
Acknowledgement The author would like to acknowledge financial assistance from the Univer-
sity Grants Commission Faculty Recharge Program (UGC-FRP) start-up grant and Science and
Engineering Research Board (EEQ/2017/000804), Government of India.
Conflicts of interest None.
References
Chung HC, Arkenau HT, Wyrwicz L, Oh DY, Lee KW, Infante JR, Lee SS, Lee J, Keilholz U, Mita
AC et al (2016) Avelumab (MSB0010718C; anti-PD-L1) in patients with advanced gastric or
gastroesophageal junction cancer from JAVELIN solid tumor phase Ib trial: analysis of safety
and clinical activity. ASCO Meet Abstr 34:4009
Crowther MD, Dolton G, Legut M et al (2020) Genome-wide CRISPR-Cas9 screening reveals
ubiquitous T cell cancer targeting via the monomorphic MHC class I-related protein MR1. Nat
Immunol 21:178–185. https://doi.org/10.1038/s41590-019-0578-8
Dekker E, Tanis PJ, Vleugels JLA, Kasi PM, Wallace MB (2019) Colorectal cancer. Lancet
394:1467–1480
Dolcetti R, Re Valli D, Canzonieri V (2018) Immunotherapy for gastric cancer: time for a
personalized approach? Int J Mol Sci 19:1602
Feng K, Liu Y, Guo Y et al (2018) Phase I study of chimeric antigen receptor modified T cells in
treating HER2-positive advanced biliary tract cancers and pancreatic cancers. Protein Cell
9:838–847
Fuchs CS, Doi T, Jang RW-J et al (2017) KEYNOTE-059 cohort 1: efficacy and safety of
pembrolizumab (pembro) monotherapy in patients with previously treated advanced gastric
cancer. J Clin Oncol 35:4003
Goode EF, Smyth EC (2016) Immunotherapy for gastroesophageal cancer. J Clin Med 5:84
Harris TJ, Drake CG (2013) Primer on tumor immunology and cancer immunotherapy. J
Immunother Cancer 1:12
Hazama S, Tamada K, Yamaguchi Y, Kawakami Y, Nagano H (2018) Current status of immuno-
therapy against gastrointestinal cancers and its biomarkers: perspective for precision immuno-
therapy. Ann Gastroenterol Surg 2:289–303
Hurwitz H et al (2004) Bevacizumab plus irinotecan, fluorouracil, and leucovorin for metastatic
colorectal cancer. N Engl J Med 350:2335–2342
Janjigian YY, Bendell JC, Calvo E, Kim JW, Ascierto PA, Sharma P, Ott PA, Bono P, Jaeger D,
Evans TRJ et al (2016) Checkmate-032: phase I/II, open-label study of safety and activity of
nivolumab (nivo) alone or with ipilimumab (ipi) in advanced and metastatic (A/M) gastric
cancer (GC). ASCO Meet Abstr 34:4010
Joshi SS, Maron SB, Catenacci DV (2018) Pembrolizumab for treatment of advanced gastric and
gastroesophageal junction adenocarcinoma. Future Oncol 14:417–430
June CH, O'Connor RS, Kawalekar OU, Ghassemi S, Milone MC (2018) CAR T cell immuno-
therapy for human cancer. Science 359:1361–1365
Kamphorst AO et al (2017) Rescue of exhausted CD8 T cells by PD-1targeted therapies is CD28-
dependent. Science 355:1423–1427
Kang YK, Boku N, Satoh T et al (2017) Nivolumab in patients with advanced gastric or gastro-
oesophageal junction cancer refractory to, or intolerant of, at least two previous chemotherapy
regimens (ONO-4538-12, ATTRACTION-2): a randomised, double-blind, placebo-controlled,
phase 3 trial. Lancet 390:2461–2471
Kuang M et al (2017) A novel signature for stratifying the molecular heterogeneity of the tissue-
infiltrating T-cell receptor repertoire reflects gastric cancer prognosis. Sci Rep 7:7762
Lang L (2008) FDA approves sorafenib for patients with inoperable liver cancer. Gastroenterology
134:379
Le DT, Durham JN, Smith KN et al (2017) Mismatch repair deficiency predicts response of solid
tumors to PD-1 blockade. Science 57:409–413
Khoueiry AB, Sangro B, Yau T et al (2017) Nivolumab in patients with advanced hepatocellular
carcinoma (CheckMate 040): an open-label, non-comparative, phase 1/2 dose escalation and
expansion trial. Lancet 389:2492–2502
Llovet JM et al (2008) Sorafenib in advanced hepatocellular carcinoma. N Engl J Med 359:378–390
Maeda Y, Yoshimura K, Matsui H et al (2015) Dendritic cells transfected with heat-shock protein
70 messenger RNA for patients with hepatitis C virus-related hepatocellular carcinoma: a phase
1 dose escalation clinical trial. Cancer Immunol Immunother 64:1047–1056
Mule JJ, Shu S, Schwarz SL, Rosenberg SA (1984) Adoptive immunotherapy of established
pulmonary metastases with LAK cells and recombinant interleukin-2. Science 225:1487–1489
Muro K, Chung HC, Shankaran V, Geva R, Catenacci D, Gupta S, Eder JP, Golan T, Le DT,
Burtness B et al (2016) Pembrolizumab for patientswithPD-L1- positive advanced gastric
cancer (KEYNOTE-012): a multicentre, open-label, phase 1b trial. Lancet Oncol 17:717–726
Myint ZW, Goel G (2017) Role of modern immunotherapy in gastrointestinal malignancies: a
review of current clinical progress. J Hematol Oncol 10:86
Nienhüser H, Schmidt T (2017) Angiogenesis and anti-angiogenic therapy in gastric cancer. Int J
Mol Sci 19(1):43. https://doi.org/10.3390/ijms19010043
Overman MJ, McDermott R, Leach JL et al (2017) Nivolumab in patients with metastatic DNA
mismatch repair-deficient or microsatellite instability-high colorectal cancer (CheckMate 142):
an open-label, multicentre, phase 2 study. Lancet Oncol 18:1182–1191
Pardoll DM (2012) The blockade of immune checkpoints in cancer immunotherapy. Nat Rev
Cancer 12:252–264
Personeni N, Pressiani T, Rimassa L (2019) Lenvatinib for the treatment of unresectable hepato-
cellular carcinoma: evidence to date. J Hepatocell Carcinoma 6:31–39
Porter DL, Levine BL, Kalos M, Bagg A, June CH (2011) Chimeric antigen receptor-modified T
cells in chronic lymphoid leukemia. N Engl J Med 365:725–733
Rahma OE, Khleif SN (2011) Therapeutic vaccines for gastrointestinal cancers. Gastroenterol
Hepatol 7:517–564
Ralph C, Elkord E, Burt DJ, O’Dwyer JF, Austin EB, Stern PL, Hawkins RE, Thistlethwaite FC
(2010) Modulation of lymphocyte regulation for cancer therapy: a phase II trial of
tremelimumab in advanced gastric and esophageal adenocarcinoma. Clin Cancer Res
16:1662–1672
Shindo Y, Hazama S, Maeda Y et al (2014) Adoptive immunotherapy with MUC1-mRNA
transfected dendritic cells and cytotoxic lymphocytes plus gemcitabine for unresectable pan-
creatic cancer. J Transl Med 12:175
Sundar R et al (2018) A phase I/Ib study of OTSGC-A24 combined peptide vaccine in advanced
gastric cancer. BMC Cancer 18:332
Topalian SL, Hodi FS, Brahmer JR et al (2012) Safety, activity, and immune correlates of anti-PD-1
antibody in cancer. N Engl J Med 366:2443–2454
Xu X et al (1995) Treatment of 23 patients with advanced gastric cancer by intravenously transfer of
autologous tumor-infiltrating lymphocytes combined with rIL-2. Chin Med Sci J 10:185–187
Yaghoubi N, Soltani A, Ghazvini K, Hassanian SM, Hashemy SI (2019) PD-1/ PD-L1 blockade as
a novel treatment for colorectal cancer. Biomed Pharmacother 110:312–318
Zhang C, Wang Z, Yang Z et al (2017) Phase I escalating-dose trial of CAR-T therapy targeting
CEA(+) metastatic colorectal cancers. Mol Ther 25:1248–1258
Zhao P, Li L, Jiang X, Li Q (2019) Mismatch repair deficiency/microsatellite instability-high as a
predictor for anti-PD-1/PD-L1 immunotherapy efficacy. J Hematol Oncol 12:54
Chapter 5
Immune Cell Therapy Against
Gastrointestinal Tract Cancers
Ravindra Donde, Manoj Kumar Gupta, Gayatri Gouda,

Sushanta Kumar Dash, Lambodar Behera, and Ramakrishna Vadde
Abstract Gastrointestinal (GI) cancers are responsible for major cancer-related

mortality around the world. It has imposed a substantial burden and pressure on
the healthcare sector across the globe. Recently advancements in high throughput
techniques provide us with a unique opportunity to detect biomarkers and treat
various diseases, including GI cancer, more comprehensively. However, most of
these approaches are ineffective for treating patients with advanced or metastatic
stages. Additionally, these treatments have severe side effects on cancer patients.
Thus, there is an urgent requirement to identify new drugs and innovative immune
therapies for the treatment of GI malignancies. Considering this, recently developed
immune cell therapy provides a unique opportunity for early detection and treatment
of various cancers, including GI cancer. It controls cancer either by activating or
suppressing the immune system of cancer patients. Recently, immune checkpoints
approaches have also been employed in the treatment and prevention of cancer.
However, various studies have reported that few of these therapies have side effects.
Thus, these therapies must be employed with utter caution. Recently several studies
have also proposed that the personalized immunotherapy approach can also be used
for therapeutic cancer treatment with fewer side effects. Authors believe that by
employing classical and advanced immunotherapeutic techniques together, we can
easily diagnose and treat GI cancer in a more comprehensive way. In the near future,
the information present in this chapter will be highly useful for the early detection
and treatment of various cancers, including GI cancer.
Keywords Gastrointestinal cancers · Immune cell therapy · Personalized

immunotherapy · Immune checkpoints · Monoclonal antibody
R. Donde · G. Gouda · S. K. Dash · L. Behera

Pradesh, India
https://doi.org/10.1007/978-981-15-6487-1_5
62 R. Donde et al.
Abbreviations
APCs Antigen-presenting cells

ATCT Adoptive T-cell therapy
BCG Bacillus Calmette–Guérin
CTL Cytotoxic T lymphocytes
CAR Chimeric antigen receptor
CpG Cytosine-phosphate-guanosine
G-CSF Granulocyte colony-stimulating factor
GI Gastrointestinal tract
GvHD Graft versus host disease
NK Natural killer
SIRPα Signal regulatory protein alpha
TCR Transgenic T-cell receptor
5.1 Introduction
Gastrointestinal tract (GI) cancer is one of the most important cancer types that are
responsible for cancer-related mortality worldwide. The most common gastrointes-
tinal tract malignancies are esophageal cancer, gastric cancer, colorectal cancer, liver
cancer, and pancreatic cancer (Pourhoseingholi et al. 2015). At the initial stage,
symptoms associated with GI cancers mostly remain unknown. However, in the case
of a few cancers, namely, esophagus and stomach cancers, patients experience
struggle in swallowing, abnormal bleeding, and digestive system associated prob-
lems. To date, several cancers treatment approaches have been designed for the early
detection and prevention of GI malignancies. These approaches mainly comprised of
surgery, chemotherapy, radiotherapy, and molecularly targeted therapy (Gupta et al.
2017, 2019a, b; Mallepalli et al. 2019). The accurate diagnosis of cancers generally
requires endoscopy and followed by biopsy for suspicious tissues and cell identifi-
cation. The tumor’s location and the cancer cell type decide which approach may be
employed for treatment. However, most of these approaches are ineffective for
treating patients with advanced or metastatic stages. Additionally, these treatments
have severe side effects on the health of cancer patients. Thus, there is an urgent
requirement to identify new drugs and innovative immune therapies for the treatment
of GI malignancies (Rao et al. 2019). Considering this, recently developed immune
cell therapy provides a unique opportunity for early detection and treatment of
various cancers, including GI cancer. It controls cancer either by activating or
suppressing the immune system of cancer patients. In 2001, Masihi and the team
reported that immunomodulatory therapy often has fewer side effects in comparison
to existing chemo as well as drug therapy (Masihi 2001). The immune cell therapy
works along with various immune effector cells, including lymphocytes, macro-
phages, “cytotoxic T lymphocytes” (CTL), “natural killer” (NK) cell, and dendritic
5 Immune Cell Therapy Against Gastrointestinal Tract Cancers 63
cells. Together they protect the body against various cancer types via targeting
antigens that are expressed on the tumor cells surface. Several studies have also
reported that immune therapies have been used effectively against several cancer
biomarkers, for instance, interferons, and “granulocyte colony-stimulating factor”
(G-CSF) (Rao et al. 2019; Moehler et al. 2016; Hazama et al. 2018; Zappasodi et al.
2018). Additionally, few other biomarkers, namely, IL-12, IL-7, IL-2, synthetic
cytosine-phosphate-guanosine (CpG) oligodeoxynucleotides, several chemokines,
as well as glucans were also employed in both pre-clinical and clinical studies
(Moehler et al. 2016; Hazama et al. 2018; Hendry et al. 2017). In 2015, Fuge and
the team reported that the “Bacillus Calmette–Guérin” (BCG) vaccine, which is
widely employed against tuberculosis, can also be used for treating bladder cancer
(Fuge et al. 2015). Similarly, monoclonal antibody rituximab, an anti-CD20, can
also be used for treating various cancers (Pento 2017). In 2019, Tannapfel and
Reinacher-Schick reported that cytokines, for instance, interleukin-2 or interferon-
alpha, are widely used for treating various cancers (Tannapfel and Reinacher-Schick
2019). In 2018, James P. Allison and Tasuku Honjo had been awarded Nobel Prizes
in Physiology or Medicine, “for their discovery of cancer therapy by inhibition of
negative immune regulation” (Guo 2018). Considering this, in the present chapter,
authors attempted to discuss the importance of different immune cell therapy and
how these approaches can be used for the treatment of GI cancer. In the near future,
immunotherapy may be the key answer for treating gastrointestinal tract cancers.
5.2 Immunotherapy Approaches
Cellular immunotherapy comprised of both active and passive immunotherapy

approaches. Active immune cell therapy directly uses the immune system of the
patient for attacking tumor cells by targeting tumor antigens. Passive immune cell
therapies increase the existing anti-tumor responses of immune cells as well as
tissues by using monoclonal antibodies, lymphocytes, and cytokines. Active cellular
immunotherapies include the removal of cancer immune cells from cancer patient’s
bodies. These tumor-specific immune cells are subsequently grown within the
culture and later injected to the cancer patient, where they attack tumor cells.
Otherwise, the genetically engineering approach can also be employed for generat-
ing immune cells, which in turn can be used for expressing tumor-specific receptors.
The genetically engineered tumor cells are cultured and later injected to the patient,
which in turn acts against the tumor cells. Cell types that work against the cancer
cells are NK cells, lymphokine-activated killer cells, dendritic cells, and cytotoxic
T-cells (Hazama et al. 2018; Zappasodi et al. 2018). Passive immune cell therapy
involves the introduction of either cytotoxic T lymphocytes or antibodies. Anti-
bodies may function either in a specific or non-specific manner (Baxter 2014).
Passive immune cell therapy usually targets the receptors present on the cell surface,
including CD20, CD274, and CD279 antibodies. These antibodies, when attached
with a cancer antigen, experience configurational changes, which in turn stimulate
64 R. Donde et al.
“antibody-dependent cell-mediated cytotoxicity” and trigger the “complement sys-

tem.” This, in turn, inhibits the interaction between the receptor and its ligand and
causes cell death (Espinoza-Sánchez and Götte 2019).
The most widely used immune cell types that are being employed in immuno-
therapies during various cancers, including gastric cancer, are dendritic cells, lym-
phocytes, myeloid-derived suppressor cells, natural killers, neutrophils,
macrophages. These cells modulate the tumor microenvironment through the pro-
duction of chemokines and cytokines. Unlike chemical drugs, cytokines can inhibit
specific proteins that are responsible for inducing the inflammatory process. Addi-
tionally, with the advancement of high throughput technologies, it is relatively
cheaper and faster to express and isolate highly purified recombinant proteins, e.g.,
cytokine. Thus, recently, cytokine therapy has also been utilized for increasing
immunity against tumors (Rider et al. 2016). Two forms of cytokines, namely,
interferons and interleukins, are commonly used in cancer treatment (Dranoff
2004). Interferons are encoded by the immune system, where they are generally
involved in the anti-viral response. Interferons are also used against tumors. The
interferons can be broadly classified into three groups, i.e., “type I (IFNα and IFNβ),
type II (IFNγ), and type III (IFNλ).” The IFNα has been approved as a drug against
AIDS-related Kaposi’s sarcoma, hairy-cell leukemia, chronic myeloid leukemia,
follicular lymphoma, and melanoma. Nowadays, researchers are also employing
type I and II IFNs as the anti-tumor immune system, but the only type I IFNs have
shown clinically useful (Rider et al. 2016; Lai and Dong 2016; Hegner et al. 2018;
Lambertsen et al. 2019). Few studies have also reported that the type III IFNλ is
potentially used for its anti-tumor response in animal models (Dunn et al. 2006;
Lasfar et al. 2011). However, type II IFNs, namely, interferon gamma, show
effective immune response only in those patients having bladder carcinoma and
melanoma cancers (Razaghi et al. 2016). The most effective immune response was
achieved when the patients were having ovarian carcinoma identified at second or
third stages. In 2016 Razaghi and the team reported that anti-proliferative activity of
IFN-gamma causes cell death or growth inhibition. This is generally induced
through autophagy and apoptosis (Razaghi et al. 2016). Another study reported
that interleukins have an array of immune system effects. Hence, interleukin-2 is
usually used in renal cell carcinoma and malignant melanoma treatment (Dranoff
2004; Coventry and Ashdown 2012).
5.3 The Cell in Immunotherapy Approaches
As stated above, the most widely used immune cell types that are being employed in
immunotherapies during various cancers, including gastric cancer are macrophages,
dendritic cells, adoptive T-cells, neutrophils.
5.3.1 Macrophages
Macrophages are mononuclear phagocytic cells that play a key role in

pro-inflammatory, homeostatic, and immune regulatory responses within tissues
(Pahl et al. 2014). Based on signals, macrophages may be classified as either
classical or alternative activation. While classical macrophages have anti-tumor
activity, alternative macrophages have low tumoricidal activity. “Tumor-associated
macrophages” (TAMs) are mostly situated within the tumor mass and thus play a
key role in the intra-tumoral activity (Eyileten et al. 2016). Few authors proposed
that TAM modulated “switch” among non-canonical and canonical Wnt signaling
pathways may help in controlling cancers. Inhibition of canonical Wnt signaling
pathway via proteins secreted by macrophages inhibits cancer. Nevertheless, it
activates the non-canonical Wnt pathway, which in turn promotes cancer cell
motility, invasiveness, and epithelial–mesenchymal transition. These authors also
proposed that, in any way, we can modulate both canonical and non-canonical Wnt
pathway, we can effectively control the formation of various cancers (Eyileten et al.
2016). In one study, Tseng and the team employed macrophages for enhancing
immune response via T-cells (Tseng et al. 2013). Anti-CD47 antibody-modulated
phagocytosis of cancer cells via macrophages enhances and reduces priming of
CD8+ and CD4+ cells, respectively. This, in turn, reduces the level of regulatory
T-cells. This causes reduced tumor mass in animals. The result obtained from that
study also suggests that anti-CD47 antibody treatment is capable of both macro-
phage phagocytosis of cancer cells and initiation of anti-tumor cytotoxic T-cell
immune response (Tseng et al. 2013). In another study, Pahl and the team tried to
initiate anti-tumor activity of macrophages via modifying macrophage phenotype
via IFN-γ and liposomal muramyl tripeptide (Pahl et al. 2014).
Since several studies have reported that M1-activates are clinically safe,
M1-activated macrophages are also used as a delivery system (Griffiths et al.
2000; Muthana et al. 2011, 2013). For instance, Griffiths and the team reported
that CYP2B6 delivery via macrophage under the constitutive human cytomegalovi-
rus promoter initiates a killing of tumor cells in the presence of cyclophosphamide
(Griffiths et al. 2000). In another study, Muthana and the team developed a novel
system that employed the infiltration of classically activated macrophages and
restricted tumor growth (Muthana et al. 2011, 2013). Seo and the team developed
stable macrophages of RAW264.7 cell line via genetically engineering approaches
(Seo et al. 2012). Seo and the team employed these macrophages for delivering the
prodrug-activating enzyme to the lung melanomas (Seo et al. 2012).
5.3.2 Dendritic Cell (DC)
In 1973, for the first time, Steinman reported that antigen-presenting cells play a key
role in activating the adaptive immune system (Steinman and Cohn 1973). DCs are
66 R. Donde et al.
the most potent APCs and can be generated from monocytoid or myeloid precursor
cells present within bone marrow or peripheral blood (Okur and Brenner 2010).
DCs, which are present throughout the body, keep continuous monitoring of anti-
gens and harmful signals. Once activated, they experience maturation and travel to
lymphoid organs, where they stimulate numerous effector immune cells, specifically
B-cells and T-cells (Banchereau and Steinman 1998). Thus, DCs are very crucial for
immunosurveillance, which in turn provides protection against pathogens and can-
cerous cells (Wirth et al. 2010). Nevertheless, this immunosurveillance sometimes
fails to detect cancer cells at the initial stage. DC vaccination can correct this failure
effectively via reversing the ignorance of the immune system towards malignant
cells (Wirth et al. 2010). The main objective of the DC vaccination is to destroy
tumor cells via the generation of functional antigen-specific T-cells (Draube et al.
2011). For enhancing maturation as well as activation of DCs, “cocktails” of various
cytokines like GM-CSF, IL-6, IL-1ß, TNF-α, and IL4 have been employed without
or with prostaglandin E2 (Okur and Brenner 2010). With the help of these agents,
monocytoid/myeloid DCs take up as well as present APCs more effectively, which
in turn enhances expression of co-stimulatory bio-molecules, for instance, CD86,
CD54, CD40, and CD80. Subsequently, they polarize the resultant immune response
towards a T effector phenotype (Okur and Brenner 2010).
Production of DC vaccination follows a few basic principles. At first, natural
circulating DC or monocytes are isolated from “autologous peripheral blood mono-
nuclear cells.” Monocytes undergo ex vivo differentiation to form DC. Later,
DC-derived from monocytes as well circulating DC undergoes maturation, which
in turn highly required for the activation of T-cell. After maturation, DC show
increased expression of co-stimulatory molecules, MHC complexes I and II, and
enhanced cytokine production capability. These processes are highly required for
inducing immunity. During the manufacturing of this vaccine, DC is laden with
appropriate tumor antigen(s) for producing a tumor-specific immune response within
any patient. Subsequent to quality control, the vaccine is later introduced in the
patient (van Willigen et al. 2018). However, this underlying protocol may vary
during the process of manufacturing the DC vaccination. These variations may be in
the culture methods, maturation methods, utility of DC subsets, used antigens,
approaches of loading antigen, and administration route (van Willigen et al. 2018).
5.3.3 Adoptive T-cell
ATC is a form of “passive immunization therapy.” In this therapy, transfusion of

adoptive T-cells takes place from blood and tissues. They generally get activated
when they come in contact with foreign protein or pathogens. These activated T-cells
are called either “antigen-presenting cells” (APCs) or infected cells. They are present
in both normal tissues and in tumor tissue. Within the tumor, this ATC is known as
“tumor-infiltrating lymphocytes” (TILs). In 2012 Restifo and the team reported these
cells could attack tumor cells. But within the tumor environment, they are highly
immune-suppressive and prevent immune-mediated tumor death (Restifo et al.

2012). Patients with cancer experience multiple ways to produce anti-tumor targeted
T-cells. The tumor antigen-specific T-cells can be either discarded from blood or
tumor samples. Subsequently, the initiation, as well as culture, is carried out via the
ex vivo approach, with the results re-infused. Several researchers have also reported
the T-cells initiation can also be carried out using gene therapy approaches and
exposing T-cells to tumor-specific antigens. As of 2014, several ATC clinical trials
were underway (Carroll 2013). Recently one important study revealed that “clinical
responses can be obtained in patients with metastatic melanoma resistant to multiple
previous immunotherapies” (Andersen et al. 2018). In 2017, the first two ATC,
namely, axicabtagene ciloleucel and tisagenlecleucel, were approved via the FDA.
Furthermore, the adoptive transfer of NK cells and haploidentical γδ T-cells from a
healthy donor can also be employed in another approach. The main benefit of
employing this therapy is that these cells do not cause “Graft versus host disease”
(GvHD). However, this approach is often associated with abnormal function of the
transferred cells (Wilhelm et al. 2014).
To date, several adoptive T-cell therapies, namely, TIL treatment and therapy
with “chimeric antigen receptor” (CAR-T) and “transgenic T cell receptor” (TCR)-
modified T-cells, have been utilized for the treatment of cancer. Out of all
approaches, CAR-T is more effective (Magalhaes et al. 2019). In this immunother-
apy, the T-cells are modified so that they can recognize cancer cells more efficiently
and abolish them. T-cells are harvested from cancer-affected patients, and subse-
quently, CAR added to them using genetically engineered approaches. This, in turn,
makes T-cells to recognize cancer cells more quickly and destroy them. For the first
time, CART-T-cell therapy was used for treating advanced follicular lymphoma.
Since then, CART-T therapy has emerged as a promising adoptive T-cell therapy
(Magalhaes et al. 2019; Almåsbak et al. 2016; Miliotou and Papadopoulou 2018). In
2017, “Tisagenlecleucel (Kymriah),” a CAR-T therapy, was approved for treating
“acute lymphoblastic leukemia” (Commissioner O 2018). However, to date, CAR-
T-cell therapy is in the initial phase. Thus, its usage has been restricted to only small
clinical trials comprised of patients with advanced blood cancers (https://www.
cancer.gov).
5.3.4 Neutrophils
Neutrophils provide the first line of defense against entering pathogens via emitting
activating cytokines and reactive oxygen species. Additionally, they also play a key
role in inhibiting tumor development. Nevertheless, their impact on tumor microen-
vironment is still a topic of debate (Eyileten et al. 2016). Few studies claim that
neutrophils in tumor may promote tumor formation (Mócsai 2013). Neutrophils
promote tumor formation via emitting various factors. For instance, oncostatin M
is a cytokine and belongs to interleukin-6 (IL-6) family (Grenier et al. 2001).
Reactive oxygen species emitted via neutrophils also play a key role in tumor
68 R. Donde et al.
development. Güngör and the team also suggested that major “neutrophilic oxidant
hypochlorous acid” stimulates three distinct forms of DNA damage as well as
mutagenicity within alveolar epithelial cells in human lung (Güngör et al. 2010).
Additionally, one study has also reported that proteinase of neutrophil elastase
encoded via TANs stimulates tumor cell proliferation within both mouse and
human lung adenocarcinomas (Houghton et al. 2010).
On the contrary, few studies have also reported that neutrophils inhibit tumor
formation (Chee et al. 1978; Dvorak et al. 1978). For the first time, two independent
groups, namely, Godleski and the team (Godleski et al. 1970) and Bubeník and the
team (Bubenïk et al. 1970), separately, reported that neutrophil may inhibit rat
mammary gland carcinosarcoma and human bladder tumors, respectively. Later,
Pickaver and the team (Pickaver et al. 1972) confirm the neutrophils inhibit tumor
cells. Another study suggested that proteases, defensins, and ROS produced via
neutrophils (Reeves et al. 2002) can directly inhibit targeted tumors cells (Reeves
et al. 2002; Stuart and Ezekowitz 2005). Dallegri and the team suggested that
apoptosis as well as necrosis in tumor cell is mainly because of the enhanced
secretion of HOCl via neutrophils (Dallegri et al. 1991). Additionally, the inhibition
of tumor cells via neutrophils can be enhanced through target-specific antibodies
(Di Carlo et al. 2001; Scott et al. 2012). Repp and the team suggested that neutro-
phils retrieved from patients that have been treated with recombinant human G-CSF
expressed FcγRI receptor, which is a high affinity receptor for IgG (Repp et al.
1991).
Few researchers also employed live bacteria and bacterial products, Mycobacte-
rium bovis (Hanna et al. 1973), Clostridium novyi (Agrawal et al. 2004), Salmonella
choleraesuis (Lee et al. 2008), Corynebacterium parvum (Lichtenstein et al. 1984),
and Salmonella typhimurium (Avogadri et al. 2005) for inducing neutrophil infiltra-
tions within the tumor microenvironment. Lee and the team subjected
S. choleraesuis within the mouse experiencing orthotopic hepatocellular carcinoma
for stimulating a plausible inflammatory response. This in turn inhibited intra-
tumoral micro-vessel density and enhances neutrophils infiltration. This results in
increased death of cancer cell, thereby increasing the survival rate of the patient (Lee
et al. 2008). Since 1970, BCG vaccine has been widely employed for treating
bladder cancer patients after surgery. BCG administration enhances neutrophil
infiltration within the bladder (de Boer et al. 1991).
5.4 Other Strategies Employed in Immune Cell Therapy
5.4.1 Monoclonal Antibodies
The monoclonal antibodies are a fundamental constituent of adaptive immune

therapy. It plays a key role in the identification of foreign antigens and stimulating
immune cell responses in tumor cells (Rao et al. 2019; Moehler et al. 2016; Mody
et al. 2019). Monoclonal antibodies are produced by fusing an immortalized cell line
with antibody-producing cells, which in turn results in a cell line known as “hybrid-
oma.” Since “hybridoma” is “immortal,” we can generate the exact antibody for
several years (Corthell 2014). To date, several monoclonal antibodies have been
produced for the treatment of various diseases, including cancer (Rajewsky 2019).
The 2018 “Nobel Prize in Physiology or Medicine” was awarded for the “discovery
of cancer therapy by [antibody-mediated] inhibition of negative immune regulation”
(Rajewsky 2019). To date, only two monoclonal antibodies, namely, ramucirumab
and trastuzumab, have been approved for the treatment of cytotoxics. Trastuzumab,
a HER2 monoclonal antibody, inhibits cell-cycle at the G1 phase. It also has anti-
cancer activity within HER2 overexpressed gastric cancer cells (Kim et al. 2008).
Ramucirumab specifically binds with “VEGF receptor-2” and restricts the binding of
“VEGF receptor ligands,” namely, VEGF-D, VEGF-C, and VEGF-A. This, in turn,
inhibits ligand-induced proliferation as well as the migration of endothelial cells in
humans (Fala 2015). While other antibodies, namely, cetuximab, panitumumab,
rilotumumab, and bevacizumab showed conflicting results during clinical trial
studies (Sibertin-Blanc et al. 2016).
5.4.2 Polysaccharide-K
In the 1980s, for the first time, polysaccharide-K as immunotherapy was used and
approved by Japan. The drug polysaccharide-K is extracted from mushroom, known
as Coriolus versicolor. It can up-regulate the immune system and have anti-cancer
properties. It stimulates the immune system's response against cancer patients that
were undergoing chemotherapy. This drug is given to the patients through orally as a
dietary supplement in the USA and other jurisdictions (http://www.cancer.org).
5.4.3 Anti-CD47 Therapy
Anti-CD47 therapy is widely used against tumor cells. Many tumor cells generally
overexpress CD47 to escape immunosurveillance of the host immune system. In
2010 Jaiswal and the team reported that CD47 binds to its receptor “Signal Regu-
latory Protein Alpha” (SIRPα), which in turn causes downregulation of phagocytosis
of tumor cell (Jaiswal et al. 2010). Therefore, the main objective of the anti-CD47
therapy is to restore the clearance of tumor cells and increase phagocytosis of tumor
cells. Additionally, few studies have also reported the application of tumor antigen-
specific T-cells in anti-CD47 therapy (Matlung et al. 2017; Weiskopf 2017). To date,
several therapeutic approaches have been developed, such as engineered decoy
receptors, anti-CD47 antibodies, bispecific agents, and anti-SIRPα antibodies
(Weiskopf 2017).
70 R. Donde et al.
5.4.4 Anti-GD2 Antibodies
The anti-GD2 therapy is also widely used to treat cancer where carbohydrate
antigens are present on the cells surface; therefore, carbohydrates are widely used
as targets for immunotherapy. GD2 is a ganglioside present on the cancer cell
surface, including retinoblastoma, neuroblastoma, melanoma, brain tumors, rhabdo-
myosarcoma, small cell lung cancer, osteosarcoma, Ewing’s sarcoma, fibrosarcoma,
leiomyosarcoma, liposarcoma, and other soft tissue sarcomas. In 2014, Roth and the
team reported that it is usually expressed only on the cancer tissue surface, which
makes it a good target for immunotherapy (Roth et al. 2014).
5.5 Immune Checkpoints Used as Biomarkers—New

Concept
In the body, there are numerous immune checkpoints that help cancer cells to protect
from immune systems. Therefore, immune checkpoints affect immune system func-
tion and can have a stimulatory or inhibitory role. To date, several immune check-
points biomarkers, such as host genomic factors, immune-regulating factors, as well
as tumor-infiltrating immune cells, have been used in immunotherapy for cancer
treatment. These checkpoints are continuously used by tumor cells for protecting
themselves from immune system attacks. Recently several approaches have been
developed for blocking inhibitory checkpoint receptors. However, reliable immuno-
therapy biomarkers are fewer due to our limited knowledge of the human immune
system. Some of the biomarkers are used as both prognostic and predictive markers.
For instance, MSI- H and PD-L1 serve as a sensible immune checkpoint biomarker
(Marin-Acevedo et al. 2018; Darvin et al. 2018; Tundo et al. 2019; Qin et al. 2019).
In 2016, Moehler and the team showed that “a stromal gene expression signature as
well as the ITS proportion quantified by morphometry in tissue sections of patient
samples was correlated and could both serve as potential prognostic markers”
(Moehler et al. 2016). Few studies have also reported that “gastric cancer patients
with high ITS were found to have poorer cancer-specific survival compared to
patients with low ITS proportion” (Moehler et al. 2016). In 2012 Pardoll and the
team reported that blocking of negative feedback signaling to immune cells enhances
the immune response against tumors (Pardoll 2012). Another author reported that
when the ligand PD-L1 binds to PD1 cell surface of an immune cell, it inhibits
immune cell response. PD-L1 on cancer cells can also inhibit interferon- and
FAS-dependent apoptosis, which in turn protect cells from cytotoxic molecules
generated via T-cells (Dong et al. 2016; Alsaab et al. 2017; Wu et al. 2019).
In 2011, the FDA approved ipilimumab for the treatment of melanoma cancer
(Cameron et al. 2011). This immune checkpoint blockade blocks the immune
checkpoint molecule CTLA-4. Several clinical trials have been shown some benefits
of anti-CTLA-4 therapy on lung cancer and pancreatic cancer, specifically in
combination treatment with other drug molecules (Lynch et al. 2012; Le et al. 2013).
Furthermore, clinical trials of the combination treatment of CTLA-4 blockade with
PD-1 or PD-L1 inhibitors were also tested on different types of cancer (https://www.
clinicaltrials.gov/show/NCT01928394). In 2017, Hooren and the team reported that
patients treated with the combination of checkpoint blocking antibodies therapy like
CTLA-4 blocking antibodies + PD-1 or PD-L1 also suffer from immune-related side
effects, for example, endocrine, gastrointestinal, dermatologic, or hepatic autoim-
mune reactions (Hooren et al. 2017). These are most likely because of the breadth of
the induced T-cell activation when anti-CTLA-4 antibodies are administered by
injection in the bloodstream. In this context, Hooren and team have used a mouse
model with bladder cancer and found that a local injection of a low dose anti-CTLA-
4 in the tumor area had the same tumor-inhibiting capacity as when the antibody was
delivered in the blood. At the same time, the levels of circulating antibodies were
lower, thereby suggesting that local administration of the anti-CTLA-4 therapy
might result in fewer adverse events (van Hooren et al. 2017).
Another IgG4 PD1 antibody, namely, nivolumab, has also been approved for the
treatment of several cancers like melanoma, lung cancer, kidney cancer, bladder
cancer, head and neck cancer, and Hodgkin's lymphoma (Rao et al. 2019; Moehler
et al. 2016; Hazama et al. 2018; Myint and Goel 2017; Cui et al. 2019). However, in
2016, a clinical trial for non-small cell lung cancer failed to meet its primary
endpoint for treatment in the first-line setting. FDA has also approved another
PD1 inhibitor, namely, pembrolizumab, for the treatment of various melanoma
and lung cancers (Borrie and Maleki Vareki 2018; Ratermann et al. 2018; Patel
and Liu 2019)
In May 2016, a PD-L1 inhibitor, namely, atezolizumab (www.roche.com/inves
tor) antibody, was approved for the treatment of bladder cancer. At present, the anti-
PD-L1 antibody is in the development stage (Hendry et al. 2017; Wang et al. 2007;
Pallin et al. 2018). There are also several types of enhancing adoptive immunother-
apy available. It includes targeting intrinsic checkpoint blockades, e.g., CISH.
Hazama and team have reported that some cancer patients do not respond to immune
checkpoint blockade because the introduction of immune checkpoint inhibitors was
not substantial (Hazama et al. 2018). This response rate may be improved in some
patients by combined treatment of immune checkpoint blockade with additional
sensibly selected anti-cancer therapies. For example, targeted therapies such as
radiotherapy, vasculature targeting agents, and immunogenic chemotherapy
(Pfirschke et al. 2016) can improve immune checkpoint blockade response in the
animal. Thus, information retrieved from literature published to date suggests that
immunotherapy may be the key answer to gastrointestinal tract cancers.
72 R. Donde et al.
5.6 Future Perspective
Recently developed immune cell therapy provides a unique opportunity for early
detection and treatment of various cancers, including GI cancer. However, multiple
studies have reported that a few of these therapies have side effects. Thus, these
therapies must be employed with utter caution. Recently several studies have also
proposed that the personalized immunotherapy approach can be used for therapeutic
cancer treatment. In this therapy, the drug molecules are truly custom-made for every
single individual. In general, the human immune system can recognize tumor cells
and kill cancer cells, but this ability of the immune system is insufficient to cure
cancer. In this context, it is an urgent need of the time to increase human immune
systems by harnessing and potentiating the ability of the immune system to fight
cancer and to prevent continuous spreading of cancer cells (Tran et al. 2015).
Furthermore, due to the higher heterogeneity present in cancer cells, each tumor
has its genetic fingerprint. Thus it is also highly required to understand the tumor
environment at the single-cell level. Therefore, it is an urgent need to identify
specific drug and individualized cancer vaccination therapy that target specific
cancer cells (Alsina et al. 2017; Sahin and Türeci 2018). Authors believe that by
employing classical and advanced techniques, like immune cell therapy, together,
we can quickly diagnose and treat GI cancer in a more comprehensive way.
5.7 Conclusion
In conclusion, recently developed immune cell therapy controls cancer either by

activating or suppressing the immune system of cancer patients. The most widely
used immune cell therapies towards the treatment of various cancers, including GI
cancers, are cellular immunotherapy, monoclonal antibodies, cytokine therapy,
polysaccharide-K, anti-CD47 therapy, anti-GD2 antibodies. The most widely used
immune cell types that are being employed in immunotherapies during various
cancers, including gastric cancer, are macrophages, dendritic cells, adoptive
T-cells, neutrophils. Recently, immune checkpoints are also employed in the treat-
ment and prevention of cancer. However, various studies have reported that few
therapies have side effects, and thus, these therapies must be employed with utter
caution. Recently, few researchers have also proposed that by applying personalized
immunotherapy and single-cell approaches, we can also treat various cancers,
including GI cancer, more effectively. Authors believe that by employing classical
and advanced techniques, like immune cell therapy, together, we can quickly
diagnose and treat GI cancer in a more comprehensive way. In the near future, the
information present in the chapter will be highly useful for medical practitioners and
researchers working in the field of cancer.
Conflict of Interest None.

References
Agrawal N, Bettegowda C, Cheong I et al (2004) Bacteriolytic therapy can generate a potent

immune response against experimental tumors. PNAS 101:15172–15177
Almåsbak H, Aarvak T, Vemuri MC (2016) CAR T cell therapy: a game changer in cancer
treatment. J Immunol Res. https://doi.org/10.1155/2016/5474602
Alsaab HO, Sau S, Alzhrani R, Tatiparti K, Bhise K, Kashaw SK, Iyer AK (2017) PD-1 and PD-L1
checkpoint signaling inhibition for cancer immunotherapy: mechanism, combinations, and
clinical outcome. Front Pharmacol. https://doi.org/10.3389/fphar.2017.00561
Alsina M, Gullo I, Carneiro F (2017) Intratumoral heterogeneity in gastric cancer: a new challenge
to face. Ann Oncol 28:912–913
Andersen R, Borch TH, Draghi A et al (2018) T cells isolated from patients with checkpoint
inhibitor-resistant melanoma are functional and can mediate tumor regression. Ann Oncol
29:1575–1581
Avogadri F, Martinoli C, Petrovska L, Chiodoni C, Transidico P, Bronte V, Longhi R, Colombo
MP, Dougan G, Rescigno M (2005) Cancer immunotherapy based on killing of salmonella-
infected tumor cells. Cancer Res 65:3920–3927
Banchereau J, Steinman RM (1998) Dendritic cells and the control of immunity. Nature
392:245–252
Baxter D (2014) Active and passive immunization for cancer. Hum Vaccin Immunother
10:2123–2129
Borrie AE, Maleki Vareki S (2018) Chapter five - T lymphocyte–based cancer immunotherapeutics.
In: Galluzzi L, Rudqvist N-P (eds) International review of cell and molecular biology. Academic
Press, New York, pp 201–276
Bubenïk J, Perlmann P, Helmstein K, Moberger G (1970) Cellular and humoral immune responses
to human urinary bladder carcinomas. Int J Cancer 5:310–319
Cameron F, Whiteside G, Perry C (2011) Ipilimumab: first global approval. Drugs 71:1093–1104
Carroll J (2013) Novartis/Penn’s customized T cell wows ASH with stellar leukemia data. In:
FierceBiotech. https://www.fiercebiotech.com/biotech/novartis-penn-s-customized-t-cell-
wows-ash-stellar-leukemia-data. Accessed 5 Feb 2020
Chee DO, Townsend CM, Galbraith MA, Eilber FR, Morton DL (1978) Selective reduction of
human tumor cell populations by human granulocytes in vitro. Cancer Res 38:4534–4539
Commissioner O (2018) FDA approval brings first gene therapy to the United States. In: FDA.
http://www.fda.gov/news-events/press-announcements/fda-approval-brings-first-gene-therapy-
united-states. Accessed 5 Feb 2020
Corthell JT (2014) Chapter 5 - antibodies and titrations. In: Corthell JT (ed) Basic molecular
protocols in neuroscience: tips, tricks, and pitfalls. Academic Press, San Diego, pp 41–46
Coventry BJ, Ashdown ML (2012) The 20th anniversary of interleukin-2 therapy: bimodal role
explaining longstanding random induction of complete clinical responses. Cancer Manag Res
4:215–221
Cui C, Yu B, Jiang Q, Li X, Shi K, Yang Z (2019) The roles of PD -1/ PD -L1 and its signalling
pathway in gastrointestinal tract cancers. Clin Exp Pharmacol Physiol 46:3–10
Dallegri F, Ottonello L, Ballestrero A, Dapino P, Ferrando F, Patrone F, Sacchetti C (1991) Tumor
cell lysis by activated human neutrophils: Analysis of neutrophil-delivered oxidative attack and
role of leukocyte function-associated antigen 1. Inflammation 15:15–30
Darvin P, Toor SM, Nair VS, Elkord E (2018) Immune checkpoint inhibitors: recent progress and
potential biomarkers. Exp Mol Med 50:1–11
de Boer EC, de Jong WH, van der Meijden APM, Steerenberg PA, Witjes F, Vegt PDJ, Debruyne
FMJ, Ruitenberg EJ (1991) Leukocytes in the urine after intravesical BCG treatment for
superficial bladder cancer. Urol Res 19:45–50
Di Carlo E, Forni G, Lollini P, Colombo MP, Modesti A, Musiani P (2001) The intriguing role of
polymorphonuclear neutrophils in antitumor reactions. Blood 97:339–345
74 R. Donde et al.
Dong Y, Sun Q, Zhang X (2016) PD-1 and its ligands are important immune checkpoints in cancer.
Oncotarget 8:2171–2186
Dranoff G (2004) Cytokines in cancer pathogenesis and cancer therapy. Nat Rev Cancer 4:11–22
Draube A, Klein-González N, Mattheus S, Brillant C, Hellmich M, Engert A, von Bergwelt-Baildon
M (2011) Dendritic cell based tumor vaccination in prostate and renal cell cancer: a systematic
review and meta-analysis. PLoS ONE 6:e18801
Dunn GP, Koebel CM, Schreiber RD (2006) Interferons, immunity and cancer immunoediting. Nat
Rev Immunol 6:836–848
Dvorak AM, Connell AB, Proppe K, Dvorak HF (1978) Immunologic rejection of mammary
adenocarcinoma (TA3-St) in C57BL/6 mice: participation of neutrophils and activated macro-
phages with fibrin formation. J Immunol 120:1240–1248
Espinoza-Sánchez NA, Götte M (2019) Role of cell surface proteoglycans in cancer immunother-
apy. Semin Cancer Biol. https://doi.org/10.1016/j.semcancer.2019.07.012
Eyileten C, Majchrzak K, Pilch Z, et al (2016) Immune cells in cancer therapy and drug delivery.
Mediat Inflamm. https://doi.org/10.1155/2016/5230219
Fala L (2015) Cyramza (Ramucirumab) approved for the treatment of advanced gastric cancer and
metastatic non–small-cell lung cancer. Am Health Drug Benefits 8:49–53
Fuge O, Vasdev N, Allchorne P, Green JS (2015) Immunotherapy for bladder cancer. Res Rep Urol
7:65–79
Godleski JJ, Lee RE, Leighton J (1970) Studies on the role of polymorphonuclear leukocytes in
neoplastic disease with the chick embryo and walker carcinosarcoma 256 in vivo and in vitro.
Cancer Res 30:1986–1993
Grenier A, Combaux D, Chastre J, Gougerot-Pocidalo MA, Gibert C, Dehoux M, Chollet-Martin S
(2001) Oncostatin M production by blood and alveolar neutrophils during acute lung injury. Lab
Investig 81:133–141
Griffiths L, Binley K, Iqball S, Kan O, Maxwell P, Ratcliffe P, Lewis C, Harris A, Kingsman S,
Naylor S (2000) The macrophage – a novel system to deliver gene therapy to pathological
hypoxia. Gene Ther 7:255–262
Güngör N, Knaapen AM, Munnia A, Peluso M, Haenen GR, Chiu RK, Godschalk RWL, van
Schooten FJ (2010) Genotoxic effects of neutrophils and hypochlorous acid. Mutagenesis
25:149–154
Guo ZS (2018) The 2018 Nobel Prize in medicine goes to cancer immunotherapy (editorial for
BMC cancer). BMC Cancer. https://doi.org/10.1186/s12885-018-5020-3
Gupta MK, Behara SK, Vadde R (2017) In silico analysis of differential gene expressions in biliary
stricture and hepatic carcinoma. Gene 597:49–58
Gupta MK, Sarojamma V, Reddy MR, Shaik JB, Vadde R (2019a) Computational biology: toward
early detection of pancreatic cancer. CRO. https://doi.org/10.1615/CritRevOncog.2019031335
Gupta MK, Vadde R, Sarojamma V (2019b) Curcumin - a novel therapeutic agent in the prevention
of colorectal cancer. Curr Drug Metab. https://doi.org/10.2174/1389200220666191007153238
Hanna MG, Snodgrass MJ, Zbar B, Rapp HJ (1973) Histopathology of tumor regression after
intralesional injection of Mycobacterium bovis. IV. Development of immunity to tumor cells
and BCG. J Natl Cancer Inst 51:1897–1908
Hazama S, Tamada K, Yamaguchi Y, Kawakami Y, Nagano H (2018) Current status of immuno-
therapy against gastrointestinal cancers and its biomarkers: Perspective for precision immuno-
therapy. Ann Gastroenterol Surg 2:289–303
Hegner B, Schaub T, Janke D, Zickler D, Lange C, Girndt M, Jankowski J, Schindler R, Dragun D
(2018) Targeting proinflammatory cytokines ameliorates calcifying phenotype conversion of
vascular progenitors under uremic conditions in vitro. Sci Rep 8:1–11
Hendry S, Salgado R, Gevaert T et al (2017) Assessing tumor-infiltrating lymphocytes in solid
tumors: a practical review for pathologists and proposal for a standardized method from the
International Immuno-Oncology Biomarkers Working Group. Adv Anat Pathol 24:311–335
Houghton AM, Rzymkiewicz DM, Ji H et al (2010) Neutrophil elastase-mediated degradation of
IRS-1 accelerates lung tumor growth. Nat Med 16:219–223
Jaiswal S, Chao MP, Majeti R, Weissman IL (2010) Macrophages as mediators of tumor

immunosurveillance. Trends Immunol 31:212–219
Kim SY, Kim HP, Kim YJ, Oh DY, Im S-A, Lee D, Jong H-S, Kim T-Y, Bang Y-J (2008)
Trastuzumab inhibits the growth of human gastric cancer cell lines with HER2 amplification
synergistically with cisplatin. Int J Oncol 32:89–95
Lai Y, Dong C (2016) Therapeutic antibodies that target inflammatory cytokines in autoimmune
diseases. Int Immunol 28:181–188
Lambertsen KL, Finsen B, Clausen BH (2019) Post-stroke inflammation—target or tool for
therapy? Acta Neuropathol 137:693–714
Lasfar A, Abushahba W, Balan M, Cohen-Solal KA (2011) Interferon lambda: a new sword in
cancer immunotherapy. Clin Dev Immunol. https://doi.org/10.1155/2011/349575
Le DT, Lutz E, Uram JN et al (2013) Evaluation of ipilimumab in combination with allogeneic
pancreatic tumor cells transfected with a GM-CSF gene in previously treated pancreatic cancer.
J Immunother 36:382–389
Lee C-H, Wu C-L, Shiau A-L (2008) Salmonella choleraesuis as an anticancer agent in a syngeneic
model of orthotopic hepatocellular carcinoma. Int J Cancer 122:930–935
Lichtenstein AK, Berek J, Kahle J, Zighelboim J (1984) Role of inflammatory neutrophils in
antitumor effects induced by intraperitoneal administration of Corynebacterium parvum in
mice. Cancer Res 44:5118–5123
Lynch TJ, Bondarenko I, Luft A et al (2012) Ipilimumab in combination with paclitaxel and
carboplatin as first-line treatment in stage IIIB/IV non–small-cell lung cancer: results from a
randomized, double-blind, multicenter phase II study. JCO 30:2046–2054
Magalhaes I, Carvalho-Queiroz C, Hartana CA, Kaiser A, Lukic A, Mints M, Nilsson O,
Grönlund H, Mattsson J, Berglund S (2019) Facing the future: challenges and opportunities in
adoptive T cell therapy in cancer. Expert Opin Biol Ther 19:811–827
Mallepalli S, Gupta MK, Vadde R (2019) Neuroblastoma: an updated review on biology and
treatment. Curr Drug Metab. https://doi.org/10.2174/1389200221666191226102231
Marin-Acevedo JA, Dholaria B, Soyano AE, Knutson KL, Chumsri S, Lou Y (2018) Next
generation of immune checkpoint therapy in cancer: new developments and challenges. J
Hematol Oncol 11:39
Masihi KN (2001) Fighting infection using immunomodulatory agents. Expert Opin Biol Ther
1:641–653
Matlung HL, Szilagyi K, Barclay NA, van den Berg TK (2017) The CD47-SIRPα signaling axis as
an innate immune checkpoint in cancer. Immunol Rev 276:145–164
Miliotou AN, Papadopoulou LC (2018) CAR T-cell therapy: a new era in cancer immunotherapy.
Curr Pharm Biotechnol 19:5–18
Mócsai A (2013) Diverse novel functions of neutrophils in immunity, inflammation, and beyond. J
Exp Med 210:1283–1299
Mody K, Starr J, Saul M, Poorman K, Weinberg BA, Salem ME, VanderWalde A, Shields AF
(2019) Patterns and genomic correlates of PD-L1 expression in patients with biliary tract
cancers. J Gastrointest Oncol 10:1099–1109
Moehler M, Delic M, Goepfert K et al (2016) Immunotherapy in gastrointestinal cancer: recent
results, current studies and future perspectives. Eur J Cancer 59:160–170
Muthana M, Giannoudis A, Scott SD et al (2011) Use of macrophages to target therapeutic
adenovirus to human prostate tumors. Cancer Res 71:1805–1815
Muthana M, Rodrigues S, Chen Y-Y, Welford A, Hughes R, Tazzyman S, Essand M, Morrow F,
Lewis CE (2013) Macrophage delivery of an oncolytic virus abolishes tumor regrowth and
metastasis after chemotherapy or irradiation. Cancer Res 73:490–495
Myint ZW, Goel G (2017) Role of modern immunotherapy in gastrointestinal malignancies: a
review of current clinical progress. J Hematol Oncol 10:86
Okur FV, Brenner MK (2010) Cellular immunotherapy of cancer. In: Yotnda P
(ed) Immunotherapy of cancer: methods and protocols. Humana Press, Totowa, pp 319–345
76 R. Donde et al.
Pahl JH, Kwappenberg KM, Varypataki EM et al (2014) Macrophages inhibit human osteosarcoma
cell growth after activation with the bacterial cell wall derivative liposomal muramyl tripeptide
in combination with interferon-γ. J Exp Clin Cancer Res 33:27
Pallin DJ, Baugh CW, Postow MA, Caterino JM, Erickson TB, Lyman GH (2018) Immune-related
adverse events in cancer patients. Acad Emerg Med 25:819–827
Cancer 12:252–264
Patel BA, Liu SV (2019) Chapter 6 - lung adenocarcinoma: second-line treatment. In: Horn L
(ed) Pulmonary adenocarcinoma: approaches to treatment. Elsevier, New York, pp 103–114
Pento JT (2017) Monoclonal antibodies for the treatment of cancer. Anticancer Res 37:5935–5939
Pfirschke C, Engblom C, Rickelt S et al (2016) Immunogenic chemotherapy sensitizes tumors to
checkpoint blockade therapy. Immunity 44:343–354
Pickaver AH, Ratcliffe NA, Williams AE, Smith H (1972) Cytotoxic effects of peritoneal neutro-
phils on a syngeneic rat tumour. Nat New Biol 235:186–187
Pourhoseingholi MA, Vahedi M, Baghestani AR (2015) Burden of gastrointestinal cancer in Asia;
an overview. Gastroenterol Hepatol Bed Bench 8:19–27
Qin S, Xu L, Yi M, Yu S, Wu K, Luo S (2019) Novel immune checkpoint targets: moving beyond
PD-1 and CTLA-4. Mol Cancer 18:155
Rajewsky K (2019) The advent and rise of monoclonal antibodies. Nature 575:47–49
Rao D, Parakrama R, Augustine T, Liu Q, Goel S, Maitra R (2019) Immunotherapeutic advances in
gastrointestinal malignancies. NPJ Precision Oncol 3:1–9
Ratermann K, Cox J, Benitez L, Davis F (2018) Chapter 36 - drugs that act on the immune system:
cytokines and monoclonal antibodies. In: Ray SD (ed) Side effects of drugs annual. Elsevier,
New York, pp 477–487
Razaghi A, Owens L, Heimann K (2016) Review of the recombinant human interferon gamma as an
immunotherapeutic: impacts of production platforms and glycosylation. J Biotechnol
240:48–60
Reeves EP, Lu H, Jacobs HL, Messina CGM, Bolsover S, Gabella G, Potma EO, Warley A, Roes J,
Segal AW (2002) Killing activity of neutrophils is mediated through activation of proteases by
K + flux. Nature 416:291–297
Repp R, Valerius T, Sendler A, Gramatzki M, Iro H, Kalden JR, Platzer E (1991) Neutrophils
express the high affinity receptor for IgG (Fc gamma RI, CD64) after in vivo application of
recombinant human granulocyte colony-stimulating factor. Blood 78:885–889
Restifo NP, Dudley ME, Rosenberg SA (2012) Adoptive immunotherapy for cancer: harnessing the
T cell response. Nat Rev Immunol 12:269–281
Rider P, Carmi Y, Cohen I (2016) Biologics for targeting inflammatory cytokines, clinical uses, and
limitations. Int J Cell Biol. https://doi.org/10.1155/2016/9259646
Roth M, Linkowski M, Tarim J, Piperdi S, Sowers R, Geller D, Gill J, Gorlick R (2014) Ganglioside
GD2 as a therapeutic target for antibody-mediated therapy in osteosarcoma. Cancer
120:548–554
Sahin U, Türeci Ö (2018) Personalized vaccines for cancer immunotherapy. Science
359:1355–1360
Scott AM, Wolchok JD, Old LJ (2012) Antibody therapy of cancer. Nat Rev Cancer 12:278–287
Seo G-M, Rachakatla RS, Balivada S et al (2012) A self-contained enzyme activating prodrug
cytotherapy for preclinical melanoma. Mol Biol Rep 39:157–165
Sibertin-Blanc C, Ciccolini J, Norguet E, Lacarelle B, Dahan L, Seitz J-F (2016) Monoclonal
antibodies for treating gastric cancer: promises and pitfalls. Expert Opin Biol Ther 16:759–769
Steinman RM, Cohn ZA (1973) Identification of a novel cell type in peripheral lymphoid organs of
mice. I. Morphology, quantitation, tissue distribution. J Exp Med 137:1142–1162
Stuart LM, Ezekowitz RAB (2005) Phagocytosis: elegant complexity. Immunity 22:539–550
Tannapfel A, Reinacher-Schick A (2019) Immunotherapy in gastrointestinal cancer: where do we
stand? VIS 1:1–2
Tran E, Ahmadzadeh M, Lu Y-C et al (2015) Immunogenicity of somatic mutations in human

gastrointestinal cancers. Science 350:1387–1390
Tseng D, Volkmer J-P, Willingham SB et al (2013) Anti-CD47 antibody-mediated phagocytosis of
cancer by macrophages primes an effective antitumor T-cell response. Proc Natl Acad Sci U S A
110:11103–11108
Tundo GR, Sbardella D, Lacal PM, Graziani G, Marini S (2019) On the horizon: targeting next-
generation immune checkpoints for cancer treatment. Chemotherapy 64:62–80
van Hooren L, Sandin LC, Moskalev I, Ellmark P, Dimberg A, Black P, Tötterman TH, Mangsbo
SM (2017) Local checkpoint inhibition of CTLA-4 as a monotherapy or in combination with
anti-PD1 prevents the growth of murine bladder cancer. Eur J Immunol 47:385–393
van Willigen WW, Bloemendal M, Gerritsen WR, Schreibelt G, de Vries IJM, Bol KF (2018)
Dendritic cell cancer therapy: vaccinating the right patient at the right time. Front Immunol.
https://doi.org/10.3389/fimmu.2018.02265
Wang D, Pei K, Fu Y, Sun Z, Li S, Liu H, Tang K, Han B, Tao Y (2007) Genome-wide analysis of
the auxin response factors (ARF) gene family in rice (Oryza sativa). Gene 394:13–24
Weiskopf K (2017) Cancer immunotherapy targeting the CD47/SIRPα axis. Eur J Cancer
76:100–109
Wilhelm M, Smetak M, Schaefer-Eckart K, Kimmel B, Birkmann J, Einsele H, Kunzmann V
(2014) Successful adoptive transfer and in vivo expansion of haploidentical γδ T cells. J Transl
Med 12:45
Wirth TC, Harty JT, Badovinac VP (2010) Modulating numbers and phenotype of CD8+ T cells in
secondary immune responses. Eur J Immunol 40:1916–1926
Wu Y, Chen W, Xu ZP, Gu W (2019) PD-L1 Distribution and perspective for cancer immunother-
apy—blockade, knockdown, or inhibition. Front Immunol. https://doi.org/10.3389/fimmu.
2019.02022
Zappasodi R, Merghoub T, Wolchok JD (2018) Emerging concepts for immune checkpoint
blockade-based combination therapies. Cancer Cell 33:581–598
Chapter 6
Immune Checkpoint Inhibitors
in Gastrointestinal Malignancies
Padmaraju Vasudevaraju and Malla Rama Rao
Abstract Gastrointestinal (GI) malignancies like esophageal, gastric, colorectal

cancers, etc. are responsible for 22% cancer deaths and are the third most cause of
cancer related deaths. GI cancers are treated by surgery, radiotherapy, and chemo-
therapy. The overall survival rate (5 years of survival) after the surgery is very poor
in patients with GI cancers. To increase the survival rate adjuvant therapies like
chemotherapy and radiotherapy were performed. As GI cancers are diagnosed at the
advanced stages by the limitations in the diagnosis methods, always there is a need to
find the improved diagnostic criteria and effective combination treatments for GI
cancers. Immunotherapy is used in combination with other therapies to treat GI
cancers. Specifically use of immune checkpoint inhibitors (ICIs) in treating the
different GI cancers is investigated by the researchers in clinical studies. Generally,
cancer cells are recognized by patients own immune system as foreign and can be
eliminated. But cancer cells escape the immune system by expressing the inhibitory
immune checkpoint (IC) signal target receptor molecules for PD-1, CTLA4, A2AR,
etc., and immune cells cannot recognize these cancer cells as foreign for attack. GI
cancer cells also express these inhibitory signals especially PD-1 and interact with
PD-L1 on natural killer cells and escape from its action. Immune checkpoint
inhibitors like nivolumab, pembrolizumab, atezolizumab, ipilimumab are used to
inhibit the inhibitory signals and activate the immune system to eliminate the cancer
cells. The use of immune checkpoint inhibitors will be beneficial to treat recurrent
malignancy as combination therapy.
P. Vasudevaraju
Department of Biochemistry and Bioinformatics, Institute of Science, GITAM (Deemed to be
University), Visakhapatnam, India
M. R. Rao (*)
Department of Biochemistry and Bioinformatics, Institute of Science, GITAM (Deemed to be
University), Visakhapatnam, India
Cancer Biology Lab, Department of Biochemistry and Bioinformatics, Institute of Science,
GITAM (Deemed to be University), Visakhapatnam, India
https://doi.org/10.1007/978-981-15-6487-1_6
80 P. Vasudevaraju and M. R. Rao
Keywords Gastrointestinal malignancies · Immunotherapy · Immune checkpoint

inhibitors · Tumor microenvironment
Abbreviations
A2AR Adenosine receptor 2

AFP Alpha-fetoprotein
BTLA B and T-lymphocyte attenuator
CTLA4 Cytotoxic T-lymphocyte-associated protein 4
CXCR4 CX-C: chemokine receptor type 4
CEA Carcinoembryonic antigen
CA 19-9
CD Cluster of differentiation
CTL4 Cytotoxic T-lymphocyte associated protein 4
CSF-1 Colony stimulating factor-1
EBV Epstein–Barr virus
ENTPD2 Ectonucleoside triphosphate diphosphohydrolase 2
ESCC Esophageal squamous cell carcinoma
EMT Epithelial to mesenchymal transition
FAP Fibroblast activation protein
FAK Focal adhesion kinase
GI Gastrointestinal
GITR Glucocorticoid-induced tumor necrosis factor receptor-related protein
HLA Human leukocyte antigen
HAT1 Histone acetyltransferase 1
HIF-1 Hypoxia inducible factor-1
HER2 Human epidermal growth factor receptor 2
ICOS Inducible Co-Stimulator
IDO Indoleamine-2,3-dioxygenase
ICIs Immune checkpoint inhibitors
IL-6 Interleukin-6
LAG3 Lymphocyte activating gene 3
ICIPI Induced pancreatic injury
IRE Irreversible electroporation
KIR Killer cell immunoglobulin-like receptors
MSS Microsatellite stable
MDSC Myeloid-derived suppressor cells
MSI Microsatellite instability
NOX2 NADPH oxidase isoform 2
NK Natural killer cells
NE Neuroendocrine
OPN Osteopontin 40
PD-1 Programmed cell death protein 1
6 Immune Checkpoint Inhibitors in Gastrointestinal Malignancies 81
PD-L1 Programmed cell death protein 1 ligand

PDAC Pancreatic ductal adenocarcinoma
SRCC Signet-ring cell carcinoma
TME Tumor microenvironment
TIM-3 T-cell immunoglobulin and mucin domain 3
TMITs Tumor microenvironment immune types
TAA Tumor-associated antigen
TIL Tumor infiltrating lymphocytes
TAMs Tumor-associated macrophages
VEGFR2 Vascular endothelial growth factor receptor 2
VISTA V-domain immunoglobulin suppressor of T-cell activation
6.1 Introduction
Gastrointestinal (GI) malignancies have a colossal impact on cancer-related mortal-

ity. They include esophageal, gastric, and colorectal cancers, which are responsible
for 22% of cancer deaths. This is due to poor dietary intake, use of tobacco, irrational
consumption of alcohol, obesity, and some pathogens (Sonnenberg 2017). Tradi-
tionally, GI cancers are being treated by surgery, radiotherapy, and chemotherapy.
Despite, prognosis and treatment of metastatic GI cancers is still dismal. They can be
diagnosed by routine serological biomarkers such as CEA, CA 19-9, and AFP
(Posner and Mayer 1994). In addition, recent advances in molecular mechanisms
of GI cancers lead to shaping of the therapeutic approaches including immunother-
apy, in which immune system of patient’s is reprogrammed to selectively target
tumor (Rao et al. 2019). The immune system presents an initial recognition and
targeting in hide and seek manner within the tumor microenvironment (TME).
Immune checkpoints are regulators of self- and non-self antigen discrimination
and auto-immunity suppression. They can also involve in immune escape of cancer
cells via genetic and epigenetic manipulation of formation, presentation, and
processing of neoantigen by modulating PD-1/PD-L1 and CTLA4 pathways (Pitt
et al. 2016). Therefore, immune evasion can be targeted by blocking checkpoints
using immune checkpoint inhibitors. Three complex systems that exist in cancer are
tumor cell, tissue microenvironment, and immune response. Understanding these
three systems and their interactions between them in specific cancer type is very
important in treating the tumors. In gastrointestinal malignancies there is a link
between infection, chronic inflammation, and malignancy development.
Helicobacter pylori infection is one such example of infection leading to tumor
development and H. pylori regarded as class I antigen (Murphy and Kelly 2015). An
antitumor mechanism of immune system involves identifying the cancer cells as
non-self by immune cells through regulating the checkpoint control. This strategy
becomes an important phenomenon in establishing potential therapies for treating
different GI cancers. Immune checkpoints suppress the cytotoxic action of immune
cells on cancer cells and cancer cells escape the destruction by immune action.
Immune checkpoints are of stimulatory and inhibitory by their action, stimulatory
signals recognize target molecules as non-self and execute the cytotoxic action and
inhibitory signals recognize the target molecules as self and prevent them from
cytotoxic action of immune cells. The stimulatory checkpoint molecules include
CD27, CD28, CD40, CD122, CD137, OX40, GITR, ICOS, etc. The inhibitory
checkpoint molecules include A2AR, B7-H3, B7-H4, BTLA, CTLA4, IDO, KIR,
LAG3, NOX2, PD-1, TIM-3, VISTA, etc. Immune checkpoint inhibitors enable the
immune cells to effectively kill the cancer cells by inhibiting the inhibitory signals.
The cancer cells express high levels of inhibitory target molecules on their surfaces
which interact with inhibitory signals and escape the cytotoxic effects of immune
cells. ICI increases the immunomodulating ability of natural killer (NK) cells and
enhances the effects of anticancer activity. Along with immune checkpoint mole-
cules like PD-L1, other components in the tumor microenvironment like tumor cell-
intrinsic osteopontin (OPN) and the expansion of tumor-associated macrophages
(TAMs) drive the immune escape. Immune checkpoint inhibitor (ICI) strategy may
have the potential to induce an abscopal effect in treating the malignancy. In this
effect, treatment of tumor with radiation therapy at one site in combination with ICI
shows response to ICI at another site providing the high beneficial effect in treating
the metastatic tumors (Cecchini et al. 2015). In this chapter, the role of ICI in
preventing the different gastric malignancies and their mechanisms are discussed
(Fig. 6.1).
6.2 Immune Checkpoint Blockade in Esophagus

Malignancies
Immunotherapy is emerging as a potential therapy for esophageal cancers and

immune checkpoint inhibitors are under clinical trials (Tanaka et al. 2017; Kojima
and Doi 2017). Esophageal squamous cell carcinoma (ESCC) patient’s population
showed a heterogeneous expression of PD-L1 (programmed cell death protein
1 ligand) with high level of amplification in programmed cell death protein 1 ligand
precursor (CD274) protein (Guo et al. 2018). Blocking the immune checkpoint
protein PD-1 interaction with PD-L1 can induce the action of immune system on
cancer cells and can act as a potential method of treating the ESCC patients. The
clinical study conducted by Chen et al. also showed the higher expression of immune
checkpoint target molecule, PD-L1 in the epithelial to mesenchymal transition
(EMT) positive subgroup of human esophageal cancer (Chen et al. 2017a). This
indicates the immune suppression is mediated by the inhibitory checkpoint molecule
PD-1 in esophageal cancer. In the study by Jang et al., also showed that the low risk
ESCC group exhibits the PD-L1 expression and immune checkpoint inhibitor
treatment is suggested to treat ESCC patients (Jang and Lee 2017). Increased
expression of PD-1 in natural killer cells (NK cells) has also been observed in
Fig. 6.1 General mechanism of immune escape of cancer cell and role of ICIs in enhancing
anticancer Immune therapy. Cancer cell expresses immune inhibitor protein molecules like
PD-L1 or B7-1/B7-2 and during priming cytotoxic T-cells (CTLs) in cancer tissue inhibitor
checkpoints like PD-1/CTLA-4 are expressed at high levels. The interaction of inhibitory signals
on CTLs with their receptors on cancer cells results in the escape of cancer cells from cytotoxic
action of CTLs. ICIs block the interaction between inhibitor signals with their receptors allowing
the attack of CTLs on cancer cells and killing them
gastrointestinal cancers indicating the role of immune checkpoint alteration in these

cancers (Liu et al. 2017a). This positive sensitization of immune cells to express
more inhibitory molecules is triggered by the cancer cells and becomes important to
know the mechanism by which the cancer cells can program immune cells to
survival. Tumor infiltrating lymphocytes (TIL)—a positive group of patients have
shown good cancer specific survival in one of the clinical studies (Sudo et al. 2017).
The tumor infiltrating lymphocytes are the immune cells that are infiltrated into
tumor from blood and fight with the cancer cells. Tumor infiltrated immune cells are
used in treatment of cancers by isolating the TILs from patients and improving their
ability to attack the cancer cells by in vitro methods in research labs. Then the
activated TIL cells which are prepared in research labs are injected to patients for
treatment. The study by Zheng et al. suggested the prognostic role of TIL subtypes in
esophageal carcinoma patient can be used as prognostic biomarkers in treating
cancer (Zheng et al. 2018). Identification of esophageal cancer subtype and markers
is important to select the treatment module.
Impaired DNA mismatch repair leads to a condition of genetic hyper mutability

termed as microsatellite instability (MSI). Yu Imamura et al. reviewed that micro-
satellite markers BAT25, BAT26, BAT40, D2S123, D5S346, and D17S250 were
high in surgically resected esophagogastric junction (EGJ) adenocarcinoma in
Japanese patients. They suggested that the MSI status is highly beneficial in selecting
immune checkpoint inhibitors treatment for EGJ adenocarcinoma (Imamura et al.
2019). The MSI status is suggested to be a prognostic biomarker for the patients
undergoing chemotherapy treatment among EGJ adenocarcinoma patients (Haag
et al. 2019). MSI positive phenotype groups are predicted to have improved response
to PD-1 inhibitors in treatment module (Lin et al. 2018). Another potential bio-
marker identified to monitor the prognosis and treatment response is the elevation of
T-cell immunoglobulin and mucin domain-containing protein 3 (Tim-3) in ESCC
with nivolumab therapy (Kato et al. 2018). Monoclonal antibody directed against
PD-1 (pembrolizumab) is approved by FDA as first and second line therapy in
combination with chemotherapy for EGJ adenocarcinoma (Joshi et al. 2018).
Based on the above studies and hypothesis the immunotherapy using immune
checkpoints is a promising strategy in treating esophageal cancers. Especially
antibodies and compounds targeting PD-1/PD-L1 are going to be a promising
method for esophageal cancers.
6.3 Immune Checkpoint Blockade in Stomach

Malignancies
Gastric cancer is one of the most cancer related cause of death. Gastric cancer has a
very poor survival rate after the conventional treatment of surgery (Abozeid et al.
2017). Gastric cancer is an aggressive type and majority of them have unresectable
disease and distant metastasis. Gastric cancer is detected generally in the advanced
stage and the treatment of advanced gastric cancer is a challenging task (Jou and
Rajdev 2016). The clinical stage I gastric adenocarcinoma is treated surgically and
class II, III stages treated with a multidisciplinary approach along with surgical
intervention. The clinical stage IV is an advanced stage and has a survival period of
around 9–10 months (Ajani et al. 2017). First line of therapy for the treatment of
advanced adenocarcinoma is chemotherapy. An effective line of treatment emerging
to treat gastric cancer is by identifying the molecular drivers of different biological
targets. This has led to the identification of human epidermal growth factor receptor
2 (HER2) and vascular endothelial growth factor receptor 2 (VEGF-R2) as biolog-
ical targets. Immunotherapy in combination with the other treatments is gaining
importance in gastric cancer treatment (Lazar et al. 2018). Along with these targets,
another new line of biological targets called immune checkpoints becoming the
target molecules and inhibition of these immune checkpoint targets by ICIs can be
used for effective treatment in gastric cancers (Sun and Yan 2016). In one of the
gastric cancer subtype tumor positive for Epstein–Barr virus (EBV), CD274
(PD-L1) and PD-L2 expression was elevated indicating the intervention of immune
checkpoint inhibitors in treatment strategy (Cancer Genome Atlas Research Network
2014). The PD-L1 expression is induced by the inhibition of autophagy in gastric
cancer cell lines (Wang et al. 2019). The use of ICIs in the treatment has to be
supported with patient expression data of immune checkpoint targets. The use of
ICIs in unselected population may lead to failure of response to the treatment
(Abdel-Rahman 2016). The blockade of PD1/PDL1 using the antibodies along
with other treatments of cancer like chemotherapy, radiotherapy, and other immu-
notherapies becomes an effective strategy to combat gastrointestinal cancers (Lote
et al. 2015). Different immune modulating agents are in clinical trials to find
molecules for immunotherapy and one such molecule is pembrolizumab.
Pembrolizumab is an anti-programmed death 1 receptor antibody that is under
clinical trial (Davidson et al. 2015).
The study by Thompson et al. showed the expression of PD-L1 in the cell
membranes of gastric adenocarcinoma tumor cells (around 12%) and immune
stromal cells (around 44%). In this study they also observed the CD8+ T-cell
densities correlating with that of PD-L1 expression in both tumor cells and stromal
cells (Thompson et al. 2017). Modification of tumor microenvironment with ICIs
and matrix metalloproteinase-9 inhibitors also gave better treatment results (Lordick
et al. 2017). Fibroblast activation protein-a (FAP) is expressed in cancer associated
fibroblasts and targeting the FAP+ cancer associated fibroblasts enhanced the
immune checkpoint inhibitor effects (Wen et al. 2017). In gastric signet-ring cell
carcinoma (SRCC) there is a correlation between PD-1, PD-L1 expression and
CD3+ T-cell infiltration. In advanced gastric cancer a positive correlation between
PD-L1 and CD8+ T-cell infiltration was observed in patients (Wang et al. 2018a).
The combination of these changes can be evaluated as potential biomarkers for
SRCC cancers and the combination therapies including the immune checkpoint
inhibitors emerge as potential treatment (Jin et al. 2017).
Tumor microenvironment (TME) is composed of cellular and non-cellular
components such as fibroblasts, adipose cells, neuroendocrine (NE) cells, immune
inflammatory cells, blood, lymphatic networks, myofibroblasts, extracellular
matrix, etc. (Wang et al. 2017). Based on PD-L1 and CD8 antigen/cytolytic
activity (CYT) the tumor microenvironment immune types (TMITs) are classified
into four types (Table 6.1). The stomach cancers fall into type I category having
high PD-L1 and CD8A expression and identifying the immune type helps in
selecting the treatment strategy (Chen et al. 2017b). Cancer Genome Atlas gastric
cancer data analysis showed that the EBV positive tumors are microsatellite stable
(MSS) group and have higher expression of PD-L1 and TILs with low mutation
burden. This suggests that EBV positive-MSS gastric cancers can be treated with
immune checkpoint inhibitors (Panda et al. 2018). Apart from that the potential
biomarkers like PD-L1 expression, TILs, CD8A expression other markers like
MSI status and DNA mismatch repair (MMR) status is used in selecting the
immunotherapy for treatment. Gastric cancers with MSI are categorized into a
new subgroup having different prognostic value and need different treatment
strategy (Ratti et al. 2018). The gastric cancers showed increased MMR deficiency
Table 6.1 Mechanism of immune escape and role of ICIs in immunotherapy of different GI
malignancies
Type of GI
cancer Mechanism of immune escape Possible ICI intervention
Esophageal • Heterogeneous expression of • Biomarker identification of molecules like
cancer PD-L1 and its precursor CD247 BAT25, DS123, Tim-3, etc., to identify
• Heterogeneous level of tumor subtype
infiltrating lymphocytes (TILs) • ICIs are used to suppress the inhibitory
signal PD-1
• TILs isolation from patient and activated
TILs in labs and then injected again
• Combination of other therapies along with
ICIs
Stomach • Epstein–Barr virus (EBV) • Identification gastric cancer subtype and
cancer subtype expresses PD-L1 and other biomarkers like MSI status, TILs, etc.
PD-L2 • Use of ICIs to inhibit the PD-1 binding to
• Both PD-L1 and CD8+ T-cell PD-L1
densities elevated • Combination therapy along with the ICIs
• Cancer associated fibroblasts like anti-VEGF-R2 therapy
express fibroblast activation pro-
tein-A
Pancreatic • Excessive stromal matrix and • Vaccine inducing T-cell response along
cancer hyper vasculature with ICIs
• Decreased level of ICI target • Targeting pathways like FAK inhibition,
molecules like PD-L1, etc. IL-6, macrophage derived granulin which
• Poor response to immunother- increase T-cell infiltration
apy • Selection of treatment with monitoring
• Decreased CTL infiltration responses
• Increased immune inhibitory • ICI treatment enhances other treatment
cells efficiency and vice versa
Liver • Decreased CTL infiltration • Treatment with ICIs like anti-PDl1 and anti-
cancer • Increased PD-L1 CTLA4
• Hypoxia increased HIF-1 and • Inhibition of myc gene and Tim-3 along
CXCR4 with ICIs
• Increased IL-6 • Other combination therapies increase the
efficiency of ICIs
Colorectal • Increased immunosuppressive • Identification of colorectal cancer subtype
cancer cells and signals • Induction of T-cell recruitment
• Blocking the immunosuppressive signals
with ICIs and immunosuppressive cells
and MSI status compared to esophageal cancers. While gastric cancers are positive
for EBV when compared to esophageal cancers, MSI and MRR are not indicating
the importance of characterizing the cancer biomarkers in selecting the immune
checkpoint inhibitor strategy (Hewitt et al. 2018).
Immunotherapy using the immune checkpoint inhibitors for the advanced stages
of gastric cancer has promising results in treatment. The targets of ICIs are PD-1,
PD-L1 and these target levels serve as biomarkers in identifying the stages of gastric
cancer (Tran et al. 2017). Pinto MP et al. hypothesized that combination therapy
using angiogenic inhibitors along with immunotherapy using immune checkpoint

inhibitors will be a good treatment model for gastric cancers (Pinto et al. 2017). PD-1
and PD-L1 expression is frequent in neuroendocrine malignancies of digestive
system and targeting PD-1and PD-L1 using checkpoint blockade has the potential
in treating these carcinomas (Roberts et al. 2017). FDA (US) approved drug
pembrolizumab is suggested for the first and second line therapy with a combination
of other therapies in treating gastric adenocarcinoma (Joshi et al. 2018). Other drugs
like nivolumab, avelumab, atezolizumab are the antibodies developed to block the
PD-1/PD-L1 blocking are showing promising results in clinical trials for gastric
cancer treatment. These drugs along with the combination of other target candidates
like anti-CTLA4 and anti-VEGF-R2 therapy are suggested for the treatment of
adenocarcinoma. Cytotoxic T-Lymphocyte associated protein 4 (CTL4 or CD152)
is a protein receptor involved in the inhibition of cytotoxic T-Lymphocytes and
VEGFR-2 is involved in the signaling pathway of immunosuppression (Smyth and
Thuss-patience 2018).
6.4 Immune Checkpoint Blockade in Pancreatic

Malignancies
Tumor microenvironment plays a critical role in treating pancreatic malignancies. A

unique TME exists in pancreatic cancer having an excessive stromal matrix and
hyper vasculature creating the immune barrier for CTL infiltration. Other resistant
factors like pancreatic stroma, genetic predisposition, immune inhibitory cells,
cytokines, and epigenetics pose difficulty in treatment. Pancreatic cancers are
regarded as non-immunogenic cancers and have a very poor response to immuno-
therapy. Pancreatic cancer has only a 9% survival (5 year survival) rate and novel
strategies have to be identified to combat this type of cancer. In a mouse model of
pancreatic ductal adenocarcinoma (PDAC), the inhibition of myeloid growth factor
receptor (CSF1R) increased the antigen presentation and T-cell antitumor responses
to ICIs (Zhu et al. 2014). Immune checkpoint inhibitors targeting CTLA-4, PD-1,
and PD-L1 did not show good promising treatment effects in PDAC when used
alone. But when ICIs are used together with other treatment strategies like vaccine
inducing T-cell response they have shown some good results. This response is
mainly due to the increased expression of ICI targets with vaccine treatment (Soares
et al. 2015). In this type of strategy, the vaccine induces T-cell to kill pancreatic
cancer cells, while other treatments used in combination with ICIs facilitates the
trafficking of T-cells to the site of cancer in cell culture model of PDAC the
combination of vaccine therapy, indoleamine-2,3-dioxygenase (IDO1) inhibitor
and PD-L1 showed no positive correlation in comparison of vaccine therapy and
IDO1 inhibitors. This indicates that the selection of combination therapy along with
ICI is essential in attempting the treatment (Blair et al. 2019). In general, the cancer
cells exposed to constant antigenic exposure lead to T-cell transformation from
active state to inactive state. This causes T-cell exhaustion and T-cell proliferation
and activation are needed to treat this stage in pancreatic cancers (Bauer et al. 2016).
Jiang et al. showed that the focal adhesion kinase (FAK) inhibition increases the
cytotoxic CD8+ T-cell infiltration and increases the ICI responses in pancreatic
cancers (Jiang and Hegde 2016). In another study it has been shown that targeting
macrophage derived granulin restored the CD8+ T-cell infiltration in metastatic
PDAC and increased response to ICIs (Quaranta et al. 2018). The targeted inhibition
of interleukin IL-6 also increased the response of ICI treatment in the preclinical
trials (Mace et al. 2018). Receptor-interacting serine/threonine protein kinase
1 (RIP1) is upregulated in tumor-associated macrophages (TAMs) in PDAC and
the inhibition of RIP1 in combination with ICIs benefits greatly in treating PDAC
with immunotherapy (Wang et al. 2018b). In pancreatic cancer, histone
acetyltransferase 1 (HAT1) is upregulated and PD-L1 is linked to the regulation of
HAT1 expression. The HAT1 expression may be used as a prognostic biomarker for
the treatment of PDAC (Fan et al. 2019). The combination therapies along with
immune checkpoint inhibitors used to treat pancreatic malignancies are vaccination,
tumor targeted oncolytic viruses, whole cell immunotherapy, CD40 agonists to
promote APC maturation, MEK inhibitors, cytokine inhibitors, etc.
The above studies indicated that the effectiveness of ICIs is enhanced by the other
combination therapies in treating the pancreatic tumors. In some cases the blockade
of PD-L1 enhanced the effectiveness of the radiotherapy in PDAC model (Azad
et al. 2017). Also the PD-L1 treatment sensitizes the antiangiogenic therapy and
in turn the antiangiogenic therapy increases response to ICIs and CTL infiltration
(Allen and Jabouille 2017). However, the PDAC patients show poor prognosis with
combination therapies and it is very challenging to find effective treatments to
PDAC treatment. A complete tumor genotyping and gene expression analysis may
provide novel targets and improves ICI effective usage in treatments. The biomarker
driven approach for finding the target molecules may give additional strength to treat
this complex PDAC patients (Zhen et al. 2018). The usage of ICIs may lead to
immune checkpoint inhibitor induced pancreatic injury (ICIPI) in some of the
patients emphasizing the use of ICIs with caution (Abu-Sbeih et al. 2019). Recently
the study by Zhao et al. using irreversible electroporation (IRE) technique in
combination with ICI treatment showed promising approach in treating the PDAC
(Zhao et al. 2019). In the cell line models the use of chemotherapy agent gemcitabine
and a novel programmed death-ligand 1 (PD-L1) inhibitor (MN-siPDL1) showed a
90% reduction in tumor growth and increased survival (Yoo et al. 2019).
Gemcitabine is a chemical compound which is incorporated into DNA during
DNA synthesis and halts DNA synthesis leading to cell death. These recent strate-
gies show some good promising results and suggest the use of immune checkpoint
inhibitors in treating pancreatic cancers.
6.5 Immune Checkpoint Blockade in Liver Malignancies
Hepatocellular carcinoma (HCC) incidence is increasing and identifying the targets

for the treatment is becoming a challenge. In the first line therapy sorafenib is
approved for the systemic therapy and second line therapy molecules like
regorafenib, lenvatinib, cabozantinib, and ramucirumab are shown to improve the
survival. To increase the median survival periods, other line of therapies like ICIs is
being incorporated in the treatment (Llovet et al. 2018). Chronic inflammation is
reported in hepatocellular carcinoma patients indicating the potential immune based
therapies in treating HCC patients. HCC models showed decreased infiltration of
cytotoxic CD8+ T-cells to the site of tumor. In the HCC tumor environment hypoxia
develops and this condition stabilizes the hypoxia inducible factor-1 (HIF-1) which
stimulates the expression of ectonucleoside triphosphate diphosphohydrolase
2 (ENTPD2/CD39L1). The ENTPD2 enzyme converts extracellular ATP to
50 -AMP and the 50 -AMP inhibits the myeloid-derived suppressor cells (MDSCs)
differentiation. The MDSCs exert immunosuppressive actions and cancer cells
escape the action of immune system to eliminate the cancer cells (Chiu et al.
2017). In HCC models the use of systemic therapy molecule, sorafenib (tyrosine
kinase inhibitor) increases hypoxia which in turn activates the immunosuppressive
actions. The hypoxia condition increases the expression of stromal cell derived
1 alpha receptor (CXCR4) and CXCR4 may be responsible for immunosuppressive
action (Chen et al. 2015). The hypoxia condition in HCC also induces increased
expression of PD-L1 along with CXCL12 (Semaan et al. 2017). The prevalence of
the above conditions makes the tumor more immunocompromised. The immune
checkpoint inhibitor treatment with antibody against PD1 receptor along with the
sorafenib and anti-CXCR4 molecule AMD3100 has better results in treating the
HCC. In one of the case study with metastatic hepatocellular carcinoma
pembrolizumab (immune checkpoint inhibitor) treatment after failure of using
sorafenib showed good response by decreasing the tumor size (Truong et al.
2016). In HCC, interleukin-6 (IL-6) is secreted by tumor-associated fibroblast and
recruits immunosuppressive cells like myeloid-derived suppressive cells inducing
the immunosuppressive mechanisms. The interleukin-6 is also involved in the
expression of immune checkpoints which inhibit the immune action against cancer
cells. In the mouse models of HCC, inhibition or targeting the IL-6 expression
increased the ability of the anti-PD-L1 treatment (Liu et al. 2017b). Radiation
therapy also showed improved response to the ICIs indicating the combination
therapies are effective methods in the treatment of cancer. Radiation therapy
increased the PD-L1 expression which resulted in effective response to anti-PD-L1
inhibitors (Kim et al. 2017). Patients treated with radiotherapy showed increased
soluble PD-L1 (sPD-L1) in blood and this sPD-L1 can act as a predictive biomarker
for the combined therapy of radiotherapy and ICIs (Kim et al. 2018). Along with the
PD-L1, other molecules like CTLA-4, lymphocyte activating gene 3 (LAG3), and
hepatitis A virus cellular receptor 2 (TIM3) are highly expressed on tumor-
associated antigen (TAA) specific-CD8+ TIL cells in HCC patients. This strongly
suggests the combination therapy with multiple ICIs will have additive effects in
HCC treatment (Zhou et al. 2017). Treatment of HCC patients with anti-CTLA4 and
tremelimumab activated the T-cell responses in HCC patients. In the treated patients,
CD4+-HLA-DR+, CD4+ PD-1+, CD8+ HLA-DR+, CD8+ PD-1+, CD4+ ICOS+, and
CD8+ ICOS+ T-cells are increased in the peripheral blood. Among these patients,
patients having high frequency of CD4+ PD-1+ respond more to treatment indicating
that CD4+ PD-1+ may act as potential biomarker for treatment (Agdashian et al.
2019). The oncogene myc inhibition in HCC induces the expression of interferon-γ
(INF-γ) which upregulates the PD-L1 levels. In lymphomas myc gene upregulates
PD-L1 in contrast to its effects in HCC, indicating different tumor environments
regulate immune checkpoint molecules differently in different types of cancers. The
identification of myc gene behavior in HCC suggests the potential of combination
therapy of inhibiting the myc gene and the use of ICIs (Zou et al. 2018). In the mouse
models of HCC, the tumors with high expression of tumor cell-intrinsic osteopontin
(OPN) in the tumor microenvironment decreased the expression of PD-L1 and
expansion of tumor-associated macrophages (TAMs). The decrease in these mole-
cules is mediated by the stimulation of the colony stimulating factor-1 (CSF1) and
CSF1 receptor (CSF1R). This study suggests the use of the ICIs along with the
inhibition of CSF1/CSF1R, OPN levels are established in the HCC patients (Zhu
et al. 2019). Some patients with HCC showed resistance to anti-PD-1 therapies and
transgenic mouse models showing the exogenous expression of antigens in myc;
Trp53/ HCCs escaped from immune actions. In this model the HCCs escaped the
immune system by upregulating the β-catenin (CTNNB1) pathway. This identifica-
tion of β-catenin induced immune escape makes to develop new strategies to treat the
anti-PD1 resistant HCCs (Ruiz de Galarreta et al. 2019; Berraondo and Ochoa 2019).
6.6 Immune Checkpoint Blockade in Colorectal Cancer
Colorectal cancer (CRC) is the third prominent cause of death in both males and
females worldwide. In the recent past, all survival (OS) of CRC patients have
notably enhanced due to advancement in chemotherapy as well as immunotherapy.
A large body of literature showed the importance of anti-PD-1 therapy for CRC
subtypes (Yaghoubi et al. 2019). Immune checkpoint inhibitors have showed prom-
ising results in metastatic CRCs (mCRCs) (Kamatham et al. 2019). For example,
FDA approved combination of nivolumab and ipilimumab has significantly
benefited mCRC patients (Morse et al. 2020). The efficacy of pembrolizumab
against mCRCs is under clinical trial at phase 2 multicenters (Le et al. 2015). The
studies on efficacy of anti-PD/PD-L1 agents, durvalumab and atezolizumab are in
progress. Alternative strategy for targeting CRCs is peptide vaccine which is in
clinical trial. In this strategy, specific neoantigen is detected using next-generation
sequencing on tumor tissue, specific peptides which can combine with human
leukocyte antigen (HLA) and coding for the neoantigen are synthesized
(Ghiringhelli and Fumet 2019). The strategies that enhance immunogenicity by
using oncolytic vaccines are currently under evaluation. They can be exploited to
induce a local immune response against cancer cells. Currently, FOLFOX plus
bevacizumab with or without an oncolytic reovirus in RAS mutated colon cancer
is in phase II trial. This strategy showed an improved response with shorter median
duration of response (Jonker et al. 2018). Another strategy for treatment of CRCs is
induction of T-cell recruitment using T-cell bispecific antibodies. In this strategy,
bispecific antibody which can bind to CD3 and tumor specific antigen
(e.g. TCB-CEA) can able to induce T-cell activation and forces them to detect and
kill cancer cells (Argilés et al. 2017). The removal of immunosuppressive cells or
molecules is also another strategy especially targeting MDSC and immunosuppres-
sive macrophages. The inhibitors of CSF1R and anti PD-1/PDL1 are currently in
development for targeting MDSC and immunosuppressive macrophages. Adenosine
is an important immunosuppressive molecule produced by both MDSC and Tregs
(Arab and Hadjati 2019). This molecule is generated by CD73 and CD39 molecules,
which degrade extracellular ATP. Therefore, combination of CD39 or CD73 inhib-
itors with checkpoints to reduce immunosuppression might be relevant (Perrot et al.
2019). Clinical trials with anti-PD1/PDL1 and anti-CD73 or anti-adenosine receptor
are ongoing. The strategies targeting immune checkpoints using inhibitors, vaccine,
bispecific mAbs as well as drugs targeting immunosuppression will probably change
the face of CRCs treatments.
6.7 Adverse Effects of ICI Usage
The use of ICIs sometimes leads to immune related adverse effects (irAEs) and are
different from other therapies. The commonly observed toxicities are gastrointesti-
nal, skin, liver, endocrine, eyes, pancreas, kidney, lung, and nervous system. These
toxicities are relieved by withdrawal of ICI treatment and sometimes suppressing the
immune response using steroids (Kottschade et al. 2016). The analysis of different
immune checkpoint inhibitors in treating cancer patients showed hepatotoxicity and
the high risk is noted with CTLA-4 treatment compared to PD-L1 treatment. Recent
study reported that ICI treatment lead to the development of insulin-dependent
diabetes in patients (Harsch and Konturek 2018).
6.8 Conclusion
Gastrointestinal (GI) tumors including esophageal, gastric, and colorectal cancers

have immense impact on cancer-related mortality and account for 22% of cancer
deaths. GI malignancies are traditionally treated with surgery, radiotherapy, and
chemotherapy, but their prognosis is still dismal due to poor dietary intake, use of
tobacco, irrational consumption of alcohol, obesity, and some pathogens. Recently,
immunotherapeutic approaches such as immune checkpoint inhibitors (ICIs) are
gaining advances for targeting GI cancers, which reprogram immune system of

patient to selectively target tumor. Even though, ICIs reported to show some
toxicities, nivolumab, pembrolizumab, atezolizumab, ipilimumab showed potential
to inhibit the inhibitory signals and activating the immune system to eliminate the
cancer cells. Therefore, use of ICIs will be beneficial to treat recurrent malignancy as
combination therapy.
Acknowledgments This review was supported by DST-EMR (EMR/2016/002694, dt. 21st

August 2017) (RRM) and CSIR (NO. 37(1683)/17/EMR-II, dt. 5th May 2017) (RRM), New
Delhi, India.
Conflict of Interest The authors declare that there are no conflicts of interest.
References
Abdel-Rahman O (2016) Immune checkpoints aberrations and gastric cancer; assessment of

prognostic value and evaluation of therapeutic potentials. Crit Rev Oncol 97:65–71
Abozeid M, Rosato A, Sommaggio R (2017) Immunotherapeutic strategies for gastric carcinoma: a
review of preclinical and clinical recent development. Biomed Res Int 2017:5791262
Abu-Sbeih H, Tang T, Lu Y, Thirumurthi S, Altan M, Jazaeri AA, Dadu R, Coronel E, Wang Y
(2019) Clinical characteristics and outcomes of immune checkpoint inhibitor-induced pancre-
atic injury. J Immunother Cancer 7(1):31
Agdashian D, ElGindi M, Xie C, Sandhu M, Pratt D, Kleiner DE, Figg WD, Rytlewski JA,
Sanders C, Yusko EC, Wood B, Venzon D, Brar G, Duffy AG, Greten TF (2019) The effect
of anti-CTLA4 treatment on peripheral and intra-tumoral T cells in patients with hepatocellular
carcinoma. Cancer Immunol Immunother 68(4):599–608
Ajani JA, Lee J, Sano T, Janjigian YY, Fan D, Song S (2017) Gastric adenocarcinoma. Nat Rev
3:17036
Allen E, Jabouille A (2017) Combined antiangiogenic and anti-PD-L1 therapy stimulates tumor
immunity through HEV formation. Sci Transl Med 9:385
Arab S, Hadjati J (2019) Adenosine blockage in tumor microenvironment and improvement of
cancer immunotherapy. Immune Netw 19(4):e23
Argilés G, Saro J, Segal NH, Melero I, Ros W, Marabelle A, Rodriguez M, Albanell J, Calvo E,
Moreno V, Cleary J, Eder P, Paz-Ares L, Hurwitz H, Bacac M, Perro M, Bouseida S,
Sandoval F, Bove DS, Sreckovic S, Jamois C, Silva A, Klein C, Umana P, Karanikas V,
Tabernero J (2017) LBA-004Novel carcinoembryonic antigen T-cell bispecific (CEA-TCB)
antibody: preliminary clinical data as a single agent and in combination with atezolizumab in
patients with metastatic colorectal cancer (mCRC). Ann Oncol 28(suppl_3):302
Azad A, Yin Lim S, D'Costa Z, Jones K, Diana A, Sansom OJ (2017) PD-L1 blockade enhances
response of pancreatic ductal adenocarcinoma to radiotherapy. EMBO Mol Med 9(2):167–180
Bauer C, Kuhnemuth B, Duewell P, Ormanns S, Gress T, Schnurr M (2016) Prevailing over T cell
exhaustion: new developments in the immunotherapy of pancreatic cancer. Cancer Lett 381
(1):259–268
Berraondo P, Ochoa MC (2019) Immune desertic landscapes in hepatocellular carcinoma shaped by
beta-catenin activation. Cancer Discov 9(8):1003–1005
Blair AB, Kleponis J, Thomas DL, Muth ST, Murphy AG, Kim V, Zheng L (2019) IDO1 inhibition
potentiates vaccine-induced immunity against pancreatic adenocarcinoma. J Clin Invest 129
(4):1742–1755
Cancer Genome Atlas Research Network (2014) Comprehensive molecular characterization of

gastric adenocarcinoma. Nature 513(7517):202–209
Cecchini MJ, Yu E, Potvin K, D'Souza D, Lock M (2015) Concurrent or sequential hormonal and
radiation therapy in breast cancer: a literature review. Cureus 7(10):e364
Chen Y, Ramjiawan RR, Reiberger T, Ng MR, Hato T, Huang Y, Ochiai H, Kitahara S, Unan EC,
Reddy TP, Fan C, Huang P, Bardeesy N, Zhu AX, Jain RK, Duda DG (2015) CXCR4 inhibition
in tumor microenvironment facilitates anti-programmed death receptor-1 immunotherapy in
sorafenib-treated hepatocellular carcinoma in mice. Hepatology 61(5):1591–1602
Chen L, Xiong Y, Li J, Zheng X, Zhou Q, Turner A, Wu C, Lu B, Jiang J (2017a) PD-L1 expression
promotes epithelial to mesenchymal transition in human esophageal cancer. Cell Physiol
Biochem 42(6):2267–2280
Chen YP, Zhang Y, Lv JW, Li YQ, Wang YQ, He QM, Yang XJ, Sun Y, Mao YP, Yun JP, Liu N,
Ma J (2017b) Genomic analysis of tumor microenvironment immune types across 14 solid
cancer types: immunotherapeutic implications. Theranostics 7(14):3585–3594
Chiu DK, Tse AP, Xu IM, Di Cui J, Lai RK, Li LL, Koh HY, Tsang FH, Wei LL, Wong CM (2017)
Hypoxia inducible factor HIF-1 promotes myeloid-derived suppressor cells accumulation
through ENTPD2/CD39L1 in hepatocellular carcinoma. Nat Commun 8(1):517
Davidson M, Okines AF, Starling N (2015) Current and future therapies for advanced gastric
cancer. Clin Colorectal Cancer 14(4):239–250
Fan P, Zhao J, Meng Z, Wu H, Wang B, Wu H, Jin X (2019) Overexpressed histone
acetyltransferase 1 regulates cancer immunity by increasing programmed death-ligand 1 expres-
sion in pancreatic cancer. J Exp Clin Cancer Res 38(1):47
Ghiringhelli F, Fumet J-D (2019) Is there a place for immunotherapy for metastatic microsatellite
stable colorectal cancer? Front Immunol 10:1816
Guo W, Wang P, Li N, Shao F, Zhang H, Yang Z, Li R, Gao Y, He J (2018) Prognostic value of
PD-L1 in esophageal squamous cell carcinoma: a meta-analysis. Oncotarget 9
(17):13920–13933
Haag GM, Czink E, Ahadova A (2019) Prognostic significance of microsatellite-instability in
gastric and gastroesophageal junction cancer patients undergoing neoadjuvant chemotherapy.
Int J Cancer 144(7):1697–1703
Harsch IA, Konturek PC (2018) Acute-onset diabetes mellitus with ketoacidosis in a nivolumab-
treated patient with hepatocellular carcinoma. Wiad Lek 71(5):945–948
Hewitt LC, Inam IZ, Saito Y, Yoshikawa T, Quaas A, Hoelscher A, Bollschweiler E, Fazzi GE,
Melotte V, Langley RE, Nankivell M, Cunningham D, Allum W, Hutchins GG, Grabsch HI
(2018) Epstein-Barr virus and mismatch repair deficiency status differ between oesophageal and
gastric cancer: a large multi-centre study. Eur J Cancer 94:104–114
Imamura Y, Watanabe M, Toihata T, Takamatsu M, Kawachi H, Haraguchi I, Ogata Y, Yoshida N,
Saeki H, Oki E, Taguchi K, Yamamoto M, Morita M, Mine S, Hiki N, Baba H, Sano T (2019)
Recent incidence trend of surgically resected esophagogastric junction adenocarcinoma and
microsatellite instability status in Japanese patients. Digestion 99(1):6–13
Jang HJ, Lee HS (2017) Integrated genomic analysis of recurrence-associated small non-coding
RNAs in oesophageal cancer. Gut 66(2):215–225
Jiang H, Hegde S (2016) Targeting focal adhesion kinase renders pancreatic cancers responsive to
checkpoint immunotherapy. Nat Med 22(8):851–860
Jin S, Xu B, Yu L, Fu Y, Wu H, Fan X, Wei J, Liu B (2017) The PD-1, PD-L1 expression and CD3+
T cell infiltration in relation to outcome in advanced gastric signet-ring cell carcinoma,
representing a potential biomarker for immunotherapy. Oncotarget 8(24):38850–38862
Jonker DJ, Tang PA, Kennecke H, Welch SA, Cripps MC, Asmis T, Chalchal H, Tomiak A, Lim H,
Ko YJ, Chen EX, Alcindor T, Goffin JR, Korpanty GJ, Feilotter H, Tsao MS, Theis A, Tu D,
Seymour L (2018) A randomized phase II study of FOLFOX6/bevacizumab with or without
pelareorep in patients with metastatic colorectal cancer: IND.210, a Canadian Cancer Trials
Group Trial. Clin Colorectal Cancer 17(3):231–239
Joshi SS, Maron SB, Catenacci DV (2018) Pembrolizumab for treatment of advanced gastric and
gastroesophageal junction adenocarcinoma. Future Oncol 14(5):417–430
Jou E, Rajdev L (2016) Current and emerging therapies in unresectable and recurrent gastric cancer.
World J Gastroenterol 22(20):4812–4823
Kamatham S, Shahjehan F, Kasi PM (2019) Immune checkpoint inhibitors in metastatic colorectal
cancer: current status, recent advances, and future directions. Curr Colorectal Cancer Rep 15
(4):112–121
Kato R, Yamasaki M, Urakawa S, Nishida K, Makino T, Morimoto-Okazawa A, Kawashima A,
Iwahori K, Suzuki S, Ueda R, Mori M, Satoh T, Doki Y, Wada H (2018) Increased Tim-3(+) T
cells in PBMCs during nivolumab therapy correlate with responses and prognosis of advanced
esophageal squamous cell carcinoma patients. Cancer Immunol Immunother 67(11):1673–1683
Kim KJ, Kim JH, Lee SJ, Lee EJ, Shin EC, Seong J (2017) Radiation improves antitumor effect of
immune checkpoint inhibitor in murine hepatocellular carcinoma model. Oncotarget 8
(25):41242–41255
Kim HJ, Park S, Kim KJ, Seong J (2018) Clinical significance of soluble programmed cell death
ligand-1 (sPD-L1) in hepatocellular carcinoma patients treated with radiotherapy. Radiother
Oncol 129(1):130–135
Kojima T, Doi T (2017) Immunotherapy for esophageal squamous cell carcinoma. Curr Oncol Rep
19(5):33
Kottschade L, Brys A, Peikert T, Ryder M, Raffals L, Brewer J, Mosca P, Markovic S (2016) A
multidisciplinary approach to toxicity management of modern immune checkpoint inhibitors in
cancer therapy. Melanoma Res 26(5):469–480
Lazar DC, Avram MF, Romosan I, Cornianu M, Taban S, Goldis A (2018) Prognostic significance
of tumor immune microenvironment and immunotherapy: novel insights and future perspectives
in gastric cancer. World J Gastroenterol 24(32):3583–3616
Le DT, Uram JN, Wang H, Bartlett BR, Kemberling H, Eyring AD, Skora AD, Luber BS, Azad NS,
Laheru D, Biedrzycki B, Donehower RC, Zaheer A, Fisher GA, Crocenzi TS, Lee JJ, Duffy SM,
Goldberg RM, de la Chapelle A, Koshiji M, Bhaijee F, Huebner T, Hruban RH, Wood LD,
Cuka N, Pardoll DM, Papadopoulos N, Kinzler KW, Zhou S, Cornish TC, Taube JM, Anders
RA, Eshleman JR, Vogelstein B, Diaz LA Jr (2015) PD-1 blockade in tumors with mismatch-
repair deficiency. N Engl J Med 372(26):2509–2520
Lin EM, Gong J, Klempner SJ, Chao J (2018) Advances in immuno-oncology biomarkers for
gastroesophageal cancer: programmed death ligand 1, microsatellite instability, and beyond.
World J Gastroenterol 24(25):2686–2697
Liu Y, Cheng Y, Xu Y, Wang Z, Du X, Li C, Peng J, Gao L, Liang X, Ma C (2017a) Increased
expression of programmed cell death protein 1 on NK cells inhibits NK-cell-mediated anti-
tumor function and indicates poor prognosis in digestive cancers. Oncogene 36(44):6143–6153
Liu H, Shen J, Lu K (2017b) IL-6 and PD-L1 blockade combination inhibits hepatocellular
carcinoma cancer development in mouse model. Biochem Biophys Res Commun 486
(2):239–244
Llovet JM, Montal R, Sia D, Finn RS (2018) Molecular therapies and precision medicine for
hepatocellular carcinoma. Nat Rev 15(10):599–616
Lordick F, Shitara K, Janjigian YY (2017) New agents on the horizon in gastric cancer. Ann Oncol
28(8):1767–1775
Lote H, Cafferkey C, Chau I (2015) PD-1 and PD-L1 blockade in gastrointestinal malignancies.
Cancer Treat Rev 41(10):893–903
Mace TA, Shakya R, Pitarresi JR, Swanson B, McQuinn CW, Loftus S, Nordquist E, Cruz-
Monserrate Z, Yu L, Young G, Zhong X, Zimmers TA, Ostrowski MC, Ludwig T,
Bloomston M, Bekaii-Saab T, Lesinski GB (2018) IL-6 and PD-L1 antibody blockade combi-
nation therapy reduces tumour progression in murine models of pancreatic cancer. Gut 67
(2):320–332
Morse MA, Hochster H, Benson A (2020) Perspectives on Treatment of Metastatic Colorectal
Cancer with Immune Checkpoint Inhibitor Therapy. Oncologist 25(1):33–45
Murphy A, Kelly RJ (2015) Immunotherapy in upper GI malignancies. Curr Treat Options in Oncol
16(5):20
Panda A, Mehnert JM, Hirshfield KM, Riedlinger G, Damare S, Saunders T, Kane M, Sokol L,
Stein MN, Poplin E, Rodriguez-Rodriguez L, Silk AW, Aisner J, Chan N, Malhotra J,
Frankel M, Kaufman HL, Ali S, Ross JS, White EP, Bhanot G, Ganesan S (2018) Immune
activation and benefit from avelumab in EBV-positive gastric cancer. J Natl Cancer Inst 110
(3):316–320
Perrot I, Michaud HA, Giraudon-Paoli M, Augier S, Docquier A, Gros L, Courtois R, Dejou C,
Jecko D, Becquart O, Rispaud-Blanc H, Gauthier L, Rossi B, Chanteux S, Gourdin N,
Amigues B, Roussel A, Bensussan A, Eliaou JF, Bastid J, Romagne F, Morel Y, Narni-
Mancinelli E, Vivier E, Paturel C, Bonnefoy N (2019) Blocking antibodies targeting the
cd39/cd73 immunosuppressive pathway unleash immune responses in combination cancer
therapies. Cell Rep 27(8):2411–2425
Pinto MP, Owen GI, Retamal I, Garrido M (2017) Angiogenesis inhibitors in early development for
gastric cancer. Expert Opin Investig Drugs 26(9):1007–1017
Pitt JM, Vetizou M, Daillere R, Roberti MP, Yamazaki T, Routy B, Lepage P, Boneca IG,
Chamaillard M, Kroemer G, Zitvogel L (2016) Resistance mechanisms to immune-checkpoint
blockade in cancer: tumor-intrinsic and -extrinsic factors. Immunity 44(6):1255–1269
Posner MR, Mayer RJ (1994) The use of serologic tumor markers in gastrointestinal malignancies.
Hematol Clin N Am 8(3):533–553
Quaranta V, Rainer C, Nielsen SR (2018) Macrophage-derived granulin drives resistance to
immune checkpoint inhibition in metastatic pancreatic cancer. Cancer Res 78(15):4253–4269
Rao D, Parakrama R, Augustine T, Liu Q, Goel S, Maitra R (2019) Immunotherapeutic advances in
gastrointestinal malignancies. NPJ Precision Oncol 3:4
Ratti M, Lampis A, Hahne JC, Passalacqua R, Valeri N (2018) Microsatellite instability in gastric
cancer: molecular bases, clinical perspectives, and new treatment approaches. Cell Mol Life Sci
75(22):4151–4162
Roberts JA, Gonzalez RS, Das S, Berlin J, Shi C (2017) Expression of PD-1 and PD-L1 in poorly
differentiated neuroendocrine carcinomas of the digestive system: a potential target for anti-PD-
1/PD-L1 therapy. Hum Pathol 70:49–54
Ruiz de Galarreta M, Bresnahan E, Molina-Sanchez P, Lindblad KE, Maier B, Sia D, Puigvehi M
(2019) Beta-Catenin activation promotes immune escape and resistance to anti-PD-1 therapy in
hepatocellular carcinoma. Cancer Discov 9(8):1124–1141
Semaan A, Dietrich D, Bergheim D, Dietrich J, Kalff JC, Branchi V, Matthaei H, Kristiansen G,
Fischer HP, Goltz D (2017) CXCL12 expression and PD-L1 expression serve as prognostic
biomarkers in HCC and are induced by hypoxia. Virchows Arch 470(2):185–196
Smyth E, Thuss-patience PC (2018) Immune checkpoint inhibition in gastro-oesophageal cancer.
Oncol Res Treatment 41(5):272–280
Soares KC, Rucki AA, Wu AA, Olino K, Xiao Q, Chai Y, Wamwea A, Bigelow E, Lutz E, Liu L,
Yao S, Anders RA, Laheru D, Wolfgang CL, Edil BH, Schulick RD, Jaffee EM, Zheng L (2015)
PD-1/PD-L1 blockade together with vaccine therapy facilitates effector T-cell infiltration into
pancreatic tumors. J Immunother 38(1):1–11
Sonnenberg WR (2017) Gastrointestinal malignancies. Prim Care 44(4):721–732
Sudo T, Nishida R, Kawahara A, Saisho K, Mimori K, Yamada A, Mizoguchi A, Kadoya K,
Matono S, Mori N, Tanaka T, Akagi Y (2017) Clinical impact of tumor-infiltrating lymphocytes
in esophageal squamous cell carcinoma. Ann Surg Oncol 24(12):3763–3770
Sun W, Yan L (2016) Gastric cancer: current and evolving treatment landscape. Chin J Cancer 35
(1):83
Tanaka T, Nakamura J, Noshiro H (2017) Promising immunotherapies for esophageal cancer.
Expert Opin Biol Ther 17(6):723–733
Thompson ED, Zahurak M, Murphy A, Cornish T, Cuka N, Abdelfatah E, Yang S, Duncan M,
Ahuja N, Taube JM, Anders RA, Kelly RJ (2017) Patterns of PD-L1 expression and CD8 T cell
infiltration in gastric adenocarcinomas and associated immune stroma. Gut 66(5):794–801
Tran PN, Sarkissian S, Chao J, Klempner SJ (2017) PD-1 and PD-L1 as emerging therapeutic
targets in gastric cancer: current evidence. Gastrointest Cancer Targets Ther 7:1–11
Truong P, Rahal A, Kallail KJ (2016) Metastatic hepatocellular carcinoma responsive to
pembrolizumab. Cureus 8(6):e631
Wang M, Zhao J, Zhang L, Wei F, Lian Y, Wu Y, Gong Z, Zhang S, Zhou J, Cao K, Li X, Xiong W,
Li G, Zeng Z, Guo C (2017) Role of tumor microenvironment in tumorigenesis. J Cancer 8
(5):761–773
Wang Y, Zhu C, Song W, Li J (2018a) PD-L1 expression and CD8(+) T cell infiltration predict a
favorable prognosis in advanced gastric cancer. J Immunol Res 2018:4180517
Wang W, Marinis JM, Beal AM, Savadkar S, Wu Y, Khan M, Taunk PS, Wu N, Su W, Wu J,
Ahsan A, Kurz E, Chen T, Yaboh I, Li F, Gutierrez J, Diskin B, Hundeyin M, Reilly M, Lich JD,
Harris PA, Mahajan MK, Thorpe JH, Nassau P, Mosley JE, Leinwand J, Rossi JAK, Mishra A,
Aykut B, Glacken M, Ochi A, Verma N, Kim JI, Vasudevaraja V, Adeegbe D, Almonte C,
Bagdatlioglu E, Cohen DJ, Wong KK, Bertin J, Miller G (2018b) RIP1 kinase drives
macrophage-mediated adaptive immune tolerance in pancreatic cancer. Cancer Cell 34
(5):757–774
Wang X, Wu WKK, Gao J, Li Z, Dong B, Lin X, Li Y, Li Y, Gong J, Qi C, Peng Z, Yu J, Shen L
(2019) Autophagy inhibition enhances PD-L1 expression in gastric cancer. J Exp Clin Cancer
Res 38(1):140
Wen X, He X, Jiao F, Wang C, Sun Y, Ren X, Li Q (2017) Fibroblast activation protein-alpha-
positive fibroblasts promote gastric cancer progression and resistance to immune checkpoint
blockade. Oncol Res 25(4):629–640
Yaghoubi N, Soltani A, Ghazvini K, Hassanian SM, Hashemy SI (2019) PD-1/ PD-L1 blockade as
a novel treatment for colorectal cancer. Biomed Pharmacother 110:312–318
Yoo B, Jordan VC, Sheedy P (2019) RNAi-mediated PD-L1 inhibition for pancreatic cancer
immunotherapy. Sci Rep 9(1):4712
Zhao J, Wen X, Tian L, Li T, Xu C, Wen X, Melancon MP, Gupta S, Shen B, Peng W (2019)
Irreversible electroporation reverses resistance to immune checkpoint blockade in pancreatic
cancer. Nat Commun 10(1):899
Zhen DB, Coveler A, Zanon S, Reni M, Chiorean EG (2018) Biomarker-driven and molecularly
targeted therapies for pancreatic adenocarcinoma. Semin Oncol 45(3):107–115
Zheng X, Song X, Shao Y, Xu B, Hu W, Zhou Q, Chen L, Zhang D, Wu C, Jiang J (2018)
Prognostic role of tumor-infiltrating lymphocytes in esophagus cancer: a meta-analysis. Cell
Physiol Biochem 45(2):720–732
Zhou G, Sprengers D, Boor PPC, Doukas M, Schutz H, Mancham S, Pedroza-Gonzalez A, Polak
WG, de Jonge J, Gaspersz M, Dong H, Thielemans K, Pan Q, JNM IJ, Bruno MJ, Kwekkeboom
J (2017) Antibodies against immune checkpoint molecules restore functions of tumor-
infiltrating T cells in hepatocellular carcinomas. Gastroenterology 153(4):1107–1119
Zhu Y, Knolhoff BL, Meyer MA, Nywening TM, West BL, Luo J, Wang-Gillam A, Goedegebuure
SP, Linehan DC, DeNardo DG (2014) CSF1/CSF1R blockade reprograms tumor-infiltrating
macrophages and improves response to T-cell checkpoint immunotherapy in pancreatic cancer
models. Cancer Res 74(18):5057–5069
Zhu Y, Yang J, Xu D, Gao XM, Zhang Z, Hsu JL, Li CW, Lim SO, Sheng YY, Zhang Y, Li JH,
Luo Q, Zheng Y, Zhao Y, Lu L, Jia HL, Hung MC, Dong QZ, Qin LX (2019) Disruption of
tumour-associated macrophage trafficking by the osteopontin-induced colony-stimulating
factor-1 signalling sensitises hepatocellular carcinoma to anti-PD-L1 blockade. Gut 68
(9):1653–1666
Zou J, Zhuang M, Yu X, Li N, Mao R, Wang Z, Wang J, Wang X, Zhou H, Zhang L, Shi Y (2018)
MYC inhibition increases PD-L1 expression induced by IFN-gamma in hepatocellular carci-
noma cells. Mol Immunol 101:203–209
Chapter 7
Monoclonal Antibody Therapy Against
Gastrointestinal Tract Cancers
Gayatri Gouda, Manoj Kumar Gupta, Ravindra Donde, Lambodar Behera,

Abstract Gastrointestinal (GI) cancer is one of the leading causes of cancer death
across the globe. To date, numerous techniques have been developed for the removal
or destruction of cancer cells via surgery, radiation, or chemotherapy. However,
these techniques have various side effects on the human body. In comparison to
other techniques, recently developed monoclonal antibodies have fewer side effects.
Thus their usage in cancer treatment has increased recently. Considering above, in
this chapter, the authors attempted to understand the molecular feature associated
with monoclonal antibodies and how they can be employed for the treatment of GI
cancer. Information obtained revealed that the two most widespread techniques used
for producing monoclonal antibodies are hybridoma and phage display. Since 1986,
various monoclonal antibodies have been developed against numerous receptors/
genes, namely epidermal growth factor receptor (EGFR), human epidermal growth
factor 2 (HER2), HER4, VEGF, CD20, CD30, tumor necrosis factor member11,
PD1 and IL4, that play a key role in causing GI cancer at different stages. For
instance, panitumumab in combination with epirubicin, oxaliplatin, and capecitabine
can be used for treating advanced esophageal gastro adenocarcinoma.
Tremelimumab, a monoclonal antibody, works against anti-CTL4 and can be used
for the treatment of gastro cancer, colon cancer, and melanoma. However, few
studies have reported that these monoclonal antibodies have side effects. For
instance, mucositis was observed for the cetuximab antibody. Thus, the monoclonal
antibody should be used carefully under the provision of the medical practitioner. In
the near future, the information present in this chapter will be highly useful for
treatment in GI cancer.
G. Gouda · R. Donde · L. Behera

Pradesh, India
https://doi.org/10.1007/978-981-15-6487-1_7
98 G. Gouda et al.
Keywords Gastrointestinal cancer · Monoclonal antibody · Hybridoma · Phage

display
Abbreviations
CTL4 Cytotoxic T lymphocyte-associated antigen 4

EBV Epstein–Barr virus
EGFR Epidermal growth factor receptor
FDA Food and Drug Administration
GI Gastrointestinal
HER2 Human epidermal growth factor 2
IDO1 Indolemine-2,3-dioxygenase
mAbs Monoclonal antibodies
PD1 Programmed cell death protein 1
PI3K Phosphatidylinositol 3-kinase
TKI Tyrosine kinase inhibitor
VH Variable heavy chain
VL Variable light chain
7.1 Introduction
Gastrointestinal (GI) cancer is a deadly disease that occurs in the gastrointestinal

tract (Bijlsma et al. 2017; Gupta et al. 2019). The GI tract begins at the mouth and
terminates at the anus. The main function of the GI tract is to digest food, absorb
nutrients from the food, protect the body against pathogens, and excrete feces
(Bruneau 2017). GI cancers denote the primary cause of cancer death globally
(Somi et al. 2019). As GI cancer is detected at the malignant state, the death rate
associated with gastric cancer is higher in comparison to other cancer types (Bijlsma
et al. 2017). Recently, the incidence of GI cancer is reported to increase globally,
which is mainly due to adaptation to the western lifestyle, including food habits
(www.cancer.org). Other well-known risk factors associated with GI cancer forma-
tion are smoking, exposure to polycyclic aromatic hydrocarbons (PAH), H. pylori
infection, higher usage of biomass, and opium (Roshandel et al. 2019). In various
studies, it was found that Helicobacter pylori causes gastric ulcers. Additionally,
Epstein–Barr virus (EBV) was also found to be associated with gastric cancer (Derks
et al. 2016). EBV was found within the epithelial cell in the malignant state of the
gastro cancer (Singh and Jha 2017). CDK2NA hyper-methylation and CIMP meth-
ylation occur in EBV infected cells to develop a tumor in the GI tract of the human
body (Birdwell et al. 2014). In addition, EBV-infected tumors are associated with
high PD-L1 expression (Derks et al. 2016). Various mutations in TP53, PIK3CA,
and ARID1A genes are also reported to be associated with the gastric cancer
7 Monoclonal Antibody Therapy Against Gastrointestinal Tract Cancers 99
development. Three nonsense mutations that occur at the genomic level of ARID1A
gene are also reported to initiate tumors formation (Zang et al. 2012). The ARID1A
gene could also help to maintain pluripotency in the stem cell. Zhang et al. reported
that ARID1A and PIK3CA together involved in gastric cancer formation (Zang et al.
2012).
To date, numerous techniques have been developed for the removal or destruction
of cancer cells via surgery, radiation, or chemotherapy. Though radiation and
surgery are highly useful for a benign tumor, chemotherapy works effectively in
the case of metastatic cancer. Nevertheless, chemotherapy may also cause various
side effects, for instance, removal of rapidly dividing healthy tissues, e.g., cells
lining the GI tract and blood cell (Pento 2017). Development of hybridoma tech-
nology along with serological techniques and various tools like monoclonal anti-
bodies (mAbs) provided a unique way for recognizing cancer cell-associated cell
surface receptors, which in turn revolutionized the field of cancer research (Pento
2017). Monoclonal antibodies affect cancer cells either by neutralizing the expres-
sion of proteins or by modifying the ligand binding to block or modify the expres-
sion of cancer causing genes (Redman et al. 2015). Additionally, due to high
specificity, monoclonal antibodies have fewer side effects, and thus their usage in
cancer treatment has increased recently (Lu et al. 2020). Considering this, in the
present chapter, the authors attempted to understand the molecular feature associated
with monoclonal antibodies and how they can be employed for the treatment of GI
cancer.
7.2 Monoclonal Antibody
Antibodies are proteins of the immune system that identify and bind tightly with
foreign particles. Antibodies may be either monoclonal (a single antibody clone is
produced) or polyclonal (various antibodies with distinct features are produced).
Because of the high specificity towards target molecules, recently monoclonal
antibodies have demonstrated as promising candidates for the treatment of various
diseases, including cancer (Shimasaki 2014). Monoclonal antibodies are single
antibodies that are produced by fusing an immortalized cell line with antibody-
producing cells, which in turn produce a new form of the cell line, namely,
hybridoma. As hybridoma is “immortal,” we can generate the exact antibody from
them for several years. Nevertheless, few studies have also reported that we must
re-test these antibodies after a few years to ensure that no new mutation has been
introduced in these cell lines. Initially, monoclonal antibodies were produced from
mice (Corthell 2014). The first licensed monoclonal antibody, namely, Orthoclone
OKT3 (muromonab-CD3), was obtained from mouse (Emmons and Hunsicker
1987). In 1988, Huang et al. reported the first monoclonal antibody, namely pepsin-
ogen, for treating intestinal gastric cancer (Huang et al. 1988). However, as rabbits
have better immune responses than mice, recently, novel approaches have been
attempted to produce monoclonal antibodies from rabbits (Corthell 2014). Since
100 G. Gouda et al.
1986, ~100 monoclonal antibodies have been designated as a drug, and the approval
rate is continuously increasing (Manis and Feldweg 2019). The global value asso-
ciated with the antibody market is ~$20 billion/year. The global value of the
antibody market is approximately $20 billion/year (Maggon 2007).
7.3 Techniques for Monoclonal Antibodies Production
Two most widely methods employed for producing monoclonal antibodies are
hybridoma and phage display. In 1975, for the first time, Milstein and Köhler
described generating hybridoma as a stable monoclonal antibody production tech-
nique (Köhler and Milstein 1975). Hybridoma production involves the removal of
activated B lymphocytes from an immunized animal spleen and mingling them
along with immortalized myeloma cells that are incapable of producing hypoxan-
thine-guanine-phosphoribosyltransferase, the key enzyme involved in salvage path-
way and is associated with nucleotide production (Chartrain and Chu 2008). For
selecting hybridomas, cells pools produced after the fusion (a mixture of non-fused
myeloma cells & B lymphocytes and hybridoma cells) are nurtured within a specific
medium comprised of aminopterin, which restricts de novo synthesis of nucleotide
(Carvalho et al. 2017). Myeloma cells are deprived of the salvage pathway that is
highly required for nucleotide production. Nevertheless, when these cells are
exposed to selective medium comprised of aminopterin, de novo synthesis of
nucleotide is also halted, which in turn cause myeloma cells inviable. On the
contrary, salvage pathway activated within non-fused B-lymphocytes works per-
fectly. Thus, in spite of de novo pathway blockage via aminopterin, non-fused
B-lymphocytes produce nucleotide continuously. But these cells are not mortal
and replicate for limited times and eventually die. Considering this, hybridomas
cells were produced that have capability to replicate indefinitely as well as synthesize
nucleotides via the salvage pathway through selection conditions (Carvalho et al.
2017).
However, the main problem associated with early monoclonal antibodies was to
detect availability of suitable myeloma cell line. Hybridomas may also be genetically
unstable, and yield is less. Recently several studies have also reported that different
expression system for monoclonal antibodies behaves differently. For instance,
E. coli may be employed for antibody fragments expressions like antigen-binding
fragments and single-chain variable fragments. But they are not suitable for the
production of full-sized antibodies (Carvalho et al. 2017; Liu 2014). To overcome
this problem, another technique, namely, phage display, was developed (Liu 2014).
During phage display, at first, B-lymphocytes are isolated from the human blood.
Later mRNA is isolated and converted into cDNA employing polymerase chain
reaction for amplifying a complete set of the “variable light chain” (VL) as well as
“variable heavy chains” (VH) segments. These segments are then cloned with the
vector, generally scFv, nearby bacteriophage’s PIII protein, and subsequently,
E. coli is infected for generating a library comprised of 1010 cells via inoculating
the library with an extra helper phage. Bacteriophage comprised of VL and VH
segments in bacteriophage coat is later secreted via E. coli. Distinct VL and VH

segments against the antigen are selected and then employed to re-inoculate E. coli
by bacteriophage. Cells comprising the plasmid can subsequently be isolated and
sequenced. The main advantage associated with phage display is that after the
generation of a single library, it can be utilized for producing novel antibodies for
infinite time. As the complete process is performed under in vitro condition, no
immunization is required at any step of processing, and antibodies are produced
more in less time in comparison to hybridomas technique. Additionally, the library
generated via phage display may also be employed for producing antibodies against
toxic antigens (Liu 2014).
7.4 Monoclonal Antibody Therapy in GI Cancer
To date, various monoclonal antibodies have been identified against numerous

receptors/genes, namely epidermal growth factor receptor (EGFR), human epider-
mal growth factor 2 (HER2), HER4, VEGF, CD20, CD30, tumor necrosis factor
member11, PD1 and IL4, that play a key role in causing GI cancer at different stages
(Table 7.1).
Table 7.1 Monoclonal antibody and its target site

Monoclonal Target
antibody Mechanism site Type of cancer References
Cetuximab EFGR EFGR Colorectal cancer, gastro- Pinto et al. (2009),
inhibition esophageal Cancer Moehler et al. (2011)
Trastuzumab HER2 HER2 Gastroesophageal cancer Moehler et al. (2011)
inhibition
Panitumumab EFGR EFGR Colorectal cancer
inhibition
Bevacizumab VEGFR VEGFR Colorectal cancer Norguet et al. (2012)
inhibition
Ramucirumab VEGFR VEGFR Gastric cancer Jung et al. (2002)
inhibition
Afatinib EFGR EFGR Esophagogastric cancer Dungo and Keating
inhibition (2013)
Lapatinib EFGR and EFGR Gastric cancer Shimoyama (2014)
HER2
Docetaxel+ EFGR EFGR Esophageal carcinoma Ruhstaller et al. (2011)
Cetuximab inhibition
Docetaxel+ VEGFR VEGFR Gastroesophageal junc- El-Rayes et al. (2010)
Oxaliplatin inhibition tion cancer
Avelumab HER2 HER2 Gastric cancer Bang et al. (2010)
inhibition
Pembrolizumab Block PD1 PDL1 Gastroesophageal junc- Shitara et al. (2018)
tion cancer
102 G. Gouda et al.
7.4.1 Epidermal Growth Factor Receptor (EGFR)
EGFR is a transmembrane glycoprotein involved in cell proliferation, angiogenesis,

and cell transduction pathways (Martinelli et al. 2009; Norguet et al. 2012). When
EGFR binds with the ligand, it prevents EGFR dimerization at the extracellular
region and enhances the apoptosis of cancerous cells. EGFR on binding with the
ligand enhances the changing of ligand confirmation, which in turn activates the
tyrosine kinase and phosphorylate tyrosine residue at the intracellular carboxy
domain of EGFR (Martinelli et al. 2009). Another EGFR inhibitor, namely
cetuximab, is an immunoglobulin G1 antibody that inhibits cell proliferation by
interacting with the MAP kinase pathway as well as the PIK3 pathway (Edris et al.
2013). It induces cell cycle arrest at the G1 phase and inhibits cancer cell prolifer-
ation. Another phase II trial study reported that 5-fluorouracil in combination with
cetuximab can effectively reduce gastric cancer (Norguet et al. 2012; Gold et al.
2010). Cetuximab, along with platinum fluoropyrimidine, has also shown a better
effect in metastatic gastric cancer during the phase III trial (Wagner et al. 2006;
Lordick et al. 2010). Lorenzen et al. observed that docetaxel, cisplatin, and
leucovorin individually provide hematologic based toxicity for gastric cancer
(Lorenzen et al. 2007). Afatinib is an irreversible, 4-anilinoquinazoline second-
generation tyrosine kinase inhibitor of EGFR. It is widely used for the treatment of
various cancers (Tridente 2017; Brody 2018). Panitumumab is another EGFR
inhibitor used for the treatment of metastatic colorectal cancer. It is injected along
with chemotherapy. In 2013, Waddel et al. reported that panitumumab in combina-
tion with epirubicin, oxaliplatin, and capecitabine could be used for treating
advanced esophageal gastro adenocarcinoma in phase III trial. For esophago-gastro
cancer, panitumumab in combination with epirubicin, oxaliplatin, and capecitabine
can be used for treating gastro cancer after the second stage of chemotherapy
(Waddell et al. 2013). Nimotuzumab blocks the binding of EGF and transforming
growth factor TGFα to EGFR that could inhibit cancer cell inhibition, proliferation,
and induce apoptosis (Talavera et al. 2009). Nimotuzumab in combination with
irinotecan shows better survival rate in gastric cancer patients. Strumberg et al.
reported that nimotuzumab could also be used for treating pancreatic cancer
(Strumberg et al. 2012).
7.4.2 Human Epidermal Growth Factor 2 (HER2)
HER2 is a protooncogene and encodes ErbB2, which plays a key role in tumori-
genesis. Initially, its overexpression was observed at the primary and secondary
stages of stomach cancer. Higher expression of HER2 was reported in ~36% of
gastroesophageal junction tumors, whereas 21% was found in gastric tumors (León-
Chong et al. 2007). For the first time, the association between gastric cancer and
HER2 was reported in 1986 (Sakai et al. 1986). To date, several inhibitors were used
to inhibit or block the expression of receptors and change the conformation of ligand
binding to stop cell signaling pathways of cancer cells. The activation of HER2 can
be inhibited by trastuzumab that could block the signaling pathway and induce
apoptosis by interfering phosphatidyl inositol-3 kinase pathway and mTOR pathway
(Bang 2012). RAS protein-mediated signaling pathway can be inhibited by
trastuzumab. On binding with HER2 domain, trastuzumab induces antibody-
dependent cytotoxicity (Collins et al. 2012). Earlier the trastuzumab antibody,
along with cisplatin, is used at phase II and III trials of gastric cancer patients
(Cortés-Funes et al. 2007). Barok et al. found that “trastuzumab emtansine,” a
conjugate for the trastuzumab antibody for HER2 positive cells, may also be used
for treating gastric cancer (Barok et al. 2011).
Lapatinib, an inhibitor of tyrosine kinase, inhibits the PI3K and RAS pathway by
interfering with the activation of EGFR and HER2 (Chen et al. 2012). In most cases,
lapatinib was used to treat the patient from having trastuzumab-resistant cells.
Lapatinib interferes with the signaling pathways of HER1 and HER2 by interrupting
ATP binding to the ATP binding domain of tyrosine kinase. Previously it was
reported that lapatinib could give positive results against gastric cancer. However,
the resistance was developed against lapatinib in the patient who has taken it before
(Chen et al. 2012). Pertuzumab, another monoclonal antibody, is distinct and
complementary to trastuzumab. Pertuzumab binds with the extracellular domain II
and dimerization arm of the HER2 receptor, which in turn disrupts HER2-HER3 and
HER2-EGFR dimerization (Nahta et al. 2004). Trastuzumab and pertuzumab in
combination cause the cell death of cancer cells at the phase II stage. Pertuzumab
in combination with trastuzumab, capecitabine, and cisplatin has also used for
treating advanced gastric cancer (Matsuoka and Yashiro 2015). Bao et al. reported
that the interaction of HER2 with CD44 upregulates the expression of the CXCR4
promoter. The CD44 acts as a mediator to form dimerization between HER2 and
HER3 when interacting with nueregulin. The team also reported that on treatment
with trastuzumab, the interaction of CD44 with HER2 was inhibited by the disulfide
bond present at the 295 position of a cysteine residue in the HER2 positive cancer
cells (Bao et al. 2011).
7.4.3 Vascular Endothelial Growth Factor (VEGF) Targeted

Pathway
Vascular endothelial growth factor is the tyrosine kinases having five ligands
(VEGF-A, B, C, D, H) that directly or indirectly associated with inhibition of
tumor cells (Rapisarda and Melillo 2012). The receptor of VEGF is expressed at
104 G. Gouda et al.
the endothelial cells containing the immunoglobulin-like domain and is associated

with the regulation of tumor lymphangiogenesis and angiogenesis (Shibuya and
Claesson-Welsh 2006). The patients of Western and Asian regions were highly
benefited by the VEGF therapy method. It was also known as angiogenic therapy.
Bevacizumab, a monoclonal antibody, can be used against vascular endothelial
growth factor to treat colorectal cancer in phase III trial of gastric cancer (Norguet
et al. 2012). Binding of bevacizumab to the VEGF-A domain inhibits the down-
stream signaling of VEGF receptor to neutralize tumor cell growth. It was found that
bevacizumab, in combination with insulin-like growth factor1, works more effec-
tively on gastric cancer. In metastatic gastroesophageal junction cancer,
bevacizumab decreases 65% of cancer cell progression (Shah et al. 2006). Another
monoclonal antibody, namely ramucirumab, is reported to bind with the VEGF
receptor and increase the survivability of gastric cancer in the phase III study
(NCT number: NCT01170663). Ramucirumab was used in advance gastric carci-
noma after the first stage of chemotherapy. Again ramucirumab along with pacli-
taxel, also called RAINBOW, was used for treating metastatic gastric cancer. This
therapy delayed the growth of cancer cells as compared with the cancer cell treated
with the first line of chemotherapy. DC101, another VEGF receptor, induces the
endothelial apoptosis by decreasing the tumor vascularity in human gastric cancer
patient (Jung et al. 2002). DC101, in combination with C225, reduces gastric tumor
growth (Park et al. 2015). Regorafenib is an oral multikinase inhibitor and target
angiogenic (VEGFR1, VEGFR2, and TIE2), stromal and oncogenic receptor tyro-
sine kinases. In a phase II trial, regorafenib significantly increases overall survival
and thus may serve as second-line or later-line therapy in advanced gastric cancer
(Kiyozumi et al. 2018).
7.4.4 cMET Pathway
MET are the tyrosine kinase receptor present at the extracellular surface that encodes
the hepatocyte growth factor (HGF). The activation of MET by HGF enhances cell
proliferation, invasion, and tumor formation in cancer cells (Lordick 2014). In
gastric cancer, the MET receptor is amplified and overexpressed at a frequent
interval. On binding with the HGF ligand, the signaling pathways such as MAPK
and AKT also get activated, which in turn develop gastric cancer. In most of the
cases, the MET mediated signaling pathway acts directly on HER2 and stimulates
the activation of downstream pathways (Chen et al. 2012). Chen and the team also
reported that the activated MET provides resistance against the lapatinib of HER2
receptor amplification and decreases the rate of cell proliferation to 70%. Together
lapatinib and MET inhibitors show positive results towards the lapatinib resistant
gastric cancer cells. Another monoclonal antibody rilotumumab blocks the interac-
tion of MET with HGF. Previously it was found that rilotumumab along with
epirubicin, cisplatin, and capecitabine gives a positive effect to gastric esophagus
cancer on first-line therapy (Iveson et al. 2014). Onartuzumab also inhibits the
binding of cMET to the HGF receptor (Kiyozumi et al. 2018). Foveau et al. reported
that on cMET inactivation, MET did not bind with HGF, which in turn results in
impaired dimerization of receptors. Onartuzumab is also reported to be used for the
phase III trial of gastric cancer (Foveau et al. 2009).
7.4.5 Cytotoxic T Lymphocyte-Associated Antigen4 (CTL4)
CTL4 is comprised of 149 amino acids, and are mainly expressed in CD4 and CD8
of T lymphocytes. Kordi-Tamandani et al. reported that the methylation at the
promoter results in silencing of CTL4 gene, which in turn increases the risk of
gastric cancer cell (Kordi-Tamandani et al. 2014). Anti-CTL4 inhibitors are used to
activate the T cells for producing antibodies against colon and gastric cancers.
Tremelimumab, a monoclonal antibody, works against anti-CTL4 and can be used
for the treatment of gastro cancer, colon cancer, and melanoma. This therapy results
in a survival rate of 4.8 months (Ralph et al. 2010; Blank and Enk 2015).
7.4.6 Tyrosine Kinase
Apatinib is a small-molecule tyrosine kinase inhibitor (TKI) that selectively binds to

and strongly inhibits VEGFR2. This in turn decreases the VEGF-mediated endothe-
lial cell migration, proliferation, and microvascular tumor density. In a phase III trial,
apatinib treatment significantly improved the survival rate of advanced gastric
cancer patients. Therefore, apatinib is focused on a novel type of targeted treatment
for advanced gastric cancer in several lines of therapy (Li et al. 2016). Regorafenib
serves as an inhibitor of angiogenic (VEGFR1, VEGFR2, and TIE2), stromal and
oncogenic receptor tyrosine kinases (Pavlakis et al. 2016). Regorafenib significantly
increases overall survival of advance gastric cancer patients.
7.4.7 mTOR
The mTOR inhibitor enhances the fluorouracil based apoptosis in gastric cancer
cells. The phosphatidylinositol 3-kinase (PI3K) and mTOR get activated in 30–60%
of gastric cancer. The PI3K and mTOR pathway dysregulations are associated with
chemotherapy resistance (Oki et al. 2005). Although in phase II trial, everolimus was
demonstrated to be significantly beneficial, in a phase III trial it failed to improvise
the survival after first- or second-line chemotherapy (Doi 2004). The reason for these
results was discussed to be partially attributable to the slightly higher percentage of
placebo groups, which initiated antineoplastic therapy after a study on drug
discontinuation.
106 G. Gouda et al.
7.4.8 Programmed Cell Death Protein 1 (PD1)
Avelumab is an intravenously administered PD-L1 blocking human IgG1 lambda

antibody. Avelumab has now been approved by the Food and Drug Administration
(FDA) for the treatment of Merkel-cell carcinoma (JAVELIN Gastric
100, NCT2625610). Durvalumab is a human IgG1κ monoclonal antibody that
blocks the interaction of PD-L1 with PD-1 and CD80 molecules. This antibody
has been approved for the treatment of patients with locally advanced or metastatic
urothelial carcinoma. Durvalumab has also been shown to be efficient in gastric
cancer. Durvalumab in combination with tremelimumab, which is a human IgG2
fully monoclonal antibody and acts against CTLA-4, is also used for treating
metastatic gastric cancer in phase Ib/II trial (Borrie and Maleki Vareki 2018; Guo
et al. 2019). Epacadostat is a potent and novel indolemine-2,3-dioxygenase (IDO1)
inhibitor (Prendergast et al. 2017). IDO1 is an enzyme responsible for oxidizing
tryptophan into kynurenine and is implicated in immune modulation through its
ability to limit T cell function and engage mechanisms of immune tolerance
(Kiyozumi 2018).
7.5 Side Effects of Monoclonal Antibody Therapy
Though monoclonal antibody therapy is widely employed in the treatment of GI

cancer, they too have various side effects (Guan et al. 2015). Anaphylactic hyper-
sensitivity occurs after the injection of the monoclonal antibodies cetuximab and
ramucirumab (Guan et al. 2015). A delayed Type III reaction was observed against
rituximab, which in turn results in serum sickness in 20% of the patients (Guan et al.
2015). Bevacizumab and ramucirumab directly cause arterial thromboembolic,
hypertension, proteinuria, arterial, non-gastrointestinal fistula, and venous thrombo-
embolism in patients (Choueiri et al. 2011; Zuo et al. 2014). Congestive heart failure
was observed in patients treated with bevacizumab in the trials on solid tumors
(Choueiri et al. 2011). Mucositis was observed for the cetuximab antibody (Dote
et al. 2018). Pembrolizumab and pidilizumab causes rashes, diarrhea, fatigue were
observed (Linardou and Gogas 2016; So and Board 2018). Trastuzumab causes
anemia in the GI tract (Barni et al. 2012). Hypersensitivity occurs due to
panitumumab (https://www.gov.uk). Thus, the monoclonal antibody should be
employed carefully while treating any diseases, including GI cancer.
7.6 Conclusion
In conclusion, recently, monoclonal antibodies have made a remarkable transforma-

tion from scientific apparatuses to powerful human therapeutics. Monoclonal anti-
bodies are single antibodies that are produced by fusing an immortalized cell line
with antibody-producing cells, which in turn produce a new form of the cell line,
namely, hybridoma. As hybridoma is “immortal,” we can generate the exact anti-
body from them for several years. Additionally, due to high specificity, monoclonal
antibodies have fewer side effects. Thus, since 1986, several monoclonal antibodies
have been approved for the treatment of a wide range of diseases, including GI
cancer. However, nothing is perfect in this world. Few studies have reported that
these monoclonal antibodies have side effects. For instance, a delayed Type III
reaction was observed against rituximab, which in turn results in serum sickness in
20% of the patients. Thus, the monoclonal antibody should be used carefully under
the provision of a medical practitioner. In the near future, the information present in
this chapter will be highly useful for treatment in GI cancer.
Conflict of Interest None.
References
Bang Y-J (2012) Advances in the management of HER2-positive advanced gastric and gastro-
esophageal junction cancer. J Clin Gastroenterol 46:637–648
Bang Y-J, Van Cutsem E, Feyereislova A et al (2010) Trastuzumab in combination with chemo-
therapy versus chemotherapy alone for treatment of HER2-positive advanced gastric or gastro-
oesophageal junction cancer (ToGA): a phase 3, open-label, randomised controlled trial. Lancet
376:687–697
Bao W, Fu H-J, Xie Q-S et al (2011) HER2 interacts with CD44 to up-regulate CXCR4 via
epigenetic silencing of microRNA-139 in gastric cancer cells. Gastroenterology 141:2076–2087
Barni S, Cabiddu M, Guarneri P, Lonati V, Petrelli F (2012) The risk for anemia with targeted
therapies for solid tumors. Oncologist 17:715–724
Barok M, Tanner M, Köninki K, Isola J (2011) Trastuzumab-DM1 is highly effective in preclinical
models of HER2-positive gastric cancer. Cancer Lett 306:171–179
Bijlsma MF, Sadanandam A, Tan P, Vermeulen L (2017) Molecular subtypes in cancers of the
gastrointestinal tract. Nat Rev Gastroenterol Hepatol 14:333–342
Birdwell CE, Queen KJ, Kilgore PCSR, Rollyson P, Trutschl M, Cvek U, Scott RS (2014) Genome-
Wide DNA methylation as an epigenetic consequence of Epstein-Barr virus infection of
immortalized keratinocytes. J Virol 88:11442–11458
Blank CU, Enk A (2015) Therapeutic use of anti-CTLA-4 antibodies. Int Immunol 27:3–10
Borrie AE, Maleki Vareki S (2018) Chapter five - T lymphocyte–based cancer immunotherapeutics.
In: Galluzzi L, Rudqvist N-P (eds) International review of cell and molecular biology. Aca-
demic, San Diego, pp 201–276
Brody T (2018) Chapter 3 - food effect studies. In: Brody T (ed) FDA’s drug review process and the
package label. Academic, San Diego, pp 35–100
Bruneau E (2017) Basic anatomy and physiology of the gastrointestinal tract. In: Loveitt A, Martin
MM, Neff MA (eds) Passing the certified bariatric nurses exam. Springer, Cham, pp 19–25
108 G. Gouda et al.
Carvalho LS, Silva OB da, deAlmeida GC, Oliveira JD de, Carmo NSP (2017) Production
processes for monoclonal antibodies. Ferment Process. https://doi.org/10.5772/64263
Chartrain M, Chu L (2008) Development and production of commercial therapeutic monoclonal
antibodies in mammalian cell expression systems: an overview of the current upstream tech-
nologies. Curr Pharm Biotechnol 9:447–467. https://doi.org/10.2174/138920108786786367
Chen C-T, Kim H, Liska D, Gao S, Christensen JG, Weiser MR (2012) MET activation mediates
resistance to lapatinib inhibition of HER2-amplified gastric cancer cells. Mol Cancer Ther
11:660–669
Choueiri TK, Mayer EL, Je Y, Rosenberg JE, Nguyen PL, Azzi GR, Bellmunt J, Burstein HJ,
Schutz FAB (2011) Congestive heart failure risk in patients with breast cancer treated with
bevacizumab. JCO 29:632–638
Collins DM, O’Donovan N, McGowan PM, O’Sullivan F, Duffy MJ, Crown J (2012) Trastuzumab
induces antibody-dependent cell-mediated cytotoxicity (ADCC) in HER-2-non-amplified breast
cancer cell lines. Ann Oncol 23:1788–1795
Cortés-Funes H, Rivera F, Alés I, Márquez A, Velasco A, Colomer R, García-Carbonero R,
Sastre J, Guerra J, Grávalos C (2007) Phase II of trastuzumab and cisplatin in patients (pts)
with advanced gastric cancer (AGC) with HER2/neu overexpression/amplification. JCO
25:4613–4613
Corthell JT (2014) Chapter 5 - antibodies and titrations. In: Corthell JT (ed) Basic molecular
protocols in neuroscience: tips, tricks, and pitfalls. Academic, San Diego, pp 41–46
Derks S, Liao X, Chiaravalli AM et al (2016) Abundant PD-L1 expression in Epstein-Barr Virus-
infected gastric cancers. Oncotarget 7:32925–32932
Doi K (2004) Ehd1, a B-type response regulator in rice, confers short-day promotion of flowering
and controls FT-like gene expression independently of Hd1. Genes Dev 18:926–936
Dote S, Itakura S, Kamei K, Hira D, Noda S, Kobayashi Y, Terada T (2018) Oral mucositis
associated with anti-EGFR therapy in colorectal cancer: single institutional retrospective cohort
study. BMC Cancer. https://doi.org/10.1186/s12885-018-4862-z
Dungo RT, Keating GM (2013) Afatinib: first global approval. Drugs 73:1503–1515
Edris B, Willingham SB, Weiskopf K et al (2013) Anti-KIT monoclonal antibody inhibits imatinib-
resistant gastrointestinal stromal tumor growth. Proc Natl Acad Sci U S A 110:3501–3506
El-Rayes BF, Zalupski M, Bekai-Saab T et al (2010) A phase II study of bevacizumab, oxaliplatin,
and docetaxel in locally advanced and metastatic gastric and gastroesophageal junction cancers.
Ann Oncol 21:1999–2004
Emmons C, Hunsicker LG (1987) Muromonab-CD3 (Orthoclone OKT3): the first monoclonal
antibody approved for therapeutic use. Iowa Med 77:78–82
Foveau B, Ancot F, Leroy C, Petrelli A, Reiss K, Vingtdeux V, Giordano S, Fafeur V, Tulasne D
(2009) Down-regulation of the met receptor tyrosine kinase by presenilin-dependent regulated
intramembrane proteolysis. Mol Biol Cell 20:2495–2507
Gold PJ, Goldman B, Iqbal S, Leichman LP, Zhang W, Lenz H-J, Blanke CD (2010) Cetuximab as
second-line therapy in patients with metastatic esophageal adenocarcinoma: a phase II South-
west Oncology Group Study (S0415). J Thorac Oncol 5:1472–1476
Guan M, Zhou Y-P, Sun J-L, Chen S-C (2015) Adverse events of monoclonal antibodies used for
cancer therapy. Biomed Res Int 2015:1–13
Guo Q, Huang F, Goncalves C, del Rincón SV, Miller WH (2019) Chapter one - translation of
cancer immunotherapy from the bench to the bedside. In: Wang X-Y, Fisher PB (eds) Advances
in cancer research. Academic, San Diego, pp 1–62
Gupta MK, Vadde R, Sarojamma V (2019) Curcumin - a novel therapeutic agent in the prevention
of colorectal cancer. Curr Drug Metab. https://doi.org/10.2174/1389200220666191007153238
Huang SC, Miki K, Sano J, Ichinose M, Kawamura N, Oka H, Hirano K, Furihata C, Masugi Y,
Takahashi K (1988) Pepsinogens I and II in gastric cancer: an immunohistochemical study using
monoclonal antibodies. Jpn J Cancer Res 79:1139–1146
Iveson T, Donehower RC, Davidenko I et al (2014) Rilotumumab in combination with epirubicin,
cisplatin, and capecitabine as first-line treatment for gastric or oesophagogastric junction
adenocarcinoma: an open-label, dose de-escalation phase 1b study and a double-blind,

randomised phase 2 study. Lancet Oncol 15:1007–1018
Jung YD, Mansfield PF, Akagi M, Takeda A, Liu W, Bucana CD, Hicklin DJ, Ellis LM (2002)
Effects of combination anti-vascular endothelial growth factor receptor and anti-epidermal
growth factor receptor therapies on the growth of gastric cancer in a nude mouse model. Eur J
Cancer 38:1133–1140
Kiyozumi Y (2018) Abstract 5700: IDO1 high expression is associated with a poor prognosis in
patients with esophageal cancer. Cancer Res 78:5700–5700
Kiyozumi Y, Iwatsuki M, Yamashita K, Koga Y, Yoshida N, Baba H (2018) Update on targeted
therapy and immune therapy for gastric cancer, 2018. J Cancer Metastasis Treat 4:31
Köhler G, Milstein C (1975) Continuous cultures of fused cells secreting antibody of predefined
specificity. Nature 256:495–497
Kordi-Tamandani DM, Davani SK, Baranzehi T, Hemati S (2014) Analysis of promoter methyl-
ation, polymorphism and expression pro le of cytotoxic T-lymphocyte-associated antigen-4 in
patients with gastric cancer. J Gastrointestin Liver Dis 23:5
León-Chong J, Lordick F, Kang YK, Park SR, Bang YJ, Sawaki A, Van Cutsem E, Stoss O, Jordan
BW, Feyereislova A (2007) HER2 positivity in advanced gastric cancer is comparable to breast
cancer. JCO 25:15057–15057
Li J, Qin S, Xu J et al (2016) Randomized, double-blind, placebo-controlled phase III trial of
apatinib in patients with chemotherapy-refractory advanced or metastatic adenocarcinoma of the
stomach or gastroesophageal junction. J Clin Oncol 34:1448–1454
Linardou H, Gogas H (2016) Toxicity management of immunotherapy for patients with metastatic
melanoma. Ann Transl Med. https://doi.org/10.21037/atm.2016.07.10
Liu JKH (2014) The history of monoclonal antibody development – progress, remaining challenges
and future innovations. Ann Med Surg 3:113–116
Lordick F (2014) Targeting the HGF/MET pathway in gastric cancer. Lancet Oncol 15:914–916
Lordick F, Luber B, Lorenzen S et al (2010) Cetuximab plus oxaliplatin/leucovorin/5-fluorouracil
in first-line metastatic gastric cancer: a phase II study of the Arbeitsgemeinschaft Internistische
Onkologie (AIO). Br J Cancer 102:500–505
Lorenzen S, Hentrich M, Haberl C, Heinemann V, Schuster T, Seroneit T, Roethling N, Peschel C,
Lordick F (2007) Split-dose docetaxel, cisplatin and leucovorin/fluorouracil as first-line therapy
in advanced gastric cancer and adenocarcinoma of the gastroesophageal junction: results of a
phase II trial. Ann Oncol 18:1673–1679
Lu R-M, Hwang Y-C, Liu I-J, Lee C-C, Tsai H-Z, Li H-J, Wu H-C (2020) Development of
therapeutic antibodies for the treatment of diseases. J Biomed Sci 27:1
M a g g o n K ( 2 0 0 7 ) M o n o c l o n a l a n t i b o d y & g o l d ru s h . h t t p s : / / d o i . o r g / 1 0 . 2 1 7 4 /
092986707781368504
Manis JP, Feldweg AM (2019) Overview of therapeutic monoclonal antibodies. US Pharm 44(1):31
Martinelli E, Palma RD, Orditura M, Vita FD, Ciardiello F (2009) Anti-epidermal growth factor
receptor monoclonal antibodies in cancer therapy. Clin Exp Immunol 158:1
Matsuoka T, Yashiro M (2015) Recent advances in the HER2 targeted therapy of gastric cancer.
World J Clin Cases 3:42–51
Moehler M, Mueller A, Trarbach T et al (2011) Cetuximab with irinotecan, folinic acid and
5-fluorouracil as first-line treatment in advanced gastroesophageal cancer: a prospective multi-
center biomarker-oriented phase II study. Ann Oncol 22:1358–1366
Nahta R, Hung M-C, Esteva FJ (2004) The HER-2-targeting antibodies trastuzumab and
pertuzumab synergistically inhibit the survival of breast cancer cells. Cancer Res 64:2343–2346
Norguet E, Dahan L, Seitz J-F (2012) Targetting esophageal and gastric cancers with monoclonal
antibodies. CTMC 12:1678–1682
Oki E, Baba H, Tokunaga E et al (2005) Akt phosphorylation associates with LOH of PTEN and
leads to chemoresistance for gastric cancer. Int J Cancer 117:376–380
Park DJ, Thomas NJ, Yoon C, Yoon SS (2015) Vascular endothelial growth factor a inhibition in
gastric cancer. Gastr Cancer 18:33–42
110 G. Gouda et al.
Pavlakis N, Sjoquist KM, Martin AJ et al (2016) Regorafenib for the treatment of advanced gastric
cancer (INTEGRATE): a multinational placebo-controlled phase II trial. JCO 34:2728–2735
Pento JT (2017) Monoclonal antibodies for the treatment of cancer. Anticancer Res 37:5935–5939
Pinto C, Di Fabio F, Barone C et al (2009) Phase II study of cetuximab in combination with cisplatin
and docetaxel in patients with untreated advanced gastric or gastro-oesophageal junction
adenocarcinoma (DOCETUX study). Br J Cancer 101:1261–1268
Prendergast GC, Malachowski WP, DuHadaway JB, Muller AJ (2017) Discovery of IDO1 inhib-
itors: from bench to bedside. Cancer Res 77:6795–6811
Ralph C, Elkord E, Burt DJ, O’Dwyer JF (2010) Modulation of lymphocyte regulation for cancer
therapy: a phase II trial of tremelimumab in advanced gastric and esophageal adenocarcinoma|
clinical cancer research. https://clincancerres.aacrjournals.org/content/16/5/1662. Accessed
14 Feb 2020
Rapisarda A, Melillo G (2012) Role of the VEGF/VEGFR axis in cancer biology and therapy. Adv
Cancer Res 114:237–267
Redman J, Hill E, AlDeghaither D, Weiner L (2015) Mechanisms of action of therapeutic anti-
bodies for cancer. Mol Immunol 67:28–45
Roshandel G, Ghanbari-Motlagh A, Partovipour E et al (2019) Cancer incidence in Iran in 2014:
results of the Iranian National Population-based Cancer Registry. Cancer Epidemiol 61:50–58
Ruhstaller T, Pless M, Dietrich D et al (2011) Cetuximab in combination with chemoradiotherapy
before surgery in patients with resectable, locally advanced esophageal carcinoma: a prospec-
tive, multicenter phase IB/II Trial (SAKK 75/06). J Clin Oncol 29:626–631
Sakai K, Mori S, Kawamoto T, Taniguchi S, Kobori O, Morioka Y, Kuroki T, Kano K (1986)
Expression of epidermal growth factor receptors on normal human gastric epithelia and gastric
carcinomas. J Natl Cancer Inst 77:1047–1052
Shah MA, Ramanathan RK, Ilson DH et al (2006) Multicenter phase II study of irinotecan,
cisplatin, and bevacizumab in patients with metastatic gastric or gastroesophageal junction
adenocarcinoma. JCO 24:5201–5206
Shibuya M, Claesson-Welsh L (2006) Signal transduction by VEGF receptors in regulation of
angiogenesis and lymphangiogenesis. Exp Cell Res 312:549–560
Shimasaki C (2014) Chapter 9 - understanding biotechnology product sectors. In: Shimasaki C
(ed) Biotechnology entrepreneurship. Academic Press, Boston, pp 113–138
Shimoyama S (2014) Unraveling trastuzumab and lapatinib inefficiency in gastric cancer: future
steps (review). Mol Clin Oncol 2:175–181
Shitara K, Özgüroğlu M, Bang Y-J et al (2018) Pembrolizumab versus paclitaxel for previously
treated, advanced gastric or gastro-oesophageal junction cancer (KEYNOTE-061): a
randomised, open-label, controlled, phase 3 trial. Lancet 392:123–133
Singh S, Jha HC (2017) Status of Epstein-Barr virus coinfection with helicobacter pylori in gastric
cancer. J Oncol. https://doi.org/10.1155/2017/3456264
So AC, Board RE (2018) Real-world experience with pembrolizumab toxicities in advanced
melanoma patients: a single-center experience in the UK. Melanoma Manage. https://doi.org/
10.2217/mmt-2017-0028
Somi MH, Dolatkhah R, Sepahi S, Belalzadeh M, Naghashi S, Asghari Jafarabadi M (2019) A
12-year trend analysis of the incidence of gastrointestinal cancers in East Azerbaijan: last
updated results of an ongoing population-based cancer registry. BMC Cancer 19:782
Strumberg D, Schultheis B, Scheulen ME et al (2012) Phase II study of nimotuzumab, a humanized
monoclonal anti-epidermal growth factor receptor (EGFR) antibody, in patients with locally
advanced or metastatic pancreatic cancer. Investig New Drugs 30:1138–1143
Talavera A, Friemann R, Gómez-Puerta S et al (2009) Nimotuzumab, an antitumor antibody that
targets the epidermal growth factor receptor, blocks ligand binding while permitting the active
receptor conformation. Cancer Res 69:5851–5859
Tridente G (2017) Chapter 25 - Afatinib. In: Tridente G (ed) Adverse events and oncotargeted
kinase inhibitors. Academic, London, pp 561–589
Waddell T, Chau I, Cunningham D et al (2013) Epirubicin, oxaliplatin, and capecitabine with or

without panitumumab for patients with previously untreated advanced oesophagogastric cancer
(REAL3): a randomised, open-label phase 3 trial. Lancet Oncol 14:481–489
Wagner AD, Grothe W, Haerting J, Kleber G, Grothey A, Fleig WE (2006) Chemotherapy in
advanced gastric cancer: a systematic review and meta-analysis based on aggregate data. J Clin
Oncol 24:2903–2909
Zang ZJ, Cutcutache I, Poon SL et al (2012) Exome sequencing of gastric adenocarcinoma
identifies recurrent somatic mutations in cell adhesion and chromatin remodeling genes. Nat
Genet 44:570–574
Zuo P-Y, Chen X-L, Liu Y-W, Xiao C-L, Liu C-Y (2014) Increased risk of cerebrovascular events
in patients with cancer treated with bevacizumab: a meta-analysis. PLoS One 9:e102484. https://
doi.org/10.1371/journal.pone.0102484
Chapter 8
Therapeutic Vaccines for Gastrointestinal
Malignancies
Bonala Sabeerabi, Venkat R. Arva Tatireddygari, and Ramakrishna Vadde
Abstract Gastrointestinal (GI) cancers are highly aggressive and display genome
instability, gene mutations, immune suppression, immune insensitivity, and
desmoplasia. GI cancers represent as one among the most common cancer type
with a burden of ~25% worldwide, with each year about 4.5 million global deaths.
GI cancers are not preventive, the prognosis of patients with advanced tumors was
difficult, and treating the GI cancers is the only option. For many years, the treatment
of GI cancer patients involve surgery, radiotherapy, and chemotherapy in combina-
tion or alone. The successes oncologists achieved so far was great but not enough,
since it is only recently, the very first promising clinical data comes into light in
2015. Hence novel therapeutic ways to treat GI cancer were much required. Pres-
ently, it appears that immunotherapy is the answer. Immunotherapy is advancing
quickly and outlines, a conventional shift in the treatment of GI cancer through its
promising benefits beyond conventional treatments. Currently, researchers are
examining a variety of medicines and factors like immune checkpoint inhibitors,
ACT, peptide vaccines, cytokines, and antibodies to treat GI cancers. In recent years,
the FDA approved the utilization of anti-PD-1, anti-VEGFR2, and anti-CTLA-4,
immunotherapy against a few GI cancers including gastric cancer, liver cancer, and
colorectal cancers. Among all the GI cancers, biliary tract cancer and pancreatic
cancer patients have limited/no immunotherapeutic options at the moment, nonethe-
less ongoing clinical investigation will provide some assuring therapeutic solutions.
It is highly important to overcome the various factors contributing to varied effec-
tiveness of immunotherapy in GI cancers. Researchers are currently investigating the
potentiality of cancer stem cells and their specific markers as targets: outcomes from
B. Sabeerabi
Biostandups, Hyderabad, Telangana, India
V. R. Arva Tatireddygari
Department of Zoology, Yogi Vemana University, Kadapa, Andhra Pradesh, India
R. Vadde (*)
Pradesh, India
https://doi.org/10.1007/978-981-15-6487-1_8
114 B. Sabeerabi et al.
such studies may become new waves in immunotherapy treating GI cancers. Let us
hope that oncologists will discover the “Magic bullet” to whitewash GI cancers in
the near future and we believe it is just the beginning of the new era for immuno-
therapy and we have a long road ahead to succeed.
Keywords Gastrointestinal cancers · Immunotherapy · Vaccines · PD-1 · CTLA-4 ·

Clinical trials · FDA
Abbreviations
(Ig)G4 Immunoglobulin G4
5-FU Fluorouracil
A2AR Adenosine A2a receptor
AES Adverse events
AGEJ Adenocarcinoma of gastric esophageal junction
APC Antigen-presenting cells
Bcl-2 B-cell lymphoma 2
Bcl2/Bax B-cell lymphoma 2/CL2 associated X
BRAF B-Raf proto-oncogene
BTC Biliary tract cancers
BTK Bruton’s tyrosine kinase
CAIX Carboxy-anhydrase-IX
CCL2 C-C motif chemokine ligand 2
CCR2 C-C motif chemokine receptor 2
CD152 Cluster of differentiation 152
CHB Chronic hepatitis B
CMS Consensus molecular subtypes
CMS1 Consensus molecular subtypes 1
CPS Combined positive score
CR Complete response
CTLA-4 Cytotoxic T-lymphocyte-associated protein 4
CTLs Cytotoxic T lymphocytes
8 Therapeutic Vaccines for Gastrointestinal Malignancies 115
DCs Dendritic cells

DFS Disease-free survival
dMMR Poor mismatch repair
DNMT DNA methyltransferase
EBV-specific CTL Epstein–Barr virus specific cytotoxic T lymphocytes
EGFR Epidermal growth factor receptor
EpCAM Epithelial cell adhesion molecule
ESCC Esophageal squamous cell carcinomas
FAK Focal adhesion kinase
FDA Food and Drug Administration
GEJ Esophagogastric junction
GEM Gemcitabine
GI Gastrointestinal
GITR Glucocorticoid-induced TNF receptor
GITRL Glucocorticoid-induced TNF receptor ligand
GM-CSF Granulocyte/macrophage-colony stimulating factor
gp100 Glycoprotein 100
GPC3 Glypican-3
HCC Hepatocellular carcinoma
HCV Hepatitis C virus
HDAC Histone deacetylases
HER-2/neu Human Epidermal Growth Factor Receptor 2/neu
HIV 1 human immunodeficiency virus 1
HLA-24 Human leukocyte antigen alpha 24
HLA-A*2402 Human leukocyte antigen alpha *2402
HLA-A2 Human leukocyte antigen alpha 24
HPV human papillomavirus
HSP70 Heat shock protein 70
ICC Intrahepatic cholangiocarcinoma
IFN-γ Interferon gamma
IL-10 Interleukin 10
IL-4 Interleukin 4
IL-6 Interleukin 6
ITT Intent-to-treat
KIF20A Kinesin family member 20A
KIF20A Kinesin Family member 20A
KIR’s Killer-cell immunoglobulin-like receptors
KOC1 Kinase of the outer chloroplast membrane 1
KRAS-G12D Kirsten rat sarcoma G12D
LAG3 Lymphocyte-activation gene 3
LAK Lymphokine-activated killer
LMP1/2/7 Latent membrane protein 1/2/7
MAGE Melanoma antigen gene
MART-1 Melanoma-associated antigen recognized by T cells
Mcl-1 Induced myeloid leukemia cell differentiation protein

mCRC Metastatic colorectal cancer
MDSC myeloid-derived suppressor cells
MEK inhibitor Mitogen-activated protein kinase inhibitor
MHC class I Major histocompatibility complex class I
mPC Metastatic pancreatic cancer
MST Median overall survival time
MUC1-CTL Mucin 1 cytotoxic T lymphocytes
MUC1-DC Mucin 1 dendritic cells
NASH Nonalcoholic steatohepatitis
NF-kB Nuclear factor NF-κB
NK cells Natural killer cells
NKT Natural killer T cells
NLR Neutrophil/lymphocyte ratio
ORFs Open reading frame
ORR Overall response rates
OS Overall survival
p53 Tumor protein p53
PAC Pancreatic adenocarcinoma
PBMCs peripheral blood mononuclear cell
PD-1 Programmed cell death protein 1
PDAC Pancreatic ductal adenocarcinoma
pDC Plasmacytoid dendritic cells
PD-L1 Programmed death-ligand 1 (PD-L1)
PFS Progression-free survival
pMMR Ultra-mismatch repair
PR Progesterone receptors
RCC Renal cell carcinoma
RNF43 Ring Finger Protein 43
SEREX Serological analysis of recombinant tumor cDNA expression
libraries
SOC Site of care
TAA Tumor associated antigens
TAP1 Transporter 1, ATP binding cassette subfamily B member
TCB T-cell bispecific
TGF-β Transforming growth factor beta
Th1 Type 1 T helper
TIL Tumor Infiltrating lymphocyte
TIM-3 T-cell immunoglobulin and mucin-domain containing-3
TLR9 Toll-like receptor 9
TNF Tumor necrosis factor
TNF-α Tumor necrosis factor alpha
TOMM34 Translocase of outer mitochondrial membrane 34
TRAEs Treatment-related adverse event

T-reg cells T regulatory cells
TSA Tumor specific antigens
VEGFR 1/2 Vascular endothelial growth factor receptor 1/2
WT1 Wilms tumor 1
8.1 Background
The most common kind of cancer that occurs in humans is Gastrointestinal

(GI) cancer and a burden of ~25% worldwide with each year about 4.5 million
global deaths and around 286,480 people diagnosed with fresh GI cancer, which is a
concerning number in which the incidence and mortality are exceeding annually
(Bray et al. 2018). GI cancers generally affect the gastrointestinal parts of the human
body hence these kinds of cancers are said to be the most life-threatening forms of
cancers (MacDonald et al. 2015). Though surgery, radiation, chemotherapy, and
targeted therapy were employed as treatment strategies, the overall survival rate of
GI cancer subjects continues to exist dull, implicating the necessity of novel thera-
peutic methods to treat GI cancer.
Researchers began to develop interest in a novel approach such as vaccine that
could subdue GI cancers and its relapse. This led to the development of therapeutic
vaccines/Immunotherapy for GI cancers on length (Busweiler et al. 2016). In 1891
the first attempt was made for treating cancers with vaccination (Coley 1891). Later
in 1909, Smith demonstrated how important it was to activate immune network to
repress tumor growth (Smith 1909). In 1970, the recognition of antigens expressed
on cancer cells by T cells postulated the existence of immunological surveillance
(Ribatti 2017; van der Bruggen et al. 1991). In the last decade, the introduction of
immunotherapy for treating GI cancers became a necessity (Bolshinsky et al. 2018).
The growth of incidences for GI cancers especially leads to the development of
therapeutic vaccines (Shaw et al. 2016).
Ongoing progress in immunotherapy is attributable primarily with the discovery
of therapeutic vaccines targeting tumor immunity and its microenvironment
(Yaguchi and Kawakami 2016). The therapeutic vaccines specific for GI cancers
comprise immune specific as well as non-specific molecular modifiers. Immuno-
therapy is now attracting more focus than ever as a treatment for GI cancer. The
immunotherapy of GI cancers is mainly divided into checkpoint inhibitors (PD1,
PD-L1, and CTLA-4), vaccine-based therapy (tumor whole cell lysates, peptide
vaccines, dendritic cell vaccines), stromal modulation (FAK inhibition), cytokine-
based therapy (CCR2/CCL2 modulation), and adoptive cell transfer (NK cells and T
cells). In the recent past immunotherapies were applied successfully against GI
cancers including peptide vaccines (HLA-A*2402-restricted peptides and
OCV-C01 from KIF20A) (Shimizu et al. 2018; Shindo et al. 2014; Miyazawa et al.
2017), dendritic cell vaccines (DCs transfected with HSP70) (Maeda et al. 2015),
CD8(+) tumor-infiltrating lymphocytes (TIL) (Turcotte et al. 2014), lymphokine-
activated killer (LAK) (Rayner et al. 1985) and non-specific immunopotentiators
(polysaccharide K aka OK-432 and lentinan) (Rayner et al. 1985; Oba et al. 2016;
Oba et al. 2007; Yoshino et al. 2016) and immune checkpoint inhibitors (blocking
PD-L1, PD-1, or CTLA-4, glypican 3, and restriction peptides HLA-24, HLA-A2)
(Yaguchi and Kawakami 2016; Shimizu et al. 2018). In 2013, anti-CTLA-4
(ipilimumab) and combination of anti–PD-1 with anti–CTLA-4 checkpoint blockers
of immune system were highlighted as “Breakthrough of the Year 2013” because of
its efficacy against cancer patients (Couzin-Frankel 2013), indicating a promising
future to treat GI cancers successfully.
8.2 How Tumors Overcome Host Immune System
The concept of vaccination for cancer began over a century ago by two physicians
namely Paul Ehrlich and William Bradley Coley in 1800s. Paul Ehrlich proposed the
term “The magic bullet,” to kill malignant cells through the use of weakened cancer
cells as Immunotherapy (Waldmann 2003). In 1896, Coley treated cancer patients with
a blend of heat-inactivated bacteria named “Coley toxin” as immunotherapy against
cancer (Vacchelli et al. 2012a). Even though treating cancer patients with vaccines had
seen success rate but largely failed to explain the anti-tumor immunity development by
cancer cells (Vacchelli et al. 2012a). While understanding the anti-tumor immune
response of cancer patients, Frank Macfarlane Burnet theorized “self/non-self” division,
briefing that tumors are capable of creating their self-tissue makes them easy to escape
immunotherapeutic interventions (Burgio 1990). Polly Matzinger published a paper in
1994, in which he proposed (Matzinger 1994) that, “Immune system does not care
about self and non-self, that its primary driving force is the need to detect and
protect against danger, and that it does not do the job alone, but receives positive
and negative communications from an extended network of other bodily tissues.” In
the following years, cancer and trauma: the immunologically silent factors now
became activators of immune system (Vacchelli et al. 2012b; Bezu et al. 2018). To
ameliorate reactions of immune system, cancer cells underwent many diversions to
install resistance to immune-therapeutics. Some of the silent features that cancer
cells adapted to escape immune system are discussed below.
8.3 Tumor Immunosurveillance
In our body cells are continually watched by vigilant immune system at all times to
detect and destroy inceptive cancer cells. However, subsequently, tumor tissue cells
accomplished to escape detection or became insensitive to immunological attacks by
the immune system, thereby avoiding destruction (Hanahan and Weinberg 2011).
Tumor immunosurveillance theory further confirmed through various experimenta-

tions where immunodeficient mice develop tumors more rapidly, particularly the
tumor incidences were more significant in mice lacking immune functioning of
natural killer (NK) cells or Th1 (CD8+ and CD4+) cells, indicating that both innate
and acquired immune responses contributed equally in escaping immune killing and
tumor immune surveillance (Vesely and Schreiber 2013; Kim et al. 2007). Various
studies from humans show that effective immunosurveillance do exist, and in fact,
the prognosis of colon cancer patients became more comfortable due to profoundly
infiltrated CTLs and NK, whereas the absence of TILs adds less prognostic signif-
icance in ovarian cancer patients (Pages et al. 2010; Leffers et al. 2009). The tumor
immunosurveillance theory further confirmed by the existence of particular cancers
in immunocompromised people (Vajdic and van Leeuwen 2009) and evoking
immune reactions specific to tumor-specific/associated antigens in cancer patients
(Wang 1999; Sahin et al. 1995).
8.4 Tumor Immunoediting
Fifty years ago, immune surveillance theory validated that the immune system is
sophisticated to detect and eliminate inceptive cancer cells (Burnet 1957); however,
the latest evidence on the role of the immune system on eliminating these cancer
cells becomes invalidated. Over the past 15 years, a substantial amount of work on
immune surveillance, nature of immunity assisted in perfecting and elaborating new
concept, Immunoediting—phases of the immune system and tumor interactions took
place. Immunoediting composed of three stages, (1) Tumor fixed immune reactions
to control growth of tumor cells effectively, thus “Eliminating” cancer cells, (2) The
gain of immune insensitivity to cytotoxic functions or loss of immunogenicity to
maintain sustainable “Equilibrium.” (3) Before-mentioned cells ultimately grow
uncurbed leading to a clinically visible tumor, hence the “Escape” (Dunn et al.
2004). Figure 8.1 demonstrates the molecular changes describing how tumor cells
evade both (innate and adaptive) immune systems. The occurrence of tumor
immunoediting as a core to explain the magnitude of the immune system’s synergy
with cancer, has, in part, inspired a recent proliferation of the scientific evidence
addressing this process as exhibited by dramatically grown citation (Mittal et al.
2014). Immunoediting relates to the transformations that take place unconsciously as
the tumor grows in the leadership of an unbroken immune system and the perception
of such mechanism provides major suggestion for immunotherapy in human cancers
where nullifying immune damage was lately recommended as a prominent trade-
mark of cancer (Hanahan and Weinberg 2011).
Fig. 8.1 How tumor cells overcome host immune system. Tumor cells follow a series of events in
order to prevent destruction by host immune system. The multi-step event occurs at three different
stages—(1) Elimination—tumor cells and tumor microenvironment dominates host immunity by
expressing tumor antigens, perforin, granzymes, FAS ligand, TNF-related apoptosis-inducing
ligand (TRAIL) receptor, major histocompatibility complex (MHC class I), Reactive oxygen
species (ROS), Interleukins (IL-1/12), Tumor necrosis factor (TNF-α), Interferons (IFN-α/β/γ).
(2) Equilibrium—tumor cells lose their antigens to undergo dormant state where tumor cells can
tolerate immune stress. Following functional dormancy, genetic changes occur within tumor cells to
produce new tumor cells with defective or low antigen capacity. (3) Escape—Tumor cells grow
resistant to immune reactions by secreting angiogenic cytokines including Interleukins (IL-6/10),
Transforming growth factor (TGF-β), Vascular endothelial growth factor (VEGF) and targets
related to immunosuppression such as adenosine receptors, Tryptophan 2,3-dioxygenase (TDO),
indoleamine-pyrrole 2,3-dioxygenase (IDO), Galectin-1/3/9, Cluster of Differentiation 39 (CD39),
Cluster of Differentiation (CD73) and immune inhibitory receptors like cytotoxic T-lymphocyte-
associated protein 4 (CTLA-4), Programmed cell death protein 1 (PD-1), Lymphocyte-activation
gene 3 (LAG-3) and T-cell immunoglobulin and mucin-domain containing-3 (TIM-3)
8.5 Tumor Immune Response
Despite inhibiting tumor growth, immune responses may promote tumor develop-
ment through activating chronic inflammation, which in turn provokes the growth,
development, and angiogenesis of cancer cells. Hosts counter infections by installing
blockades and stimulating various levels of both (innate and adaptive) immune
protection, where the contaminated tissue coordinates the health, condition, and type
of the immune response for effective infection elimination and tissue replacement
while checking corresponding tissue loss (Matzinger and Kamala 2011). At the site
of infection derived inflammation, tumors might originate, and begin to live symbi-
otically in the host by suppressing extreme inflammation with anti-tumor immune
responses. The proinflammatory wound healing microenvironment created by stro-
mal and epithelial cells at the injected site, in turn, promotes tumor development
through angiogenic-tissues remodeling expansion that drives tumor cell invasion and
progression (Edme et al. 2002; Salcedo et al. 2013)
Malignant cancers stem inside differentiated tissues and have some of the func-
tional, architectural, and immune features of their tissue of origin and mimicking the
original tissue (Pierce and Speers 1988). The immune response generated by the
neoplasm will be in most examples helpless to destroy it and will install a Darwinian
environment picking the genetically adapted cancer cells that unfold into threatening
malignant tumors or live momentarily in equilibrium with non-malignant host cells
(Schreiber et al. 2011). In addition to tissues of tumor origin, pathogens, carcino-
gens, the nature of tissue damage, and proinflammatory mediators secreted from
tumor or their stroma determine the class of inflammatory/immune response
observed in cysts. Establishment of the suppressed immune response through a
pathway that promotes tissue growth, T-cells deficient in IFN-γ, TNF, granzymes,
perforin effector molecule, and high amounts of (CTLA-4, PD-1, LAG3, TIM-3,
A2AR and KIR’s) inhibitory molecules is inevitable (Goldszmid et al. 2014). The
proinflammatory cytokine TNF-α, released from either macrophage or mast cells, is
involved in initial melanoma growth during contaminations. TNF-α aids tumor
development, continuation following the enrollment of immune effector cells
along with active angiogenesis (Dougan and Dranoff 2009). In a colon cancer
mouse model, immune cells lacking NF-κβ proved a decline in tumor progression
and limited tumor prevalence in intestinal epithelium when NF-κβ was removed
(Greten et al. 2004).
8.6 Tumor Immune Escape
The immune evasion mechanisms of tumors become a question to address. The

immune surveillance system eradicates a considerable amount of rogue cancer cells,
yet for a variety of unknown reasons melanoma cells are still able to progress the
suppression by the immune system. Mechanisms of evading immune attention
include but not limited to various stages of tumor development. The efficacy of
immune mechanisms to discriminate healthy cells from cancerous ones is vital in
immunotherapy, which depends to some extent not entirely on cancerous cells
storing enough immunogenicity. Tumor displays a mixture having both (mutated
and non-mutated) antigens which contain the potentiality toward immune responses
that are tumor-specific (Coulie et al. 2014). Though, in bypassing the immune
attacks, tumor cell can succumb their immunogenicity. Not having immunogenicity
may come from careful immune assortment of tumor cells which require either
defective tumor antigens or attainment of errors or insufficiencies in presenting
antigen (Schreiber et al. 2011).
Tumor cells on their own acquire various tactics permitting cancer cell to evade
monitoring and removal through immune system. Tolerance stimulation is one
among the primary means that comprises different stages. In addition to losing
HLA-allele expression, in cases whole MHC class I absence was reported where
β2-microglobulin gene mutations are solely responsible for MHC I loss, this loss
corroborates with evasion for CTL recognition (Poggi et al. 2005; Upadhyay et al.
2015). In some cases, tumors are sensitive to immune attack though MHC I is lost
completely, here NK cells carry out immune reactions; however, certain tumors
present themselves with either poor NK cell immunological memory or contain very
few NK cells in them (Poggi et al. 2005; Kaufman and Disis 2004). Adding more
complexity to the current situation is that absence of TAA in some tumors makes
them resistant to immune attack irrespective of MHC I and NK cells, CTL responses
(Poggi and Zocchi 2006). Tumor cells acquire defective antigen presentation and
processing through down regulation of delivery molecules such as LMP1/2/7
(Hayashi et al. 2011), proteasome components, and TAP1 (Johnsen et al. 1999),
and loss of tapasin protein (Shionoya et al. 2017). The downregulation sometimes
results in defective molecule synthesis or complete loss (CD80 and CD86) of
antigens on cell surfaces (Poggi et al. 2005; Staveley-O’Carroll et al. 1998). The
two concepts immunodominance and immunoselection by tumor cells are also
linked with immune evasion mechanism. In tumor microenvironment immune
responses are always aimed at dominant antigen holding tumor cells, creating a
hierarchy within tumor antigens (Cohen et al. 2010). As the tumor growth continues
dominant antigens will disappear and a new hierarchy is built within emerging
antigens creating immunodominant thus creating an immunoselection process.
Defects in molecular pathways like apoptosis (Bcl-2, Mcl-1, p53, and Bcl2/Bax)
in tumor host can provoke immune escape (Lopez and Tait 2015; Sayers 2011).
Discharge of immune-suppressive cytokines [IL-6/10 (Fisher et al. 2014; Dennis
et al. 2013), VEGF (Mulligan et al. 2010), and TGF beta (Massague 2008)] from
either tumors or tumor stroma is also considered one of the immune escape plans.
Studies recommend that functionally abnormal immune cells residing in tumors play
role in developing an immune-suppressive state (Pinheiro et al. 2011). Presence of
immature MDSC, non-functional macrophages, and Tregs confers suppressive envi-
ronment in tumors (Kumar et al. 2016; Noy and Pollard 2014; Chaudhary and Elkord
2016).
8.7 Tumor Immune Checkpoints
A broad array of both stimulatory and inhibitory immune checkpoints molecules is

identified and only few of them were discussed in the current section. The neoplastic
immune microenvironment comprises a broad array of mixed cooperation between
tumor cell, tumor stroma, and immune cells (APC, T cell, NK cell, B cell). Immune
response toward neoplasm is a consequence of competition among stimulatory and
signals. Immune checkpoints are primary immune regulators in controlling immune
homeostasis and inhibiting autoimmunity. The checkpoints of the immune system
consist of both inhibitory and stimulatory agents; these are significant in preserving
self-tolerance, monitoring the type, and the extent continuation of the immune
response. Under ordinary situations, immune checkpoints support the immune
system to react against pathological condition and tumor invasion while defending
tissues from any harm that may stem from this action. But, the circulation of immune
checkpoint proteins from tumor cells dysregulates the tumor resistance and supports
growth and development (Pardoll 2012). The checkpoint protein such as PD-1
always expressed as a cell surface receptor by cells (pro-B or T cells) of immune
system binds with one of the PD-L1/2 ligands. The PD-1 signaling prevents T-cell
reactions at the former effector step limiting unnecessary activation of T cells.
However, the ligands for PD-1 are present on tumor cells to evade anti-cancer
immune reactions (Urszula and Krzysztof 2016). The contact of PD-1 receptor
with own ligands on tumor cells provokes chronic T-cells inhibition, where T-cells
lose their immune potential which leads to a drop in the immune response to cancer
cells.
CTLA-4 is another checkpoint molecule expressed by only activated T cells
which interacts with APC associated B7-1 and B7-2 ligands with higher affinity
(Buchbinder and Desai 2016). CTLA-4 blocks T cell activation and performs an
essential part in the initial phases of an immune reactions. Instead, CTLA-4 consti-
tutively expressed on tumor cells to prevent T cell proliferation and effective
functioning (Upadhyay et al. 2015; Contardi et al. 2005). GITR is a checkpoint
protein highly displayed by T regulatory cells and interacts with GITRL ligand
present on DC (Knee et al. 2016). At the inflammatory site, the binding GITR from
T-reg cells with GITRL of DC blocks the repressed action of T-reg cells with
subsequent enrichment of T-effector cell persistence. GITRL downregulates expres-
sion of the immune-stimulatory molecules (CD40 and CD54), influences the expres-
sion of TGF β, an immunosuppressive factor released from cancer cell, and blocks
the expression of EpCAM (Urszula and Krzysztof 2016). LAG-3 is another immune
checkpoint inhibitor protein involved in the immune escape mechanism of tumor
cells (Long et al. 2018). LAG-3 is present on immune cells (T/B cells, NK cells, and
pDC) and can bind to MHC class II. The LAG-3/MHC-II complex can work as
bidirectional preventive mechanism shared by both immune and cancer cells
(Hemon et al. 2011). In a similar fashion to CTLA-4 and PD-1 functioning,
LAG-3 inhibits immune cell activation, proliferation, and homeostasis. Basic knowl-
edge of the immune evasion procedures employed by checkpoint molecules may
direct to better prognostic markers and escort the advancement of targeted medica-
tions that are both reliable and more powerful than current standards of care.
8.8 Antigen Identification and Cancer Immunotherapy
Immunotherapy is a procedure that boosts or engineers the immune system as a

tumor-killing machine. Controlling the immune system to abolish tumor cells is
growing as the most efficient method to treat carcinoma in patients. To earmark and
kill tumors our immune system must be proficient in noticing the cancer antigen as
“foreign intruder” (Fuchs et al. 2016). Both innate and acquired immune pathways
play a central part in surveillance, verification, and removal of cancer tissues (Fuchs
et al. 2016). But, when tumor continues to grow, our immune network fails in
eradicating malignant cells as the immune network is compromised. Identification
and characterization of tumor antigens provide great help in developing vaccines
against tumors to stop. When tumor growth continues, immune system fails to
recognize most of the antigens present on tumor cells and tumor microenvironment,
hence tumor continues to grow exponentially and even spreads to nearby tissues.
The antigens corresponding to tumor are divided into two individual groups based
on their antigen specificity: TSA (tumor-specific antigens) and TAA (tumor-
associated antigens) (Vigneron 2015). Tumor-specific antigens exhibit high tumor
specificity and only expressed on tumor cells, including (1) viral antigens, (2) anti-
gens encoded by mutated genes (neoantigen) from tumors, (3) cancer-germline
genes (Vigneron 2015). TAAs exhibit low tumor specificity and present on few
healthy tissues as differentiated antigens and some derived from overexpression of
tumor genes. Figure 8.2 provides some of the familiar tumor antigen types and
examples.
In parallel to understand suppressed tumor immunity, significant attempts have
been performed in the past 25 years in cancer antigen detection with aims to generate
cancer vaccines. Without the knowledge of tumor antigens, it seems dark to develop
immunotherapeutics for cancers. Identification of different molecular mechanisms
contributing to the formation of various T cell epitopes on tumors aided in discov-
ering novel tumor-reactive T cell epitopes in the past. Among the many mechanisms
contributing synthesis of diverse T cell epitopes, few important possibilities were
presented here, such as alternative ORFs, somatic mutations, from intronic
sequences and protein splicing (Fuchs et al. 2016). The discovery of tumor antigens
(T cell specific antigens) involves the use of tumor-responsive T cells from humans
with cancer or cancer cell models. Target cells including PBMCs or TILs get
transfected with tumor cDNA library. Later by applying peptide recognition and
truncation CTL epitopes are defined. This strategy is most direct and mainly used to
identify antigens as well as epitopes specific to T cells. Tumor-specific T-cell
antigens defined through current immunological procedures include tyrosinase,
MART-1, MAGE families, and gp100 (Vigneron 2015). In 1991 for the first time,
cDNA library screening with tumor-responsive HLA-res CD8+ T cells led to the
discovery of human tumor antigen (van der Bruggen et al. 1991). The overexpressed
antigens located in tumors are identified by using gene-expression profiling method
since these antigens can be distinguished by CTL to induce an immune reaction.
Tumors that are high in the expression of the catalytic subunit of telomerase can
Fig. 8.2 Varieties of tumor antigens expressed by tumor cells. Tumor antigens are classified into
two groups called Tumor specific antigens (TSA) and Tumor Associated Antigen (TAA). Viral
antigens—Human papillomavirus type 16—Cluster of Differentiation 4 (HPV-16-CD4), Human
papillomavirus type 16—Cluster of Differentiation 8 (HPV-16-CD8), Epstein–Barr virus (EBV),
hepatitis B virus (HBV) and hepatitis C virus (HCV), Cancer-Germline Genes - Melanoma Antigen
Gene (MAGE A/B/C), B melanoma antigen (BAGE), GAGE (G antigen), L Antigen (LAGE) and
synovial sarcomas X (SSX) and Neoantigens—Tumor protein (p53), Cyclin-dependent kinase 4
(CDK4), Kirsten rat sarcoma (KRAS), breakpoint cluster region—Abelson murine leukemia
(BCR-ABL), Caspase 8 (CASP8), Cell division cycle protein 27 (CDC27), Catenin Beta
1 (CTNNB1), ETS Variant 6—Acute Myeloid Leukemia 1 (ETV6-AML1), Neuroblastoma RAS
Viral (NRAS), α actinin-4 and β-catenin) belong to tumor specific antigens. Differentiation anti-
gens—Carcinoembryonic antigen (CEA), Ganglioside (GD3), Monosialoganglioside (GM2),
Premelanosome protein (pmel17), Tyrosinase related protein 1 (TRP1), Melan-A, Prostatic acid
phosphatase (PAP), Prostate-specific antigen (PSA), Tyrosinase related protein 2 (TRP2) and
Tyrosinase and Overexpressed antigens Renal Cell Carcinoma Antigen (RAGE-1), B cell differ-
entiation antigen (CD20), Epidermal growth factor receptor (EGFR), Erb-B2 Receptor Tyrosine
Kinase 2 (ERBB2), Tumor protein (p53), preferentially expressed antigen in melanoma (PRAME),
survivin and Wilms Tumor antigen WT1), and Oncofetal antigens Alpha-fetoprotein (AFP), cancer
antigen 125 (CA125), Cancer antigen 19-9 (CA19-9), Carcinoembryonic antigen (CEA) and
Prostate-specific antigen (PSA) belong to tumor-associated antigens
mediate cytotoxic T lymphocytes to provoke an immune reaction (Vonderheide et al.

1999). Serological screening of recombinant cDNA expression libraries SEREX is
applied to identify T cell targets via B cell responses in patients (Sahin et al. 1995;
Fuchs et al. 2016).
8.9 Types of Immunotherapeutic Vaccines
A therapeutic vaccine is generally used by clinicians once the detection of GI cancer.

However, therapeutic vaccines have manifested to be potent in case of averting the
occurrence of cancers by subduing infections in the human body that could lead to
GI cancers. Therapeutic vaccines have been effective in preventing tumor growth in
gastrointestinal areas (Spira et al. 2016). There are many types of therapeutic
vaccines that could prevent the growth of cancers in gastrointestinal areas. Some
major types of therapeutic vaccines are explained.
Autologous vaccines that are used in the treatment of GI cancers are personalized
vaccination developed from the cells of an individual. The autologous vaccine is
developed by removing few cells from the GI tumor. These cells are then treated in a
certain way that would make the cells a target for the human immune system.
Engineered cells are then injected into the human body. The immune system then
recognizes the injected cells and eventually disables those. In a similar way, the now
activated immune cells disable the cancer cells in the body. HLA and blood group
antigens are examples of autologous vaccines that were developed using this
method.
Allogeneic vaccines are also used in the treatment of GI cancers. The word “allo”
is a synonym for “other.” Allogeneic vaccines for treating GI cancers are developed
from cancer cells that not derived from the body of the patient but are generated in
the lab. These kinds of vaccines have already been tested for preventing growth of
pancreatic and colorectal tumors. Allogeneic vaccines have high demand because
these are cheaper and also the production cost is low. However, these vaccines are
not enough effective compared to other therapeutic vaccinations. The vaccine is yet
to be licensed. However, at an early stage of GI cancers, this vaccine could be
effective to some extent. Human blood group and EGFR antigens is an example of
allogenic vaccine.
Peptide vaccines are generally protein parts. These parts could also be smaller
components of proteins called peptides. The peptides and protein parts are delivered
into the human body as vaccine generally paired with viruses or molecules that could
stimulate the immune system. These vaccines are still at trial but some clinics are
using these vaccines, for example epitopes.
DNA vaccines are another therapeutic approach to treat GI cancers and designed
using tumor antigen DNA via dendrite cells to provoke the immune system against
an existing GI tumor. The patient subjected to GI cancer is vaccinated with DNA
rings. These rings of DNA are known as plasmids. The plasmids develop antigens
for preventing further growth of GI tumors. Cancer vaccines for treating GI are
required to be cost-effective so that patients could afford these vaccines. Doctors are
required to develop vaccines that could prevent the occurrence of cancers. HPV and
HIV 1, BRAF, and stemness are examples of DNA vaccines.
8.10 Molecular Targets of Immunotherapeutic
Oncologists are marching forward to consider immunotherapies against multiple GI

cancers pardoning the presently accessible plans. It was notable that treatments like
chemotherapy, surgery, anti-angiogenic therapy, and radiation therapies were aiding
in the treatment of GI cancer; however, recent reports on immunotherapies and their
efficacies against GI cancers attract a lot of interest among oncologists and clini-
cians. New procedures involving immunotherapies such as checkpoint inhibitors,
adoptive cell therapies, protein/peptide, cytokines, whole cell/dendritic cell vac-
cines, and their efficiencies were well documented through many clinical studies
against GI cancers. Figure 8.3 provides a broad understanding on different kinds of
molecular targets and means of immunotherapy applied on a range of gastrointesti-
nal cancer.
8.11 Checkpoint Inhibitors
Immunosurveillance crucially engages in tumor growth and development. Similar to

cell cycle arrest pathways, cancer cells bear the adaptability to activate different
pathways specifically immune checkpoints as a way to suppress the anti-tumor immune
function of tumor cells. Therapeutic monoclonal Ab’s that target immune checkpoints
hold a tremendous potential to treat GI cancer and hold a breakthrough in the realm of
immuno-oncology. Immune checkpoint blockers such as PD-1/PD-L1 and CTLA-4
revealed assuring therapeutic upshots in the recent past, and some were recommended
for specific tumor treatments, meanwhile other checkpoint protein targets undergoing
clinical investigations (Darvin et al. 2018). In 2013, FDA approved the use of
ipilimumab (CTLA-4) as an immunotherapeutic agent against metastatic melanoma,
colorectal cancer, and renal cell cancers. Following success with ipilimumab approval,
a study reported beneficial outcomes in 300 cancer patients with anti-PD1. Later
nivolumab, pembrolizumab and atezolizumab approved to treat colon cance, liver
cancer, and stomach cancer (Lipson et al. 2013; Topalian et al. 2012). Other potential
PD-1/PD-L1 drugs currently employed to treat bladder cancer include pembrolizumab,
nivolumab, cemiplimab, atezolizumab, avelumab, and durvalumab.
8.12 Adoptive Cell Therapies (ACT)
In this approach immune cells mostly NK cells or CD8+ T cells from either tumor or
guarding lymph node are sequestered, increased in number under ex vivo conditions,
and finally infused into the host using fludarabine/cyclophosphamide. Early in 1988,
the first successful application of adaptive cell therapy via tumor-infiltrating lym-
phocytes (TIL’s) on solid tumors was conducted by Rosenberg and his colleagues.
The use of node-derived autologous CD4+ Th1 cells against colorectal cancer
128
B. Sabeerabi et al.
Fig. 8.3 Modes of Immunotherapy on broad range of GI cancers. A schematic representation of classification of general therapeutics against GI cancers. The
modern-day immunotherapy in GI cancers including small molecules, monoclonal antibodies, vaccines, checkpoint inhibitors, and adaptive cell transfer
patients resulted in tumor regression and long-term survival (Karlsson et al. 2010). In
2016, a study reported that TILs derived from colon cancer could induce an immune
response in tumor-specific driver mutation (KRAS-G12D) bearing tumors implying
beneficial outcomes of using adoptive cell therapies involving T cells (Tran et al.
2016). Administrating TILs in humans with metastatic melanoma elicited tumor
suppression (Phan and Rosenberg 2013). Activated CTLs such as mucin 1 (MUC1-
CTLs) were shown to be effective against pancreatic cancers and liver metastasis in
patients who underwent radical pancreatectomy (Matsui et al. 2017). Many inde-
pendent studies got assuring results in a variety of solid tumors using adaptive cell
transfer technology on nasopharyngeal cancer (EBV-specific CTL) (Secondino et al.
2012), hepatocellular carcinoma (Interleukin-2 and anti-CD3) (Takayama et al.
2000), renal cell carcinoma (RCC) anti-carboxy-anhydrase-IX (CAIX) (Lamers
et al. 2013) and gastric cancer (T cell specific anti-HER-2/neu peptide) (Kono
et al. 2002). So far adoptive cell immunotherapy is proven to be safe, viable in
lowering GI cancers. The adoptive cell immunotherapy currently growing as one of
the most favorable master plan in cancer treatment, and several clinical studies are
happening worldwide.
8.13 Dendritic-Cell Vaccines
The biological nature and active participation in T-cell activation of DC’s have been
the great importance in developing DC-based vaccines for cancer immunotherapy,
hence opening new paradigms in the advancement of practicable clinical protocols
(Guo et al. 2013). DCs are functional as APC when challenged with antigens DCs
can initiate and sustain immune responses (Banchereau and Steinman 1998). DCs
role as antigen presenting cells can trigger the participation of NK and/or NKT cells
in both cellular and humoral immune responses (Osada et al. 2006). Both adaptive
and innate immune pathways are well attended by DCs thus making a substantiating
place in anti-cancer immunotherapy for cancer patients (Sabado and Bhardwaj
2015). DCs can be pulsed with peptides, whole proteins, DNA constructs, tumor
lysates, or tumor cells in the process of generating DCs vaccines (Shang et al. 2017).
A study treated 16 melanoma patients with DC pulsed with a cocktail of tumor
lysates using IL-4/GM-CSF found beneficial results in five patients since then this
approach has been applied worldwide as standard procedure (Nestle et al. 1998). A
phase I clinical investigation conducted on HCV-based HCC subjects using DCs
pulsed with HSP70-mRNA reported that HSP70-DCs based treatment is safe and
viable as HCV-based HCC express high levels of HSP70 and linked with loss of
HLA-1 and improved tumor differentiation (Maeda et al. 2015). In trail outcomes, at
grade III/IV zero side effects were seen; complete response (CR) with an absence of
relapse was accomplished in a pair of patients, indicating HSP70-DC adapted
therapy efficiency against HCC. Another study employed DC pulsed with mucin1-
mRNA/MUC1-CTL complexes in combination with chemotherapeutic drug
gemcitabine tested on 42 subjects with cyclical pancreatic cancer (Shindo et al.
2014). The outcomes of the study included 13.9 months of median survival, 51.1%
rate of 1-year survival, and 61.9% disease control with no side effects contributing
efficient immunotherapy on pancreatic cancer. Another clinical investigation
conducted on progressive pancreatic carcinoma patients treating with DC vaccine
plus LAK cells in combination with gemcitabine nearly on 49 subjects reported
complete/partial remission, stabilized diseases in 10 with overall survival time
increased following no side effects. This study implied that immunotherapy with
DC vaccines in combination with chemotherapy provides an effective strategy to
treat pancreatic cancer (Kimura et al. 2012). Phase II study in HCC patients with
DCs pulsed with tumor lysate demonstrated that DC vaccination is well tolerated,
safe, and promising with anti-tumor ability (Palmer et al. 2009). All the above-
discussed results indicate the growing importance of DCs as a winning immuno-
therapeutic strategy to treat GI cancers.
8.14 Peptide Vaccines
Over the decade maneuverings of cancer-vaccination claimed enormous interest and

many reports are coming out delineating importance of peptide vaccines in clinical
practice to treat cancer. In 1995, the first-rate clinical analysis of the MAGE-1 based
vaccine took place. The initial creations of peptide vaccines did constitute of one or
more HLA-I based antigen types. The current varieties of peptides based vaccines
fall under six different categories such as (1) long multivalent peptides; (2) multiple
peptide vaccines (CTL-helper epitope); (3) blend of peptide vaccines; (4) peptide-
pulsed DC vaccines; (5) hybrid peptide vaccines; (6) personalized peptide vaccines
(Yamada et al. 2013).
The anti-cancer benefits of glypican-3 (GPC3) peptide vaccine against HCC as
adjuvant immunotherapy reported through phase II studies. 35 subjects who
underwent surgery and vaccination did not show any variations in recurrence rate
compared with subjects who underwent surgery alone; however, there was a lower
recurrence rate in GPC3 vaccinated subjects who developed GPC3-positive tumors
improved for 1-year in a subgroup analysis (Sawada et al. 2016). Clinical treatment
with GPC3 derived vaccine on a single patient possessing HCC revealed tumor lysis
and durable effects, nonetheless, the subjects died from circulatory failure (Sawada
et al. 2013). Another phase I trial study proclaimed safety, anti-tumor efficacy,
improved overall survival and clinical responses of GPC-3 peptide vaccination
against HCC in humans (Sawada et al. 2012).
In the phase II clinical study, pancreatic cancer patients treated with cocktail
peptide vaccines called OCV-C01 derived from kinesin family member 20A
(KIF20A), VEGFR 1/2 along with gemcitabine after going through surgery. In
this setting, peptide cocktail vaccines combined with chemo drug were endurable
with 15.8 months of median disease-free survival (DFS) (Miyazawa et al. 2017). In
another phase II study, VEGF receptors and tumor antigens used to derive five HLA-
A*2402-limited peptides for treating advanced colorectal cancer subjected in com-
bination with chemotherapy drug oxaliplatin. In this study, the expected endpoints
remain the same between treatment and untreated groups, yet a continued response
with <3.0 neutrophil/lymphocyte ratio was observed (Hazama et al. 2014a).

Humans with advanced CRC were treated with multiple peptides (HLA-A*2402-
restricted peptides, VEGFR1/2, RNF43, oncoantigens, KOC1 and TOMM34) to
evaluate the immunological outcomes following endpoint results in alleviating
cancer symptoms in phase I clinical study. The treatment was safe, well-tolerated
and the presence of peptide-specific CTL reported. The clinical significance included
that one subject lived for 10 years without cancer relapse; in six subjects the cancer
was stable for 4–7 months and 13.5 months of median overall survival time (MST)
recorded (Hazama et al. 2014b).
Currently available immune-based peptide vaccinations for CRC gave a response
rate (0.9%) and objective response rate (2.6%) that is regarded as insignificant by
National Health Insurance to provide financial support (Nagorsen and Thiel 2006).
Although TAA based vaccines proved less efficient on CRC, a clinical trial using
monoclonal antibody against EGFR called cetuximab has been approved by FDA to
treat CRC (Bou-Assaly and Mukherji 2010). Also, most recently, studies reported
that cetuximab combination with chemo treatment improves the infiltration of the
immune cell population into metastatic liver sites in CRC patients (Inoue et al.
2017). Two independent clinical investigations revealed the importance of immu-
notherapy to treat melanoma. Ott et al. showed that the use of the neoantigen
vaccines against melanoma patients as a promising therapeutic strategy since the
neoantigen vaccination provided safety, feasibility, and immunogenicity (The Can-
cer Genome Atlas Research Network 2017). Moreover, RNA-based poly-neo-epi-
tope vaccination approach against melanoma invoked T-cell responses, reduced
metastasis, and sustained progression-free survival (PFS) in patients (Sahin et al.
2017). Noteworthy to mention that applying abovementioned two strategies can
endure a purpose in the future to treat GI cancers.
8.15 Therapeutic Vaccines and GI Cancers
8.15.1 Esophageal and Gastric Cancer Vaccines
Though multiple treatments like radiotherapy, surgery, and chemotherapy have been
performed to treat esophageal squamous cell carcinoma, the five-year global survival
is quite weak at 30–40%, suggesting an immediate need for improvised treatments.
ESCC exhibits high somatic mutation rates making it amenable to treat with
therapeutic vaccines (Mimura et al. 2018). Previously over expression of PD-L1/2
has reported in 41 esophageal cancer resection specimens, thus PD-L1/2 becomes a
fundamental prediction agent in ESCC patients (Ohigashi et al. 2005; Loos et al.
2011; Zheng et al. 2014). A monoclonal (Ig)G4 antibody commonly referred to as
Nivolumab is used against 65 Japanese ESCC patients where the antibody provided
safety and promising immune responses involving PD-1 enervation (El-Khoueiry
et al. 2017). Limited data support the employment of immunotherapy over ESCC
because ESCC now is separated from esophageal adenocarcinoma (The Cancer
Genome Atlas Research Network 2017). A clinical investigation (KEYNOTE-028)

enrolled mixed patients with either ESCC (74%) or AGEJ (22%) positive for PD-1 to
test pembrolizumab. The study achieved a viable toxicity and grade 3 treatment-
linked unfavorable episodes (Doi et al. 2016). Table 8.1 provides clinical investiga-
tions undertaken to evaluate different types of immunotherapies on EC.
A clinical study (KEYNOTE-012) with 36 GEJ or advanced stomach cancer
patients evaluated and reported the beneficial anti-tumor nature of pembrolizumab
(anti-PD-1) for the first time. The ORR was 22%, TRAEs of grade 3 or 4 recorded in
13% (Muro et al. 2016). Currently, phase II and III clinical investigations are
ongoing with anti-PD-1 treatments in ESCC. Primary outcomes of multi-cohort
study KEYNOTE-059 conducted on advanced gastric cancer subjects (259) reported
the use of pembrolizumab and chemotherapy as the first line of treatment. Upon data
cut-off in 67% of subjects grade 3/4 TRAEs were recorded, none of which implied to
pembrolizumab (Fuchs et al. 2016). A phase II study recently reported the positive
outcomes of pembrolizumab on previously treated advanced gastric tumros. Endur-
ing counter was witnessed in subjects with either negative or positive for PD-L1
(Fuchs et al. 2018). Based on the aforementioned data FDA recommended
pembrolizumab over PD-L1-positive gastric/GEJ adenocarcinomas in September
2017 (Mehta et al. 2018).
KEYNOTE-180, phase II trial studied the efficacy and safety of pembrolizumab
monotherapy on ESCC, advanced/metastatic adenocarcinoma patients and
published that pembrolizumab granted long-lasting anti-tumor actions with manage-
able safety of esophageal cancer patients and awaits data from an ongoing phase III
trial (Shah et al. 2018). Another phase III trial, KEYNOTE-061 evaluated
chemotherapy vs. pembrolizumab on GEJ adenocarcinomas and metastatic gastric
tumors positive with PD-L1 (Ohtsu et al. 2016). The study failed to meet OS, the
primary endpoint, but maintained pembrolizumab safety profile (Shitara et al. 2018).
To estimate the potency of pembrolizumab as chosen medication in PD-L1 positive/
HER-2neu-negative advanced metastatic GEJ adenocarcinomas, KEYNOTE-062
phase III combination studies did not increase OS or PFS when compared with
chemotherapy alone. However, in a branch assessment pembrolizumab
monotherapy met the primary outcomes of OS in the whole intent-to-treat (ITT)
patients whose neoplasms display PD-L1 compared with chemotherapy. Moreover,
the safety characterization of the pembrolizumab was uniform with what has been
earlier seen in gastric cancer leaving the trial KEYNOTE-062 with ambiguous
results (https://clinicaltrials.gov/ct2/show/NCT02494583) (Tabernero et al. 2016).
KEYNOTE-181, phase III trial aimed to find out the pembrolizumab ability com-
pared to chemotherapy in adenocarcinoma, ESCC, or GEJ. The study concluded that
anti-PD-L1 drug significantly enhanced OS related to chemo suggesting that PD-L1
as second-line therapy for advanced ESCC (Kojima et al. 2019). The ramucirumab
(anti-VEGFR2 antibody) as mono or in combination with chemotherapy is shown to
increase survival benefit in GEC patients in phase III trial RAINBOW (Wilke et al.
2014). Additionally, preliminary beneficial outcomes of the phase I study (JVDF)
using anti-PD-1 and anti-VEGFR2 on advanced GEJ and gastric tumors reported
Table 8.1 Immunotherapies under clinical investigation against esophageal cancers

Phase
Trial # Immunotherapy Status
I II III
NCT02490735 CIK A-NR
NCT00004178 Autologous lymphocytes CT
NCT01143545 Allogeneic Tumor Cell Vaccine + Celecoxib + CT
Cyclophosphamide
NCT01003808 IMF-001 CT
NCT00561275 Peptide cocktail (LY6K, VEGFR1 & VEGFR2) CT
NCT00632333 Multiple peptides (URLC10, TTK, KOC1, VEGFR1 & A-NR
VEGFR2) + Cisplatin + Fluorouraci
NCT00753844 URLC10 peptide CT
NCT00020787 G17DT Immunogen + Cisplatin + Fluorouracil CT
NCT02743494 Nivolumab RT
NCT02564263 Pembrolizumab + Paclitaxel + Docetaxel + Irinotecan A-NR
NCT02642809 Pembrolizumab + Radiation RT
NCT02569242 Nivolumab + Docetaxel/Paclitaxel A-NR
NCT02971956 Pembrolizumab RT
NCT02318901 Pembrolizumab + Trastuzumab + Ado-trastuzumab UN
emtansine + Cetuximab
NCT02735239 Durvalumab + Tremelimumab + Oxaliplatin + RT
Capecitabine + Radiation + Paclitaxel + Carboplatin
NCT02460224 IMP701 + PDR001 A-NR
NCT02834013 Ipilimumab + Nivolumab RT
NCT00995358 Multiple Peptides (TTK, LY6K & IMP-3) A-NR
NCT00682227 Multiple Peptides (TTK, LY6K & IMP-3) A-NR
NCT00669292 Multiple Peptides (URLC10-177, TTK-567& CpG-7909) A-NR
NCT02520453 Durvalumab A-NR
NCT03087864 Atezolizumab + Carboplatin + Paclitaxel + Radiation RT
NCT01375842 Atezolizumab CT
NCT02830594 Pembrolizumab + Radiation RT
NCT02559687 Pembrolizumab A-NR
NCT02946671 Mogamulizumab + Nivolumab RT
NCT02476123 Mogamulizumab + Nivolumab A-NR
NCT03044613 Nivolumab + Relatlimab + Carboplatin + Paclitaxel RT
+Radiation
NCT02872116 Nivolumab + Ipilimumab+ Oxaliplatin+ Capecitabine+ A-NR
Leucovorin + Fluorouracil
NCT02544737 Apatinib A-NR
NCT02096614 TBI-1201+ Cyclophosphamide + Fludarabine RT
NCT02366546 TBI-1301+ Cyclophosphamide + Fludarabine A-NR
NCT02457650 Cyclophosphamide + Fludarabine+ Anti-NY ESO-1 TCR- RT
transduced T cells
RT recruiting, A-NR active not recruiting, UN unknown, TER terminated, CT completed, NYT not
yet recruiting, CIK cytokine-induced killer, LY6K lymphocyte antigen 6 complex locus K, VEGFR1
vascular endothelial growth factor receptor 1, VEGFR2 vascular endothelial growth factor receptor
2, URLC10 up-regulated lung cancer 10, TTK TTK protein kinase, KOC1 IGF II mRNA binding
protein 3, IMP-3 insulin-like growth factor II mRNA-binding protein 3
Note: the sum of immunotherapy molecules listed under any trial do not represent the combinations
designed by the researchers to evaluate potency against mentioned cancer variety
(Chau et al. 2018). Table 8.2 provides clinical investigations undertaken to evaluate
different types of immunotherapies on GC.
Another antibody targeting PD-L1 called avelumab, safety, and efficacy on
progressive GEJC was evaluated in JAVELIN Solid Tumor trial phase 1b trial
(Chung et al. 2016). The study stands out as the first one to report the benefits of
avelumab antibody as a switch-maintenance therapeutic agent in advanced GC/
GEJC. GC/GEJC cancer subjects who encountered avelumab monotherapy gained
help in recovering from cancer symptoms in comparison with chemotherapy
(NCT02625623) (Bang et al. 2018). After the satisfactory safety outcomes from
avelumab, a phase III study (NCT02625610) on humans with advanced GC/GEJC is
currently happening with subject recruitment (Moehler et al. 2018).
Recently in 2017, a phase III trial used nivolumab in subjects with advanced
(GEC/gastric) tumors intolerance to chemo drugs was reported. Nivolumab therapy
gave a statistically meaningful OS, and ORR was 31% maximum (Kang et al. 2017).
In a separate clinical setting where recurrent gastric cancer subjects treated with
either nivolumab or a combination of nivolumab+chemotherapy, the nivolumab
seems tolerated with grade 3-4 AEs (ATTRACTION-04/ONO-4538-37). A 68.4%
ORR with ten patients achieved complete response (CR) (Diaz et al. 2017). Though
numerous trials are proceeding with new checkpoint inhibitors (atezolizumab and
durvalumab), some studies with nivolumab (anti-CTLA-4) or nivolumab together
with ipilimumab (anti-PD-1) presented few assuring effects. Monotherapy with
ipilimumab on metastatic GC/GEJ cancers has been validated through phase II
trial (NCT01585987) (Moehler et al. 2016). Though this investigation did not obtain
its first endpoint, the safety profile of ipilimumab in GC/GEJC installed a framework
for possible future use in combination therapy (Bang et al. 2017). Both nivolumab
and nivolumab+ipilimumab exhibited clinically essential anti-tumor activity, long-
lasting responses, boosting long-term OS, and with moderate side effects in subjects
with ECC underwent chemotherapy-refractory in CheckMate-032 Study. Currently,
phase III clinical study evaluating both mono nivolumab and ipilimumab
+nivolumab as the first-line treatment for ECC is happening (Janjigian et al.
2018). Though EGC continues as a forbidding adversary for patients and surgeons,
advancements in resection methods, targeted systemic medicines, and more refined
radiation therapy procedures will drive us closer to winning.
8.15.2 Colorectal Cancer
On a global scale, the third most frequently diagnosed cancer type is CRC and the
second most leading cause of cancer deaths. This global oppress going to increase by
2.2 million new cases and deaths by 1.1 million in 2030. Notwithstanding the
striking progress made at quality therapies, the 5-year survival rate for diagnosed
metastatic CRC stays remarkably low with an approximation of 12% (Siegel et al.
2015). The current progress made in terms of therapeutic vaccine development
against various cancer types instills hope for the betterment in treating cancer. The
Table 8.2 Immunotherapies under clinical investigation against gastric cancers

Phase
I II III
NCT02658214 Oxaliplatin + 5FU + Leucovorin + Durvalumab + Tremelimumab A-NR
NCT02678182 Capecitabine + MEDI4736 + Trastuzumab + Rucaparib RT
NCT02572687 Ramucirumab + MEDI4736 A-NR
NCT02734004 Olaparib + MEDI4736 + Bevacizumab RT
NCT02554812 Avelumab + Utomilumab + PF-04518600 + PD 0360324 RT
NCT02625610 Avelumab + Oxaliplatin + 5-Fluorouracil + Leucovorin + Capecitabine A-NR
NCT02625623 Avelumab + Irinotecan + Paclitaxel A-NR

5-FU + Leucovorin + Oxaliplatin + Atezolizumab + Cobimetinib+ Ramucirumab +
NCT03281369 Paclitaxel + PEGPH20 + BL-8040 + Linagliptin RT
NCT03126110 INCAGN01876 + Nivolumab + Ipilimumab RT
NCT03409848 Nivolumab + Ipilimumab RT
NCT02999295 Ramucirumab + Nivolumab RT
NCT02935634 Nivolumab + Ipilimumab + Relatlimab + BMS-986205 RT
NCT02872116 Nivolumab + Ipilimumab + Oxaliplatin + Capecitabine + Leucovorin + Fluorouracil A-NR
NCT02746796 ONO-4538 + Oxaliplatin + Tegafur- Gimeracil-Oteracil potassium + Capecitabine A-NR
NCT02267343 ONO-4538 A-NR
NCT02370498 Pembroliziumab A-NR
NCT02494583 Pembrolizumab + Cisplatin + 5-FU + Capecitabine A-NR
NCT03196232 Epacadostat + Pembrolizumab RT
NCT02954536 Pembrolizumab + Trastuzumab + Capecitabine + Cisplatin + Oxaliplatin + 5-FU RT
NCT03342937 Oxaliplatin + Capecitabine + Pembrolizumab RT
NCT02178722 MK-3475 + INCB024360 A-NR
NCT03095781 XL888 + Pembrolizumab RT
NCT02689284 Margetuximab + Pembrolizumab A-NR
NCT02901301 Pembrolizumab + Trastuzumab + Capecitabine + Cisplatin RT
NCT02494583 Pembrolizumab+ Cisplatin + 5-FU + Capecitabine A-NR
NCT02625610 Avelumab + Oxaliplatin + 5-FU + Leucovori + Capecitabine A-NR
NCT02625623 Avelumab + Irinotecan+ Paclitaxel A-NR
NCT02689284 Margetuximab + Pembrolizumab A-NR
NCT02734004 Olaparib + MEDI4736 + Bevacizumab RT
NCT02864381 Andecaliximab + Nivolumab A-NR
NCT02872116 Nivolumab + Ipilimumab + Oxaliplatin + Capecitabine+ Leucovorin + Fluorouracil A-NR
NCT02935634 Nivolumab + Ipilimumab + Relatlimab + BMS-986205 RT
NCT03019588 Pembrolizumab+ Paclitaxel A-NR
NCT03382600 Pembrolizumab + Oxaliplatin + TS-1 + Cisplatin RT
RT recruiting, A-NR active not recruiting, UN Unknown, TER terminated, CT completed, NYT not
yet recruiting, 5FU fluorouracil, PEGPH20 pegvorhyaluronidase alfa, TS-1 titanium silicate
novel medications were appreciated quickly because of their potential efficacy and
safety in treating cancer patients. In the past, it was evident that gastrointestinal
malignancies were becoming insensitive to vaccines, and the insensitivity of colo-
rectal cancers is a big concern since emerging data support the observations that
some but not all patients who may profit from these vaccines. Therapeutics with
TAS-102 (Mayer et al. 2015), ramucirumab (Goel and Sun 2015), and regorafenib
(Grothey et al. 2013) got a green signal from the FDA to treat CRC. Unfortunately,
the clinical outcomes involving these drugs remain modest. As a consequence of
this, innovative therapeutic strategies involving immunotherapy have come into the
evaluation by researchers and clinicians as anti-tumor therapeutics. Molecular
genetic instability in chromosomes (CIN) and microsatellite DNA marks the little
variation that divided CRC into various subgroups. Following instruction from The
Cancer Genome Atlas Project, CRC splits into two: (i) tumors with microsatellite
instability (MSI) either ultra-mismatch repair (pMMR) or poor mismatch repair
(dMMR), (ii) tumors having high-frequency in DNA copy number mutation are
termed microsatellite stable (MSS) and ~84% are non-hypermutated (Muller et al.
2016). Another pedagogy comes from the Consensus Molecular Subtypes (CMS)
Consortium investigating CRC pattern in various reports detailed in four groups:
(1) CMS1, (2) CMS2, (3) CMS3, and (4) CMS4 (Muller et al. 2016).
In the recent past, many clinical investigations were conducted based on the
above stated CRC classification to find suitable therapeutics to these tumor subtypes
(Le et al. 2015). An immune checkpoint inhibitor pembrolizumab was tested on
32 subjects having advanced metastatic either positive or negative dMMR
(NCT01876511). The study indicated that dMMR positive tumors stand an excellent
chance to treat with pembrolizumab (Bang et al. 2015). Predating Le et al., a clinical
study with anti-PD1 antibody treatment served only one CRC subject who had
dMMR (Brahmer et al. 2010). Next, a study evaluated the potency of anti-PD-1
against patients having advanced dMMR cancers out of 12 distinct tumor types. The
reactions were durable and supported that genome instability related to dMMR
tumors can be preventable by using immune checkpoint inhibitors (Le et al. 2017).
Soon, FDA on 23 May 2017 certified pembrolizumab to treat patients with hard to
operate, metastatic, microsatellite instability cancers such as MSI-H and dMMR
(Marcus et al. 2019). In another study, nivolumab (anti-PD-1 antibody) has been
given to metastatic CRC subjects positive for dMMR/MSI-H in CheckMate-142
(phase II study) and observed long-lasting benefits and disease control (Overman
et al. 2017; Overman et al. 2018). Based on the above prospective, nivolumab got
approval from the FDA on July 31, 2017 for the treatment for MSI-H/dMMR
metastatic CRC. Data from a cohort study on subjects with advanced MSI-H CRC
(KEYNOTE-164/NCT02460198) using pembrolizumab offered potential anti-
tumor actions with a manageable safety profile (Le et al. 2018). The gathered clinical
information recommended a further investigation to evaluate the anti-tumor benefits
of pembrolizumab (anti-PD-1) against dMMR/MSI-H mCRC (KEYNOTE-177)
(Diaz et al. 2017). A therapeutic approach to treat pMMR mCRC patients using
pembrolizumab alone or in combination with either radiotherapy or surgery
following phase II study (NCT02437071) reported ambiguous primary endpoints

(Segal et al. 2016).
Moreover, in mismatch repair (MMR) CRC monotherapy with nivolumab (anti-
PD-1) further improved when ipilimumab is added to the treatment (Overman et al.
2018) in CheckMate-142 phase II trial. An interim analysis of CheckMate-142 using
a combination approach with ipilimumab and nivolumab resulted in 55% ORR
among 119 subjects following OS at 85%. The trial CheckMate-142 had multiple
arms comparing the mono and combinational treatments majorly with nivolumab
implying that combination therapy gave more beneficial reactions compared to
monotherapy in CRC patients (Andre et al. 2018). So far combinational therapies
proved valid for CRC treatment over single factor treatments, noteworthy to mention
that use of atezolizumab (anti-PD-L1) and cobimetinib (MEK inhibitor) on 84 sub-
jects (NCT01988896) confirmed an endurable protection and improved OS com-
pared to pretreated mCRC subjects, inferring advantage of combination therapy
(Bendell et al. 2018a). A phase III trial (IMblaze370) has been conducted on
chemotherapy-refractory mCRC with atezolizumab in association with cobimetinib
vs. regorafenib recently. The outcomes explain that IMblaze370 failed to satisfy its
initial endpoint; also the combinational therapies employed fail to demonstrate
significant OS benefits, while the safety profile remains consistent with previous
studies (Bendell et al. 2018b).
In the past, carcinoembryonic antigen (CEA), which is a TAA found on the
majority of CRC tumors, has been tested in clinical tests containing DC pulsed with
HLA-A24-restricted peptide of CEA proved worthy in terms of safety and efficiency
in producing an anti-tumor response (Fong et al. 2001; Morse et al. 1999; Itoh et al.
2002). These studies remain history because of the absence of futuristic studies since
their first outcomes reported. The first line of evidence from phase I a/b (RG7802)
using mono agent (CEA CD3 TCB) and in combination with atezolizumab
suggested that agent CEA CD3 TCB could induce anti-tumor activity, such activity
is further improved in the presence of atezolizumab mCRC patients (Tabernero et al.
2017). Other studies (phase II trial) involving DC pulsed with tumor lysates evoked
immune responses but no benefits on OS and PSF (Caballero-Banos et al. 2016).
Additionally, DC pulsed with class I and class II WT1 peptides provided beneficial
endpoints in mCRC subjects and highlighted the potential nature of DC vaccination
for advanced cancer. Though the resistance proceeded for two years providing
prolonged survival, the trail failed to represent strong sample size to support immune
benefits (Shimodaira et al. 2015; Higuchi et al. 2015). A phase II study
(NCT01208194) reported that MGN1703 (TLR9 agonist) maintenance medication
has been well accepted and allowed long-lasting prolonged PFS with disease
management in a subset of victims bearing mCRC (Riera-Knorrenschild et al.
2015; Schmoll et al. 2014). These outcomes acted as groundwork to invent
IMPALA/phase III trial is currently selecting subjects to test TLR9 agonist anti-
cancer benefits on CRC subjects. In an open-label, randomized pilot study
(NCT02512172), before treating pMMR mCRC patients with pembrolizumab epi-
genetic priming was suggested to see whether inhibiting HDAC/DNMT influences
sensitivity of checkpoint blockers, since in preclinical models the idea was well
established. The results obtained from the NCT02512172 trial manifested that use of
pembrolizumab with romidepsin/5-azacitidine was judged safe and tolerable in
advanced pMMR CRC. Additional connection of pre- and post-care biopsies is
needed in defining presage of reactions (Murphy et al. 2019). In phase II study
first-line treatment regimen in CRC such as (bevacizumab + fluoropyrimidine +
atezolizumab or bevacizumab + fluoropyrimidine) failed to provide positive out-
comes. Trials opting radiation rather than chemotherapy in association with check-
point inhibitors causing tumor shrinkage effect are ongoing (NCT02291289).
Table 8.3 provides clinical investigations undertaken to evaluate different types of
immunotherapies on CRC.
8.15.3 Hepatocellular Carcinoma (HCC)
Liver cancer stands as third most reason of cancer-linked deaths globally at nearly
745,000 lives per annum. Certain viral infections like CHB, HCV, NASH, and
alcoholic cirrhosis are the most related factor causing liver cancer (Ferlay et al.
2015; Torre et al. 2015). Currently, the treatment options for preventing HCC are
short. Surgery and tissue transplantation stand best chances to treat HCC; however,
cancer relapse beats the current options for cure (Song and Wai Kit 2004). Expan-
sion of current therapeutics for high-grade HCC has delivered approval of sorafenib
freshly (Medavaram and Zhang 2018). In KEYNOTE 224 trail patients with
sorafenib, refractory HCC treated with pembrolizumab which executed efficient
and sustainable responses confirming pembrolizumab might be a choice to lean on
for treating HCC (Zhu et al. 2018). Based on the trial KEYNOTE 224 outcomes
another phase III trial is ongoing to evaluate a secondary approach on HCC.
KEYNOTE-240 phase III study assessing placebo vs. pembrolizumab effects on
sorafenib-refractory HCC humans, the trial failed to report co-primary endpoints of
PFS and OS in subjects pretreated with systemic therapy (Merk.com), yet enrollment
and continuation of the trial ongoing (NCT02702401) (Finn et al. 2017). In addition,
recent clinical investigation proposed effective treatment choices including
cabozantinib, lenvatinib, and regorafenib, symbolizing the greatness of immuno-
therapy in treating humans with liver cancer thus providing a novel paradigm in the
era of oncology (Medavaram and Zhang 2018). A phase III (CHECKMATE 459)
study currently monitoring the nivolumab vs. sorafenib effects in HCC patients who
never received any therapy (NCT02576509) (Sangro et al. 2016).
The TILs of liver cancers display PD-1, and this phenomenon establishes the
probability of testing immune-based PD-1 therapeutics (Prieto et al. 2015). In this
line of investigation, phase I and II (CheckMate 040/NCT01658878) study investi-
gated the benefits of nivolumab (anti-PD1) in patients with advanced HCC. The
study observed that nivolumab was able to provide adequate and tolerable effects in
HCC subjects (Melero et al. 2017). The outputs indicated that anti-PD1 provided
tractable safety outcomes and positive unbiased responses decoded anti-PD1, poten-
tial remedy against advanced HCC (El-Khoueiry et al. 2017; Melero et al. 2017).
Table 8.3 Immunotherapies under clinical investigation against colorectal cancer

Phase
I II III
NCT02997228 Atezolizumab + Bevacizumab + Fluorouracil + RT
Leucovorin calcium + Oxaliplatin
NCT02563002 Bevacizumab + Cetuximab + FOLFIRI + A-NR
mFOLFOX6 + Pembrolizumab
NCT02227667 MEDI4736 A-NR
NCT01885702 DC vaccination A-NR
NCT03007407 Durvalumab + Tremelimumab RT
NCT02484404 Cediranib + MEDI4736 + Olaparib RT
NCT02860546 Nivolumab + TAS-102 CT
NCT02834052 Pembrolizumab + Poly-ICLC RT
NCT03008499 High-activity Natural Killer cells RT
NCT02466906 rhGM-CSF RT
NCT02688712 Capecitabine + Fluorouracil + LY2157299 RT
NCT02077868 MGN1703 A-NR
NCT02715882 CBLB502 NT
NCT02617134 anti-MUC1 CAR-T cells RT
NCT02839954 anti-MUC1 CAR-pNK cells RT
NCT01174121 Aldesleukin + Cyclophosphamide + Fludarabine RT
+ Pembrolizumab + Young TIL
NCT03047525 CIK RT
NCT02886897 D-CIK & anti-PD-1 antibody RT
NCT02280278 Adjuvant chemotherapy + CIK RT
NCT02202928 DC-CIK A-NR
NCT01741038 AlloStim®Procedure: cryoablation NRT
NCT02380443 AlloStimProcedure: cryoablation A-NR
NCT02415699 DC-CIK + Fluorouracil + Leucovorin + A-NR
Oxaliplatin
NCT01929499 CIK A-NR
NCT02448173 OncoVAX & Surgery RT
NCT02327078 Chemotherapy + Epacadostat + Nivolumab A-NR
NCT03026140 Celecoxib + Ipilimumab + Nivolumab RT
NCT02060188 anti-LAG-3 + Cobimetinib + Daratumumab + A-NR
Ipilimumab + Nivolumab
NCT02335918 Nivolumab + Varlilumab CT
yet recruiting, DC dendritic cells, Poly-ICLC polyinosinic-polycytidylic acid, and poly-L-lysine
double-stranded RNA, rhGM-CSF recombinant human granulocyte-macrophage colony-stimulat-
ing factor, MUC1 mucin 1, CAR-T cells chimeric antigen receptor T cells, CAR-pNK cells chimeric
antigen receptor NK92 cells, CIK cytokine-induced killer, D-CIK dendritic-cytokine-induced killer,
anti-PD-1 antibody anti-programmed cell death protein 1 antibody, anti-LAG-3 anti-lymphocyte-
activation gene 3
Table 8.3 (continued)
Phase
I II III
NCT02992912 Anti-PD-L1 + Atezolizumab RT
NCT02713373 Cetuximab + Pembrolizumab RT
NCT02437071 Pembrolizumab + Radiotherapy A-NR
NCT02260440 Azacitidine + Pembrolizumab A-NR
NCT01876511 MK-3475 RT
NCT02375672 Pembrolizumab + mFOLFOX6 A-NR
NCT03258398 Avelumab + eFT508 A-NR
NCT03081494 PDR001 + Regorafenib RT
Binimetinib + Irinotecan + Leucovorin + Oxaliplatin +
NCT03374254 RT
Pembrolizumab + 5-FU
Azacitidine + Epacadostat + INCB057643 +
NCT02959437 A-NR
INCB059872 + Pembrolizumab
NCT02512172 CC-486 + Romidepsin + MK-3475 A-NR
NCT03442569 Ipilimumab + Panitumumab + Nivolumab RT
NCT03377361 Ipilimumab + Nivolumab + Trametinib RT
NCT03104439 Ipilimumab + Nivolumab+ Radiation RT
NCT03271047 Binimetinib nivolumab ipilimumab A-NR
NCT02811497 Azacitidine + Durvalumab RT
NCT03428126 Durvalumab + Trametinib RT
NCT03122509 Durvalumab tremelimumab + Radiation RT
NCT02888743 Durvalumab + Radiation + Tremelimumab A-NR
Atezolizumab + Anti-PDL1 + Cobimetinib +
NCT02788279 CT
Regorafenib
NCT02873195 Atezolizumab + Bevacizumab + Capecitabine A-NR
NCT02876224 Atezolizumab + Bevacizumab + Cobimetinib A-NR
NCT03150706 Avelumab RT
Atezolizumab + Fluorouracil + Calcium + Leucovorin
NCT02912559 RT
+ Oxaliplatin
NCT03202758 Durvalumab + FOLFOX + Tremelimumab RT
Nivolumab + Oxaliplatin + Leucovorin + Fluorouracil
NCT03414983 RT
+ Bevacizumab
Avelumab + Ad-CEA vaccine + Bevacizumab +
NCT03050814 RT
Capecitabine + Leucovorin + Oxaliplatin 5-FU
Bevacizumab + Irinotecan + Leucovorin +
NCT01274624 CT
REOLYSIN® + 5-FU
NCT03256344 Atezolizumab + Talimogene + Laherparepvec RT
NCT02777710 Durvalumab + Pexidartinib A-NR
NCT02559024 MEDI6469 A-NR
NCT02650713 Atezolizumab + RO6958688 A-NR
NCT02870920 Durvalumab + Tremelimumab A-NR
yet recruiting, Anti-PD-L1 anti-Programmed cell death protein ligand 1 antibody, 5-FU fluorouracil
Another study (NCT01008358) evaluated the potential of tremelimumab in humans

bearing HCC having HCV infection, where most of the cancer subjects had altered
liver function (Child-Pugh class B). The study reported that tremelimumab is able to
provide an anti-tumor response with safety profile following a reduced burden of

viral infection as well (Sangro et al. 2013). Therapy with tremelimumab either in
combination with chemo ablation or radiofrequency ablation (NCT01853618) holds
the ability to increase CD18 lymphocyte infiltration in sensitive tumors showing
median OS of ~1 year (Duffy et al. 2017). Currently, a phase II study
(NCT02061761) figuring out the anti-cancer benefits of mono or combination
therapy of BMS-986016 and nivolumab in relapsed liver tumor patients (Andrews
et al. 2017). A phase II dose-determination trial, Pexa-Vec intramural injection into
patients with advanced HCC described tolerable safety and a notable increment in
OS in the high-dose group (Breitbach et al. 2015; Heo et al. 2013). Following the
previous outcomes, a phase III clinical research aimed at delineating tolerability and
efficacy monotherapy with sorafenib or combination of Pexa-Vec + sorafenib is
currently on the evaluation on advanced HCC (PHOCUS, NCT02562755) (Abou-
Alfa et al. 2016). An oral therapeutic vaccine named Hepko-V5 undergoing a
clinical examination to produce beneficial effects on advanced HCC at the moment
(NCT02232490- phase III) (Tarakanovskaya et al. 2015). Table 8.4 provides clinical
investigations undertaken to evaluate different types of immunotherapies on HCC.
8.15.4 Pancreatic Cancer
Pancreatic ductal adenocarcinoma (PDAC) has the potential to grow desmoplasia

around the tumor. These PDAC tumors are resistant to immune reactions, cancer
medication, and promote melanoma growth rapidly (Neesse et al. 2011). Despite the
sophisticated knowledge of the associated molecular pathways, yet no clinically
significant change in the 5-year SR (less than five years) for PC subjects. By 2030,
the projected pancreatic cancers tend to rise where PC being the second supreme
reason for cancer expiries. To avoid such future loss, nearly ~35 therapeutic agents
as solo or in grouping undergone evaluation in clinical setups on advanced PAC
subjects (Matrisian and Berlin 2016). Indeed, when PC individuals administered
with BMS-936559, a negative response was reported (Brahmer et al. 2012). More-
over, desmoplastic stroma appears to be an indispensable block in making new
therapeutics (Erkan et al. 2012). Nonetheless, currently, few pre-clinical and clinical
investigations ongoing against PC towards finding new immune therapeutic targets.
Despite the efforts, currently, there are no successful immune-based therapeutics
approved from clinical investigations against PC. Since in other cancer treatments,
the immunotherapeutic approach aiming at PC with anti-CTLA-4 or anti-PD-1/PD-
L1 seemed insignificant in clinical trials. For instance, a phase II study revealed that
ipilimumab as an inefficient therapeutic on PC (Royal et al. 2010). The failure
principally ascribed to the immunologically suppressed microenvironment grown
out of desmoplasia in PC. To achieve effective treatments for PC, researchers
acceded to evaluate immunotherapy in combination with additional therapies—the
use of both ipilimumab and gemcitabine in a dose-defining phase Ib study
(NCT01473940) gave supporting details like ipilimumab and gemcitabine is
Table 8.4 Immunotherapies under clinical investigation against liver cancers

Phase
I II III IV
Pembrolizumab + Y90 radioembolization
NCT03099564 (Device) RT
NCT02837029 Nivolumab + Radiation RT
Nivolumab + Y90 radioembolization
NCT03033446 (Device) RT
NCT03143270 Nivolumab + (deb-TACE) RT
NCT02325739 FGF401+ PDR001 A-NR
NCT02474537 INC280 CT
NCT03095781 XL888 + Pembrolizumab RT
NCT02859324 Avadomide + Nivolumab A-NR
NCT02423343 Galunisertib + Nivolumab A-NR
NCT02988440 PDR001 + Sorafenib A-NR
NCT02942329 Apatinib + SHR-1210 RT
NCT03006926 Lenvatinib + Pembrolizumab A-NR
NCT02572687 Ramucirumab + MEDI4736 A-NR
NCT03071094 Pexa Vec + Nivolumab RT
Durvalumab + Tremelimumab +
NCT02519348 Bevacizumab RT
Nivolumab + Sorafenib + Ipilimumab +
NCT01658878 Cabozantinib A-NR
NCT02576509 Nivolumab + Sorafenib A-NR
NCT02702401 Pembrolizumab + Placebo A-NR
NCT03298451 Durvalumab + Tremelimumab + Sorafenib RT
NCT02699515 MSB0011359C A-NR
NCT02795429 PDR001+INC280 RT
NCT03099109 LY3321367 + LY3300054 RT
NCT03289533 Avelumab + Axitinib A-NR
NCT03418922 Lenvatinib + Nivolumab A-NR
NCT03170960 Cabozantinib + Atezolizumab RT
NCT03434379 Atezolizumab + Bevacizumab + Sorafenib RT
NCT01462903 TILs + IL2 UN
NCT01758679 Licartin + CIK UN
NCT01897610 Immuncell-LC CT
NCT02008929 MG4101 CT
NCT01914263 CIK UN
NCT02587689 anti-MUC1 CAR T Cells UN
NCT02959151 CAR-T cell UN
yet recruiting, deb-TACE drug eluting bead transarterial chemoembolization, FGF401 fibroblast
growth factor 401, TILs tumor infiltrating lymphocyte, IL-2 Interleukin-2, CIK cytokine-induced
killer, MUC1 mucin 1, CAR T Cells chimeric antigen receptor T cells
Note: the sum of immunotherapy molecules listed under any trial do not represent the combination’s

Phase
I II III
NCT02725996 NK cells + Curative therapy UN
NCT02856815 Immuncell-LC RT
NCT02715362 TAI-GPC3-CART cells UN
NCT02839954 anti-MUC1 CAR-pNK cells UN
NCT02854839 MG4101 UN
NCT03175679 iNKT cells + IL-2 +Tegafur RT
NCT03199807 NRT + Radiation NYT
NCT03130712 GPC3-CART cells UN
NCT03132792 Alpha Fetoprotein (AFPᶜ³³²T) RT
NCT02905188 GPC3-CART cells + Cytoxan + Fludarabine RT
NCT03441100 IMA202 RT
NCT02232490 Hepcortespenlisimut-L RT
NCT02409524 AlloVax + AlloStim + CRCL UN
NCT03203005 IMA970A + CV8102 + Cyclophosphamide RT
Tremelimumab + RFA + TACE +
NCT01853618 A-NR
Cryoablation
NCT01821482 DC + CIK UN
NCT02562755 Pexa Vec + Sorafenib RT
NCT02487017 TACE + DC-CIK UN
NCT02432963 p53MVA + Pembrolizumab UN
Durvalumab + Tremelimumab + TACE+ RFA
NCT02821754 RT
+ Cryoablation
NCT02886897 DC-CIK + anti-PD-1 antibody RT
NCT03259867 Nivolumab + Pembrolizumab + TATE RT
NCT03380130 Nivolumab A-NR
INCAGN01876 + Epacadostat +
NCT03277352 A-NR
Pembrolizumab
NCT03241173 INCAGN01949 + Nivolumab + Ipilimumab A-NR
NCT03126110 INCAGN01876 + Nivolumab + Ipilimumab RT
NCT03067493 Neo-MASCT RT
NCT03482102 Tremelimumab + Durvalumab + Radiation RT
NCT03439891 Nivolumab + Sorafenib RT
NCT03511222 Vorolanib + Nivolumab + Pembrolizumab RT
NCT03412773 BGB-A317+ Sorafenib RT
yet recruiting, NK natural killer, TAI transcatheter arterial infusion, GPC3-CAR T cells glypican 3—
chimeric antigen receptor cells, CAR T cells chimeric antigen receptor T cells, MUC1 mucin
1, CAR-pNK cells chimeric antigen receptor NK92 cells, iNKT cells Invariant natural killer T,
IL-2 interleukin-2, NRT new antigen reactive immune cells, CRCL chaperone rich cell lysate, RFA
radiofrequency ablation, TACE transarterial chemoembolization, DC dendritic cells, CIK cytokine-
induced killer, p53MVA p53 modified vaccinia ankara, anti-PD-1 programmed cell death protein
1, TATE trans-arterial tirapazamine embolization, Neo-MASCT multiple-antigen specific cell ther-
apy-I
tolerable and viable therapy vouching for further assessment (Kalyan et al. 2016).
The pancreatic tumors do not have intra-tumoral effector T-cells. Activating T-cell
mediated immune responses in pancreatic tumor cells via live attenuated and
modified Listeria monocytogenes to secrete mesothelin; a tumor-associated anti-
gen (CRS-207) account as a better therapeutic choice for PC (Dalgleish et al.
2016). A phase II study (STELLAR, NCT02243371) is analyzing with or without
nivolumab in combination with GVAX/CRS-207 on metastatic PC subjects,
those who failed earlier at pre-treatment with any chemotherapy (Dalgleish
et al. 2016). Consequently, the blend of GVAX/CRS-207 weighed on pretreated
advanced PC patients in phase IIb clinical study (ECLIPSE-NCT02004262). The
study flopped at reporting primary conclusions (Le et al. 2017). Table 8.5 pro-
vides clinical investigations undertaken to evaluate different types of immuno-
therapies on PC.
In a different clinical study, a combinational therapy involving nivolumab + DC
(monocyte antigens) vaccine in mPC revealed out of seven two PR have been
observed (Nesselhut et al. 2016). Tremelimumab and durvalumab immune check-
point inhibitors provided potency in treating multiple cancer types individually or in
a compound. In a randomized phase II trial (ALPS NCT02558894) assessing
durvalumab+tremelimumab as secondary choice to treat PC, the disease control
rate was low with 9.4%, median PSF was low (1.5 months). The development of
this combination in second-line PC canceled at the moment (O’Reilly et al. 2018). A
phase II (NCT02362048) analysis tested pembrolizumab with acalabrutinib
(Bruton’s tyrosine kinase (BTK) inhibitor) together on metastatic PC, at the data
cut-off, data suggests that the study had promising prior activity and a manageable
side effect profile, patients had stable disease with partial reactions after 3.7 months
of treatment (Overman et al. 2016). Stimulating the host immune system to treat
pancreatic cancer seems challenging since several clinical investigations failed to
achieve significant anti-cancer benefits until today. Adaptive cell therapy involving
Algenpantucel-L: made of irradiated malignant cells expressing alpha-1,3-
galactosyltransferase, yielded hopeful ends in the NCT01072981 phase II report,
where Algenpantucel-L vaccine+radiochemotherapy in an adjuvant background
with a median DSF of 1.4 years noted (Hardacre et al. 2013). IMPRESS
(NCT01072981) clinical study failed to achieve primary endpoints hence the
manufacturing of Algenpantucel-L was terminated (McCormick et al. 2016).
Another phase III trial conducted on resectable and non-resectable borderline
advanced tumors of the pancreas with algenpantucel-L failed to achieve beneficial
outcomes (NCT01836432). Another clinical study (NCT02405585) testing
algenpantucel-L and SBRT on borderline resectable PC met the similar end (termi-
nated). Many other clinical investigations such as NCT00358566 and TeloVac,
ISRCTN4382138 involving GV1001 (telomerase peptide vaccine) in advanced
unresectable PC was annulled shortly due to lack of survival benefits.
Several tumors including PDAC overexpress WT1 gene. In advanced PC
patients, application of WT1 peptide along with gemcitabine exhibited a superior
PFS in comparison to chemotherapy alone (Nishida et al. 2018; Nishida et al. 2016).
IMAGE-1/NCT01303172, a randomized phase II study evaluated treating advancer
Table 8.5 Immunotherapies under clinical investigation against pancreatic cancer

Phase
I II III
Cyclophosphamide + GVAX + IMC-CS4 +
NCT03153410 RT
Pembrolizumab
NCT02777710 Durvalumab + Pexidartinib A- NR
NCT03277209 Plerixafor A- NR
Gemcitabine + Nab-paclitaxel +
NCT02588443 CT
RO70097890
NCT02960594 INO-1400/1401 + INO-9012 CT
NCT02465983 CART-meso-19 T cells + Cyclophosphamide CT
RO70097890 + Gemcitabine + Nab-
NCT02588443 CT
paclitaxel
APX005M + Gemcitabine + Nab-Paclitaxel +
NCT03214250 RT
Nivolumab
NCT02732938 Gemcitabine + Nab-paclitaxel + PF04136309 TER
NCT02715804 Gemcitabine + Nab-paclitaxel + PEGPH20 A- NR
NCT03481920 Avelumab + PEGPH20 RT
NCT02758587 Defactinib + Pembrolizumab RT
NCT01876511 MK-3475 RT
NCT01417000 Cyclophosphamide + CRS-207 + GVAX CT
UMIN000004855 DC pulsed with WT1 + Gemcitabine UN
ISRCTN4382138 Capecitabine + Gemcitabine + GV1001 CT
NCT02004262 CRS-207 + Cyclophosphamide + GVAX CT
NCT01072981 Gemcitabine + HyperAcute-Pancreas + 5FU CT
NCT02546531 Defactinib + Gemcitabine + Pembrolizumab RT
Chemotherapy + Epacadostat +
NCT03085914 A- NR
Pembrolizumab
NCT02829723 BLZ945 + PDR001 RT
NCT02907099 BL-8040 + Pembrolizumab RT
NCT02526017 Cabiralizumab + Nivolumab A- NR
NCT02826486 BL-8040 + Pembrolizumab UN
NCT02880371 ARRY-382 + Pembrolizumab A- NR
NCT01896869 FOLFIRINOX + Ipilimumab + Vaccine A- NR
NCT02432963 Pembrolizumab + p53MVA vaccine A- NR
Cyclophosphamide + GVAX + Nivolumab +
NCT02451982
Urelumab RT
NCT02517398 MSB0011359C RT
NCT01174121 Aldesleukin + Cyclophosphamide + RT
Fludarabine + Pembrolizumab +Young TIL
NCT02451553 Afatinib Dimaleate + Capecitabine RT
yet recruiting, NK natural killer, CART-meso-19 chimeric antigen receptor-modified T cells-mes-19,
PEGPH20 pegvorhyaluronidase alfa, DC dendritic cells, WT1 Wilms tumor, 5FU fluorouracil,
p53MVA vaccine P53 modified vaccinia ankara, TIL tumor infiltrating lymphocyte
PC patients with IMM-101 (heat-killed Mycobacterium obuense) in combination

with chemotherapy that reported IMM-101 + chemotherapy was safe and well-
tolerated (Dalgleish et al. 2016). Subsequently, a more extensive phase III study is
needed to support the claim of WT1 and IMM-101 as anti-cancer agents. Altogether,
it is clear that despite enormous efforts made in evaluating and identifying beneficial
effects of chemo-immunotherapies for pancreatic cancer, the journey did not result
in satisfactory outcomes so far. In the recent past, the FDA approved only two
treatment regimens like FOLFIRINOX + chemotherapy and irinotecan liposome

injection to treat pancreatic cancer.
8.15.5 Biliary Tract Cancer
Extrahepatic cholangiocarcinoma, Intrahepatic cholangiocarcinoma (ICC), and gall-

bladder carcinoma are groups of Biliary tract cancers (BTC). Chronic infection,
inflammation, desmoplasia, and microsatellite instability play vital role in turning
cancerous cells into immunosuppressed cells. BTC are highly aggressive tumors
linked with immunity to chemotherapy with weak prognostic degrees. Hence, novel
therapies are in demand. Immunotherapy signifies ensuring discoveries by using a
patient’s immune system to fight against cancer. Earlier preclinical and clinical
studies insinuate supporting mechanistic results because immunotherapy over BTC
presents hope for the growing therapeutic part for this cancer. The two specific
antigens namely MUC1 and WT1 are of great interest in treating BTC through
immunotherapy (Marks and Yee 2015). In BTC and pancreatic patients MUC1
peptide vaccine was well tolerated though disease succession is observed in seven
out of eight subjects (Yamamoto et al. 2005). Clinical trial using vaccines of WT1 or
mixture of WT1/gemcitabine on advanced BTC and PC subjects, aimed at studying
safety, toxicity and excellent immune responses was carried out (Kaida et al. 2011).
Although objective clinical productiveness was not ostensible, the WT1 + GEM
combination therapy provided protection. Moreover, peptide cocktail vaccines,
personalized multi-peptide vaccine, and 3-peptide vaccine were injected into
patients with advanced BTC (Aruga et al. 2013; Aruga et al. 2014; Yoshitomi
et al. 2012). The peptide vaccination was able to stimulate peptide-related T cell
immune reactions in treated subjects. The outcomes from these trials demand for
further evolution of safety and efficacy of peptide cocktail vaccination via Phase II
trial in BTC patients.
Dendritic cells pulsed with tumor lysate provided ~3 long-term survival (Higuchi
et al. 2006) whereas mutated DNA pulsed DC treatment to metastatic
cholangiocarcinoma resulted in tumor deterioration appropriately 30 weeks (Tran
et al. 2014). A sum of 36 ICC patients received DC pulsed with tumor lysate and
TIL’s. The outcomes comprised median PFS up to 18.3 months, and OS with 2.6
years in subjects taking adjuvant immunotherapy (Shimizu et al. 2012). In addition,
phase II/III study is required for establishing scientific effectiveness of ACT and DC
vaccine blend as adjuvant remedy against ICC. Short term safety and potency terms
of KEYNOTE-028 (NCT02054806) study with pembrolizumab evaluated for a
small group of patients with BTC, however, failed to achieve primary results for
OS and PSF. Eventhough the safety and durability of pembrolizumab were encour-
aging (Bang et al. 2015). The KEYNOTE-028 trial assuring the safety and efficacy
of pembrolizumab in BTC inspired an ongoing KEYNOTE-158/NCT02628067
basket trial in BC with 100 patients. Preliminary outcomes of the KEYNOTE-158
studying the ability and welfare of anti-PD1 in progressive BTC showed that
pembrolizumab is useful in a small subgroup of patients demanding extra studies

(Ueno et al. 2018). At present, various clinical investigations considering the
influence of checkpoint inhibitors along with other medications as a remedy for
advanced BTC could work through acclaiming prospective healing procedures.
Effective, substantial, and safe outcomes have been expected from
(NCT02834013, NCT02923934, NCT02821754, NCT03111732, NCT03101566,
NCT02821754, and NCT03101566) these clinical investigations to strengthen the
concept of immunotherapy in BTC. Table 8.6 provides clinical investigations
undertaken to evaluate different types of immunotherapies on BTC.
Table 8.6 Immunotherapies under clinical investigation against biliary tract cancer
Phase
I II III
NCT01174121 Aldesleukin + Cyclophosphamide + RT
Fludarabine + Pembrolizumab +Young TIL
NCT02982720 Pembrolizumab + Sylatron A-NR
NCT02703714 Pembrolizumab + Sargramostim RT
NCT03111732 Capecitabine/oxaliplatin + Pembrolizumab RT
NCT02821754 Cryoablation + Durvalumab + TACE/RFA + RT
Tremelimumab
NCT03101566 Gemcitabine/cisplatin + Ipilimumab + RT
Nivolumab
NCT02829918 Nivolumab A-NR
NCT03260712 Cisplatin + Gemcitabine + Pembrolizumab NRT
NCT02924376 Pemigatinib RT
NCT03230318 Derazantinib RT
NCT02834780 H3B-6527 RT
NCT03144661 INCB062079 RT
NCT02989857 AG-120 A-NR
NCT02091141 Alectinib + Atezolizumab + Cobimetinib + RT
Erlotinib + Pertuzumab + Trastuzumab +
Vemurafenib + Vismodegib
NCT01953926 Fulvestrant + Neratinib + Paclitaxel + RT
Trastuzumab
NCT02451553 Afatinib dimaleate + Capecitabine RT
NCT02609958 Varlitinib CT
NCT02992340 Cisplatin + Gemcitabine + Varlitinib RT
NCT03093870 Capecitabine +Varlitinib A-NR
NCT02419417 BMS-986158 + Nivolumab RT
NCT02091999 Enfortumab vedotin RT
yet recruiting, TIL tumor infiltrating lymphocyte, TACE transarterial chemoembolization, RFA
radiofrequency ablation
8.16 Clinical Significance of Immunotherapy in GI Cancers
Immunotherapies are the new advantageous strategy to fight multiple cancers and
researchers are examining a variety of medicines and factors like immune checkpoint
inhibitors, ACT, peptide vaccines, cytokines, and antibodies. The immunotherapies
must provide significant, reliable, and substantiating outcomes in terms of side
effects, safety, disease progression, tolerability, and survival. The therapeutic
agent must corroborate the primary endpoints. FDA finally approves the target if it
provides at least some or all beneficial effects when administered. Despite the
tremendous amount of money, time, and expertise invested in developing successful
therapeutic targets to treat GI cancer, the success rate of therapeutic agent crossing
FDA approval is limited. Among many therapeutic methods validated on GI cancers,
immunotherapy represents promising means to treat these tumors. Since it is evident
from the FDA approved immunotherapy list on GI cancers.
Some of the recent FDA approved immunotherapies against GI are discussed
here.
(a) On July 10, 2018, FDA granted permission to use a blend of ipilimumab
(Yervoy) and nivolumab (Opdivo) in some metastatic CRC patients who previ-
ously underwent chemotherapy.
(b) On May 23, 2017, FDA favored the use of pembrolizumab (Keytruda) in MSI-H
or dMMR tumors, despite the origin of tumor in the body.
(c) On July 31, 2017, the FDA granted hastened support to the immunotherapy drug
nivolumab (Opdivo®) for metastatic CRC with MSI-H and dMMR, whose
disease progressed after chemotherapy.
(d) On September 22, 2017, the FDA sanctioned the immunotherapy drug
nivolumab-Opdivo® in advanced HCC who previously treated with sorafenib-
Nexavar®.
(e) On September 22, 2017, the FDA permitted the use of immunotherapy drug
pembrolizumab (Keytruda®) against advanced gastric cancers.
(f) On April 27, 2017, the FDA recommended regorafenib (Stivarga®) in HCC
patients. The approval aimed to treat HCC tumors who become insensitive to
sorafenib (Nexavar®).
(g) On October 22, 2015, FDA approved the irinotecan liposome-Onivyde AU92®
to use on chemotherapy-resistant metastatic PC.
(h) On September 22, 2015, FDA granted a tablet composed of tipiracil hydrochlo-
ride and trifluridine (Lonsurf®) to treat mCRC patients.
(i) On April 21, 2014, FDA approved the ramucirumab-Cyramza to treat advanced
gastric or GEJ adenocarcinoma.
8.17 Future Prospectus
The future of immune-oncology depends on the choices made in preferring the right
vaccine type, selecting correct combination of anti-cancer agents, and also choosing
the right person to treat with the selected immunotherapy. GI cancers are aggressive,
display genome instability/gene mutations, immune suppression, immune insensi-
tivity, and desmoplasia. All these features make GI cancers invincible to wash with
immunotherapy. Whatever oncologists achieved so far was great but not enough,
since the very first promising clinical data comes into light just in 2015 and many
studies are still figuring out the puzzle, though the first immunotherapy concept
came out long ago in 1909. A perfect combination that exerts potential anti-cancer
benefits for GI patients must involve precise prognostic factors, knowledge in
vaccine development following choice of anti-cancer treatment. Immune based
vaccines proved efficient as anti-cancer agents in many GI malignancies; still
selection of patients for particular immunotherapy must be done with much more
care to achieve probable treatment. The idea lays the foundation for developing
personalised immunotheraputics to treat GI cancers in the future. Personalized
immunotherapy considers patients’ molecular and immune makeup to provide a
strong backbone in developing most suitable anti-cancer therapy which can confer
safe and prolonged disease control. However, the healthcare cost must be considered
while making efficient therapies for GI cancers. In the next 20 years, the future of
immunotherapy is going to shift the phase of current treatment choices of GI cancers.
The future treatments must be designed in such a way to eliminate unwanted
toxicities while shrinking the tumor. Among all the GI cancers, BTC and PC patients
have limited/no immunotherapeutic options at the moment, nonetheless ongoing
clinical investigation must provide some assuring therapeutic solutions. It is highly
important to overcome the various factors contributing to varied effectiveness of
immunotherapy in GI cancers. Let us hope that oncologist will discover the “Magic
bullet” to whitewash GI cancers in the near future.
Conflicts of Interest None.
References
Abou-Alfa GK et al (2016) PHOCUS: a phase 3 randomized, open-label study comparing the

oncolytic immunotherapy Pexa-Vec followed by sorafenib (SOR) vs SOR in patients with
advanced hepatocellular carcinoma (HCC) without prior systemic therapy. J Clin Oncol 34
(15_suppl):TPS4146
Andre T et al (2018) Nivolumab + ipilimumab combination in patients with DNA mismatch repair-
deficient/microsatellite instability-high (dMMR/MSI-H) metastatic colorectal cancer (mCRC):
first report of the full cohort from CheckMate-142. J Clin Oncol 36(4_suppl):553
Andrews LP et al (2017) LAG3 (CD223) as a cancer immunotherapy target. Immunol Rev 276
(1):80–96
Aruga A et al (2013) Long-term vaccination with multiple peptides derived from cancer-testis
antigens can maintain a specific T-cell response and achieve disease stability in advanced biliary
tract cancer. Clin Cancer Res 19(8):2224–2231
Aruga A et al (2014) Phase I clinical trial of multiple-peptide vaccination for patients with advanced
biliary tract cancer. J Transl Med 12:61
Banchereau J, Steinman RM (1998) Dendritic cells and the control of immunity. Nature 392
(6673):245–252
Bang YJ et al (2015) 525 safety and efficacy of pembrolizumab (MK-3475) in patients (pts) with
advanced biliary tract cancer: interim results of KEYNOTE-028. Eur J Cancer 51:S112
Bang YJ et al (2017) Efficacy of sequential ipilimumab monotherapy versus best supportive care for
unresectable locally advanced/metastatic gastric or gastroesophageal junction cancer. Clin
Cancer Res 23(19):5671–5678
Bang YJ et al (2018) Phase III, randomised trial of avelumab versus physician’s choice of
chemotherapy as third-line treatment of patients with advanced gastric or gastro-oesophageal
junction cancer: primary analysis of JAVELIN Gastric 300. Ann Oncol 29(10):2052–2060
Bendell JC et al (2018a) A phase Ib study of safety and clinical activity of atezolizumab (A) and
cobimetinib (C) in patients (pts) with metastatic colorectal cancer (mCRC). J Clin Oncol 36
(4_suppl):560
Bendell J et al (2018b) Efficacy and safety results from IMblaze370, a randomised Phase III study
comparing atezolizumab+cobimetinib and atezolizumab monotherapy vs regorafenib in chemo-
therapy-refractory metastatic colorectal cancer. Ann Oncol 29, v123. https://doi.org/10.1093/
annonc/mdy208.003
Bezu L et al (2018) Trial watch: peptide-based vaccines in anticancer therapy. Onco Targets Ther 7
(12):e1511506
Bolshinsky V et al (2018) Multimodal prehabilitation programs as a bundle of care in gastrointes-
tinal cancer surgery: a systematic review. Dis Colon Rectum 61(1):124–138
Bou-Assaly W, Mukherji S (2010) Cetuximab (erbitux). AJNR Am J Neuroradiol 31(4):626–627
Brahmer JR et al (2010) Phase I study of single-agent anti-programmed death-1 (MDX-1106) in
refractory solid tumors: safety, clinical activity, pharmacodynamics, and immunologic corre-
lates. J Clin Oncol 28(19):3167–3175
Brahmer JR et al (2012) Safety and activity of anti–PD-L1 antibody in patients with advanced
cancer. N Engl J Med 366(26):2455–2465
Bray F et al (2018) Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality
worldwide for 36 cancers in 185 countries. CA Cancer J Clin 68(6):394–424
Breitbach CJ et al (2015) A phase 2, open-label, randomized study of Pexa-Vec (JX-594) admin-
istered by intratumoral injection in patients with unresectable primary hepatocellular carcinoma.
Methods Mol Biol 1317:343–357
Buchbinder EI, Desai A (2016) CTLA-4 and PD-1 pathways: similarities, differences, and impli-
cations of their inhibition. Am J Clin Oncol 39(1):98–106
Burgio GR (1990) Commentary on the biological self: toward a “Biological Ego”. From Garrod’s
“chemical individuality” to Burnet’s “self”. Thymus 16(2):99–117
Burnet M (1957) Cancer; a biological approach. I. the processes of control. Br Med J 1
(5022):779–786
Busweiler LA et al (2016) Early outcomes from the Dutch upper gastrointestinal cancer audit. Br J
Surg 103(13):1855–1863
Caballero-Banos M et al (2016) Phase II randomised trial of autologous tumour lysate dendritic cell
plus best supportive care compared with best supportive care in pre-treated advanced colorectal
cancer patients. Eur J Cancer 64:167–174
Chau I et al (2018) Safety and antitumor activity of ramucirumab plus pembrolizumab in treatment
naïve advanced gastric or gastroesophageal junction (G/GEJ) adenocarcinoma: preliminary
results from a multi-disease phase I study (JVDF). J Clin Oncol 36(4_suppl):101
Chaudhary B, Elkord E (2016) Regulatory T cells in the tumor microenvironment and cancer
progression: role and therapeutic targeting. Vaccines (Basel) 4(3):28
Chung HC et al (2016) Avelumab (MSB0010718C; anti-PD-L1) in patients with advanced gastric
or gastroesophageal junction cancer from JAVELIN solid tumor phase Ib trial: analysis of safety
and clinical activity. J Clin Oncol 34(15_suppl):4009
Cohen AD et al (2010) Agonist anti-GITR monoclonal antibody induces melanoma tumor immu-
nity in mice by altering regulatory T cell stability and intra-tumor accumulation. PLoS One 5(5):
e10436
Coley WB II (1891) Contribution to the knowledge of sarcoma. Ann Surg 14(3):199–220
Contardi E et al (2005) CTLA-4 is constitutively expressed on tumor cells and can trigger apoptosis
upon ligand interaction. Int J Cancer 117(4):538–550
Coulie PG et al (2014) Tumour antigens recognized by T lymphocytes: at the core of cancer
immunotherapy. Nat Rev Cancer 14(2):135–146
Couzin-Frankel J (2013) Breakthrough of the year 2013. Cancer Immunother Sci 342
(6165):1432–1433
Dalgleish AG et al (2016) Randomised, open-label, phase II study of gemcitabine with and without
IMM-101 for advanced pancreatic cancer. Br J Cancer 115(7):789–796
Darvin P et al (2018) Immune checkpoint inhibitors: recent progress and potential biomarkers. Exp
Mol Med 50(12):165
Dennis KL et al (2013) Current status of interleukin-10 and regulatory T-cells in cancer. Curr Opin
Oncol 25(6):637–645
Diaz LA et al (2017) KEYNOTE-177: randomized phase III study of pembrolizumab versus
investigator-choice chemotherapy for mismatch repair-deficient or microsatellite instability-
high metastatic colorectal carcinoma. J Clin Oncol 35(4_suppl):TPS815
Doi T et al (2016) Updated results for the advanced esophageal carcinoma cohort of the phase Ib
KEYNOTE-028 study of pembrolizumab (MK-3475). J Clin Oncol 34(4_suppl):7
Dougan M, Dranoff G (2009) Immune therapy for cancer. Annu Rev Immunol 27:83–117
Duffy AG et al (2017) Tremelimumab in combination with ablation in patients with advanced
hepatocellular carcinoma. J Hepatol 66(3):545–551
Dunn GP, Old LJ, Schreiber RD (2004) The three Es of cancer immunoediting. Annu Rev Immunol
22:329–360
Edme N et al (2002) Ras induces NBT-II epithelial cell scattering through the coordinate activities
of Rac and MAPK pathways. J Cell Sci 115(Pt 12):2591–2601
El-Khoueiry AB et al (2017) Nivolumab in patients with advanced hepatocellular carcinoma
(CheckMate 040): an open-label, non-comparative, phase 1/2 dose escalation and expansion
trial. Lancet 389(10088):2492–2502
Erkan M et al (2012) The role of stroma in pancreatic cancer: diagnostic and therapeutic implica-
tions. Nat Rev Gastroenterol Hepatol 9(8):454–467
Ferlay J et al (2015) Cancer incidence and mortality worldwide: sources, methods and major
patterns in GLOBOCAN 2012. Int J Cancer 136(5):E359–E386
Finn RS et al (2017) KEYNOTE-240: randomized phase III study of pembrolizumab versus best
supportive care for second-line advanced hepatocellular carcinoma. J Clin Oncol 35(4_suppl):
TPS503
Fisher DT, Appenheimer MM, Evans SS (2014) The two faces of IL-6 in the tumor microenviron-
ment. Semin Immunol 26(1):38–47
Fong L et al (2001) Altered peptide ligand vaccination with Flt3 ligand expanded dendritic cells for
tumor immunotherapy. Proc Natl Acad Sci U S A 98(15):8809–8814
Fuchs CS et al (2016) Pembrolizumab (MK-3475) plus 5-fluorouracil (5-FU) and cisplatin for first-
line treatment of advanced gastric cancer: preliminary safety data from KEYNOTE-059. J Clin
Oncol 34(4_suppl):161–161
Fuchs CS et al (2018) Safety and efficacy of pembrolizumab monotherapy in patients with
previously treated advanced gastric and gastroesophageal junction cancer: phase 2 clinical
KEYNOTE-059 trial. JAMA Oncol 4(5):e180013
Goel G, Sun W (2015) Ramucirumab, another anti-angiogenic agent for metastatic colorectal
cancer in second-line setting--its impact on clinical practice. J Hematol Oncol 8:92
Goldszmid RS, Dzutsev A, Trinchieri G (2014) Host immune response to infection and cancer:
unexpected commonalities. Cell Host Microbe 15(3):295–305
Greten FR et al (2004) IKKbeta links inflammation and tumorigenesis in a mouse model of colitis-
associated cancer. Cell 118(3):285–296
Grothey A et al (2013) Regorafenib monotherapy for previously treated metastatic colorectal cancer
(CORRECT): an international, multicentre, randomised, placebo-controlled, phase 3 trial. Lan-
cet 381(9863):303–312
Guo C et al (2013) Therapeutic cancer vaccines: past, present, and future. Adv Cancer Res
119:421–475
Hanahan D, Weinberg RA (2011) Hallmarks of cancer: the next generation. Cell 144(5):646–674
Hardacre JM et al (2013) Addition of algenpantucel-L immunotherapy to standard adjuvant therapy
for pancreatic cancer: a phase 2 study. J Gastrointest Surg 17(1):94–100. discussion, 100–101
Hayashi T et al (2011) Potential role of LMP2 as tumor-suppressor defines new targets for uterine
leiomyosarcoma therapy. Sci Rep 1:180
Hazama S et al (2014a) A phase II study of five peptides combination with oxaliplatin-based
chemotherapy as a first-line therapy for advanced colorectal cancer (FXV study). J Transl Med
12:108
Hazama S et al (2014b) A phase I study of combination vaccine treatment of five therapeutic
epitope-peptides for metastatic colorectal cancer; safety, immunological response, and clinical
outcome. J Transl Med 12:63
Hemon P et al (2011) MHC class II engagement by its ligand LAG-3 (CD223) contributes to
melanoma resistance to apoptosis. J Immunol 186(9):5173–5183
Heo J et al (2013) Phase II trial of Pexa-Vec (pexastimogene devacirepvec; JX-594), an oncolytic
and immunotherapeutic vaccinia virus, followed by sorafenib in patients with advanced hepa-
tocellular carcinoma (HCC). J Clin Oncol 31(15_suppl):4122
Higuchi R et al (2006) Intrahepatic cholangiocarcinoma with lymph node metastasis successfully
treated by immunotherapy with CD3-activated T cells and dendritic cells after surgery: report of
a case. Surg Today 36(6):559–562
Higuchi Y et al (2015) Enzyme-linked immunosorbent spot assay for the detection of Wilms’ tumor
1-specific T cells induced by dendritic cell vaccination. Biomedicine 3(4):304–315
Inoue Y et al (2017) Cetuximab strongly enhances immune cell infiltration into liver metastatic sites
in colorectal cancer. Cancer Sci 108(3):455–460
Itoh T et al (2002) Immunotherapy of solid cancer using dendritic cells pulsed with the HLA-A24-
restricted peptide of carcinoembryonic antigen. Cancer Immunol Immunother 51(2):99–106
Janjigian YY et al (2018) CheckMate-032 study: efficacy and safety of nivolumab and nivolumab
plus ipilimumab in patients with metastatic esophagogastric cancer. J Clin Oncol 36
(28):2836–2844
Johnsen AK et al (1999) Deficiency of transporter for antigen presentation (TAP) in tumor cells
allows evasion of immune surveillance and increases tumorigenesis. J Immunol 163
(8):4224–4231
Kaida M et al (2011) Phase 1 trial of Wilms tumor 1 (WT1) peptide vaccine and gemcitabine
combination therapy in patients with advanced pancreatic or biliary tract cancer. J Immunother
34(1):92–99
Kalyan A et al (2016) Ipilimumab and gemcitabine for advanced pancreas cancer: a phase Ib study.
J Clin Oncol 34(15_suppl):e15747–e15747
Kang YK et al (2017) Nivolumab in patients with advanced gastric or gastro-oesophageal junction
cancer refractory to, or intolerant of, at least two previous chemotherapy regimens (ONO-4538-
12, ATTRACTION-2): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet
390(10111):2461–2471
Karlsson M et al (2010) Pilot study of sentinel-node-based adoptive immunotherapy in advanced
colorectal cancer. Ann Surg Oncol 17(7):1747–1757
Kaufman HL, Disis ML (2004) Immune system versus tumor: shifting the balance in favor of DCs
and effective immunity. J Clin Invest 113(5):664–667
Kim R, Emi M, Tanabe K (2007) Cancer immunoediting from immune surveillance to immune
escape. Immunology 121(1):1–14
Kimura Y et al (2012) Clinical and immunologic evaluation of dendritic cell-based immunotherapy

in combination with gemcitabine and/or S-1 in patients with advanced pancreatic carcinoma.
Pancreas 41(2):195–205
Knee DA, Hewes B, Brogdon JL (2016) Rationale for anti-GITR cancer immunotherapy. Eur J
Cancer 67:1–10
Kojima T et al (2019) Pembrolizumab versus chemotherapy as second-line therapy for advanced
esophageal cancer: phase III KEYNOTE-181 study. J Clin Oncol 37(4_suppl):2
Kono K et al (2002) Dendritic cells pulsed with HER-2/neu-derived peptides can induce specific
T-cell responses in patients with gastric cancer. Clin Cancer Res 8(11):3394–3400
Kumar V et al (2016) The nature of myeloid-derived suppressor cells in the tumor microenviron-
ment. Trends Immunol 37(3):208–220
Lamers CH et al (2013) Treatment of metastatic renal cell carcinoma with CAIX CAR-engineered T
cells: clinical evaluation and management of on-target toxicity. Mol Ther 21(4):904–912
Le DT et al (2015) PD-1 blockade in tumors with mismatch-repair deficiency. N Engl J Med 372
(26):2509–2520
Le DT et al (2017) Results from a phase 2b, randomized, multicenter study of GVAX pancreas and
CRS-207 compared to chemotherapy in adults with previously-treated metastatic pancreatic
adenocarcinoma (ECLIPSE study). J Clin Oncol 35(4_suppl):345
Le DT et al (2018) KEYNOTE-164: pembrolizumab for patients with advanced microsatellite
instability high (MSI-H) colorectal cancer. J Clin Oncol 36(15_suppl):3514
Leffers N et al (2009) Prognostic significance of tumor-infiltrating T-lymphocytes in primary and
metastatic lesions of advanced stage ovarian cancer. Cancer Immunol Immunother 58
(3):449–459
Lipson EJ et al (2013) Durable cancer regression off-treatment and effective reinduction therapy
with an anti-PD-1 antibody. Clin Cancer Res 19(2):462–468
Long L et al (2018) The promising immune checkpoint LAG-3: from tumor microenvironment to
cancer immunotherapy. Genes Cancer 9(5–6):176–189
Loos M et al (2011) Clinical significance of the costimulatory molecule B7-H1 in Barrett carci-
noma. Ann Thorac Surg 91(4):1025–1031
Lopez J, Tait SW (2015) Mitochondrial apoptosis: killing cancer using the enemy within. Br J
Cancer 112(6):957–962
MacDonald AJ et al (2015) Habitual myofibrillar protein synthesis is Normal in patients with upper
GI cancer cachexia. Clin Cancer Res 21(7):1734–1740
Maeda Y et al (2015) Dendritic cells transfected with heat-shock protein 70 messenger RNA for
patients with hepatitis C virus-related hepatocellular carcinoma: a phase 1 dose escalation
clinical trial. Cancer Immunol Immunother 64(8):1047–1056
Marcus L et al (2019) FDA approval summary: pembrolizumab for the treatment of microsatellite
instability-high solid tumors. Clin Cancer Res 25(13):3753–3758
Marks EI, Yee NS (2015) Immunotherapeutic approaches in biliary tract carcinoma: current status
and emerging strategies. World J Gastrointest Oncol 7(11):338–346
Massague J (2008) TGFbeta in cancer. Cell 134(2):215–230
Matrisian LM, Berlin JD (2016) The past, present, and future of pancreatic Cancer clinical trials.
Am Soc Clin Oncol Educ Book 35:e205–e215
Matsui H et al (2017) Postoperative adjuvant therapy for resectable pancreatic cancer with
gemcitabine and adoptive immunotherapy. Pancreas 46(8):994–1002
Matzinger P (1994) Tolerance, danger, and the extended family. Annu Rev Immunol 12:991–1045
Matzinger P, Kamala T (2011) Tissue-based class control: the other side of tolerance. Nat Rev
Immunol 11(3):221–230
Mayer RJ et al (2015) Randomized trial of TAS-102 for refractory metastatic colorectal cancer. N
Engl J Med 372(20):1909–1919
McCormick KA et al (2016) Pancreatic cancer: update on immunotherapies and algenpantucel-L.
Hum Vaccin Immunother 12(3):563–575
Medavaram S, Zhang Y (2018) Emerging therapies in advanced hepatocellular carcinoma. Exp

Hematol Oncol 7(1):17
Mehta R, Shah A, Almhanna K (2018) Pembrolizumab for the treatment of patients with recurrent
locally advanced or metastatic gastric or gastroesophageal junction cancer: an evidence-based
review of place in therapy. Onco Targets Ther 11:6525–6537
Melero I et al (2017) Nivolumab dose escalation and expansion in patients with advanced hepato-
cellular carcinoma (HCC): the CheckMate 040 study. J Clin Oncol 35(4_suppl):226
Mimura K et al (2018) Immunotherapy for esophageal squamous cell carcinoma: a review.
Fukushima J Med Sci 64(2):46–53
Mittal D et al (2014) New insights into cancer immunoediting and its three component phases—
elimination, equilibrium and escape. Curr Opin Immunol 27:16–25
Miyazawa M et al (2017) Phase II clinical trial using novel peptide cocktail vaccine as a postop-
erative adjuvant treatment for surgically resected pancreatic cancer patients. Int J Cancer 140
(4):973–982
Moehler MH et al (2016) A randomized, open-label, two-arm phase II trial comparing the efficacy
of sequential ipilimumab (ipi) versus best supportive care (BSC) following first-line
(1L) chemotherapy in patients with unresectable, locally advanced/metastatic (A/M) gastric or
gastro-esophageal junction (G/GEJ) cancer. J Clin Oncol 34(15_suppl):4011
Moehler MH et al (2018) JAVELIN Gastric 100: phase 3 trial of avelumab (anti-PD-L1) mainte-
nance therapy versus continuation of first-line chemotherapy in patients with advanced gastric or
gastroesophageal junction cancer (GC/GEJC). J Clin Oncol 36(4_suppl):TPS195
Morse MA et al (1999) A Phase I study of active immunotherapy with carcinoembryonic antigen
peptide (CAP-1)-pulsed, autologous human cultured dendritic cells in patients with metastatic
malignancies expressing carcinoembryonic antigen. Clin Cancer Res 5(6):1331–1338
Muller MF, Ibrahim AE, Arends MJ (2016) Molecular pathological classification of colorectal
cancer. Virchows Arch 469(2):125–134
Mulligan JK, Rosenzweig SA, Young MR (2010) Tumor secretion of VEGF induces endothelial
cells to suppress T cell functions through the production of PGE2. J Immunother 33(2):126–135
Muro K et al (2016) Pembrolizumab for patients with PD-L1-positive advanced gastric cancer
(KEYNOTE-012): a multicentre, open-label, phase 1b trial. Lancet Oncol 17(6):717–726
Murphy AG et al (2019) Epigenetic priming prior to pembrolizumab in mismatch repair-proficient
advanced colorectal cancer. J Clin Oncol 37(4_suppl):591
Nagorsen D, Thiel E (2006) Clinical and immunologic responses to active specific cancer vaccines
in human colorectal cancer. Clin Cancer Res 12(10):3064–3069
Neesse A et al (2011) Stromal biology and therapy in pancreatic cancer. Gut 60(6):861–868
Nesselhut J et al (2016) Systemic treatment with anti-PD-1 antibody nivolumab in combination
with vaccine therapy in advanced pancreatic cancer. J Clin Oncol 34(15_suppl):3092–3092
Nestle FO et al (1998) Vaccination of melanoma patients with peptide- or tumor lysate-pulsed
dendritic cells. Nat Med 4(3):328–332
Nishida S et al (2016) Randomized phase II study of WT1 peptide vaccine plus gemcitabine for
advanced pancreatic ductal adenocarcinoma (PDAC): clinical efficacy and immune response. J
Clin Oncol 34(15_suppl):3085
Nishida S et al (2018) Combination gemcitabine and WT1 peptide vaccination improves
progression-free survival in advanced pancreatic ductal adenocarcinoma: a phase II randomized
study. Cancer Immunol Res 6(3):320–331
Noy R, Pollard JW (2014) Tumor-associated macrophages: from mechanisms to therapy. Immunity
41(1):49–61
Oba K et al (2007) Efficacy of adjuvant immunochemotherapy with polysaccharide K for patients
with curative resections of gastric cancer. Cancer Immunol Immunother 56(6):905–911
Oba MS et al (2016) The efficacy of adjuvant immunochemotherapy with OK-432 after curative
resection of gastric cancer: an individual patient data meta-analysis of randomized controlled
trials. Gastric Cancer 19(2):616–624
Ohigashi Y et al (2005) Clinical significance of programmed death-1 ligand-1 and programmed

death-1 ligand-2 expression in human esophageal cancer. Clin Cancer Res 11(8):2947–2953
Ohtsu A et al (2016) Pembrolizumab versus paclitaxel as second-line therapy for advanced gastric
or gastroesophageal junction (GEJ) adenocarcinoma: phase 3 KEYNOTE-061 study. J Clin
Oncol 34(15_suppl):TPS4137
O’Reilly EM et al (2018) A randomized phase 2 study of durvalumab monotherapy and in
combination with tremelimumab in patients with metastatic pancreatic ductal adenocarcinoma
(mPDAC): ALPS study. J Clin Oncol 36(4_suppl):217
Osada T et al (2006) NK cell activation by dendritic cell vaccine: a mechanism of action for clinical
activity. Cancer Immunol Immunother 55(9):1122–1131
Overman MJ et al (2016) A randomized phase 2 study of the Bruton tyrosine kinase (Btk) inhibitor
acalabrutinib alone or with pembrolizumab for metastatic pancreatic cancer (mPC). J Clin Oncol
34(15_suppl):4130
Overman MJ et al (2017) Nivolumab in patients with metastatic DNA mismatch repair-deficient or
microsatellite instability-high colorectal cancer (CheckMate 142): an open-label, multicentre,
phase 2 study. Lancet Oncol 18(9):1182–1191
Overman MJ et al (2018) Nivolumab in patients with DNA mismatch repair-deficient/microsatellite
instability-high (dMMR/MSI-H) metastatic colorectal cancer (mCRC): long-term survival
according to prior line of treatment from CheckMate-142. J Clin Oncol 36(4_suppl):554
Pages F et al (2010) Immune infiltration in human tumors: a prognostic factor that should not be
ignored. Oncogene 29(8):1093–1102
Palmer DH et al (2009) A phase II study of adoptive immunotherapy using dendritic cells pulsed
with tumor lysate in patients with hepatocellular carcinoma. Hepatology 49(1):124–132
Cancer 12(4):252–264
Phan GQ, Rosenberg SA (2013) Adoptive cell transfer for patients with metastatic melanoma: the
potential and promise of cancer immunotherapy. Cancer Control 20(4):289–297
Pierce GB, Speers WC (1988) Tumors as caricatures of the process of tissue renewal: prospects for
therapy by directing differentiation. Cancer Res 48(8):1996–2004
Pinheiro D et al (2011) Phenotypic and functional characterization of a CD4(+) CD25(high) FOXP3
(high) regulatory T-cell population in the dog. Immunology 132(1):111–122
Poggi A, Zocchi MR (2006) Mechanisms of tumor escape: role of tumor microenvironment in
inducing apoptosis of cytolytic effector cells. Arch Immunol Ther Exp 54(5):323–333
Poggi A et al (2005) Tumor-induced apoptosis of human IL-2-activated NK cells: role of natural
cytotoxicity receptors. J Immunol 174(5):2653–2660
Prieto J, Melero I, Sangro B (2015) Immunological landscape and immunotherapy of hepatocellular
carcinoma. Nat Rev Gastroenterol Hepatol 12(12):681–700
Rayner AA et al (1985) Lymphokine-activated killer (LAK) cells. Analysis of factors relevant to the
immunotherapy of human cancer. Cancer 55(6):1327–1333
Ribatti D (2017) The concept of immune surveillance against tumors. The first theories. Oncotarget
8(4):7175–7180
Riera-Knorrenschild J et al (2015) A subgroup with improved overall survival from the phase
2 IMPACT study: maintenance therapy of metastatic colorectal cancer patients with the TLR-9
agonist MGN1703. J Clin Oncol 33(15_suppl):3049
Royal RE et al (2010) Phase 2 trial of single agent Ipilimumab (anti-CTLA-4) for locally advanced
or metastatic pancreatic adenocarcinoma. J Immunother 33(8):828–833
Sabado RL, Bhardwaj N (2015) Cancer immunotherapy: dendritic-cell vaccines on the move.
Nature 519(7543):300–301
Sahin U et al (1995) Human neoplasms elicit multiple specific immune responses in the autologous
host. Proc Natl Acad Sci U S A 92(25):11810–11813
Sahin U et al (2017) Personalized RNA mutanome vaccines mobilize poly-specific therapeutic
immunity against cancer. Nature 547(7662):222–226
Salcedo R et al (2013) MyD88 and its divergent toll in carcinogenesis. Trends Immunol 34
(8):379–389
Sangro B et al (2013) A clinical trial of CTLA-4 blockade with tremelimumab in patients with
hepatocellular carcinoma and chronic hepatitis C. J Hepatol 59(1):81–88
Sangro B et al (2016) A randomized, multicenter, phase 3 study of nivolumab vs sorafenib as first-
line treatment in patients (pts) with advanced hepatocellular carcinoma (HCC): CheckMate-459.
J Clin Oncol 34(15_suppl):TPS4147
Sawada Y et al (2012) Phase I trial of a glypican-3-derived peptide vaccine for advanced hepato-
cellular carcinoma: immunologic evidence and potential for improving overall survival. Clin
Cancer Res 18(13):3686–3696
Sawada Y et al (2013) Remarkable tumor lysis in a hepatocellular carcinoma patient immediately
following glypican-3-derived peptide vaccination: an autopsy case. Hum Vaccin Immunother 9
(6):1228–1233
Sawada Y et al (2016) Phase II study of the GPC3-derived peptide vaccine as an adjuvant therapy
for hepatocellular carcinoma patients. Onco Targets Ther 5(5):e1129483
Sayers TJ (2011) Targeting the extrinsic apoptosis signaling pathway for cancer therapy. Cancer
Immunol Immunother 60(8):1173–1180
Schmoll HJ et al (2014) Maintenance treatment with the immunomodulator MGN1703, a Toll-like
receptor 9 (TLR9) agonist, in patients with metastatic colorectal carcinoma and disease control
after chemotherapy: a randomised, double-blind, placebo-controlled trial. J Cancer Res Clin
Oncol 140(9):1615–1624
Schreiber RD, Old LJ, Smyth MJ (2011) Cancer immunoediting: integrating immunity’s roles in
cancer suppression and promotion. Science 331(6024):1565–1570
Secondino S et al (2012) T-cell therapy for EBV-associated nasopharyngeal carcinoma: preparative
lymphodepleting chemotherapy does not improve clinical results. Ann Oncol 23(2):435–441
Segal NH et al (2016) Non-randomized phase II study to assess the efficacy of pembrolizumab
(Pem) plus radiotherapy (RT) or ablation in mismatch repair proficient (pMMR) metastatic
colorectal cancer (mCRC) patients. J Clin Oncol 34(15_suppl):3539
Shah MA et al (2018) Efficacy and safety of pembrolizumab for heavily pretreated patients with
advanced, metastatic adenocarcinoma or squamous cell carcinoma of the esophagus: the phase
2 KEYNOTE-180 study. JAMA Oncol 5(4):546–550
Shang N et al (2017) Dendritic cells based immunotherapy. Am J Cancer Res 7(10):2091–2102
Shaw JM et al (2016) Improving psychosocial outcomes for caregivers of people with poor
prognosis gastrointestinal cancers: a randomized controlled trial (family connect). Support
Care Cancer 24(2):585–595
Shimizu K et al (2012) Clinical utilization of postoperative dendritic cell vaccine plus activated
T-cell transfer in patients with intrahepatic cholangiocarcinoma. J Hepatobiliary Pancreat Sci 19
(2):171–178
Shimizu Y et al (2018) Cancer immunotherapy-targeted glypican-3 or neoantigens. Cancer Sci 109
(3):531–541
Shimodaira S et al (2015) Dendritic cell-based adjuvant vaccination targeting Wilms’ tumor 1 in
patients with advanced colorectal cancer. Vaccines (Basel) 3(4):1004–1018
Shindo Y et al (2014) Adoptive immunotherapy with MUC1-mRNA transfected dendritic cells and
cytotoxic lymphocytes plus gemcitabine for unresectable pancreatic cancer. J Transl Med
12:175
Shionoya Y et al (2017) Loss of tapasin in human lung and colon cancer cells and escape from
tumor-associated antigen-specific CTL recognition. Onco Targets Ther 6(2):e1274476
Shitara K et al (2018) Pembrolizumab versus paclitaxel for previously treated, advanced gastric or
gastro-oesophageal junction cancer (KEYNOTE-061): a randomised, open-label, controlled,
phase 3 trial. Lancet 392(10142):123–133
Siegel RL, Miller KD, Jemal A (2015) Cancer statistics, 2015. CA Cancer J Clin 65(1):5–29
Smith T (1909) Active immunity produced by so called balanced or neutral mixtures of diphtheria
toxin and antitoxin. J Exp Med 11(2):241–256
Song T-J, Ip EWK, Fong Y (2004) Hepatocellular carcinoma: current surgical management.
Gastroenterology 127(5):S248–S260
Spira A et al (2016) Leveraging premalignant biology for immune-based cancer prevention. Proc
Natl Acad Sci U S A 113(39):10750–10758
Staveley-O’Carroll K et al (1998) Induction of antigen-specific T cell anergy: an early event in the
course of tumor progression. Proc Natl Acad Sci U S A 95(3):1178–1183
Tabernero J et al (2016) KEYNOTE-062: phase III study of pembrolizumab (MK-3475) alone or in
combination with chemotherapy versus chemotherapy alone as first-line therapy for advanced
gastric or gastroesophageal junction (GEJ) adenocarcinoma. J Clin Oncol 34(4_suppl):TPS185
Tabernero J et al (2017) Phase Ia and Ib studies of the novel carcinoembryonic antigen (CEA) T-cell
bispecific (CEA CD3 TCB) antibody as a single agent and in combination with atezolizumab:
preliminary efficacy and safety in patients with metastatic colorectal cancer (mCRC). J Clin
Oncol 35(15_suppl):3002
Takayama T et al (2000) Adoptive immunotherapy to lower postsurgical recurrence rates of
hepatocellular carcinoma: a randomised trial. Lancet 356(9232):802–807
Tarakanovskaya MG et al (2015) Immunotherapy of liver cancer with hepcortespenlisimut-L: open-
label phase II clinical study in patients with advanced HCC. J Immunother Cancer 3(2):P200
The Cancer Genome Atlas Research Network et al (2017) Integrated genomic characterization of
oesophageal carcinoma. Nature 541:169
Topalian SL et al (2012) Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N
Engl J Med 366(26):2443–2454
Torre LA et al (2015) Global cancer statistics, 2012. CA Cancer J Clin 65(2):87–108
Tran E et al (2014) Cancer immunotherapy based on mutation-specific CD4+ T cells in a patient
with epithelial cancer. Science 344(6184):641–645
Tran E et al (2016) T-cell transfer therapy targeting mutant KRAS in cancer. N Engl J Med 375
(23):2255–2262
Turcotte S et al (2014) Tumor-reactive CD8+ T cells in metastatic gastrointestinal cancer refractory
to chemotherapy. Clin Cancer Res 20(2):331–343
Ueno M et al (2018) 625PD Pembrolizumab for advanced biliary adenocarcinoma: Results from the
multicohort, phase II KEYNOTE-158 study. Ann Oncol 29(suppl_8):mdy282–009
Upadhyay R et al (2015) Lymphoma: immune evasion strategies. Cancers (Basel) 7(2):736–762
Urszula L, Krzysztof K (2016) Mechanisms of tumour escape from immune surveillance. J Vet Res
60(4):453–460
Vacchelli E et al (2012a) Trial watch: FDA-approved toll-like receptor agonists for cancer therapy.
Onco Targets Ther 1(6):894–907
Vacchelli E et al (2012b) Trial watch: peptide vaccines in cancer therapy. Onco Targets Ther 1
(9):1557–1576
Vajdic CM, van Leeuwen MT (2009) Cancer incidence and risk factors after solid organ transplan-
tation. Int J Cancer 125(8):1747–1754
van der Bruggen P et al (1991) A gene encoding an antigen recognized by cytolytic T lymphocytes
on a human melanoma. Science 254(5038):1643–1647
Vesely MD, Schreiber RD (2013) Cancer immunoediting: antigens, mechanisms, and implications
to cancer immunotherapy. Ann N Y Acad Sci 1284:1–5
Vigneron N (2015) Human tumor antigens and cancer immunotherapy. Biomed Res Int
2015:948501
Vonderheide RH et al (1999) The telomerase catalytic subunit is a widely expressed tumor-
associated antigen recognized by cytotoxic T lymphocytes. Immunity 10(6):673–679
Waldmann TA (2003) Immunotherapy: past, present and future. Nat Med 9(3):269–277
Wang RF (1999) Human tumor antigens: implications for cancer vaccine development. J Mol Med
(Berl) 77(9):640–655
Wilke H et al (2014) Ramucirumab plus paclitaxel versus placebo plus paclitaxel in patients with
previously treated advanced gastric or gastro-oesophageal junction adenocarcinoma (RAIN-
BOW): a double-blind, randomised phase 3 trial. Lancet Oncol 15(11):1224–1235
Yaguchi T, Kawakami Y (2016) Cancer-induced heterogeneous immunosuppressive tumor micro-

environments and their personalized modulation. Int Immunol 28(8):393–399
Yamada A et al (2013) Next-generation peptide vaccines for advanced cancer. Cancer Sci 104
(1):15–21
Yamamoto K et al (2005) MUC1 peptide vaccination in patients with advanced pancreas or biliary
tract cancer. Anticancer Res 25(5):3575–3579
Yoshino S et al (2016) Randomised phase III study of S-1 alone versus S-1 plus lentinan for
unresectable or recurrent gastric cancer (JFMC36-0701). Eur J Cancer 65:164–171
Yoshitomi M et al (2012) Personalized peptide vaccination for advanced biliary tract cancer: IL-6,
nutritional status and pre-existing antigen-specific immunity as possible biomarkers for patient
prognosis. Exp Ther Med 3(3):463–469
Zheng Z et al (2014) Level of circulating PD-L1 expression in patients with advanced gastric cancer
and its clinical implications. Chin J Cancer Res 26(1):104–111
Zhu AX et al (2018) Pembrolizumab in patients with advanced hepatocellular carcinoma previously
treated with sorafenib (KEYNOTE-224): a non-randomised, open-label phase 2 trial. Lancet
Oncol 19(7):940–952
Chapter 9
Immuno-Oncology of Oesophageal Cancer
Bindu Prasuna Aloor and Senthilkumar Rajagopal
Abstract A most worldwide health challenge is oesophageal cancer and is standing

in 6th place of cancer deaths all over the world. Oesophageal squamous cell
carcinoma (OSCC) and oesophageal adenocarcinoma (OAC) are the two types of
oesophageal cancer which are epidemiologically and biologically distinct. More than
90% of the disease is OSCC in East regions of Africa and southern states of America.
The disease originates in the epithelial lining. It can metastasize in lungs, liver,
stomach, and also other body parts. The disease is most observed in males than
females. The major causing agents are tobacco usage and alcohol consumption. The
disease is mostly fatal with less survival rate of 5–30%. Patient can be cured if
diagnosed in the early stage by surgical removal of the tumour, chemotherapy,
radiation. This chapter is mainly focused on possible role of immunotherapy for
oesophageal cancer.
Keywords Achalasia · Adenocarcinoma · Barrett’s oesophagus · Gastro

oesophageal reflux disease · Oesophageal squamous cell carcinoma
Abbreviations
AC Adenocarcinoma
GERD Gastro oesophageal reflux disease
HER2 Human epidermal growth factor receptor 2
OAC Oesophageal adenocarcinoma
OSCC Oesophageal squamous cell carcinoma
PD-1 Programmed cell death protein I
PET-CT Positron emission tomography and computed tomography
B. P. Aloor
Department of Botany, Rayalaseema University, Kurnool, AP, India
S. Rajagopal (*)
Department of Biochemistry, Rayalaseema University, Kurnool, AP, India
https://doi.org/10.1007/978-981-15-6487-1_9
160 B. P. Aloor and S. Rajagopal
SCC Squamous cell carcinoma

9.1 Introduction
Oesophagus is the muscular tube that carries food and drink from the mouth to the
stomach. Oesophageal cancer refers to malignant tumours of the oesophagus.
Oesophageal cancers are named specifically relating to the localization of the tumour
as relation “gastro esophageal junction adenocarcinoma” which explains as the
adenoma localized where the stomach and oesophagus are jointly related (Mont-
gomery 2014).
9.2 Anatomy
A brief outline described here of the structure and function of the oesophagus will
help understand the disease in malignant stage. The oesophagus or food tube is the
hollow and muscular tubular structure that connects the oral cavity and the upper end
point of the stomach. It conducts swallowed food and liquid to the stomach to be
digested. It measures around 25–30 cm in length and has few constrictions present at
various points throughout its length. The narrowest portion of oesophagus measures
3/4 inch in diameter. The wall of the oesophagus is four layered. Immediate mucosal
lining that surrounds the central lumen. This is made up of flat squamous cell type.
Underlying the epithelium is the submucosal layer consisting of blood vessels and
nerves.
Next to this is the smooth muscle layer. The contractions of this thick muscular
layer help in propelling the food downwards to the stomach for digestion. Beneath
the muscular layer is the serosal layer or called adventitia. The upper and lower
oesophagus is controlled by the sphincters, cricopharyngeus muscle and gastro
oesophageal sphincter, respectively. Oesophagus bears a dense mesh of lymph
cells in lamina propria cells and sub mucosa, which runs all along the sub mucosa.
Under normal conditions, both sphincters are in closed form. When the lower
sphincter is incompetent or fails to relax, it can lead to gastric acid reflux, a condition
called achalasia. This condition has the risk of oesophageal cancer increasing
slightly. Usually oesophageal cancers occur in the lining epithelium of the oesoph-
agus and spread to the other layers, nearby organs or spread to distant sites called
metastasis.
The four main segments of oesophagus are cervical oesophagus of 15–20 cm,
upper part of thoracic oesophagus about 20–25 cm, middle part of thoracic oesoph-
agus about 25–30 cm, lower thoracic oesophagus and gastro oesophageal junction
about 30–40 cm from the incisors (Fig. 9.1). Tumours caused in the oesophagus are
9 Immuno-Oncology of Oesophageal Cancer 161
Fig. 9.1 Anatomy of oesophagus (courtesy: American Cancer Society: Cancer Facts and
Figures (American Cancer Society: Cancer Facts and Figures 2019))
usually measured by the distance of the upper end point of the tumour to the point of
incisors location.
9.3 Subtypes
The subtypes are named after their origin in the oesophagus. Squamous cell carci-
noma (SCC) begins in the squamous cells that line the oesophageal cells. Mostly
originates in the middle portion of the oesophagus. SCC is found in people who have
excess usage of cigars and other alcoholic beverages (Prabhu et al. 2014). The
disease is also prevalent in people who were diagnosed with head/neck squamous
cell carcinoma (Priante et al. 2011; Scherübl et al. 2008).
Fig. 9.2 Acid reflux and

relation to oesophageal
cancer (courtesy: slide
share, GERD)
Adenocarcinoma (AC) occurs in the distal oesophagus, at the opening to the

abdomen. When squamous cells are replaced by glandular cells, and grow abnor-
mally, it is named as adenocarcinoma. It arises from a pathological change occurring
in the normal oesophageal lining squamous epithelium (DeJonge et al. 2014). This
change is termed as Barrett’s oesophagus and is associated with abnormal chronic
reflux in gastric juice into the lower oesophagus, chronic symptomatic acid reflux
disease (DeJonge et al. 2014). This results in columnar transformation of the normal
cells which are lining the oesophagus to that of intestinal and colon lining. The
condition is diagnosed as symptom of cancer (Fig. 9.2).
Usually, Barrett’s oesophagus is benign and chance of malignancy ranges from

1–5%. ACC incidence is in the last third portion of the oesophagus. Chewing
tobacco acts as an enhancer showing less impact in AC and higher in SCC. No
report has evidences alcohol as the causing agent (Lagergren and Lagergren 2013).
Rarer cases of oesophageal cancers found so far are carcinoma of lymph, chorion,
melanoma, and sarcoma.
9.4 Incidence and Mortality
The exact reason behind the disease is still unknown. Researchers say that some
factors associated with DNA damage may cause the disease (Pennathur et al. 2013).
This cancer is very rare in United States but most occurred in Asia and parts of
Africa. Recorded new cancers and deaths from the disease among US population in
2019 were 17,650 and 16,080, respectively (American Cancer Society: Cancer Facts
and Figures 2019). There has been more incidence of oesophageal cancer in recent
decades with change in histology and tumour localization. In the USA, SCC is more
and the prevalence of adenocarcinoma was also recorded recently in the USA and
Western Europe (Brown et al. 2008; Blot and McLaughlin 1999). Disease was
recorded more in males (Kubo and Corley 2004). The average age of patients
found with oesophageal cancer is 55 years old (Ginsberg 1998). ACs are localized
in the distal region of oesophagus. The cause of the disease and demographic
distribution are unknown.
Oesophageal carcinoma is the sixth commonly causing cancer related death
worldwide and is considered as one of the crucial global health challenges. Even
though oesophageal cancer survival rates have improved, the prognosis is poor when
compared to other cancers; Survival rate is only 20% for at least 5 years after being
diagnosed with oesophageal cancer. These statistics emphasize the need for a new
therapy or therapies to prevent and treat oesophageal cancer.
The occurrence of oesophageal carcinoma is very rare in younger population. As
age advances, there are higher chances of incidence of the disease with its peak in the
70s and 80s. AC is commonly observed in males, while SCC seems to spread
irrespective of sex (Kim et al. 2009). Generally, medical practitioner describes stages
of cancer in terms of size, part affected, and organs affected by the spread of cancer
cells through blood (Figs. 9.3, 9.4, and 9.5). Staging of the disease helps in proper
treatment for the disease. The TNM staging system (Rice et al. 2017) describes
cancers by Tumour (T)—primary tumour or slightly extended; Nodes (N)—cancer-
ous cells move to adjacent lymph nodes in the primary tumour located organ;
Metastasis (M)—gradual movement of cancerous cells to different organs which
are away from the primary tumour.
Fig. 9.3 T1, T2, and T3

stages of oesophageal
cancer (courtesy: American
Cancer Society: Cancer
Facts and
Figures (American Cancer
Society: Cancer Facts and
Figures 2019))
Fig. 9.4 Stage T4

oesophageal cancer
(courtesy: American Cancer
Figures 2019))
Fig. 9.5 Oesophageal

cancer spread to lymph
nodes (courtesy: American
Cancer Society: Cancer
Facts and
Figures 2019))
9.5 Risk Factors
Oesophageal cancer develops when the DNA in the cells is altered or mutated that
causes cancer cells to grow and multiply out of control leading to the formation of a
tumour mass (Sewram et al. 2014). Rupture or irritation in the mucosal lining of the
oesophagus is caused by many factors that include smoking, alcohol consumption,
gastro oesophageal reflux disease (GERD) (Falk 2009), bile reflux, Barrett’s
oesophagus, drinking hot liquids, obesity, achalasia cardia, radiotherapy given to

upper abdomen or chest for lung or breast cancer can increase oesophageal
cancer risk.
9.6 Symptoms
Symptoms of oesophageal cancers are Dysphagia—pain or discomfort in

swallowing, and sensation of food blockage in the throat or chest. It is very important
not to neglect the above symptoms and one has to seek urgent medical attention
(Ferri 2013).
Persistent heartburn/indigestion—Tumour present in the lower part of the
oesophagus causes dysfunction of the lower oesophageal sphincter and causes acid
reflux leading to burning sensation or chest discomfort, soon after eating
(Lao-Sirieix et al. 2010). Even though heartburn or indigestion can be harmless, it
is important to consult a doctor and get investigated (Cook et al. 2014). Loss of
weight—If consuming food becomes less due to swallowing difficulties can lead to
marked loss in weight of the human (Yamada 2011).
Regurgitation—Because of difficulty in swallowing, swallowed food starts to
come back. This begins initially with solid food and with disease progression, soft
mashed food as well as liquids come back (Mayer 2008). Persistent cough or
hoarseness of voice—It can be due to pressure on the windpipe. Vomiting
blood—This rarely occurs due to an ulcerated growth bleed or there is infiltration
of the tumour into a blood vessel (Gerdes and Ferguson 2002). Dark coloured stools.
When the blood from the tumour is swallowed, it undergoes digestion by the acid in
the stomach and becomes dark coloured and passed out as dark coloured stools.
9.7 Diagnosis
Patients with the above symptoms have to undergo an upper intestinal endoscopy
(Stahl et al. 2013). A flexible tube equipped with an illuminated lens at its distal end
is passed in to the mouth down the throat into the food pipe. Just before the
procedure the throat is numbed with an anaesthetic, gargle and the endoscopic
tube is passed into the oesophagus. The doctor can directly view the interior of the
oesophagus and identify abnormal areas such as tumour or inflammation (Vazquez-
Sequeiros et al. 2001).
Seventy-five percent of ACs occurs in the distal part of oesophagus, while SCCs
appear in the region of proximal to middle oesophagus (Montgomery 2014). Biop-
sies have to be taken from all suspected areas. PET-CT (positron emission tomog-
raphy and computed tomography) scans and other related tests can visualize cancer
cells with rapid metabolism (Bruzzi et al. 2007). Diagnostic tests for different
cancers include mammography, pap smear test, tumour marker test, bone scan, MRI,
tissue biopsy (Stahl et al. 2013; Krasna et al. 2001).
Barium Swallow—oesophagus can be used as a marker for imaging metastasized
cancer by radiological procedure. Fast for a few hours prior to the procedure is
recommended (Cynthia and Barbara 2012). Patient is given some barium containing
liquid to swallow and following the swallowing of liquid, x-ray images of the
oesophagus are captured. If the results are suggestive of a growth, next set of
procedures may be necessary. Blood and urine tests will be conducted to determine
the general health status of the patient. Once diagnosis of oesophageal cancer is
confirmed, further tests are required to stage the disease. Staging of the carcinoma is
necessary to decide medication (Figs. 9.3, 9.4, and 9.5). Tests such as PET-CT and
MRI help in staging the disease.
Stage I—tumour growth is confined to the superficial layer of the oesophagus
lining. There is no spread to local lymph nodes (Stahl et al. 2013).
Stage II—tumour growth has extended in depth into muscular layers of the
oesophagus or into neighbour lymph nodes (Mariette et al. 2014).
Stage III—tumour has extensively involved the wall of the oesophagus, has
moved to tissues surrounding or lymph nodes (Montgomery 2014).
Stage IV—tumour has spread all over travelling in blood and metastasized and
may be seen in the liver, lungs, brain, or bone (Stahl et al. 2013).
9.8 Prognosis
Favourable prognostic factors are disease recognition in budding stage and complete
surgical removal. Acute dysplasia in distal oesophageal mucosal layer may get
invasive cancer within the dysplasia region. Prognosis is high in such cases after
resection (Reed et al. 2005). In many cases, oesophageal cancer patient’s life span
can be increased, but is rarely completely curable. The overall 5-year survival time in
patients with definitive treatment is from 5% to 30% (Polednak 2003). Regular
doctor consultation following therapy is must. Patients’ post-surgery of their oesoph-
agus exhibits side effects of narrowing of oesophagus at the site of the surgery. In
such complications, need oesophageal dilatations with stents (Tietjen et al. 1994).
9.9 Treatment
In cancer care multidisciplinary doctors collaborate to design a patient’s overall

medication plan that is in combination with different types of treatments. Cancer care
teams are usually associated with physician assistants, oncology nurses, social
workers, pharmacists, counsellors, dietitians, and others.
Immunotherapy approaches for oesophageal carcinoma are
9.9.1 Targeted Antibodies
The treatment is by a monoclonal antibody, Ramucirumab that specifically targets

the VEGF/VEGFR2 pathway and hinders blood vessel growth in tumours; this is
approved for patients in advanced stage of gastro oesophageal cancer.
Trastuzumab is another monoclonal antibody that interferes in the HER2 path-
way; and has been approved to medicate advanced, HER2-positive gastro
oesophageal cancer as a first-line therapy.
9.9.2 Immunomodulators
Pembrolizumab: A checkpoint inhibitor that has interference in PD-1/PD-L1 path-

way; has been used in patients with advanced, PD-L1-positive gastro oesophageal
cancer or squamous cell carcinoma of the oesophagus.
Many immunotherapy researches for oesophageal cancer have shown promising
results in their early clinical trials (Table 9.1) (Fiorica et al. 2004).
Table 9.1 Standard treatment options for oesophageal cancer (courtesy (Fiorica et al. 2004))
Stage (TNM staging
criteria) Treatment options
Stage 0—oesophageal Surgery
cancer Endoscopic resection
Stage I—oesophageal Chemo radiation therapy followed by surgery
cancer Surgery alone
Stage II—oesophageal Chemo radiation followed by surgery
cancer Surgery alone
Chemotherapy followed by surgery
Definitive chemo radiation
Stage III—oesophageal Chemo radiation followed by surgery
cancer Preoperative chemotherapy followed by surgery
Definitive chemo radiation
Stage IV—oesophageal Chemo radiation followed by surgery (for patients with stage IVA
cancer disease)
Chemotherapy, which has provided partial responses for patients with
metastatic distal oesophageal adenocarcinomas
Nd:YAG endoluminal tumour destruction or electrocoagulation
Endoscopic-placed stents to provide palliation of dysphagia
Radiation therapy with or without intraluminal intubation and dilation
Intraluminal brachytherapy to provide palliation of dysphagia
Recurrent oesophageal Palliative use of any of the standard therapies, including supportive
cancer care
9.10 Conclusion
As there is increased incidence of cancers everywhere, there is the need to create

awareness among people. People who are in remote villages have to be educated
about the causes of cancer and hygiene should be maintained in relation to the
drainages, slums. Any symptom of difficult swallowing, inflammation in throat
should not be neglected and ruled out by thorough investigations. Initial stage of
oesophageal cancer has prolonged life span. Proper medication has to be followed
along with regular doctor checkups. Final stage of oesophageal cancer requires high
dosage of chemo and ratio therapies simultaneously. In such cases, patient has to be
admitted and given intra venous supplement of proteins to cope with the treatment
procedures.
There is the immediate need to enhance the prognosis of final stage oesophageal
cancer patients. Treatment should be in such a way that the effect of the drugs should
not damage the other organs in the body. A combined administration of supporting
drugs that minimize the effect of radiation and chemos has to be recommended to
patients. The kind of nutrients that supports patients from treatment has to be
developed according to the age of the patients.
Conflicts of Interest None
References
American Cancer Society: Cancer Facts and Figures. 2019

Blot WJ, McLaughlin JK (1999) The changing epidemiology of esophageal cancer. Semin Oncol
26(5 Suppl 15):2–8
Brown LM, Devesa SS, Chow WH (2008) Incidence of adenocarcinoma of the esophagus among
white Americans by sex, stage, and age. J Natl Cancer Inst 100(16):1184–1187
Bruzzi JF, Munden RF, Truong MT, Marom EM, Sabloff BS, Gladish GW, Iyer RB, Pan T-S,
Macapinlac HA (2007) PET/CT of esophageal cancer: it’s role in clinical management. Radio-
graphics 27(6):1635–1652
Cook MB, Corley DA, Murray LJ (2014) Gastro esophageal reflux in relation to adenocarcinomas
of the esophagus: a pooled analysis from the Barrett’s and Esophageal Adenocarcinoma
Consortium (BEACON). PLoS One 9:e103508
Cynthia C, Barbara B (2012) Laboratory tests and diagnostic procedures. Elsevier Health Sciences,
Philadelphia
DeJonge PJ, van Blankenstein M, Grady WM, Kuipers EJ (2014) Barrett’s esophagus: epidemiol-
ogy, cancer risk and implications for management. Gut 63(1):191–202
Falk GW (2009) Risk factors for esophageal cancer development. Surg Oncol Clin N Am 18
(3):469–485
Ferri FF (2013) Tumors. Ferri’s clinical advisor. Mosby, Philadelphia, pp 389–391
Fiorica F, Di Bona D, Schepis F (2004) Preoperative chemoradiotherapy for oesophageal cancer: a
systematic review and meta-analysis. Gut 53(7):925–930
Gerdes H, Ferguson MK (2002) Palliation of esophageal cancer. In: Posner MC, Vokes EE,
Weichselbaum RR (eds) Cancer of the upper gastrointestinal tract. PMPH, Raleigh, p 184
Ginsberg RJ (1998) Cancer treatment in the elderly. J Am Coll Surg 187(4):427–428
Kim TJ, Kim HY, Lee KW, Kim MS (2009) Multimodality assessment of esophageal cancer:
preoperative staging and monitoring of response to therapy. Radiographics 29(2):403–421
Krasna MJ, Reed CE, Nedzwiecki D (2001) CALGB 9380: a prospective trial of the feasibility of
thoracoscopy/laparoscopy in staging esophageal cancer. Ann Thorac Surg 71(4):1073–1079
Kubo A, Corley DA (2004) Marked multi-ethnic variation of esophageal and gastric cardiac
carcinomas within the United States. Am J Gastroenterol 99(4):582–588
Lagergren J, Lagergren P (2013) Recent developments in esophageal adenocarcinoma. CA Cancer J
Clin 63(4):232–248
Lao-Sirieix P, Caldas C, Fitzgerald RC (2010) Genetic predisposition to gastro-esophageal cancer.
Curr Opin Genet Dev 20(3):210–217
Mariette C, Dahan L, Mornex F (2014) Surgery alone versus chemo radiotherapy followed by
surgery for stage I and II esophageal cancer: final analysis of randomized controlled phase III
trial FFCD 9901. J Clin Oncol 32(23):2416–2422
Mayer RJ (2008) Gastrointestinal tract cancer. In: Longo DL, Fauci AS, Kasper DL, Hauser SL,
Jameson JL, Loscalzo J (eds) Harrison’s principles of internal medicine. 1, 18th edn. McGraw-
Hill Medical Publishing Division, New York, pp 764–765
Montgomery EA (2014) Oesophageal cancer. In: Stewart BW, Wild CP (eds) World cancer report.
World Health Organization, Geneva, pp 528–543
Pennathur A, Gibson MK, Jobe BA, Luketich JD (2013) Oesophageal carcinoma. Lancet 381
(9864):400–412
Polednak AP (2003) Trends in survival for both histologic types of esophageal cancer in US
surveillance, epidemiology and end results areas. Int J Cancer 105(1):98–100
Prabhu A, Obi KO, Rubenstein JH (2014) The synergistic effects of alcohol and tobacco consump-
tion on the risk of esophageal squamous cell carcinoma: a meta-analysis. Am J Gastroenterol
109(6):822–827
Priante AV, Castilho EC, Kowalski LP (2011) Second primary tumors in patients with head and
neck cancer. Curr Oncol Rep 13(2):132–137
Reed MF, Tolis G Jr, Edil BH (2005) Surgical treatment of esophageal high-grade dysplasia. Ann
Thorac Surg 79(4):1110–1115
Rice TW, Kelsen D, Blackstone EH (2017) Esophagus and esophagogastric junction. In: Amin MB,
Edge SB, Greene FL et al (eds) AJCC cancer staging manual, 8th edn. Springer, New York, pp
185–202
Scherübl H, Steinberg J, Schwertner C, Mir-Salim P, Stölzel U, de Villiers EM (2008) Coincidental
squamous cell cancers of the esophagus, head, and neck: risk and screening. HNO 56
(6):603–608
Sewram V, Sitas F, O’connell D, Myers J (2014) Diet and esophageal cancer risk in the Eastern
Cape Province of South Africa. Nutr Cancer 66:791–799
Stahl M, Mariette C, Haustermans K, Cervantes A, Arnold D (2013) ESMO Guidelines Working,
Group. Oesophageal cancer: ESMO clinical practice guidelines for diagnosis, treatment and
follow-up. Ann Oncol 24(6):24–25
Tietjen TG, Pasricha PJ, Kalloo AN (1994) Management of malignant esophageal stricture with
esophageal dilation and esophageal stents. Gastrointest Endosc Clin N Am 4(4):851–862
Vazquez-Sequeiros E, Norton ID, Clain JE (2001) Impact of EUS-guided fine-needle aspiration on
lymph node staging in patients with esophageal carcinoma. Gastrointest Endosc 53(7):751–757
Yamada T (2011) Textbook of gastroenterology. Wiley, Chichester, pp 1590–1591
Chapter 10
Association Between IL6 Gene
Polymorphisms and Gastric Cancer Risk: A
Meta-Analysis of Case-Control Studies
Henu Kumar Verma, Neha Merchant, and L. V. K. S. Bhaskar
Abstract Interleukin-6 (IL-6) is a multifunctional cytokine, which plays a vital role

in inflammation as well as tumorigenesis. Several studies have demonstrated that the
association of IL6 -174 G/C (rs1800795) and -572 G/C (rs1800796) promoter
polymorphisms influences transcription and has been found to trigger the risk of
gastric tumor advancement with inconsistent and controversial result. The present
study aims at collecting eligible articles through extensive search in PubMed,
MEDLINE, and Embase databases. Additionally, the analysis also included
15 case–control investigations. MetaGenyo web tool was used to perform the
meta-analysis. No substantial association was observed between IL6 polymorphisms
and GC. In conclusion, our study signifies that polymorphisms of IL6, -174 G/C, and
-572 G/C are not linked with GC risk.
Keywords Gastric cancer · IL-6 gene · -174 G/C · -572 G/C · Meta-analysis
Abbreviations
GC Gastric cancer
IL-6 Interleukin 6
H. pylori Helicobacter pylori
NLM National Library of Medicine
SNPs Single nucleotide polymorphisms
CBLD Chinese Biomedical Literature Database
H. K. Verma
Stem Cell Laboratory, Institute of Endocrinology and Oncology, Naples, Italy
N. Merchant
Department of Hematology and Medical Oncology, Winship Cancer Institute, Emory
University, Atlanta, GA, USA
L. V. K. S. Bhaskar (*)
Department of Zoology, Gurughasidas University, Bilaspur, India
https://doi.org/10.1007/978-981-15-6487-1_10
172 H. K. Verma et al.
HWE Hardy–Weinberg equilibrium

P value Probability value
OR Odds ratio
10.1 Introduction
Inflammation is an essential innate immune response induced by microbial infection

and tissue damage. Numerous studies have provided a wide range of clinical
evidence that chronic inflammation is linked with elevated risk of Gastric cancer
(GC) (Greten and Grivennikov 2019; Multhoff et al. 2011; Bockerstett and DiPaolo
2017). Cytokines are a wide range of small proteins secreted by immune cells,
including nucleated cells and work as an intracellular messenger in the immune
system (Lowry 1993). Cytokine is a key mediator of diagnosis and treatment during
inflammation in many diseases (Verma et al. 2016). The potential association
between multifunctional cytokines and GC has been examined by several investi-
gators. Among those, Interleukin 6 (IL-6) is known to function as both a
pro-inflammatory cytokine as well as an anti-inflammatory myokine regulator
(Tanaka et al. 2014). IL-6 belongs to a family of pleiotropic cytokine and modulates
cell proliferation and differentiation. Previous data has demonstrated that IL-6 level
was increased in mucosa, which leads to the inflammatory microenvironment in
Helicobacter pylori (H. pylori) related gastritis (Yamaoka et al. 1996). Further,
overexpression of IL6 is strongly associated with an increased risk of GC develop-
ment and progression (Madej-Michniewicz et al. 2015). Therefore, based on the
earlier reports, IL-6 is closely linked to occurrence and development of cancer.
The gene coding for IL6 is located on chromosome 7p21 and comprises
184 amino acids, which fold as a 4 alpha-helix bundle structure (Choy and Rose-
John 2017). Understanding the genetic diversity with population genetic structure of
IL6 will aid in predicting tumor risk as well as in reducing mortality. To date, several
single nucleotide polymorphisms (SNPs) have been identified in the promoter region
of IL6 (Terry et al. 2000). Among them, IL6 -174 G/C (rs1800795) and -572 G/C
(rs1800796) are the most widely studied polymorphisms in several cancers including
GC. However, previous investigations have yielded varying results regarding the
relationship between IL6 promoter polymorphisms and gastric cancer (Chakraborty
et al. 2017; Markkula et al. 2014). It could be because of the insignificant sample
size, variations in genotyping methods, and ethnicity of the populations. In order to
assess the precise role of IL6 promoter polymorphism on GC susceptibility, we have
conducted this meta-analysis of all existing case–control studies.
10 Association Between IL6 Gene Polymorphisms and Gastric Cancer Risk: A. . . 173
10.2 Methods
10.2.1 Study Selection Strategy
To evaluate the relation between IL6 promoter polymorphisms and the risk of GC,
all potentially pertinent articles were searched and identified according to the
PRISMA guidelines (Liberati et al. 2009). Pubmed, Web of Science, and EMBASE
Database were searched using the following keywords: Interleukin-6 and gastric
cancer, IL6, IL6 -174 G/C, rs1800795, -572 G/C, and rs1800796. The last search
was executed on 26 April 2020.
10.2.2 Literature Inclusion and Exclusion Criteria
Two investigators selected eligible studies independently. Studies that met the
following criteria were included in this meta-analysis: (1) case–control study on
GC and IL6 promoter polymorphisms; (2) genotypes available for calculating odds
ratio (OR) and 95% confidence interval (CI). The exclusion criteria for this meta-
analysis were as follows: (1) studies with no specific control group;
(2) non-availability of genotype data. The quality evaluation of all eligible studies
and data extraction of information was made with consensus and the discrepancy
between investigators was resolved by cross-checking the data. From each paper,
name of the first author, publication year, country and ethnicity of the participants,
genotypes in cases and control subjects were collected and documented in
Table 10.1.
10.2.3 Statistical Analysis
The strength of association between IL6 polymorphism (-174 G/C and -572 G/C)
and GC was assessed for all studies. The crude ORs and their corresponding 95%
confidence interval (CI) limits were calculated. The presence of heterogeneity was
evaluated with the Cochran’s Q test and inconsistency I2 statistics. Based on the
extent of heterogeneity, fixed effects model (FEM) or random effects model (REM)
were adopted for pooled analysis. The association between IL6 polymorphisms and
GC was analyzed in dominant, recessive, and allelic genetic models. To assess the
robustness of the study, sensitivity analysis was performed by overlooking each
study one time and estimating the Odd Ratio (OR) for the remaining studies.
Publication bias was measured by the use of a funnel plot and Egger’s test.
MetaGenyo web tool was used to perform the meta-analysis (Martorell-Marugan
et al. 2017).
Table 10.1 The characteristics of included studies in present meta-analysis
Country/ Case/ Cases Control HW

First author (year) ethnicity control CC GC GG CC GC GG P value
IL6 -174 G/C (rs1800795)
Dos Santos et al. Brazil/ 52/87 6 17 29 10 35 42 0.517
(2019) Caucasian
Attar et al. (2017) Iran/ 100/ 7 30 63 13 187 161 <0.001
Caucasian 361
Ramis et al. (2017) Brazil/ 0.09/38 0 2 7 2 13 23 0.927
Caucasian
Sampaio et al. Portugal/ 50/50 8 25 17 6 25 19 0.608
(2015) Caucasian
Pohjanen et al. Finland/ 56/179 8 34 14 56 86 37 0.706
(2013) Caucasian
Yong et al. (2010) China/Asian 142/ 0 37 105 0 2 198 0.943
200
Crusius et al. (2008)France/ 243/ 43 122 78 206 517 415 0.044
Caucasian 1138
Deans et al. (2007) UK/ 197/ 43 83 71 44 101 79 0.258
Caucasian 224
Gatti et al. (2007) Brazil/ 56/112 1 13 42 11 53 48 0.509
Caucasian
Kamangar et al. Finland/ 102/ 27 54 21 43 58 51 0.004
(2006) Caucasian 152
Xing et al. (2006) China/Asian 65/71 0 3 62 0 4 67 0.807
El-Omar et al. USA/ 209/ 28 98 83 34 91 88 0.205
(2003) Caucasian 213
Hwang et al. (2003) USA/ 30/30 2 9 19 0 8 22 0.399
Caucasian
IL6 -572 G/C (rs1800796)
Mrtinez-Campos Mexico/ 122/ 18 55 49 15 58 49 0.733
et al. (2019) Caucasian 122
Dos Santos et al. Brazil/ 52/87 2 10 40 1 22 64 0.555
(2019) Caucasian
Kang et al. (2009) Korea/Asian 332/ 21 133 178 17 140 169 0.078
326
Xing et al. (2006) China/Asian 65/71 2 4 59 4 11 56 0.005
Hwang et al. (2003) USA/Asian 30/30 16 13 1 16 13 1 0.394
Hwang et al. (2003) USA/ 30/30 3 16 11 5 7 18 0.020
Caucasian
10.3 Results
10.3.1 Characteristics of Published Studies
Our systematic literature search identified 436 articles. Based on the inclusion
and exclusion criteria, unrelated or duplicate studies were excluded by reading titles
and abstracts. Ninety-six relevant articles were selected for further assessment and
71 studies were consequently excluded after reading the full text to avoid discrep-
ancy. Finally, 15 case–control studies fulfilled our study criteria (Fig. 10.1). Out of
which, IL6 -174 G/C genotypes were extracted from thirteen papers (Dos Santos
et al. 2019; Attar et al. 2017; Ramis et al. 2017; Sampaio et al. 2015; Pohjanen et al.
2013; Yong et al. 2010; Crusius et al. 2008; Deans et al. 2007; Gatti et al. 2007;
Kamangar et al. 2006; Xing et al. 2006; El-Omar et al. 2003; Hwang et al. 2003). The
IL6 -572 G/C genotypes were extracted from six papers (Dos Santos et al. 2019;
Xing et al. 2006; Hwang et al. 2003; Martínez-Campos et al. 2019; Kang et al. 2009).
Hwang et al. paper has analyzed samples from two ethnicities, hence it is considered
as two studies (Hwang et al. 2003). The genotype distributions and main character-
istics of studies are presented in Table 10.1. For IL6 -174 G/C, the heterogeneity test
indicated significant heterogeneity between studies (CG+CC vs. GG: Pheterogeneity
<0.001, I2 ¼ 72%), but no heterogeneity was observed between studies of IL6 -572
G/C (CG+CC vs. GG: Pheterogeneity ¼ 0.232, I2 ¼ 27%) (Table 10.2).
Records identified through

PubMed, Embase and other
database searching (n=436)
Duplicates and irrelevant

Records removed (n=340)
Records excluded after

Records screened (n=96) reading titles and
abstracts (n=81)
Papers included in meta analysis

(n=15)
IL6 -174 G/C data IL6 -572 G/C data extracted

extracted (n=13) (n=6)
Fig. 10.1 Flowchart of study selection for the current study

Table 10.2 Associations of interleukin 6 gene polymorphisms with the risk of gastric cancer
Allele model Recessive model Dominant model (CG
IL6 -174 G/C (rs1800795) (C vs. G) (CC vs. GC+GG) +CC vs. GG)
Number of studies 13 11 13
Test of OR 0.96 0.95 1.01
association 95% CI [0.74–1.24] [0.77–1.16] [0.69–1.48]
p value 0.738 0.584 0.960
Model REM FEM REM
Test of p value <0.001 0.222 <0.001
heterogeneity
I2% 76% 23% 79%
Publication Egger’s test 0.903 0.980 0.791
bias p value
IL6 -572 G/C (rs1800796) Allele model Recessive model Dominant model (CG
(C vs. G) (CC vs. GC+GG) +CC vs. GG)
Number of studies 6 6 6
Test of OR 0.99 1.11 0.94
association 95% CI [0.82–1.18] [0.74–1.66] [0.74; 1.19]
p value 0.872 0.627 0.611
Model FEM FEM FEM
Test of p value 0.440 0.773 0.232
heterogeneity I2% 0% 0% 27%
Egger’s test p value 0.680 0.642 0.968
FEM fixed effect model, REM random effect model, OR Odds ratio, 95% CI 95% confidence
interval
10.4 Quantitative Data Synthesis
To explore the correlation between IL6 promoter polymorphisms and the risk of GC,
15 studies of IL6 -174 G/C polymorphism (1311 cases/ 2855 control), and six
studies of IL6 -572 G/C polymorphism (631 cases /666 controls) were used. Meta-
analysis of IL6 -174 G/C polymorphism and GC is documented in Fig. 10.2a, which
did not reveal significant association between IL6 -174 G/C polymorphism and
gastric cancer in the allelic model (C vs. G; OR ¼ 0.96, 95% CI: 0.74–1.24, P ¼
0.738), recessive model (CC vs. GC+GG; OR ¼ 0.95, 95% CI: 0.77–1.16, P ¼
0.584), and dominant models (CG+CC vs. GG; OR ¼ 1.01, 95% CI: 0.69–1.48, P ¼
0.960). The pooled effect estimates presented in Fig. 10.2b shows that IL6 -572 G/C
is not associated with GC in allelic model (C vs. G; OR ¼ 0.99, 95% CI: 0.82–1.18,
P ¼ 0.872), recessive model (CC vs. GC+GG; OR ¼ 1.11, 95% CI: 0.74–1.66, P ¼
0.627), and dominant models (CG+CC vs. GG; OR ¼ 0.94, 95% CI: 0.74–1.19, P ¼
0.611).
Fig. 10.2 Forest Plot of meta-analysis of the IL-6 polymorphism and gastric cancer risk. (a) IL6
-174 G/C; (b) IL6 -572 G/C
10.4.1 Sensitivity Analysis and Publication Biases
Sensitivity analysis was carried out with pooled effect estimates by omitting each
study one time to evaluate the stability of the outcomes. The outcomes of sensitiv-
ity analysis presented in Fig. 10.3 suggest that no single study could influence
the pooled ORs of IL6 -174 G/C and IL6 -572 G/C polymorphisms. Visual
inspection of Begg’s funnel plots did not show asymmetry for both IL6 -174 G/C
and IL6 -572 G/C polymorphisms (Fig. 10.4a, b) indicating that there is no
publication bias. The same was confirmed by Egger’s test p values (P > 0.05).
10.5 Discussion
Despite recent progress in clinical practice, GC remains the third most common
cancer-related death worldwide. According to current data, in 2017, more than 1.22
million new cases of GC occurred and nearly 8,65,000 patients have died due to GC
Fig. 10.3 Sensitivity analysis for the association between IL-6 polymorphisms and gastric cancer
risk. (a) IL6 -174 G/C; (b) IL6 -572 G/C
(Russi et al. 2019; Etemadi et al. 2020). To date, the exact causes of GC still remain
unknown. Nevertheless, it has been proven that cytokines play a role in inflamma-
tion, and can also induce cell transformation in the development of cancer and
chemoresistance (Conlon et al. 2019; Verma et al. 2020). Interleukins are low-
molecular-weight cytokine expressed by leukocytes and are involved in normal
functioning of the immune system. Further, disruptions of interleukins level may
lead to immune deficiencies and tumorigenesis (Larsen et al. 2018). Subsequently, it
has been reported that some mutations in interleukin genes lead to increased risk of
GC development (Wang et al. 2014).
To date, several case–control studies have explored the association between IL6 -
174 G/C and IL6 -572 G/C polymorphism on the susceptibility to GC. However,
small sample sizes, different genotyping methods, and variation in minor allele
frequencies across ethnicities leads to the lack of consistency in results. Therefore,
we have performed the present meta-analysis to precisely study the association of
Fig. 10.4 Funnel plot to publication bias in meta-analysis about IL-6 polymorphisms and gastric
cancer risk. (a) IL6 -174 G/C; (b) IL6 -572 G/C
IL6 polymorphism with GC risk. In this comprehensive meta-analysis we have

observed that the IL6 -174 G/C and IL6 -572 G/C polymorphisms are not signif-
icantly associated with the risk of GC. The results of this meta-analysis are consistent
with the results of previous meta-analysis in which no association between GC risk
and IL6 -174 G/C (Jafari-Nedooshan et al. 2019; Yunxia Liu et al. 2018; Wang et al.
2018, 2012) or IL6 -572 G/C (Wang et al. 2018, 2012; Peng et al. 2018; Du et al.
2015) was documented. However, some meta-analyses have demonstrated increased
GC risk for IL6 -174 G/C (Wang et al. 2018; Tian et al. 2015) or IL6 -572 G/C (Liu
et al. 2018) in Asian populations.
In conclusion, our study indicates that the IL6 -174 G/C and IL6 -572 G/C
polymorphisms are not correlated with GC risk. Soon, a large population based
case–control studies would be potentially needed for validation of Interleukin 6 gene
association with GC risk.
References
Attar M, Mansoori M, Shahbazi M (2017) Interleukin-6 genetic variation and susceptibility to

gastric cancer in an Iranian population. APJCP 18(11):3025–3029
Bockerstett KA, DiPaolo RJ (2017) Regulation of gastric carcinogenesis by inflammatory cyto-
kines. Cell Mol Gastroenterol Hepatol 4(1):47–53
Chakraborty B, Vishnoi G, Gowda SH, Goswami B (2017) Interleukin-6 gene-174 G/C promoter
polymorphism and its association with clinical profile of patients with multiple myeloma. Asia
Pac J Clin Oncol 13(5):e402
Choy E, Rose-John S (2017) Interleukin-6 as a multifunctional regulator: inflammation, immune
response, and fibrosis. J Scleroderma Relat Disord 2(2_suppl):S1–S5
Conlon KC, Miljkovic MD, Waldmann TA (2019) Cytokines in the treatment of cancer. J Interf
Cytokine Res 39(1):6–21
Crusius JB, Canzian F, Capella G, Pena AS, Pera G, Sala N et al (2008) Cytokine gene poly-
morphisms and the risk of adenocarcinoma of the stomach in the European prospective
investigation into cancer and nutrition (EPIC-EURGAST). Ann Oncol 19(11):1894–1902
Deans C, Rose-Zerilli M, Wigmore S, Ross J, Howell M, Jackson A et al (2007) Host cytokine
genotype is related to adverse prognosis and systemic inflammation in gastro-oesophageal
cancer. Ann Surg Oncol 14(2):329–339
Dos Santos MP, Sallas ML, Zapparoli D, Orcini WA, Chen E, Smith MAC et al (2019) Lack of
association between IL-6 polymorphisms and haplotypes with gastric cancer. J Cell Biochem
120(6):9448–9454
Du Y, Gao L, Zhang K, Wang J (2015) Association of the IL6 polymorphism rs1800796 with
cancer risk: a meta-analysis. Genet Mol Res 14(4):13236–13246
El-Omar EM, Rabkin CS, Gammon MD, Vaughan TL, Risch HA, Schoenberg JB et al (2003)
Increased risk of noncardia gastric cancer associated with proinflammatory cytokine gene
polymorphisms. Gastroenterology 124(5):1193–1201
Etemadi A et al (2020) The global, regional, and national burden of stomach cancer in 195 countries,
1990-2017: a systematic analysis for the Global Burden of Disease study 2017. Lancet
Gastroenterol Hepatol 5(1):42–54
Gatti LL, Burbano RR, Zambaldi-Tunes M, de Lábio RW, de Assumpção PP, de Arruda Cardoso-
Smith M et al (2007) Interleukin-6 polymorphisms, Helicobacter pylori infection in adult
Brazilian patients with chronic gastritis and gastric adenocarcinoma. Arch Med Res 38
(5):551–555
Greten FR, Grivennikov SI (2019) Inflammation and cancer: triggers, mechanisms, and conse-
quences. Immunity 51(1):27–41
Hwang IR, Hsu PI, Peterson LE, Gutierrez O, Kim JG, Graham DY et al (2003) Interleukin-6
genetic polymorphisms are not related to Helicobacter pylori-associated gastroduodenal dis-
eases. Helicobacter 8(2):142–148
Jafari-Nedooshan J, Dastgheib SA, Kargar S, Zare M, Raee-Ezzabadi A, Heiranizadeh N et al
(2019) Association of IL-6 -174 G>C polymorphism with susceptibility to colorectal cancer
and gastric cancer: a systematic review and meta-analysis. Acta Med 62(4):137–146
Kamangar F, Abnet CC, Hutchinson AA, Newschaffer CJ, Helzlsouer K, Shugart YY et al (2006)
Polymorphisms in inflammation-related genes and risk of gastric cancer (Finland). Cancer
Causes Control 17(1):117–125
Kang JM, Kim N, Lee DH, Park JH, Lee MK, Kim JS et al (2009) The effects of genetic
polymorphisms of IL-6, IL-8, and IL-10 on Helicobacter pylori-induced gastroduodenal dis-
eases in Korea. J Clin Gastroenterol 43(5):420–428
Larsen KM, Minaya MK, Vaish V, Peña MMO (2018) The role of IL-33/ST2 pathway in
tumorigenesis. Int J Mol Sci 19(9):2676
Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gotzsche PC, Ioannidis JP et al (2009) The PRISMA
statement for reporting systematic reviews and meta-analyses of studies that evaluate health care
interventions: explanation and elaboration. Ann Intern Med 151(4):W65–W94
Liu Y, Xu Y, Wang Y, Yao Y, Yang J (2018) Associations between interleukin gene polymor-
phisms and the risk of gastric cancer: a meta-analysis. Clin Exp Pharmacol Physiol 45
(12):1236–1244
Lowry SF (1993) Cytokine mediators of immunity and inflammation. Arch Surg 128
(11):1235–1241
Madej-Michniewicz A, Budkowska M, Sałata D, Dołęgowska B, Starzyńska T, Błogowski W
(2015) Evaluation of selected interleukins in patients with different gastric neoplasms: a
preliminary report. Sci Rep 5:14382
Markkula A, Simonsson M, Ingvar C, Rose C, Jernstrom H (2014) IL6 genotype, tumour ER-status,
and treatment predicted disease-free survival in a prospective breast cancer cohort. BMC Cancer
14:759
Martínez-Campos C, Torres-Poveda K, Camorlinga-Ponce M, Flores-Luna L, Maldonado-Bernal C,
Madrid-Marina V et al (2019) Polymorphisms in IL-10 and TGF-β gene promoter are associated
with lower risk to gastric cancer in a Mexican population. BMC Cancer 19(1):453
Martorell-Marugan J, Toro-Dominguez D, Alarcon-Riquelme ME, Carmona-Saez P (2017)
MetaGenyo: a web tool for meta-analysis of genetic association studies. BMC Bioinf 18(1):563
Multhoff G, Molls M, Radons J (2011) Chronic inflammation in cancer development. Front
Immunol 2:98
Peng X, Shi J, Sun W, Ruan X, Guo Y, Zhao L et al (2018) Genetic polymorphisms of IL-6
promoter in cancer susceptibility and prognosis: a meta-analysis. Oncotarget 9
(15):12351–12364
Pohjanen VM, Koivurova OP, Makinen JM, Karhukorpi JM, Joensuu T, Koistinen PO et al (2013)
Interleukin 6 gene polymorphism -174 is associated with the diffuse type gastric carcinoma.
Genes Chromosomes Cancer 52(10):976–982
Ramis IB, Vianna JS, Gonçalves CV, von Groll A, Dellagostin OA, da Silva PEA (2017) Poly-
morphisms of the IL-6, IL-8 and IL-10 genes and the risk of gastric pathology in patients
infected with Helicobacter pylori. J Microbiol Immunol Infect 50(2):153–159
Russi S, Verma HK, Laurino S, Mazzone P, Storto G, Nardelli A et al (2019) Adapting and
surviving: intra and extra-cellular remodeling in drug-resistant gastric cancer cells. Int J Mol Sci
20:15
Sampaio AM, Balseiro SC, Silva MR, Alarcão A, d'Aguiar MJ, Ferreira T et al (2015) Association
between IL-4 and IL-6 expression variants and gastric cancer among Portuguese population. GE
Port J Gastroenterol 22(4):143–152
Tanaka T, Narazaki M, Kishimoto T (2014) IL-6 in inflammation, immunity, and disease. Cold
Spring Harb Perspect Biol 6(10):a016295
Terry CF, Loukaci V, Green FR (2000) Cooperative influence of genetic polymorphisms on
interleukin 6 transcriptional regulation. J Biol Chem 275(24):18138–18144
Tian G, Mi J, Wei X, Zhao D, Qiao L, Yang C et al (2015) Circulating interleukin-6 and cancer: a
meta-analysis using Mendelian randomization. Sci Rep 5:11394
Verma H, Mishra H, Khodiar PK, Patra PK, Bhaskar LV (2016) NOS3 27-bp and IL4 70-bp VNTR
polymorphisms do not contribute to the risk of sickle cell crisis. Turk J Haematol 33(4):365–366
Verma HK, Falco G, Bhaskar LVKS (2020) Molecular signaling pathways involved in gastric
cancer chemoresistance. In: Raju GSR, Bhaskar LVKS (eds) Theranostics approaches to gastric
and colon cancer. Springer, Singapore, pp 117–134
Wang J, He W, Liu J, Nong L, Wei Y, Yang F (2012) Association of IL-6 polymorphisms with
gastric cancer risk: evidences from a meta-analysis. Cytokine 59(1):176–183
Wang XQ, Terry PD, Cheng L, Yan H, Wang JS, Wu WA et al (2014) Interactions between pork
consumption, CagA status and IL-1B-31 genotypes in gastric cancer. World J Gastroenterol 20
(25):8151–8157
Wang X, Yang F, Xu G, Zhong S (2018) The roles of IL-6, IL-8 and IL-10 gene polymorphisms in
gastric cancer: a meta-analysis. Cytokine 111:230–236
Xing P, Xiao D, Zeng Q, Gao W, Wang Y, Wang H (2006) Relationship between cytokine gene
polymorphisms on development and clinical characteristics of gastric adenocarcinoma. Chin J
General Surg 15:659–663
Yamaoka Y, Kita M, Kodama T, Sawai N, Imanishi J (1996) Helicobacter pylori cagA gene and
expression of cytokine messenger RNA in gastric mucosa. Gastroenterology 110(6):1744–1752
Yong Z, Ying X, Feng G, Xin Z, Feng S (2010) Relativity research on the association between the
interleukin-6 gene polymorphisms and risk of gastric cancer in Wuwei Area of Gansu Province.
Clin J Med Officers 1:23199
Yunxia Liu YX, Wang Y, Yao Y, Yang J (2018) Associations between interleukin gene poly-
morphisms and the risk of gastric cancer: a meta-analysis. Clin Exp Pharmacol Physiol 45
(12):1236–1244
Chapter 11
Immuno-Oncology of Colorectal Cancer
Ramachandra Reddy Pamuru, K. V. Sucharitha, and Ramakrishna Vadde
Abstract The colorectal cancer (CRC) a second leading cancer become most
predominant and causing deaths worldwide. Since its spread, more attention has
been made to control the CRC. For developing anti-tumor therapies, it is important
to know the immune-oncology of CRC. A number of events are identified in the
tumor microenvironment of CRC. This chapter gives details of the basics of CRC,
immune cells of tumor microenvironment, tumor suppression, and repression. These
details of tumor immune-oncology of CRC may help to provide better understanding
of CRC and suggest ways to control CRC.
Keywords Colorectal cancer · Microenvironment · Immune cells · Immune

response · Immunosuppression
11.1 Introduction
Colon carcinoma (CRC), a third leading cancer reported more than 1.2 million cases
worldwide every year and second leading chronic disease in the USA (Rebecca et al.
2019). CRC occupies fourth place in mortality among all cancers in western
countries (Globocan, Agency for research on cancer, WHO, 2017) whereas, in the
USA 2nd death causing most common carcinoma among other cancers (Tenesa and
Dunlop 2009; Jemal et al. 2009). It is very unfortunate that CRCs are silent tumors;
they grow slowly and do not show most of the symptoms until they attain large size.
R. R. Pamuru (*)
Department of Biochemistry, Yogi Vemana University, Kadapa, AP, India
K. V. Sucharitha
Department of Home Sciences, Sri Venkateswara University, Tirupathi, India
R. Vadde
Department of Biotechnology and Bioinformatics, Yogi Vemana University, Kadapa, AP, India
https://doi.org/10.1007/978-981-15-6487-1_11
184 R. R. Pamuru et al.
Due to its heterogeneous nature, CRC does not hold correct prognostic evades and
became most common disease. The reasons for getting CRC are not very clear, but
found majority of these cases are linked to environmental causes rather than muta-
tions at the gene level (heredity). In the colon and rectum, development of CRC is
linked to a variety of risk factors, including microbial environment, food borne
mutagens, and inflammation. Inflammation found 2000 years ago by Greek Physi-
cian Galenus (Reedy 1975) shares close relation with CRC (angiogenesis, lympho-
cytes, macrophages, and mast cells). Most commonly people of age 50 and above are
more prone to CRC. Though it is not very clear about the CRC risk factors, some of
the possible risk factors are mentioned by American Cancer Society (American
Cancer Society 2019) in its report. Moreover, the carcinomas can also call ‘unhealed
wounds’ with a characteristic property of inflammation (heal wounds). One of the
CRC subtypes difficult to react and has high mortality is colitis associated carcinoma
associated with inflammatory bowel disease (Feagins et al. 2009).
The occurrence of CRC is not only restricted to developed and western countries,
it is also causing dreadfulness among populations all over the world. There is a shove
for control and therapeutic developments for CRC and is one of the thrust areas of
research in recent days. In this juncture, lot of information is reviewed on CRC
development, histology, screening, and immunotherapy, but still certain aspects of
CRC are undercover. One of such part not having lot many reviews is immunology
of colorectal cancer, which provides basic information to develop efficient stage
specific immune-therapeutics. It gives a lot of importance if we know the different
aspects situated in microenvironment of CRC along with basics of risk factors for
tumor formation and development. In view of the fact that, the present chapter
emphasized on the basics, microenvironment, cells and immuno-oncology of colo-
rectal cancer.
11.2 Risk Factors and Development of CRC
The most common modifiers and prophesied risk factors for development of CRC
are lack of physical exercise, diet, chain smoking/chewing tobacco, obesity, low
intake of plant based foods and calcium, high intake of processed/red meat, and
alcohol drinking (Table 11.1). These are forecasted risk factors for 55% CRC cases
in the USA. Family/personal history of CRC, hereditary diseases like inflammatory
bowel disease, diabetes, and background of ethnic/race are some of the
non-modifiable risk factors of CRC (Reedy 1975). Age (55 years and above) is
found to be one of the risk factors for CRC, but an increased % of CRC is found in
younger than 55 years and above age group is not limiting the age as a risk factor.
The carcinomas in the colon grow slowly (several years or even a decade) without
showing any symptoms at the early and middle stages of cancer. The identified
symptom at the last stage is blockage of feces and pain, cramping, bleeding, and
rarely tarry stools due to occupation and blockage of polyps/cancer tissue in the
colon (Lisanne et al. 2016). Polyps are the external growths occur on the inner lining
Table 11.1 Showing the possible risk factors and symptoms and diagnosis of colorectal cancer
11
S. No. Possible conditions/factors References

Risk factors
1 A family or personal history of having polyps and CRC Potter (1999), Chang and Ulrich (2003), Pinczowski et al. (1994)
2 Consumption of high amount of processed and red meat
3 Having Crohn’s disease or ulcerative colitis (inflammatory bowel
diseases)
4 Physical inactivity
5 Type 2 diabetes
6 Overweight (obesity)
7 Chain smoking
8 African–Americans
9 High alcohol consumption
Immuno-Oncology of Colorectal Cancer
10 Low consumption of folate or vegetable foods

11 Hormone replacement therapy or use of anti-inflammatory non-
steroidal drugs
Symptoms
1 Abdominal pain and discomfort American Cancer Society-Facts and Figures (American Cancer Society 2019)
2 Change in bowel habits
3 Colon bleeding in the stool
4 Anemia
5 Constipation and diarrhea
6 Sudden weight loss, weakness, and fatigue
Diagnosis of colorectal polyps and cancer
1 Medical test and physical examination American Cancer Society-Facts and Figures (American Cancer Society 2019)
2 Blood tests for complete blood count, liver enzymes, and tumor
markers
3 Proctoscopy: suspected CRC conditions can be identified using
185
proctoscopy by inserting it through anus into colon/rectum to

identify the exact location of CRC
(continued)
186
S. No. Possible conditions/factors References

4 Biopsy: laboratory test can be performed for CRC suspected tis-
sues/polyps by testing genetic mutations, microsatellite instability,
and any mismatch repairs in DNA
5 Imaging test: using sound waves and X-rays under applied mag-
netic field, images can be obtained to know the area of cancer,
spreading of cancer, and CRC response to treatment
6 Sigmoidoscopy: this is a procedure used to examine the rectum
and very last part of the colon. This test can detect polyps, cancer,
and other abnormalities in the sigmoid colon and rectum. During
this exam, a biopsy (tissue sample) may also be removed and sent
for testing
7 Stool DNA: a stool DNA test looks for changes in genes that are
sometimes found in colon cancer cells. This test can find some
colon cancers before symptoms develop
8 Colonoscopy: a colonoscopy examines the entire colon and rec-
tum. During this procedure, polyps can be removed and sent for
testing
9 CT colonography: this is a special X-ray test (also referred to as a
virtual colonoscopy) done of the entire colon using a CT (com-
puted tomography) scanner. This test takes less time and is less
invasive than other tests. However, if a polyp is detected, a
standard colonoscopy needs to be performed
10 Magnetic resonance imaging (MRI): Using radio waves in mag-
netic field images of tissue can be obtained. Endorectal MRI can
help to find and remove CRCs before and after surgery. Metastasis
of CRC can also be detected with MRI
11 Angiography: used to know the metastasis of CRC
R. R. Pamuru et al.
11 Immuno-Oncology of Colorectal Cancer 187
Fig. 11.1 Developmental stages of colorectal carcinoma in colon. (a) Transformation of cryptal
polyp into colorectal carcinoma. (b) Different stages of colorectal cancer and its metastasis to other
parts of the body
of the colon and rectum which grows towards intestinal lumen called colorectal
tumors (Fig. 11.1a). Two types of polyps are identified in colorectal region. They are
adenomas/adenomatous and hyperplasias/inflammatory polyps. Polyps like hyper-
plastic and inflammatory are generally not pre-cancerous and they do not develop
into CRCs, whereas adenomas or adenomatous polyps are pre-cancerous and
responsible for CRCs. Enlarge in polyp size along the length of the colon and rectum
increases the risk of adenoma to develop CRC (Conteduca et al. 2013). Another
pre-cancerous state identified in patients after removal of polyps from the colorectal
region is dysplasia, which shows abnormal cells which develop CRC. Dysplasia is
common in people suffering with Crohn's disease and/or ulcerative colitis, an
inflammatory bowel disease (Fig. 11.2).
The overall risk factors for CRC in general are consumption of high fat diet and
low fiber diet, aging, high consumption of alcohol, chain smoking, no physical
activity, obesity, CRC history in the family, colon or rectal polyps, irritable bowel
disease, and suffering with other cancers. Besides these, consumption of processed
foods/meat and having sprouty2 (tumor suppressor) gene are the high risk factors for
occurrence of CRC. Men are more prone for CRC than women, even at young stage
men can develop the CRC.
Fig. 11.2 Role of polyps in

developing colorectal cancer
11.3 Stages of CRC
The development of CRC is divided into five stages which includes stages 0–4. Each
stage of CRC has distinguished with the varied characters of cell mass (Fig. 11.1b).
Most of the CRC diagnostic in patients are identified in the stage 4 (metastasis).
11.3.1 “0th” Stage
This stage is named as in situ carcinoma where the tumor cells are developing in the
internal layer of rectum/colon and inside the mucosal layer. The cells of this stage are
in initial stage of cancer.
11.3.2 “1st” Stage
Cells in this stage come out from the internal layers of the rectum/colon and appear
on the outer surface of mucosal layers. Spreading of cancerous cells further than the
wall of colon/rectum is not established at this stage.
11.3.3 “2nd” Stage
Cancer cells grow faster and spread towards the lumen of colon/rectum. Cells at this
stage are not grown up to nearby lymph nodes.
11.3.4 “3rd” Stage
Nearby lymph nodes are attached to cancer cells and no spreading of cancer cells to
other parts of the body is characterized in this stage.
11.3.5 “4th” Stage
Tumor grows much bigger and cancer cells extend to other organs of the body. This
stage is also called metastasis. Most affected body parts are lungs, liver, ovaries, and
abdominal cavity membrane lining.
11.4 Symptoms of CRC
Symptoms are not specific at the earliest and stage 2 of the CRC. Many symptoms
are excelling on the stage 3 and 4 of the CRC. The symptoms are supposed to be
observed continuously for not less than 4 weeks to confirm CRC under the doctor’s
observation. The symptoms are (1) feeling not hungry or heaviness of abdomen even
for long time after having food, (2) loss of weight without reason, (3) looks tired or
patient feels fatigue, (4) abdominal pain, (5) red/black blood in stools, which comes
from rectum, (6) iron deficiency due to continuous loss of blood in stools, (7) con-
stipation/diarrhea, (8) changes in habits of bowel, (9) bowel movement cannot make
the bowel empty. The symptoms and diagnosis of CRC is not so easy. However, as
per American Cancer Society report (American Cancer Society 2019) some of these
are presented in Table 11.1.
11.5 Immunology of CRC Microenvironment
The CRC microenvironment is developed due to oncogenic or inflammatory/infec-

tions pathways (Fig. 11.3). A number of cells and events have been taking place in
the microenvironment of CRC. The stromal cells are maintained in the CRC
microenvironment by transforming gut epithelial cells for their survival, growth,
invasion, and metastasis. It is very clear with CRC that these cells are immunogenic
and immune response of the host system is a key for survival of patients. The
extracellular matrix (ECM), vasculature, tumor-infiltrating cells, and molecules
connected to matrix create a microenvironment in colorectal cancer. A variety of
cells and agents are identified in the CRC microenvironment which exhibit distinct
efficient phenotypes that promote adenocarcinoma. In depth study of cancer
Fig. 11.3 Development of colorectal cancer microenvironment
microenvironment may provide solutions for the development of potential drugs

against CRC.
The two main pathways contribute to develop new tumor is extrinsic (inflamma-
tion/infection) and intrinsic (oncogenic activation). In this, infected/damaged cells
release pathogen/damage-associated molecular profile which recognize TLR recep-
tors for activating the nuclear factor-kβ (NF-kβ), hypoxia-inducible factor-1α
(HIF-1α), signal transduce (ST), and its activator of transcription 3 (STAT3).
These factors maintain the inflammatory microenvironment by upregulating the
gene expression of prostaglandins, chemokines, COX2, and cytokines.
11.5.1 Cells of Immune System
The tumor microenvironment activates the immune system by the involvement of

innate immune system, adaptive immune system, and colorectal cancer cells. During
CRC the major cells accumulate in the tumor microenvironment are natural killer
Fig. 11.4 Immune and other cells present in colorectal cancer microenvironment
(NK) cells (Papanikolaou et al. 2004), Macrophages (Algars et al. 2012), Neutro-
phils (Rao et al. 2012), and CDs (Nagorsen et al. 2007) by the response of innate
immune system, whereas adaptive immune system releases T lymphocytes, CD8
cytotoxic, and CD4 helper cells (Koch et al. 2006). These cells can show
prometastatic and proangiogenic effects by releasing inflammatory modulators
(Coussens and Werb 2002). Vijay et al. (2010) reviewed tumor-infiltrating cells in
the CRC microenvironment. The release of a variety of cells in the CRC microen-
vironment intimately linked to suppression or promotion of the tumor development.
Infiltrated cells, such as NK cells, mast cells, myeloid derived suppressor cells
(MDSCs), cancer-associated fibroblasts (CAFs), tumor-associated macrophages
(TAMs), CD4 and CD8 cells, neutrophils, monocytes, dendritic cells (DCs), endo-
thelial progenitor cells (EPCs), endothelial cells, mesenchymal stem cells (MSCs),
and platelets are some of them identified in the CRC microenvironment (Fig. 11.4).
The detailed account of these cells and its functions facilitates to proceed with
immunotherapies.
11.5.1.1 Natural Killer Cells (NKs)
The first line of defense through innate immunity against pathogens is mediated by
natural killer cells (NKs). They also called innate lymphocytes holding cytotoxicity,
which includes tumor suppression through activated immune function and thereby
promots tumor cell apoptosis in CRC (Moriwaki et al. 2009). Besides apoptotic
actions NKs are involved in morphogenesis, repair, metabolism, regeneration, and
tissue remodeling homeostasis (Paul and Lal 2017). There are different subsets of
NKs identified in tissues with diverse homing properties and local maturation
(Stabile et al. 2017). NKs are rich in granzyme-containing granules and perforins
and show potent in vitro cytotoxicity on cancer cells. This action of NKs is explained
with high serum MHC class I molecules which reduce the expression of NKG2D
receptor. Doubrovina et al. (2003) demonstrated in vitro and in vivo tumoricidal
activity of NK cells bearing NKG2D.
11.5.1.2 Mast Cells
Mast cells can express during cancer, besides allergic and other pathological condi-
tions. Though the higher numbers of mast cells are common in major human cancers,
but hypovascularity and better survival of tumor cells are associated with lower
numbers of mast cells in CRC condition (Gulubova and Vlaykova 2009; Fisher et al.
1989). In the periphery of developing tumors accretion of mast cells leads to the
production of stem cell factor from the cancerous tissue (Huang et al. 2006).
Angiogenesis in tumors are triggered by infiltration of mast cell into cancerous
tissue during early stage of tumor growth and mast cell independent angiogenesis
takes up when tumors grow bigger (Coussens et al. 1999). The release of growth
stimulator and proangiogenic factors such as histamine (Dvorak 2005), angiopeptin-
1(Nakayama et al. 2004), BFGF (basic fibroblast growth factor; (Lin et al. 2004)),
TNF-α (tumor necrosis factor-α; (Kneilling et al. 2009)), heparin (Hallgren et al.
2001), VEGF (vascular endothelial growth factor; (Crivellato et al. 2008), and
proteases (Ribatti and Crivellato 2009) in the tumors are mediated by the activated
mast cells.
11.5.1.3 Myeloid Derived Suppressor Cells (MDSCs)
The cells that show similar phenotypic characters if granulocytes and macrophages
belong to myeloid population with immature features are named as myeloid derived
suppressor cells (MDSCs). These cells are identified in the advanced tumor stages of
CRC, especially in the peripheral blood and cancer tissues (Zhang et al. 2013).
MDSCs produce anti-inflammatory cytokines like prostaglandin E2 and arginase,
which are holding strong immune-suppressive functions (Veglia et al. 2018), but are
poor prognostics of CRC (Tada et al. 2016).
11.5.1.4 Tumor-Associated T cells and Macrophages (TAT and TAMs)
The tumor-associated T lymphocytes (T cells; Tregs) and macrophages play an

important role in the behavior of CRC. The T cells repress cell mediated response
of T helper cell type 1 (Th1) and cytotoxic-T cells. The role of T cells in CRC is well
explained where these cells accumulate and perform anti-cancer immune response
along with Th1 inflammatory response, which in turn resolves the inflammation in
colon and rectum (Fridman et al. 2017). In contrast, Tregs immune repression
through expressing FOXP3+ CD4+ T cell types promotes inflammation during
CRC (Saito et al. 2016).
Based on the phenotype and function, macrophages are divided into two subsets
TAM1 and TAM2. The tumor cell death induced molecules like TNF-α, relative
oxygen species, and nitric oxide belong to TAM1 type and are raised during
pro-inflammatory condition (Mantovani et al. 2004). The immunosuppressive,
proangiogenic, and cell growth factors belongs to TAM2 macrophage subtype
which releases at chronic inflammatory condition holds pro-tumorigenic function.
TAM2 macrophages are majorly called tumor-associated macrophages (Qian and
Pollard 2010). However, the elevated phenotypic agility was reported by TAM1 and
2 subtype dichotomization (Aras and Zaidi 2017). The TAMs play a crucial role in
tumor growth, immune suppression, angiogenesis, inflammation, tumor invasion/
metastasis, epithelial-to-mesenchymal transition (EMT), extracellular matrix, and
matrix-associated molecule formation (ECM and MAM) with an association of a
number of factors (Fig. 11.5). Nevertheless, more emphasis is needed to use TATs
and TAMs as immunotherapeutic agents for CRC treatment.
11.5.1.5 CD4 and CD8 Cells
Immunosuppression, a state of reduced immunogenic cytokines IFN-γ and TNF-α

by macrophages or monocytes can initiate the differentiation of CD4+ T lympho-
cytes into T helper 1 and 2 (Th1 or Th2). Th1 and Th2 are responsible to induce
cytokine dependent immune responses. The IFN-γ and TNF-α levels are elevated by
Th1 which would initiate cellular immune response through the production and
activation of NK cells, cytotoxic CD8+ T lymphocytes, monocytes, and macro-
phages. IL-10, IL-4, IL-5, and IL-13 another set of cytokines produce by Th2 are
involved in the humeral immunity (Rubén and Oscar 2015). Moreover, the tumor-
infiltrating lymphocytes (TILs) reduce the response of CD8+ cells and kill the cancer
tissue. But the TILs are inhibited by native T cells with a hold of tumor acquiring
function (Hsiao et al. 2004). Longer disease free survival time is maintained by T
lymphocytes holding a low number of CD8+ where it is correlated positively with
neoplastic epithelium (Deschoolmeester et al. 2010). The Foxp3+ CD8+ cells would
suppress the secretion of IFN-α and proliferation of T lymphocytes (Chaput et al.
2009).
Fig. 11.5 Differential functions of stromal tumor-associated macrophages (TAMs). Various func-
tions of TAMs include (1) cancer progression by releasing growth factors (GFs) such as vascular
endothelial growth factor (VEGF), interleukin (IL)-6, prostaglandin (PGE)-2, basic fibroblast
growth factor (BFGF), platelet derived growth factor (PDGF), and endothelial growth factor
(EGF); (2) angiogenesis (AG) by IL-8, IL-1β, PDGF-β, VEGF, BFGF, cyclooxygenase-2, and
matrix metalloprotease (MMP) release; (3) epithelial-to-mesenchymal transition (EMT)/invasion
(In)/metastasis (Met) function by MMPs (2 and 9), transforming growth factor (TGF)-β, and tumor
necrosis factor (TNF)-α release; (4) release of IL-10, IL-6, PGE-2, nitric oxide (NO), reactive
oxygen intermediates (ROI), and TNF-α induces inflammation; (5) formation of extra cellular
matrix (ECM) and matrix-associated molecules (MAM) through release of MMPs (2 and 9),
cysteine cathepsins (CS), and serine proteases (SP); (6) promotes immunosuppression through
TGF-β, IL-10, PGE-2, prostaglandins (PGs), and indoleamine dioxygenase (IDO)
11.5.1.6 Tumor-Associated Neutrophils
The primary innate responsive cells derived from myeloid precursors and belongs to
the white blood cell group are predominantly know as neutrophils (Coffelt et al.
2016). The longest life in the CRC microenvironment and the pivotal role of
neutrophils in the tumor angiogenesis are becoming popular in recent days (Pillay
et al. 2010). The pro-inflammatory factor interferon gamma (INFγ) plays a crucial
role in extending longer life span of neutrophil (Akgul et al. 2001) and activated
tumor-associated neutrophils function as anti-tumor and pro-tumor (Fridlender et al.
2009). Release of VEGF from tumor cells is stimulated by neutrophils through
oncostatin M release (Queen et al. 2005). Moreover neutrophils are identified with
inflammatory bowel disease related CRC during oxidative stress associated patho-
genesis (Roessner et al. 2008). The anti-cancer action of neutrophils is explained in
many studies (Fig. 11.6). Hydrogen peroxide released by the interaction of neutro-
phils with tumor cells activates Ca2+ influx using Ca2+ channel (TRPM2) and causes
cancer cell death (Gershkovitz et al. 2019). Tumor suppression by nitric oxide
mediated by neutrophils through hepatocyte growth factor, Met and its ligands is
also reported (Finisguerra et al. 2015). Sun et al. (2018) isolated Fas interaction or
Fas ligand mediated cancer suppression of neutrophils from healthy subjects. The
collagenase-2, an enzyme expressed during cancer state is released by the action of
Fig. 11.6 Anti-cancer role of tumor-associated neutrophils
neutrophils. High amount of serum collagenase-2 is an indicator for adverse condi-

tion in CRC patients (Bockelman et al. 2018). Furthermore the role of neutrophils is
not the same in all types of cancers due to its variation in phenotypic heterogeneity
and efficient adaptability.
11.5.1.7 Inflammatory Monocytes
The cells transport from bone marrow to CRC microenvironment shows a typical
role in cancer growth, metastasis and resistance to chemotherapy are called mono-
cytes which belongs to myeloid origin. The level of anti-tumor function of inflam-
matory monocytes always depends on the stage of the tumor and metastasis (Heeren
et al. 2015). Initially the counts of peripheral blood monocytes along with differen-
tiation of CD4+ CD25+ regulatory T cells correlated with the immunity level of the
CRC patients (Chen et al. 2019). The inflammatory monocytes are shown to have
more importance in many cancers, but are still less known in CRC.
11.5.1.8 Dendritic Cells (DCs)
In CRC condition dendritic cells (DCs) show anti-tumor response by induction of

immune response and are identified key antigen presenting cells (APCs) (Palucka
et al. 2010). During development DCs can exhibit tumerogenic and anti-tumerogenic
activities. Steinman et al. (2003) identified the tolerance against T cells in immature
CDs where they carry CD4+ and CD8+ self-antigens. Whereas matured and activated
CDs are identified with T cell proliferation and its differentiation into the helper and
effector lymphocytes (Banchereau et al. 2000). Due to its amphoteric behavior the
role of CDs in CRC is contentious and this has been notified in many studies. Low
levels of CD83, CD86, CD54, and HLA-DR, and elevated IL-10 besides the
suppression of an anti-cancerous IL-12p70 have been reported in the in vitro CRC
explants incubation study with DCs (Michielsen et al. 2011). In an another DCs
tumor-infiltrating in vitro study, Schwaab et al. (2001) found immature phenotypes
with no tumor-associated antigenic systemic response in correlation with Treg cells.

However, the CD4+ and CD8+ polyclonal cell populations are recognized by a range
of antigens which includes antigens of cancer, neoantigens and self or viral derived
antigens (Gee et al. 2018; Scheper et al. 2019). Taking together the immature CDs
can be used as potent immunotherapeutic to improve the survival in the CRC
patients.
11.5.1.9 Mesenchymal Stem Cells (MSCs)
The pluripotent nonhemopoietic cells that are produced from bone marrow, umbil-
ical card, muscles, and adipose tissue and differentiate into various types of immune
cells are known as mesenchymal stem cells (MSCs) (Yuehua et al. 2002). The
human MSCs has receptors of IL-II, TNF-β and γ-interferon. MSCs phenotypes
show CD105, CD90, CD29, CD73, CD44, CD34, CD45, CD14, CD31, vWF,
leukocyte function-associated antigen-3, and stromal cell antigen-1 (Vijay et al.
2010; Marofi et al. 2017). MSCs are the predominant cells in CRC microenviron-
ment. These cells are responsible for tumor-associated stroma formation in primary
tumors. They also possess proangiogenic and immunosuppressive properties,
thereby promote tumor growth and metastasis (Kemp et al. 2005). In addition to
this, MSCs involved in the production of PDGF, CXCL12 and FGF (proangiogenic
factor) from fibroblasts. Cancer growth promoting factors such as endothelial and
pericyte-like cells originated from MSCs (Sanz et al. 2008). Moreover, cancer stem
cell survival is postulated by MSCs (Ning et al. 2008).
11.5.1.10 Eosinophils
Healthy individuals generally hold eosinophils in the colon mucosa with geograph-
ical variations in their number. Eosinophils are identified as anti-CRC immune cells.
The amount of eosinophils is low in the early stages and even at invasive carcino-
mas, whereas highly abundant in adenomas indicates its protective role of eosino-
phils (Moezzi et al. 2000). But the appearance of these cells in advanced cancer is
viewed as a marker than tumor active immune response.
11.5.1.11 Platelets
The platelet components in the blood are important for the restoration and mainte-
nance of endothelial function besides their major function, homeostasis. Early
studies of tumor microenvironment suggested that elevated levels of platelets are
linked to cancer progression (Verheul and Pinedo 1998). Later studies described the
role of platelets in cancer angiogenesis and metastasis (Karpatkin 2003). Activated
platelets release α-granules and dense granules (includes proangiogenic factors like
CXCL12, VEGF, and PDGF) through thromboxane A2 (Stellos et al. 2009). The
proposed mechanistic action of platelets during tumorigenesis is well explained. At

first thrombin production is stimulated by platelets in CRC patients, which activates
the development of cancer cells. Platelets can also activate surface molecules of
cancer cell membranes either by direct contact or ADP activation (Karpatkin 2003).
CRC metastasis spreads by anti-tumor action of the immune system through embry-
onic cancer cells and circulation clearance of tumor cells is contributed by platelets
(Burdick and Konstantopoulos 2004). The studies on CRC in relation to platelets
need more focus to establish the clear-cut mechanism, which may help to improve
the immunotherapy of CRC.
11.5.1.12 Mesenchymal Stromal Cells (MSCs)
The new set of cells used to identify the crime suspects are mesenchymal stromal
cells (MSCs) and are identified in the intestine. In the intestine MSCs are located
closely to lymphatic network and blood vessels, nearby to the CRC cells, suggesting
the role of these cells in the maintenance of homeostasis and cancer in the intestine.
The subsets of MSCs play against pathogens and inflammation by expressing
FAP-α+, ICAM-1+, α-SMA, gp38+, and CD90+ in the healthy intestine (Owens
2015). MSCs promote carcinogenesis in CRC microenvironment. These cells pro-
mote invasion, metastasis, and angiogenesis in the microenvironment of CRC. It is
known that the interaction of MSCs plays a key role in function and proliferation of
immune cells, such as macrophages, T-lymphocytes, DCs, and natural killer cells
which induce tumorigenesis and facilitate tumors to escape from suppression by the
immune system. Moreover, the innate and adaptive immunity of cells are influenced
by MSCs and its secretary factors (Malley et al. 2016). The interaction of MSCs with
cancer cells and immune cells during CRC development and in its microenviron-
ment provides a better understanding to invade the efficacious therapy for CRC.
11.5.2 Endothelial Progenitor Cells
Endothelial cells are specifically lined on the inner side of colon and rectum.
Though, these cells are not directly involved in the CRC development but are the
mediators for several reactions takes place in the colon/rectum during the develop-
ment of different CRC stages. Tumor endothelial cells are holding angiopoietin
receptors (TIE-2) which act as dominant tumor development factors (Lewis et al.
2007). Colon tumor cells can adhere to the walls of microvascular endothelia in
presence of reactive oxygen species promoted by N-nitrosamines of activated human
neutrophils (Ten Kate et al. 2007). The CD34, CD31, and vWF are the identified
markers of endothelial cells during CRC (Kemp et al. 2005). Endothelial type of
MSCs are responsible for cancer progression (Sanz et al. 2008). Moreover, endo-
thelial cells mediate the betaig-h3 extravasation during metastatic transport of tumor
cells through Src (αγβ5) signaling pathway (Ma et al. 2008). Platelets mediated
neoangiogenesis in CRC is done through endothelial progenitor cells. MDSCs can

promote expression of endothelial markers (CD31 and VEGFR2) during early or in
immature cells (Yang et al. 2004) and enter into the cancer tissue endothelia.
However, the light on effective role of endothelial cells in CRC progression is still
in its infancy and open for researchers to continue in this direction.
11.5.3 Cancer-Associated Fibroblasts (CAFs)
The special cells identified in the CRC microenvironment are cancer-associated

fibroblasts (CAFs) crucial molecules for regulation of immunogenicity. The CAF
is the main source of immunomodulatory molecules, including TGF-β and initiates
TGF-β anti-tumor pathway in innate and adaptive immune cells through a “+”ve
feedback mechanism (Hawinkels et al. 2014). Besides this, CAF in association with
extracellular matrix proteins constitute a substantial link for direct contact between
stroma and CRC cells (Vangangelt et al. 2018). The angiogenic factors secreted by
both tumor and the stroma cells interact with respective receptors on endothelial
cells, activating tumor-associated angiogenesis (Michele et al. 2017; Yasuhiko
2010).
11.6 Immune Response in CRC
The gut is rich with immune cells due to its continuous exposure to a large variety of
antigens and microbial flora, which includes many pathogens and toxicants of
different origin. Immunosuppression in tumors is associated with immune response
against cancer growth. At first, in cancerous cells immune system responds with
elevated neoantigens through the antigen processing pathway, where the produced
proteins are converted into peptides by the action of immunoproteasomes (Yewdell
et al. 2003). These peptides through transporter associated antigen processing pro-
teins (TAP) enter into the endoplasmic reticulum (ER) and subsequently onto human
leukocyte antigen class I (HLA class I; (Neefjes et al. 1993)) holding chaperones
such as calreticulin, calnexin, and ER-glycoprotein 57 as associated proteins. The
chaperone and TAP dissociate after stabilization of HLA class I—peptide complex
which reaches to the cell surface through Golgi complex (Neefjes et al. 2011) and are
recognized by CD8+ T cells (Kurts et al. 2010). Furthermore, the attachment of
neoantigens and its intermediates to T cell surface is highly determined by its level of
affinity towards HLA class I alleles (Garstka et al. 2015).
The immune response against tumor growth of TLRs is notable in the CRC
microenvironment. They may show pro- or anti-cancerous effects depends on the
conditions in the CRC microenvironment. TGF-β is another molecule shows gut
homeostasis in its presence and interrupted signaling or mutation in its gene acts as
pro-cancerous.
11.7 Immune Suppression in CRC
Mutations/genetic aberrations of genes responsible to produce antigenic processing

pathway would lead to immune suppression in CRC cells. More than 10 mutations/
megabase of DNA do not restrict the neoantigens to recognize the T cells in CRC
patients. Anyhow the CRCs are strong to evade immune recognition. However, the
presence or absence of MMR in CRCs decides the elevation of immune suppression.
CRCs with no MMR usually alter the antigen processing pathway thereby complete
inhibition of HLA class I expression and immune suppression (Ijsselsteijn et al.
2019). Significant CRC immune suppression is not only restricted to loss of HLA
class I gene (B2M) expression, but also other components of antigen processing
pathway (Dierssen et al. 2007). The tumor cells execute an extraordinary mechanism
to escape from immune action of the cells, even from the self-antigens raised against
them. The amount of neoantigens at the time of colorectal tumor removal is low
which is an abnormal prediction with no immune selection (Rooney et al. 2015).
11.8 Conclusion
The microenvironment of normal cells is not the same as CRC microenvironment. It

is different and a complexed stromal system. CRC microenvironment holds several
stromal cells of different phenotypes which promotes both growth and suppression
of tumor cell growth. A majority of stromal and its associated cells show anti-tumor
activity or tumor suppression function but are not attracted the attention of scientists
to develop therapeutics. The cells like TAM2, neutrophils, and CAFs support the
survival, growth, and metastasis of CRC. The therapeutics are always raised against
the cells involved in the tumor progression. The immuno-oncology of CRC repre-
sents by neutrophils, TAMs, COX-2 inhibitors, ECM, matrix-associated molecules,
NSAIDS, MDSCs, CAFs, MCs and components of cells like prostaglandins etc., are
facilitates the extravagances in the development of therapeutics thereby CRC control
worldwide.
Acknowledgements Authors thank Dr. Jairam Vanamala KP, Associate Professor at Pennsylvania
State University, USA and Dr. Lavanya Reddivari, Assistant Professor at Pennsylvania State
University, USA for their constant support and guidance in writing this book chapter.
Conflicts of Interest Authors declare no conflict of interest.
References
Akgul C, Moulding DA, Edwards SW (2001) Molecular control of neutrophil apoptosis. FEBS Lett
487:318–322
Algars A, Irjala H, Vaittinen S, Huhtinen H, Sundstrom J, Salmi M, Ristamäki R, Jalkanen S (2012)

Type and location of tumor-infiltrating macrophages and lymphatic vessels predict survival of
colorectal cancer patients. Int J Cancer 131:864–873
American Cancer Society (2019) Cancer facts and figures. American Cancer Society, Atlanta
Aras S, Zaidi MR (2017) TAMeless traitors: macrophages in cancer progression and metastasis. Br
J Cancer 117:1583–1591
Banchereau J, Briere F, Caux C, Davoust J, Lebecque S, Liu YJ, Pulendran, Palucka K (2000)
Immunobiology of dendritic cells. Annu Rev Immunol 18:767–811
Bockelman C, Beilmann-Lehtonen I, Kaprio T, Koskensalo S, Tervahartiala T, Mustonen H,
Stenman UH, Sorsa T, Haglund C (2018) Serum MMP-8 and TIMP-1 predict prognosis in
colorectal cancer. BMC Cancer 18:679
Burdick MM, Konstantopoulos K (2004) Platelet-induced enhancement of LS174T colon carci-
noma and THP-1 monocytoid cell adhesion to vascular endothelium under flow. Am J Physiol
Cell Physiol 287(2):C539–C547
Chang CK, Ulrich CM (2003) Hyperinsulinaemia and hyperglycaemia: possible risk factors of
colorectal cancer among diabetic patients. Diabetologia 46:595–607
Chaput N, Louafi S, Bardier A, Charlotte F, Vaillant JC, Menegaux F, Rosenzwajg M, Lemoine F,
Klatzmann D, Taieb J (2009) Identification of CD8 + CD25 + Foxp3 + suppressive T cells in
colorectal cancer. Gut 58:520–529
Chen WZ, Jiang JX, Yu XY, Xia WJ, Yu PX, Wang K, Zhao ZY, Chen ZG (2019) Endothelial cells
in colorectal cancer. World J Gastrointest Oncol 11(11):946–956
Coffelt SB, Max DW, Karin EDV (2016) Neutrophils in cancer: neutral no more. Nat Rev Cancer
16:431–446
Conteduca V, Domenico S, Gianfranco L, Sabino R, Giuseppe I, Franco D (2013) H. pylori
infection and gastric cancer: state of the art (review). Int J Oncol 42:5–18
Coussens LM, Werb Z (2002) Inflammation and cancer. Nature 420(6917):860–867
Coussens LM, Raymond WW, Bergers G, Laig-Webster M, Ole B, Zena W, George HC, Douglas
H (1999) Inflammatory mast cells up-regulate angiogenesis during squamous epithelial carci-
nogenesis. Genes Dev 13(11):1382–1397
Crivellato E, Nico B, Ribatti D (2008) Mast cells and tumour angiogenesis: new insight from
experimental carcinogenesis. Cancer Lett 269(1):1–6
Deschoolmeester V, Boeckx C, Baay M, Weyler J, Wuyts W, Van Marck E, Peeters M, Lardon F,
Vermorken JB (2010) KRAS mutation detection and prognostic potential in sporadic colorectal
cancer using high-resolution melting analysis. Br J Cancer 103:1627–1636
Dierssen JW, de Miranda NF, Ferrone S, van Puijenbroek M, Cornelisse CJ, Fleuren GJ, van
Wezel T, Morreau H (2007) HNPCC versus sporadic microsatellite- unstable colon cancers
follow different routes toward loss of HLA class I expression. BMC Cancer 7:33
Doubrovina ES, Doubrovin MM, Vider E, Sisson RB, O’Reilly RJ, Dupont B, Vyas YM (2003)
Evasion from NK cell immunity by MHC class I chain-related molecules expressing colon
adenocarcinoma. J Immunol 171(12):6891–6899
Dvorak AM (2005) Mast cell-derived mediators of enhanced microvascular permeability, vascular
permeability factor/vascular endothelial growth factor, histamine, and serotonin, cause leakage
of macromolecules through a new endothelial cell permeability organelle, the vesiculo-vacuolar
organelle. Chem Immunol Allergy 85:185–204
Feagins LA, Souza RF, Spechler SJ (2009) Carcinogenesis in IBD: potential targets for the
prevention of colorectal cancer. Nat Rev Gastroenterol Hepatol 6:297–305
Finisguerra V, Di Conza G, Di Matteo M, Serneels J, Costa S, Thompson AA, Wauters E,
Walmsley S, Prenen H, Granot Z, Casazza A, Mazzone M (2015) MET is required for the
recruitment of anti-tumoural neutrophils. Nature 522(7556):349–353
Fisher ER, Paik SM, Rockette H, Jones J, Caplan R, Fisher B (1989) Prognostic significance of
eosinophils and mast cells in rectal cancer: findings from the National Surgical Adjuvant Breast
and Bowel Project (protocol R-01). Hum Pathol 20(2):159–163
Fridlender ZG, Sun J, Kim S, Kapoor V, Cheng G, Ling L, Worthen GS, Albelda SM (2009)
Polarization of tumor associated neutrophil phenotype by TGF-beta: “N1” versus “N2” TAN.
Cancer Cell 16(3):183–194
Fridman WH, Zitvogel L, Sautes-Fridman C, Kroemer G (2017) The immune contexture in cancer
prognosis and treatment. Nat Rev Clin Oncol 14(12):717–734
Garstka MA, Fish A, Celie PH, Joosten RP, Janssen GM, Berlin I, Hoppes R, Stadnik M, Janssen L,
Ovaa H, van Veelen PA, Perrakis A, Neefjes J (2015) The first step of peptide selection in
antigen presentation by MHC class I molecules. Proc Natl Acad Sci U S A 112(5):1505–1510
Gee MH, Han A, Lofgren SM, Beausang JF, Mendoza JL, Birnbaum ME, Bethune MT, Fischer S,
Yang X, Gomez-Eerland R, Bingham DB, Sibener LV, Fernandes RA, Velasco A, Baltimore D,
Schumacher TN, Khatri P, Quake SR, Davis MM, Garcia KC (2018) Antigen identification for
orphan T cell receptors expressed on tumor-infiltrating lymphocytes. Cell 172(3):549–563
Gershkovitz M, Fainsod-Levi T, Zelter T, Sionov RV, Granot Z (2019) TRPM2 modulates
neutrophil attraction to murine tumor cells by regulating CXCL2 expression. Cancer Immunol
Immunother 68:33–43
Gulubova M, Vlaykova T (2009) Prognostic significance of mast cell number and microvascular
density for the survival of patients with primary colorectal cancer. J Gastroenterol Hepatol 24
(7):1265–1275
Hallgren J, Estrada S, Karlson U, Alving K, Pejler G (2001) Heparin antagonists are potent
inhibitors of mast cell tryptase. Biochemistry 40(24):7342–7349
Hawinkels LJ, Paauwe M, Verspaget HW, Wiercinska E, van der Zon JM, van der Ploeg K, Koelink
PJ, Lindeman JH, Mesker W, ten Dijke P, Sier CF (2014) Interaction with colon cancer cells
hyperactivates TGF-beta signaling in cancer-associated fibroblasts. Oncogene 33(1):97–107
Heeren AM, Koster BD, Samuels S, Ferns DM, Chondronasiou D, Kenter GG, Jordanova ES, de
Gruijl TD (2015) High and interrelated rates of PD-L1+CD14+ antigen-presenting cells and
regulatory T cells mark the microenvironment of metastatic lymph nodes from patients with
cervical cancer. Cancer Immunol Res 3:48–58
Hsiao YW, Liao KW, Hung SW, Chu RM (2004) Tumor infiltrating lymphocyte secretion of IL-6
antagonizes tumor-derived TGF-beta 1 and restores the lymphokine- activated killing activity. J
Immunol 172:1508–1514
Huang B, Pan PY, Li Q, Sato AI, Levy DE, Bromberg J, Divino CM, Chen SH (2006) Gr-1+CD115
+ immature myeloid suppressor cells mediate the development of tumor-induced T regulatory
cells and T-cell anergy in tumor-bearing host. Cancer Res 66(2):1123–1131
Ijsselsteijn ME, Petitprez F, Lacroix L, Ruano D, van der Breggen R, Juie C, Morreau H, Sautes-
Fridman C, Fridman WH, de Miranda N (2019) Revisiting immune escape in colorectal cancer
in the era of immunotherapy. Br J Cancer 120(8):815–818
Jemal A, Center MM, Ward E, Thun MJ (2009) Cancer occurrence. Methods Mol Biol 471:3–29
Karpatkin S (2003) Role of thrombin in tumor angiogenesis, implantation, and metastasis.
Pathophysiol Haemost Thromb 33(1):54–55
Kemp KC, Hows J, Donaldson C (2005) Bone marrow-derived mesenchymal stem cells. Leuk
Lymphoma 46(11):1531–1544
Kneilling M, Mailhammer R, Hultner L, Tanja S, Kerstin F, Martin S, Daniel B, Steffen M,
Christian AS, Heidi B, Martin E, Konrad LM, Rupert H, Bernd JP, Roland H, Meinrad G,
Klaus P, Tilo B, Martin R (2009) Direct crosstalk between mast cell-TNF and TNFR1-
expressing endothelia mediates local tissue inflammation. Blood 114(8):1696–1706
Koch M, Beckhove P, Op den Winkel J, Autenrieth D, Wagner P, Nummer D, Specht S,
Antolovic D, Galindo L, Schmitz-Winnenthal FH, Schirrmacher V, Büchler MW, Weitz J
(2006) Tumor infiltrating T lymphocytes in colorectal cancer: tumor-selective activation and
cytotoxic activity in situ. Ann Surg 244:986–992
Kurts C, Robinson BW, Knolle PA (2010) Cross-priming in health and disease. Nat Rev Immunol
10(6):403–414
Lewis CE, De Palma M, Naldini L (2007) Tie2-expressing monocytes and tumor angiogenesis:
regulation by hypoxia and angiopoietin-2. Cancer Res 67(18):8429–8432
Lin XP, Liu WX, Li J (2004) The study on expression of bFGF and quantity of mast cell in infant
hemangiomas of grandulae parotid gland. Shanghai Kou Qiang Yi Xue 13(3):167–178
Lisanne SR, Frank GJK, Barbara B, Theo AMVO, Floor EVL, Monique EVL, Evelien DC (2016)
A case series of intestinal adenomatous polyposis of unidentified etiology; a late effect of
irradiation? BMC Cancer 16:862. https://doi.org/10.1186/s12885-016-2880-2
Ma C, Rong Y, Radiloff DR, Michael BD, Barbara C, Shideng B, Anthony WMC, Fumin L,
Shibo J, Timothy JY, Xiao-Fan W (2008) Extracellular matrix protein betaig-h3/TGFBI pro-
motes metastasis of colon cancer by enhancing cell extravasation. Genes Dev 22(3):308–321
Malley GO, Madelon H, Aileen MH, Rani S, Thomas R, Laurence JE, Aideen ER (2016)
Mesenchymal stromal cells (MSCs) and colorectal cancer: a troublesome twosome for the
anti-tumour immune response? Oncotarget 7(37):60752–60774
Mantovani A, Sica A, Sozzani S, Paola A, Annunciata V, Massimo L (2004) The chemokine system
in diverse forms of macrophage activation and polarization. Trends Immunol 25(12):677–686
Marofi F, Vahedi G, Biglari A, Esmaeilzadeh A, Athari SS (2017) Mesenchymal stromal/stem cells:
a new era in the cell based targeted gene therapy of cancer. Front Immunol 8:1770
Michele DP, Daniela B, Tatiana VP (2017) Microenvironmental regulation of tumour angiogenesis.
Nat Rev Cancer 17:457–474
Michielsen AJ, Hogan AE, Marry J, Tosetto M, Cox F, Hyland JM, Sheahan KD, O’Donoghue DP,
Mulcahy HE, Ryan EJ, O’Sullivan JN (2011) Tumor tissue microenvironment can inhibit
dendritic cell maturation in colorectal cancer. PLoS ONE 6:e27944
Moezzi J, Gopalswamy N, Jr Haas RJ, Markert RJ, Suryaprasad S, Bhutani MS (2000) Stromal
eosinophilia in colonic epithelial neoplasms. Am J Gastroenterol 95:520–523
Moriwaki K, Noda K, Furukawa Y, Kenji O, Airi U, Tsutomu N, Naoyuki T, Yataro D, Yusuke N,
Norio H, Eiji M (2009) Deficiency of GMDS leads to escape from NK cell-mediated tumor
surveillance through modulation of TRAIL signaling. Gastroenterology 137(1):188–198
Nagorsen D, Voigt S, Berg E, Stein H, Thiel E, Loddenkemper C (2007) Tumor-infiltrating
macrophages and dendritic cells in human colorectal cancer: relation to local regulatory T
cells, systemic T-cell response against tumor-associated antigens and survival. J Transl Med
5:62. https://doi.org/10.1186/1479-5876-5-62
Nakayama T, Yao L, Tosato G (2004) Mast cell-derived angiopoietin-1 plays a critical role in the
growth of plasma cell tumors. J Clin Invest 114(9):1317–1325
Neefjes JJ, Momburg F, Hammerling GJ (1993) Selective and ATP-dependent translocation of
peptides by the MHC-encoded transporter. Science 261(5122):769–771
Neefjes J, Jongsma ML, Paul P, Bakke O (2011) Towards a systems understanding of MHC class I
and MHC class II antigen presentation. Nat Rev Immunol 11(12):823–836
Ning H, Yang F, Jiang M, Hu L, Feng K, Zhang J, Yu Z, Li B, Xu C, Li Y, Wang J, Hu J, Lou X,
Chen H (2008) The correlation between cotransplantation of mesenchymal stem cells and higher
recurrence rate in hematologic malignancy patients: outcome of a pilot clinical study. Leukemia
22(3):593–599
Owens BM (2015) Inflammation, innate immunity, and the intestinal stromal cell niche: opportu-
nities and challenges. Front Immunol 6:319
Palucka K, Ueno H, Roberts L (2010) Dendritic cells: are they relevant? Cancer J 16:318–324
Papanikolaou IS, Lazaris AC, Apostolopoulos P, Kavantzas N, Papas MG, Mavrogiannis C,
Patsouris ES, Archimandritis A (2004) Tissue detection of natural killer cells in colorectal
adenocarcinoma. BMC Gastroenterol 4:20
Paul S, Lal G (2017) The molecular mechanism of natural killer cells function and its importance in
cancer immunotherapy. Front Immunol 8:1–15
Pillay J, den Braber I, Vrisekoop N, Kwast LM, de Boer RJ, Borghans JA, Tesselaar K,
Koenderman L (2010) In vivo labeling with 2H2O reveals a human neutrophil lifespan of 5.4
days. Blood 116:625–627
Pinczowski D, Ekbom A, Baron J, Yuen J, Adami HO (1994) Risk factors for colorectal cancer in
patients with ulcerative colitis: a case-control study. Gastroenterology 107(1):117–120
Potter JD (1999) Colorectal cancer: molecules and populations. J Natl Cancer Inst 91(11):916–932
Qian BZ, Pollard JW (2010) Macrophage diversity enhances tumor progression and metastasis. Cell
141(1):39–51
Queen MM, Ryan RE, Holzer RG, Cynthia R, Keller-Peck CLJ (2005) Breast cancer cells stimulate
neutrophils to produce oncostatin M: potential implications for tumor progression. Cancer Res
65(19):8896–8904
Rao HL, Chen JW, Li M, Xiao YB, Fu J, Zeng YX, Cai MY, Xie D (2012) Increased intratumoral
neutrophil in colorectal carcinomas correlates closely with malignant phenotype and predicts
patients’ adverse prognosis. PLoS ONE 7(1):e30806. https://doi.org/10.1371/journal.pone.
0030806
Rebecca LS, Kimberly DM, Ahmedin J (2019) Cancer statistics, 2019. CA Cancer J Clin 69:7–34
Reedy J (1975) Galen on cancer and related diseases. Clin Med 10:227–238
Ribatti D, Crivellato E (2009) The controversial role of mast cells in tumor growth. Int Rev Cell
Mol Biol 275:89–131
Roessner A, Kuester D, Malfertheiner P, Schneider-Stock R (2008) Oxidative stress in ulcerative
colitis-associated carcinogenesis. Pathol Res Pract 204(7):511–524
Rooney MS, Shukla SA, Wu CJ, Getz G, Hacohen N (2015) Molecular and genetic properties of
tumors associated with local immune cytolytic activity. Cell 160:48–61
Rubén VC, Oscar JC (2015) Immunology and immunotherapy of colorectal cancer. In: Rezaei N
(ed) Cancer immunology: cancer immunotherapy for organ-specific tumors. Springer, Berlin, pp
217–230. https://doi.org/10.1007/978-3-662-46410-6_11
Saito T, Nishikawa H, Wada H, Nagano Y, Sugiyama D, Atarashi K, Maeda Y, Hamaguchi M,
Ohkura N, Sato E, Nagase H, Nishimura J, Yamamoto H, Takiguchi S, Tanoue T, Suda W,
Morita H, Hattori M, Honda K, Mori M, Doki Y, Sakaguchi S (2016) Two FOXP3(+)CD4(+) T
cell subpopulations distinctly control the prognosis of colorectal cancers. Nat Med 22:679–684.
https://doi.org/10.1038/nm.4086
Sanz L, Santos-Valle P, Alonso-Camino V, Clara S, Antonio S, José LV, Angel MC, Marta C,
Sánchez-Martín D, Alvarez-Vallina L (2008) Longterm in vivo imaging of human angiogenesis:
critical role of bone marrow-derived mesenchymal stem cells for the generation of durable blood
vessels. Microvasc Res 75(3):308–314
Scheper W, Kelderman S, Fanchi LF, Linnemann C, Bendle G, de Rooij MAJ, Hirt C, Mezzadra R,
Slagter M, Dijkstra K, Kluin RJC, Snaebjornsson P, Milne K, Nelson BH, Zijlmans H,
Kenter G, Voest EE, Haanen J, Schumacher TN (2019) Low and variable tumor reactivity of
the intratumoral TCR repertoire in human cancers. Nat Med 25(1):89–94
Schwaab T, Weiss JE, Schned AR, Jr Barth RJ (2001) Dendritic cell infiltration in colon cancer. J
Immunother 24:130–137
Stabile H, Cinzia F, Angela G, Angela S (2017) Role of distinct natural killer cell subsets in
anticancer response. Front Immunol 8:1–8
Steinman RM, Hawiger D, Nussenzweing MC (2003) Tolerogenic dendritic cells. Annu Rev
Immunol 21:685–711
Stellos K, Bigalke B, Langer H, Tobias G, Annika S, Andreas K, Florian P, Dimitrios S, Peter S,
Iris M, Patrick H, Stephan L, Meinrad G (2009) Expression of stromal-cell-derived factor-1 on
circulating platelets is increased in patients with acute coronary syndrome and correlates with
the number of CD34+ progenitor cells. Eur Heart J 30(5):584–593
Sun B, Qin W, Song M, Liu L, Yu Y, Qi X, Sun H (2018) Neutrophil suppresses tumor cell
proliferation via Fas /Fas ligand pathway mediated cell cycle arrested. Int J Biol Sci
14:2103–2113
Tada K, Kitano S, Shoji H, Nishimura T, Shimada Y, Nagashima K, Aoki K, Hiraoka N, Honma Y,
Iwasa S, Okita N, Takashima A, Kato K, Yamada Y, Katayama N, Boku N, Heike Y,
Hamaguchi T (2016) Pretreatment immune status correlates with progression-free survival in
chemotherapy-treated metastatic colorectal cancer patients. Cancer Immunol Res 4(7):592–599
Ten Kate M, Aalbers AG, Sluiter W, Leo JH, Pieter S, Johannes J, Van Eijck CHJ (2007)
Polymorphonuclear leukocytes increase the adhesion of circulating tumor cells to microvascular
endothelium. Anticancer Res 27(1A):17–22
Tenesa A, Dunlop MG (2009) New insights into the aetiology of colorectal cancer from genome-
wide association studies. Nat Rev Genet 10:353–358
Vangangelt KMH, van Pelt GW, Engels CC, Putter H, Liefers GJ, Smit V, Tollenaar R, Kuppen
PJK, Mesker WE (2018) Prognostic value of tumor-stroma ratio combined with the immune
status of tumors in invasive breast carcinoma. Breast Cancer Res Treat 168(3):601–612
Veglia F, Perego M, Gabrilovich D (2018) Myeloid-derived suppressor cells coming of age. Nat
Immunol 19(2):108–119
Verheul HM, Pinedo HM (1998) Tumor growth: a putative role for platelets? Oncologist 3(2):2
Vijay GP, Dingzhi W, DuBois RN (2010) The tumor microenvironment in colorectal carcinogen-
esis. Cancer Microenviron 3:149–166
Yang L, DeBusk LM, Fukuda K, Fingleton B, Green-Jarvis B, Shyr Y, Matrisian LM, Carbone DP,
Lin PC (2004) Expansion of myeloid immune suppressor Gr+CD11b+ cells in tumor-bearing
host directly promotes tumor angiogenesis. Cancer Cell 6(4):409–421
Yasuhiko K (2010) Angiogenesis and lymphangiogenesis of gastric cancer. J Oncol 2010:468725.
https://doi.org/10.1155/2010/468725
Yewdell JW, Reits E, Neefjes J (2003) Making sense of mass destruction: quantitating MHC class I
antigen presentation. Nat Rev Immunol 3(12):952–961
Yuehua J, Balkrishna N, Reinhardt RL, Robert ES, Keene CD, Ortiz-Gonzalez XR, Morayma R,
Todd L, Troy L, Mark B, Jingbo D, Sara A, Aaron L, Walter CL, David AL, Catherine MV
(2002) Pluripotency of mesenchymal stem cells derived from adult marrow. Nature 418
(6893):41–49
Zhang B, Wang Z, Wu L, Zhang M, Li W, Ding J, Zhu J, Wei H, Zhao K (2013) Circulating and
tumor-infiltrating myeloid derived suppressor cells in patients with colorectal carcinoma. PLoS
ONE 8(2):e57114
Chapter 12
Immune Targets in Colorectal Cancer
Begum Dariya and Ganji Purnachandra Nagaraju
Abstract Colorectal cancer (CRC) is a multifactorial malignancy, with highest

mortality rate amid of the cancer-related deaths in the USA and worldwide. It
ranks as the third most recorded cancer irrespective of gender. CRC is that tumor
type with high mutation prevalence caused due to mismatch repair (MMR) gene
developing MSI and MSS along with high antigenic potentiality. It is impacted by
numerous factors like genetic, environment, and inflammation, is always determined
to be a dreadful malignancy if detected in its late stages. The other factors that
determine the progression and therapy of cancer is the tumor microenvironment
(TME). It is critically suggested that the immune system in TME plays a pivotal role
in promoting tumor progression. Therefore, understanding the immune cells and
their signaling pathways enables the advancement of immune based therapies for
better prognosis. For instance, immune checkpoint inhibitors like anti-programmed
cell death protein-1 (antiPD-1), anti-programmed cell death ligand protein-1 (anti-
PD-L1), and anti-cytotoxic T lymphocyte associated protein 4 (anti-CTLA4) with
other growth factor inhibitors or chemodrugs are found effective in treating MSI
CRC to inhibit tumor progression. In this article we focused on the immune cells, its
pathway, TME of CRC, and immune targeted therapies.
Keywords CRC · TME · MSI · MSS · Immune checkpoint · CTLA4 · PD-1 · PD-L1
B. Dariya
Department of Bioscience and Biotechnology, Banasthali University, Vanasthali, Rajasthan,
India
G. P. Nagaraju (*)
Department of Hematology and Medical Oncology, Winship Cancer Institute, Emory
University School of Medicine, Atlanta, GA, USA
e-mail: pganji@emory.edu
https://doi.org/10.1007/978-981-15-6487-1_12
206 B. Dariya and G. P. Nagaraju
Abbreviations
ACT Adoptive cell transfer therapy

APC Antigen presenting cells
Β-hCG Beta-human chorionic gonadotropin
CMS Consensus molecular subtypes
CTLA-4 Cytotoxic T lymphocyte associated protein 4
DAC DNMTi 5-aza-2’deoxycytidine
DNMTi DNA methyltransferase inhibitor
FoxP3 Forkhead box P3
IDO Indoleamine 2,3-dioxygenase
IFN-γ Interferon gamma
LAG3 Lymphocyte activation gene 3
mAbs Monoclonal antibodies
MDSCs Myeloid derived suppressor cells
MHC Major histocompatibility cells
MMP Matrix metalloproteinases
MMR Mismatch repair
MMRD Mismatch repair deficient
MMRP Mismatch repair proficient
MSS Microsatellite stability
NK Natural killer cells
PD-1 Programmed cell death protein-1
PD-L1 Programmed cell death ligand protein-1
TCR T cell receptor
Teff Effector T cells
TGF-β Transcription growth factor beta
TH T helper cells
TME Tumor microenvironment
TNF-α Tumor necrosis factor-alpha
Tregs Regulator T cells
12.1 Introduction
Colorectal cancer is the heterogenous disease that recorded as third most common
cancer diagnosed worldwide in both men and women (Siegel et al. 2020). It is a
multifactorial disease with high mortality rate. The risk factors including immune
system of the host, microbiota in the gut, and altered risk factors like alcohol
consumption and unhealthy lifestyle. This results into a sequence of pathological
12 Immune Targets in Colorectal Cancer 207
conditions that ultimately alters the healthy colon epithelium into an invasive
carcinoma (Mármol et al. 2017; Sun and Kato 2016). The immune system is the
host defense system on the other side plays crucial role in protecting the body against
disease conditions like cancer. Moreover, the tumor immunogenicity is developed
due to the elevated release of neoantigens as a result of mutations (Schumacher and
Schreiber 2015). As an immune response, the chronic inflammation of the body
persuades dysplasia in the epithelial cells of intestine that further initiates CRC
progression (Lucas et al. 2017). The somatic mutation induces tumorigenesis caus-
ing inactivation of DNA mismatch repair (MMR) develops sporadic and familial
microsatellite instability (MSI) in CRC (Galon et al. 2006). This increased the
tumor infiltrating lymphocytes in CRC. Tumor necrosis factor (TNF-α) is a
pro-inflammatory cytokine that plays crucial role in immune response initiation
(Luo and Zhang 2017). Moreover, the tumor microenvironment (TME) that consti-
tutes natural killer cells (NK) detects stress associated molecules and dendritic cells
(DC). They activate pre-existing cytotoxic immune cells called T lymphocytes that
play crucial part in sensing the tumor associated antigens via their receptors called T
cell receptors (TCR) (Jobin et al. 2017). They are involved in tumor regression via
attacking CRC cells. The immune response is also supported by other co-receptors
like CD4+ and CD8+ (Löfroos et al. 2017). The NK cells together with T cells are
found to possess anti-tumor properties via producing enzymes like perforin and
granzymes that is further followed by the apoptosis of the cancer cells (Banerjea
et al. 2004; Phillips et al. 2004). Moreover, previous research studies showed that
lower activity of NK cells results in poor prognosis (Jobin et al. 2017). The T helper
cells (Th) support this immune response and promote the production of cytotoxic T
lymphocytes. They also help in secreting cytokines like IFN-γ (Sun et al. 2002). This
further promotes the production of more NK cells. Similarly, tumor associated
macrophages also confer with poor prognosis. However, the heterogenous nature
of the tumor prevents them from being recognized by the immune cells due to
presence of certain cells like PD-L1. Additionally, the tumor cells also alter the
immune cells and to function as immunosuppressive cells. For instance, the tumor
associated macrophages are the circulating monocytes initially, later differentiated
into macrophages and contribute to angiogenesis and metastasis in CRC under
oxidative stress conditions (Grivennikov et al. 2010; Qian et al. 2011).
The immunity strategies developed for cancer focus on restoring the immune
system to activate the anti-tumor immunity via generating T cell responses that
distinguish and eliminate tumor cells. However, the tumor cells behave trickily with
the host immune system by camouflaging themselves as normal cells. Thus, the
immune therapy acts to shred away the camouflage to distinguish the tumor cells and
kill them. Advancements in understanding about the interaction between tumor and
immune system potentiated the therapeutic strategies to boost up the natural defense
system against tumorigenesis. The DNA mismatch repair-deficient (MMRD) caus-
ing microsatellite instability high (MSI-H) result in positive CRC are found to
respond to immunotherapy (Hemminki et al. 1994). This is due to the presence of
tumor infiltrating lymphocytes, tumor neoantigens, and immune checkpoints. The
therapeutics are further potentiated to improve the efficacy with the revitalizations of
targeted immunotherapy. These therapies include T cell therapy and immune check-
point blockers that are antibody based. These blockers include anti-PD-1/PD-L1
(programmed cell death 1) and anti-CTLA-4 (cytotoxic T lymphocyte associated
protein 4).
12.2 Understanding Immune System
Understanding immune system and its surveillance would potentiate the use of
immune cells to inhibit the cancer cell progression. There are advanced therapeutic
strategies to activate immune response. The immune system of the host through
innate or adaptive is capable of differentiating and eliminating the tumor cells in their
early stages of tumorigenesis. The innate immunity is pre-existing and the first line
of defense system. It includes immune cells—myeloid derived suppressor cells
(MDSCs), neutrophils, macrophages, NK, DC, and mast cells (Hanahan and Wein-
berg 2011). The adaptive immune cells have memory and can recall before exposed
to any stimuli. T and B lymphocytes are the adaptive immune cells (Goldszmid et al.
2014). As determined, both these innate and adaptive immune cells either interact
directly with TME or indirectly with the help of signaling cascade of cytokine and
chemokine that alters the behavior of tumor cells as per the therapy. The innate
immune cells respond to the inflammatory signals generated by the diseased tissue
that further activates adaptive immunity via the cascade of inflammations
(Goldszmid et al. 2014). This produces the antigen presentation by macrophages
and DC on to the T cells. Whereas in case of tumor, the immune cells distinguish the
tumor specific antigens present on the cancer cell surface with the healthy cells. Later
the NK cells kill the cancer cells that lack MHC-I on their surface that further recruit
inflammatory cells via the production of cytokines (Purdy and Campbell 2009). The
macrophages and DC phagocyte the tumor cells and present tumor related antigens
on the surface of tumor cells (Munn and Cheung 1990). This activates the T cells and
directs against tumor cells. As an immune response, the effector T cells divide and
infiltrate through the tumor to eliminate it from the body (Van Pel and Boon 1982).
However, cancer cells, the cleverest follow few selection mechanisms and have the
ability to camouflage the immune system.
12.3 Tumor Immune Microenvironment
The tumor microenvironment (TME) of a CRC patient always affects the progres-
sion and metastasis of the tumor. It contains extracellular matrix that constitutes
collagen fibers, lymphatic vessels, fibroblast, nerves, and hematopoietic cells
(Fridman et al. 2012; Kobayashi et al. 2019). The adaptive and innate immune
cells present in the TME interact with the cancer cells directly or through the
signaling factors including cytokines and chemokines. They alter the behavior of
tumor cells and retort against the therapy. The immune cells found act variedly as per
the host cells and tumor cells factors. The immune cells behave both as anti-tumor
and pro-tumor basing on the context. For instance, DC release cytotoxic cytokines
like IL-2, TNF-α and IFN-γ and present antigens to T cell during the attack of any
pathogen. But, under abnormal conditions it inhibits T cell function and promotes
tumor survival and progression. The T cells (CD8+ and CD4+) in general kill the
tumor cells and release the cytotoxic cytokines like IFN-γ; however, as a
pro-tumorigenic it secretes tumor promoting cytokines like IL-10, IL-13, and IL-4.
The Tregs are found to restore homeostasis in order to reduce the chronic inflam-
mation but it inhibits anti-tumor immune response via inducing inflammatory
cytokine secretion. The MDSCs are found limited in the microenvironment, yet
they are involved in inhibiting T cell activity and recruit immunosuppressive
immune cells (Wang et al. 2014). The macrophages and NK cells are cytotoxic to
tumor cells, release cytotoxic cytokines, and produce antigen presenting cells
(APCs) to T cells. The macrophages however, act abnormally and promote tumor
proliferation, angiogenesis, and metastasis. The necrotic cell death other than
phagocytosis generates signals for proinflammation in the local tissue for the
employment of immune cells (Hanahan and Weinberg 2011). These inflammatory
signals comprise high mobility group box-1 and IL-1 that induce angiogenesis and
contribute to survival of tumor cells (Grivennikov et al. 2010). Additionally, the
activation of cytokines via the immune cells also activates transcription factors like
STAT3 and NF-κB that promote growth and survival (Grivennikov et al. 2010). The
immune cells in the TME function by interacting tumor cell with the surrounding
stroma. This invades the peripheral cells through the activation of macrophages that
secretes enzymes like metalloproteinases (MMP) (Coussens et al. 2000) and cysteine
cathepsin proteases (Joyce et al. 2004), that later causes metastasis (Grivennikov
et al. 2010; Hanahan and Weinberg 2011). The colitis associated CRC and colon
cancer produce IL-6 as the inflammatory response was found to activate STAT3 that
further promotes tumorigenesis. Further reports suggested that the MMP-9 transcript
levels higher in tumor tissues than in the non-tumor tissues in CRC patients. Thus,
the presence of MMP-9 in higher levels determines the metastatic nature in CRC
(Zeng et al. 1996). The immunocytes affect the progression and evolution of tumor
cells (Joyce and Fearon 2015; Spill et al. 2016). The impairments for the success of
anti-tumor immunity are due to reduced immunogenicity and potentiating microen-
vironment with protein factors promote angiogenesis and remodeling of matrix.
Additionally, the TME has many immunosuppressive influences. They include
increased level of suppressive cytokines, highly expressed Tregs, MDSCs,
decreased expression of MHC molecules/ antigens, increased PD-L1 expression
by the tumor, and increased levels of checkpoint proteins by the T cells.
Basing on the TME colorectal tumor can be differentiated into different types. For
instance, highly infiltrated, medium infiltrated, and low infiltrated by lymphocytes
(Dolcetti et al. 1999). The CRC patients with highly infiltration via lymphocytes are
with microsatellite instability, low level infiltration is with varied fibroblast, lym-
phatic and endothelial cells (Spranger et al. 2015; Luke et al. 2019). Whereas, the
medium level infiltration is with high density of fibroblast and endothelial cells.
Table 12.1 Molecular classification of CRC

T cell
% of inhibited
CMS CRC Mutations Consequence TME by Ref
CMS1 14% Hypermutated Inhibition of PD1, Herman
MSI, BRAF, and MLHI, MMR PD-L1, et al.
CpG island gene CTLA-4, (1998))
methylator transcription LAG3
phenotype
CMS2 37% Canonical, APC Activation of Low number of lym- Guinney
WNT and phocytes, endothelial et al.
MYC cells, macrophages, (2015))
and fibroblastic cells
CMS3 13% Metabolic, Decreased levels of Becht
KRAS immune cell et al.
infiltration (2016b))
CMS4 23% Mesenchymal " EMT, TGFB, PD1, Guinney
angiogenesis LAG3, et al.
(VEGFA, CTLA-4, (2015))
VEGFB, PD-L1
VEGFC)
They resulted with high metastatic potentiality and poor prognosis of patient (Becht
et al. 2016a). In CRC the tumor infiltration is heavily carried by the macrophages and
subsequently by T and B cells (Schumacher and Schreiber 2015).
The deficient MMR or Microsatellite instability-heavy (MSI-H) contributes 15%
of CRC cases but encounters for only 4% of mCRC. Whereas for MMRP and MSI-L
encounters 85% of CRC cases (Fleisher et al. 2000). The TME for these deficient and
MMRP differs that contributes to variation in the immune response and therapy
(Mlecnik et al. 2016; Ogino et al. 2009). The high mutation effect on MMRD-MSI-
H CRC showed increased neoantigens on MHC-1 molecules expressed on cancer
cells thus, promoting T cells to detect them as distant cells. Additionally, the TME of
colorectal tumor is classified based on the transcriptome into four consensus molec-
ular subtypes (CMS) (Willett et al. 2012; Roepman et al. 2014; Budinska et al. 2013;
Schlicker et al. 2012; Sadanandam et al. 2013; Marisa et al. 2013; Felipe De Sousa
et al. 2013; Villamil et al. 2012; Guinney et al. 2015). Among the four CMS, CMS1
and CMS4 are regulated by the immune cells and are found overexpressed in
samples that have high proportion of stromal tissue (Alderdice et al. 2018). The
classification is illustrated in Table 12.1.
12.4 The T Cell Classification
The mature T cells are the role players, Fig. 12.1 explains the process of T cell
maturation. The mature T cells have co-receptors CD4+ and CD8+. They are
classified into three different types of T cells such as naïve, effector (Teff), and
Fig. 12.1 Maturation of T cells and its differentiation. T cell precursors produced from the bone
marrow migrate into the thymus where the T cells maturate and are then transferred into the blood
streams. The mature T cells are of three types: Naïve T cells, effector T cells, and memory T cells.
They have 2 co-receptors: CD4+ and CD8+
memory cells. The naïve cells are the T cells that are not yet encountered by any
APCs. The active T cells undergo differentiation and proliferation to develop several
T cells called Teff cells. The Teff cells are capable of mediating the immune
function. They effectively promote immunotherapies via destroying tumor, mediate
its activation, and inhibit the immunosuppressive activity present in the TME. The
Teff cells are subdivided into TH cells and CTL. The TH cells assist the activation of
other cells in developing immune response. They also regulate antibody production
of B cells. These further have subsets including TH1, TH12, TH17, and Tregs. The
immune cells Teff (effector T cells) and Tregs (regulatory T cells) act differently
toward the progression of tumor cells. The function and classification of T cells are
tabulated in Table 12.2. The Treg cells are critical effector cells that maintain
homeostasis of immune response and play essential role in averting ailments like
autoimmune disease (Brunkow et al. 2001; Bennett et al. 2001). They are catego-
rized as the subgroup of CD4+ T cells that express forkhead box P3 (FoxP3)
transcription factor and IL2R α chain (CD25) as the surface molecule along with
T cell receptor and CD4 co-receptor. CD25 is otherwise called as IL-2RA and is a
receptor for IL-2. IL-2 is the prime cytokine that efficiently potentiates T and B
lymphocyte proliferation. FoxP3 is maintained in high level by Tregs. It is a cell
lineage marker of Treg and its deletion in the germline would develop improper
Table 12.2 Classification of T cells

T cells Activation Types Subsets Function
Naïve T Lymphocytes not Naïve CD4+ T Not encountered by
cell encountered by any cells and Naïve antigen
antigens CD8+
Effector Lymphocytes capable of Effector CD4+ Helper T cells Respond to APCs
T cells mediating immune T cells!!! (TH cells)— TH1, and activate T cells
function/ Short lived Effector CD8+ TH12, TH17, Tregs differentiation and
T cells!!! Cytotoxic T cells/ proliferation
CTLs
Memory Long lived antigen Protects if the same
T cells specific lymphocytes, pathogen invades
responsible for immu- Rapidly generates
nological memory more T cells and
memory cells
Tregs that enhance autoimmune disorders. However, if FoxP3 is overexpressed it

gives rise to increased Tregs and promotes expression of IL-10. The identity of Treg
is maintained by the signals from TCR, IL2, and TGF-β that promotes the expression
of FoxP3. Tregs show different immunoregulatory mechanisms but also have anti-
inflammatory function. It interacts with macrophages and prevents pro-inflammatory
cytokines secretion including IL1 and IL6, thus prevents the production of CD4+ T
cells. Treg also directly competes with CD4+ T cell to bind with IL-2 that is involved
in production of T cells and Tregs. However, IL-2 are hardly secreted by Tregs as the
FoxP3 alters the transcription factors that are responsible for the secretion of IL-2.
But, CD25 that is highly expressed on Tregs competitively binds with IL-2 and
inhibits proliferation of T cells. Similarly, Tregs also secrete cytokines like IL-35,
TGF-β, and IL-10 that inhibit CD4+ T cells to control down the inflammation. IL10
is an immune suppressive cytokine that downregulates CD4+ cells. Treg often
persuades neighboring immune cells including DCs to secrete IL-10 (Whitehead
et al. 2012). IL-10 controls the self-activation of DCs and activates CD4+ T cells and
CD8+ Teff cells in vitro and in vivo (Ouyang and O’Garra 2019). However, IL-10
activation dependent signaling cascade may not be a proposed Tregs mechanism for
immunosuppression. Furthermore, there are certain enzymes secreted by Tregs
including granzyme B that causes apoptosis of T cells (Perrella et al. 2014).
Additionally, in contact with DCs Tregs also secrete indoleamine 2,3-dioxygenase
(IDO) that disrupts T cell function (Munn and Mellor 2013; Jiang et al. 2015). It was
found that presence of highly expressed CD25 also constitutes to suppress T cell
proliferation.
The high levels of infiltrations of Tregs in various cancer like CRC, head, bladder,
and neck cancer are found with better prognosis (Fridman et al. 2012; Saito et al.
2016). However, in certain cancers like gastric, hepatocellular, pancreatic, renal,
breast, melanoma, cervical, and non-small cell lung cancer are found with poor
prognosis with increased Tregs number (Sasada et al. 2003; Curiel et al. 2004; Bates
et al. 2006; Shang et al. 2015). Basing on the functionality, Tregs would be classified
into subtypes effector Tregs (eTregs) and chemokine receptor (CCR4) (Miyara et al.
2009; Sugiyama et al. 2013). The eTregs are highly immunosuppressive and express
CD45RA-FoxP3++ phenotype. CRC patients showed high tumor infiltration with
high subpopulation of CD45RA-FoxP3++ and are reported with poor prognosis
(Saito et al. 2016). However, in few cases of CRC, low levels of CD45RA-
FoxP3++ reported with better prognosis. Additionally, these low levels and
non-Tregs also secreted pro-inflammatory cytokines such as IL-17 and IFN-γ
(Saito et al. 2016; Miyara et al. 2009). Later, high levels of FoxP3+IL-17+CD4+
Tregs were detected in microenvironment of colitis with ulcerative colitis related
colon cancer. These FoxP3+IL-17+ Tregs inhibit T cell proliferation and promote
inflammation via inflammatory cytokine stimulation with the release of IL-2 and
IFN-γ in the tissue of colitis (Kryczek et al. 2011). The higher levels of Tregs in
sporadic colon cancer are also associated with poor prognosis. Thus, Tregs were
believed to promote tumorigenesis that more efficiently suppresses the local inflam-
matory process (Haas et al. 2009).
Tregs also show higher expression of PD-1 and CTLA-4. The blocking of CTLA-
4 and PD-1 would deactivate Treg. However, its property of maintaining immune
homeostasis, explains the reason for blocking PD-1 and CTLA4 that may develop
immune associated inflammation (Francisco et al. 2009; Walker 2013). CTLA4 and
PD-1 are the inhibitory checkpoints and known target for immunotherapies in
cancer. These immune checkpoints play a crucial role in blocking the activation of
T cells, Treg, and other inhibitory cytokines and immunosuppressive cells.
12.5 The Cancer Immunotherapy
12.5.1 Immunosurveillance
Immune system of the body involves in distinguishing the cancer cells (non-self)
from the healthy cell (self). This process aims at protecting from tumor development
and is called as immunosurveillance. The immunosurveillance is the process where
the host immune cells efficiently patrol for the cancerous or abnormal cells, recog-
nize them, and eliminate before they harm the healthy cells (Teng et al. 2008). The
immune cells recognize the antigen present on the tumor surface. They can either be
oncogenes or tumor suppressor genes or can be viral antigens. These antigens are
presented as peptides by the MHC-1 express on the surface of tumor cells. The
second phase is the elimination phase. In this phase the cancer cells are incorporated
into APCs that are specifically for exposing or presenting tumor antigens as peptides
by MHC-II. The APCs further activate TH cells that stimulate B cells for antibody
production. Additionally, the TH cells also stimulate the expression of macrophages
that engulf the tumor cells and eliminate them. Similarly, the cytotoxic T cells
directly bind with the tumor cells and devastate them. Occasionally, the tumor
cells escape the immune system as they secrete few mediators to inhibit APCs and
T cells. Additionally, they produce mutated or modified tumor antigen on their
surface being non-recognizable by the immune system. This develops into increased
proliferation of tumor cells and the immune cells reach the stage called immune
tolerance. NK cells are the widely acted immune cells in immunosurveillance that
promotes cytotoxicity in tumor cells that have MHC-I on their surface and are highly
prone to be attacked by them (Zamai et al. 2007). Similarly, NK cells also develop
cytotoxicity in the cancer cells via producing granules that contain granzyme B and
perforin (Halama et al. 2011). Additionally, CD8+ T cells also kill cancer cells via
promoting cytotoxicity in the tumor cells produced by the activated cytokines like
IFN-γ (Pardoll 2002). CD4+ TH1 and TH17 also promote CTL function to produce
cytokines including IL-4 and IFN-γ (Munegowda et al. 2011; Gerrard et al. 1981).
Thus, these anti-tumor immune cells can be taken as prognostic biomarkers as
targets for better outcome in the immunotherapy. Considering the tumor samples
of CRC patients with stages ranging from II and IV are found with higher cytotoxic
CD8+ (CD69+ and CD107a+) tumor infiltrating lymphocytes (Markman and Shiao
2015). Higher the cytotoxic CD8+ cells, higher will be the tumor antigen-reactive T
cells in the bone marrow and blood. Thus, they are inversely corelated, wherein the
earlier stage of cancer showed higher proportion of active CD8+ tumor infiltration
lymphocytes. This suggest that the initial stages of CRC can be easily detected and
endure surveillance by the immune system.
12.5.2 Immunoediting
Immunoediting is a process that selects tumor cells with reduced immunogenicity

and maintains the immune response through varied mechanisms in those tumor cells.
The communal relationship between the host immune system and TME is differen-
tiated into 3 phases. They include elimination phase, equilibrium, and escape phase.
As the initial step, the elimination phase includes cancer immunosurveillance of the
host cells that is followed as a two-signal phase which is already discussed earlier.
The first signal includes presenting of the tumor antigen on the T cell receptor via
MHC and consequently followed by the activation of T lymphocytes. Both the
immune response adaptive and innate immunity are activated in the host immune
system that efficiently prevents tumor. The equilibrium phase is the extended phase,
the immune cells even though active in TME are not capable to destroy tumor cells
but maintain the tumor cells in a dormancy state (Dunn et al. 2004). The immune
cells, though they are unable to eliminate the tumor cells but prevents metastasis to
occur, maintaining tumor cells in a static phase. The tumor cells make use of various
biochemical pathways to inhibit the immune response, to reach a state of immune
tolerance. Thus, in this stage, the T lymphocytes lose their functionality of
suppressing tumor. The dormant stage remains active until the escape phase initiates.
In the escape phase the tumor cells are determined to be highly active. The hetero-
geneity nature of the cancer cells potentiated by various signaling cascade to defend
themselves from the activity of immune effector cells. Thus, this phase is highly
advantageous for the cancer cells that tolerate the immune response of the host and
suppress it via various physiological pathways. The active tumor cells later bind to
the co-inhibitory molecules present on the T cells. For instance, CTLA-4, PD1, T
cell immunoglobulin mucin 3, and lymphocyte activation gene 3 (LAG3). Addi-
tionally, they also activate the inhibitory co-receptor, PDL-1 that secrete enzymes
like IDO which contribute to the secretion of anti-inflammatory IL-10 and TGF-β in
TME (Mahoney et al. 2015; Das et al. 2017; Postow et al. 2015). Thus, TGF-β, an
immunosuppressive factor secreted by the tumor cells prevents NK cells and CTLs
from eliminating them. Secondly, Tregs and MDSCs recruited by the tumor cells
camouflage them from the lymphocyte induced apoptosis (Hanahan and Weinberg
2011). Tregs function by inhibiting proliferation, expression of cytokines, and
activation of T cells like CD8+ and CD4+ cells. Moreover, intra-tumoral Tregs in
the increased number are associated with tumor progression and deprived prognosis
(de Leeuw et al. 2012). Additionally, it was detected that CRC patients showed
increased percentage of MDSCs in the peripheral blood that promoted metastasis.
The in vitro studies also revealed that the MDSCs extracted from the diseased CRC
patients were able to inhibit T cell proliferation (Zhang et al. 2013).
Thus, the co-inhibitory molecules otherwise called immune checkpoints play a
pivotal role in obstructing immune response of the host. Researchers are now
converging to understand the mechanism to restore the immune response via
targeting drugs against this altered immune checkpoint to disrupt the immunosup-
pression signaling against tumor.
12.6 Immunotargets
12.6.1 Immune Checkpoints
The hypermutation in the CRC results in deficient MMR system resulting in the
formation of MSI-H that are vigorously expressed on check proteins including
CTLA4, PD-1, and PD-L1. Thus, this supports the escape of tumor from being
detected by the immune system by acting against MSI-H TME and preventing the
exclusion of neoplastic cells. The current immunotherapeutic strategies are aiming to
potentiate the activation of effectors of T cells via altering the immune response
(Topalian et al. 2016). The targets focused mainly for immunotherapeutic strategies
are CTLA4, PD1, and its ligand PD-L1.
12.6.2 CTLA4
CTLA4 is a membrane glycoprotein receptor present on the active T cell surface. It

resembles CD28 and thus competes with it, to bind with the common natural ligands
of B7 family. The B7 family ligands include CD80 and CD86 that are present on the
surface of APCs. As the first step, with the antigenic stimulation at the T cell
receptor, the T cell activates and expresses CTLA4 on its surface that binds with B7
more efficiently than CD28. The interaction of CD28-B7 stimulates the cytotoxic
immunity, whereas the interaction of CTLA4 with B7 suppresses T response and
promotes immune tolerance (Pardoll 2012). CTLA4 expression is found normal on T
cell activation; however, with Tregs, CTLA4 overexpresses due to increased levels
of FoxP3 on Tregs that regulate the expression of CTLA4 (Pardoll 2012; Perkins
et al. 1996). In case of tumor patients CTLA4 is found highly expressed in both Teff
and Tregs (Plitas et al. 2016). The effect of CTLA4 activates the intrinsic signaling
pathway of T cells and was found to inhibit production of IL-2 and proliferation of T
cell. Furthermore, it cross-talks with other pathways including PI3K, MAPK, and
NF-κB to regulate cell survival and proliferation of cells (Intlekofer and Thompson
2013; Chikuma et al. 2005; Schneider et al. 2009; Fraser et al. 1999; Bhandaru and
Rotte 2019). The cancer therapy involved in developing anti-CTLA4 antibodies as
CTLA4 blockade was tested in murine tumor models (Leach et al. 1996).
12.6.3 PD-1 and PD-L1
The programmed cell death-1/PD-1 (CD279) are the co-receptors expressed on the
surface of tumor infiltrating lymphocytes, NK cells, T (CD8+ and CD4+) and B
lymphocytes (Postow et al. 2015). PD-1 shows almost 21–33% of similarity with
CTLA-4, but PD-1 is a monomer and CTLA4 is a dimeric protein (Rotte 2019).
PD-1 has deficiency of extracellular cysteine residue necessary for covalent dimer-
ization and exists as monomer, unlike CTLA4. The presence of PD-1 on the cell
surface of T and B cells activates T cell and B cell receptor. PD-1 plays a pivotal role
in maintaining the inflammatory response and tumor immunity that alters the
functionality of T cells that travel toward TME. PD-L1 (B7-H1) and PD-L2
(B7-DC) are the two ligands for PD-1 receptors. PD-L2 are mostly expressed on
DC and macrophages (Francisco et al. 2009; Latchman et al. 2001), whereas PD-L1
are also expressed on organs cells, T, B cells, NK cells, and tumor cells (Topalian
et al. 2016; Naboush et al. 2017). The interaction of PD-1 with PD-L1 inhibits T cell
proliferation, secretion of cytokines like TNF-α, IFN-γ, and IL-2, and cytotoxic
nature of the immune cells. It also avoids the onset of autoimmune diseases by
maintaining the immune homeostasis (Kim and Eder 2014). Moreover, during the T
cell activation the PD-1 receptor was restricted to bind with PD-L1 and allowed
CD80 to bind with PD-L1 (Sugiura et al. 2019). The pathway of PD-1/PD-L1 plays a
crucial role in evading tumor cells from the immunosurveillance. PD-1 expressed on
the T cells in TME that lost the effector function and PD-L1 expressed on APCs or
tumor cells. The interaction of PD-1 and PD-L1 adapts the mechanism of adaptive
immune resistance or adaptive suppression and inhibits the infiltration of T cells in
TME (Topalian et al. 2016). Thus, PD-L1 is associated with poor prognosis in varied
type of cancers. The blockade of this pathway promotes the anti-tumor immune
response via recurrence of cytotoxic T cells and is determined to be the successful
therapeutic strategy till date.
The current advances in immunotherapies progressed in developing therapeutic

strategies including cancer vaccines, adoptive cell transfer therapy (ACT), and
antibody-based cancer immunotherapy to treat CRC.
12.6.4 Monoclonal Antibody-Based Cancer Immunotherapy

(mAb)
The monoclonal antibodies (mAbs) are found clinically effective since decades
(Weiner et al. 2012) (Table 12.3). mAbs like bevacizumab (anti-VEGF mAb) and
cetuximab, (anti-EGFR mAb) are approved clinically for CRC therapy in the USA.
They focus on targeting vital signaling pathways and promote innate immune
effector process. They distinguish Fc portion of Ab through Fc receptor and per-
suade Ab dependent cytotoxicity via cellular mechanisms (Jiang et al. 2011). mAbs
are also called as checkpoint inhibitors, block the CTLA4, PD-1, and PD-L1 that
came out with positive result in many cancers. The cancer therapy is thus focusing
on developing anti-CTLA4, anti-PD-1, anti-PD-L1 antibodies as to block the acti-
vation of CTLA4, PD-1, and PD-L1, respectively.
The current anti-CTLA4 blockade developed are Ipilimumab and tremelimumab
against humans. They are used to restore Teff effect to potentiate tumor cytotoxicity.
Ipilimumab was approved by FDA for the therapy against metastatic melanoma with
no resection history. This is also used as an adjuvant therapy for melanoma with high
risk (Rotte et al. 2018; Ascierto et al. 2017; Di Giacomo et al. 2015; Eggermont et al.
2016, 2019; Robert et al. 2011). Ipilimumab showed increased overall survival
(OS) rate; however, 20–30% of the patients showed sever autoimmune disease
(Topalian et al. 2015). Tremelimumab is a human anti-CTLA4 IgG2 monoclonal
antibody (mAb). The phase II clinical trial for tremelimumab is conducted as a single
arm multicenter administered intravenously for every 90 days in metastatic CRC
patients after the standard chemotherapeutic therapy failure (Chung et al. 2010)
(Table 12.3). The median OS was detected to be 19.1 months and median
progression-free survival was about 2.3 months. However, this drug was not encour-
aged for future research against mCRC. Poon et al. (2017) demonstrated the com-
bination activity of MEK inhibitor and anti-CTLA4 in CT26 preclinical tumor
model. They used selumetinib as a MEK inhibitor, combining with anti-CTLA4
negatively controlled the upregulation of immunosuppressive mediators including
Cox-2 and Arg1 present in TME. This combination decreased the frequency of
CD11+ Ly6G+ myeloid cells as well as accumulated monocytes at Ly6C+ MHC+
tumor state. Anti-CTLA4 increases the T cell proliferation, activation, and improves
the infiltration of T cells into the TME that is found more efficient with MEK
inhibition. The mutation in Kras gene dysregulated the pathway RAS-RAF-MEK-
ERK in various cancers promoting cell proliferation. Thus, targeting MEK with its
inhibitors found benefit to the patients when combined with checkpoint blockade
like anti-CTLA4. Similarly, there is combination of chemodrug with targeted
Table 12.3 Ongoing clinical trials for immune vaccines and immune checkpoint inhibitors
218
S. no Research hypothesis Condition Intervention/treatment Phase Identifier

1 Combination of chemotherapy with mCRC Durvalumab (Anti-PD-L1), Phase I NCT03202758
immunotherapy (anti-PD-L1+anti- Tremelimumab (Anti-CTLA4) and Phase II
CTLA4) acting synergistically in CRC FOLFOX
patients
2 Treating CRC patient with immune mCRC in the liver Durvalumab (Anti-PD-L1), Phase I NCT02754856
drugs with liver metastasis that can be Tremelimumab (Anti-CTLA4).
removed by surgery. Procedure: Therapeutic conventional
surgery
3 The MSS mCRC to liver treated with mCRC in liver Durvalumab (Anti-PD-L1), Phase I NCT03005002
mAbs Gene mutation: MLH1, MSH6, PMS2 Tremelimumab (Anti-CTLA4)
CRC:Stage IV, IVA, IVB
4 Multicenter randomized Phase II study mCRC, MSI FOLFOX, FOLFIRI, avelumab Phase 2 NCT03186326
to compare the effectiveness and toler- (Anti-PD-L1), panitumumab,
ance of avelumab vs standard 2nd line cetuximab, bevacizumab, aflibercept
treatment chemotherapy in mCRC with
MSI
5 Atezolizumab with stereotactic ablative CRC, renal cell carcinoma, non-small Atezolizumab (Anti-PD-L1) Phase II NCT02992912
radiotherapy in metastatic tumors lung cancer
(SABR-PD-L1)
Study of immunodrug against chemo- MSI, CRC, chemotherapy resistance, Atezolizumab (Anti-PD-L1), Phase II NCT02982694
therapy resistant, MSI-like, CRC APC bevacizumab
Immunotherapy in locally advanced CRC Avelumab (Anti-PD-L1), capecitabine Phase II NCT03854799
rectal cancer (AVANA) Radiation: External—Beam irradiation
Study of cabozantinib in combination CRC, gastric cancer, hepatocellular Cabozantinib, atezolizumab Phase I NCT03170960
with atezolizumab to subjects with carcinoma, ovarian cancer, renal cell (Anti-PD-L1) Phase II
locally advanced or metastatic solid carcinoma, lower esophageal cancer
tumor
B. Dariya and G. P. Nagaraju
12
6 Personalized neoantigen cancer vaccine CRC, non-small cell lung cancer, GRT-C901, GRT-R902, nivolumab Phase I NCT03639714
gastroesophageal adenocarcinoma, (Anti-PD-1), ipilimumab (Anti- Phase II
urothelial carcinoma CTLA4)
7 Personalized cancer vaccine targeting CRC, pancreatic cancer, shared GRT-C903, GRT-R904, nivolumab Phase I, NCT03953235
shared neoantigens neoantigen-positive solid tumors, (Anti-PD-1), ipilimumab (Anti- Phase II
non-small cell lung cancer CTLA4)
8 Study of XmAb®20717 against selected CRC, renal cell carcinoma, melanoma, XmAb®20717 Phase I NCT03517488
advanced solid tumors endometrial cancer, non-small cell lung
carcinoma, breast carcinoma, and
hepatocellular carcinoma
A study of PI3K inhibition (copanlisib) Unresectable, metastatic MSS solid Copanlisib (PI3K inhibitor) Phase I NCT03711058
and anti-PD-1 in refractory solid tumor tumor along with MSS colon cancer Nivolumab (Anti-PD-1) Phase II
with expansion in MMR proficient CRC
Immune Targets in Colorectal Cancer
Source: www.clinicaltrials.gov
219
therapy as a standard first line therapy for mCRC. The phase Ib/II study
(NCT03202758) was performed for detecting the efficacy of drug combined
FOLFOX (5-FU, Leucovorin, and oxaliplatin) with inhibitors of PD-L1 and
CTLA4. A research study on a combo drug: durvalumab and tremelimumab is tested
for mCRC associated with MSI. Durvalumab is a human mAb found to inhibit
binding of PD-L1 with PD-1 and tremelimumab is a CTA4 inhibitor (Fumet et al.
2018). Recently, the phase II study of this combo drug resulted in prolonged overall
survival (Chen et al. 2020). Ipilimumab is another drug used in combination with
nivolumab against CRC and metastatic renal cell carcinoma with miss match repair
and heavy-MSI as CTLA4 and PD-1 blockades (Perez-Ruiz et al. 2019). Thus, these
clinically feasible strategies can be used as immune checkpoint blockades, however
further clinical studies are still warranted.
The US FDA approved the monoclonal PD-1 antibodies and monoclonal PD-L2
antibodies. The anti-PD1 antibodies include pembrolizumab, cemiplimab, and
nivolumab. Similarly, the anti-PD-L1 monoclonal antibodies include atezolizumab,
durvalumab, and avelumab (Bhandaru and Rotte 2017; Giaccone et al. 2018; Garon
et al. 2015). The gastrointestinal cancer cases experienced pseudoprogression as they
are treated with nivolumab and pembrolizumab as anti-PD1 and anti-PDL1 for
checkpoint inhibitory therapy (Michalarea et al. 2019). Nivolumab is the PD-1
blocker used against CRC with MSI-H and MMR. Similarly, a multicenter phase
Ib, open label study was conducted to compare the overall respond rate for Arm A
that includes combination of atezolizumab and bevacizumab with Arm B having
combination of bevacizumab and FOLFOX for mCRC patients with MSS to block
PD-L1. The Arm B showed better overall response rate that Arm A (Bendell et al.
2015) (Table 12.3). Thus, combination of drugs encourages the clinical activity and
also improved survival rate in mCRC patients.
12.6.5 Cancer Vaccine
The cancer vaccine elicits anti-tumor immune response successfully. The main
concept for vaccination develops from the immune cells to recognize the reformed
self-antigen called as tumor associated antigens present on the tumor cells. Thus, this
eventually elicits the immune response against the tumor to eliminate it and continue
with the immunosurveillance and avoiding the regrowth. Vaccination agents can be
grouped into 4 types: peptide antigens, viral/bacterial vaccination, whole tumor, or
dendritic cell. Few are explained here.
12.6.6 Whole Tumor Vaccine
These are the most primitive vaccine as the material for vaccination including the
known and unknown tumor associated antigen is readily obtainable. The vaccine
preparation initiates with irradiation of tumor tissue sample, later mixed with
immune adjuvant like alum and finally reinjected into CRC patient (Blankenstein
et al. 2012). For instance, the autologous whole cancer vaccine is used for several
cancers including CRC, renal, and melanoma cancer that induce cytotoxic anti-
tumor immune response (Shang et al. 2015; Miyara et al. 2009; Sugiyama et al.
2013). Along with the advantages, it also has limitations as the majority of vaccine
having tumor antigens is diluted with normal cells. The Eastern Cooperative Oncol-
ogy Group performed randomized phase III clinical trial for CRC patients, to
compare the disease-free survival in surgically resected patient given autologous
whole tumor cell and BCG vaccine with the resection alone. The study however
showed no significant result (Hanna Jr et al. 2001). More recently, a neoantigen-
based EpiGVAX vaccine was developed against mCRC combined with DNA
methyltransferase inhibitor (DNMTi), 5-aza-2’-deoxycytidine (DAC). The DNMTi
improved the efficacy of GVAX via inducing antigen specific anti-tumor T cell
responses to epigenetically regulated proteins. mCRC have very less neoantigens,
therefore DNMTi via the epigenetic therapy induces cancer testis antigen expression
and also sensitizes the cancer cells to immunotherapy (Kim et al. 2020). However,
further research for using irradiation or chemodrugs would efficiently produce whole
tumor vaccine with better anti-tumor immune response.
12.6.7 Peptide Vaccines
The peptide vaccines include fragments or whole protein extracted from the tumor
specific protein and is administered together with an adjuvant. The peptides
employed for designing vaccine include MHC I recognized by the CD8+ cytotoxic
T cells. In CRC, there are varied tumor associated antigens encouraged for vaccine
development. They include carcinoembryonic antigen (CEA) (Bilusic et al. 2014),
survivin-B/p53 (Idenoue et al. 2005; Speetjens et al. 2009), mucin-1 (Kimura et al.
2013), β-human chorionic gonadotropin (β-hCG) (Moulton et al. 2002), and squa-
mous cell carcinoma antigen recognized by T cells (SART3) (Miyagi et al. 2001).
These tumor associated antigens are taken as immunotherapy targets in various
cancers like CRC that induce antigen specific immune response. For instance, the
β-hCG vaccine induced anti-βhCG antibody production in CRC patients resulted in
better overall survival rate (Moulton et al. 2002). Yasuhiro et al. (Shimizu et al.
2019) used heat shock protein 105 (HSP105) as a peptide vaccine for CRC and
esophageal cancer as they are overexpressed in CRC patients. HSP105 vaccine was
found to induce peptide specific cytotoxic T lymphocytes and cytokine secretion.
They also suggested that this vaccine induced immune response as well resulted in
better prognosis. More recently, novel oral vaccine was developed with long tumor
peptides combined with toll like receptor 2 ligand Pam2Cys. They are formulated
with liposomes with or without emulsions. The novel vaccine increased the activa-
tion of T, B cells, and CD11c+ F4/80+CD11b+ when compared with the control
vaccine and is associated with decrease in tumor size (Naciute et al. 2020).
Furthermore, the personalized peptide vaccine have also emerged that could be a
promising therapeutic strategy (Parizadeh et al. 2019). However, further clinical trial
is necessitated for the benefit of patient.
12.6.8 Adoptive Cell Transfer Therapy (ACT)
Adoptive cell transfer therapy is the novel emerging therapy model for CRC. The
process includes collection of cytotoxic T cells from the patient’s tumor cell,
peripheral blood of lymph. They are then infused into the blood stream of the patient
as to distinguish the tumor cell and kill it to attain sustained immune response
(Rosenberg and Restifo 2015; Ruella and Kalos 2014). For instance, the NK cells
extracted from the umbilical cord of a mouse model resulted positively against
BRAF and RAS mutation related malignancy when administered. They also gave
positive outcome with cetuximab resistant tumor cells (Veluchamy et al. 2016,
2017). In case of human patients, the administration of IL-2 or IL-15 with incubated
NK-cell transplants showed positive results with mCRC and mutated EGFR. The
chimeric antigen receptors (CAR) T cell immunotherapy is in preclinical phase that
is tested in mCRC mouse model. It includes the engineering of T cells to express
more immune stimulator ligands that are designed as lipid nanoparticles encapsu-
lated with IL-2, IL-7, or IL-15 receptor (Yeku and Brentjens 2016; Shum et al.
2018). Thus, they enhance the killing of tumor cells by selectively binding to tumor
cells. Similarly, CEA is taken as a biomarker that is targeted by CAR administered in
mCRC (Parkhurst et al. 2011; Katz et al. 2015; Zhang et al. 2017). The mCRC
patients treated with CAR T cell infusion showed decrease in the size of tumor (Katz
et al. 2015). It was suggested as a successful therapy to treat B cell malignancy
(Maude et al. 2014; Kochenderfer et al. 2015) as well advantageous for CRC but
undetermined (Johnson and June 2017; Newick et al. 2017) (Table 12.3).
12.7 Conclusion
Apart from other therapeutic strategies for CRC, immunotherapy assists as a

pioneering step toward novel rational therapeutic option and lays platform for the
combinational therapy. For instance, the combination of nivolumab and ipilimumab
found efficient with positive results and increased survival in MSI-heavy mCRC
patients. Furthermore, discovering novel predictive biomarkers could be the extreme
therapeutic option in clinical settings. A thorough understanding about the genetical
features and mechanisms related to MMR is very much essential to detect the
immune targets. The traditional chemotherapeutic strategies are found effective but
with adverse side effects and the patient turn back with recurrence cancer. The
immunotherapy is found better with increased survival rate of patient. Other than
this the personalized immunotherapy and combinational immunotherapy are found
to be the promising avenues with better survival rate targeting the immune check-
points. Additionally, combining cytotoxic immune therapies with radiation and
chemotherapy are highly advantageous. The clinical findings till now provided are
with possible way for CRC therapy. Future preclinical and clinical trials approved by
FDA for drugs essential for immune targeted therapies for the benefit of the patient
are needed.
References
Alderdice M, Richman SD, Gollins S, Stewart JP, Hurt C, Adams R, McCorry AM, Roddy AC,
Vimalachandran D, Isella C (2018) Prospective patient stratification into robust cancer-cell
intrinsic subtypes from colorectal cancer biopsies. J Pathol 245:19–28
Ascierto PA, Del Vecchio M, Robert C, Mackiewicz A, Chiarion-Sileni V, Arance A, Lebbé C,
Bastholt L, Hamid O, Rutkowski P (2017) Ipilimumab 10 mg/kg versus ipilimumab 3 mg/kg in
patients with unresectable or metastatic melanoma: a randomised, double-blind, multicentre,
phase 3 trial. Lancet Oncol 18:611–622
Banerjea A, Ahmed S, Hands RE, Huang F, Han X, Shaw PM, Feakins R, Bustin SA, Dorudi S
(2004) Colorectal cancers with microsatellite instability display mRNA expression signatures
characteristic of increased immunogenicity. Mol Cancer 3:21
Bates G, Fox SB, Han C, Leek RD, Garcia JF, Harris AL, Banham AH (2006) Quantification of
regulatory T cells enables the identification of high-risk breast cancer patients and those at risk
of late relapse. J Clin Oncol 24:5373–5380
Becht E, Giraldo NA, Germain C, de Reynies A, Laurent-Puig P, Zucman-Rossi J, Dieu-Nosjean
M-C, Sautes-Fridman C, Fridman WH (2016a) Immune contexture, immunoscore, and malig-
nant cell molecular subgroups for prognostic and theranostic classifications of cancers. In:
Advances in immunology. Elsevier, San Diego, pp 95–190
Becht E, de Reyniès A, Giraldo NA, Pilati C, Buttard B, Lacroix L, Selves J, Sautès-Fridman C,
Laurent-Puig P, Fridman WH (2016b) Immune and stromal classification of colorectal cancer is
associated with molecular subtypes and relevant for precision immunotherapy. Clin Cancer Res
22:4057–4066
Bendell JC, Powderly JD, Lieu CH, Eckhardt SG, Hurwitz H, Hochster HS, Murphy JE, Funke RP,
Rossi C, Wallin J (2015) Safety and efficacy of MPDL3280A (anti-PDL1) in combination with
bevacizumab (bev) and/or FOLFOX in patients (pts) with metastatic colorectal cancer (mCRC).
J Clin Oncol 33:704
Bennett C, Christie J, Ramsdell F, Brunkow ME, Ferguson PJ, Whitesell L, Kelly TE, Saulsbury
FT, Chance PF, Ochs HD (2001) The immune dysregulation, polyendocrinopathy, enteropathy,
X-linked syndrome (IPEX) is caused by mutations of FOXP3. Nat Genet 27:20–21
Bhandaru M, Rotte A (2017) Blockade of programmed cell death protein-1 pathway for the
treatment of melanoma. J Dermatol Res Ther 1:1
Bhandaru M, Rotte A (2019) Monoclonal antibodies for the treatment of melanoma: present and
future strategies. In: Human monoclonal antibodies. Springer, New York, pp 83–108
Bilusic M, Heery CR, Arlen PM, Rauckhorst M, Apelian D, Tsang KY, Tucker JA, Jochems C,
Schlom J, Gulley JL (2014) Phase I trial of a recombinant yeast-CEA vaccine (GI-6207) in
adults with metastatic CEA-expressing carcinoma, Cancer Immunology. Immunotherapy
63:225–234
Blankenstein T, Coulie PG, Gilboa E, Jaffee EM (2012) The determinants of tumour immunoge-
nicity. Nat Rev Cancer 12:307–313
Brunkow ME, Jeffery EW, Hjerrild KA, Paeper B, Clark LB, Yasayko S-A, Wilkinson JE, Galas D,
Ziegler SF, Ramsdell F (2001) Disruption of a new forkhead/winged-helix protein, scurfin,
results in the fatal lymphoproliferative disorder of the scurfy mouse. Nat Genet 27:68–73
Budinska E, Popovici V, Tejpar S, D’Ario G, Lapique N, Sikora KO, Di Narzo AF, Yan P,
Hodgson JG, Weinrich S (2013) Gene expression patterns unveil a new level of molecular
heterogeneity in colorectal cancer. J Pathol 231:63–76
Chen EX, Jonker DJ, Loree JM, Kennecke HF, Berry SR, Couture F, Ahmad CE, Goffin JR,
Kavan P, Harb M (2020) Effect of combined immune checkpoint inhibition vs best supportive
care alone in patients with advanced colorectal cancer: the Canadian Cancer Trials Group
CO. 26 Study. JAMA Oncol. https://doi.org/10.1001/jamaoncol.2020.0910
Chikuma S, Abbas AK, Bluestone JA (2005) B7-independent inhibition of T cells by CTLA-4. J
Immunol 175:177–181
Chung KY, Gore I, Fong L, Venook A, Beck SB, Dorazio P, Criscitiello PJ, Healey DI, Huang B,
Gomez-Navarro J (2010) Phase II study of the anti-cytotoxic T-lymphocyte–associated antigen
4 monoclonal antibody, tremelimumab, in patients with refractory metastatic colorectal cancer. J
Clin Oncol 28:3485–3490
Coussens LM, Tinkle CL, Hanahan D, Werb Z (2000) MMP-9 supplied by bone marrow–derived
cells contributes to skin carcinogenesis. Cell 103:481–490
Curiel TJ, Coukos G, Zou L, Alvarez X, Cheng P, Mottram P, Evdemon-Hogan M, Conejo-Garcia
JR, Zhang L, Burow M (2004) Specific recruitment of regulatory T cells in ovarian carcinoma
fosters immune privilege and predicts reduced survival. Nat Med 10:942–949
Das M, Zhu C, Kuchroo VK (2017) Tim-3 and its role in regulating anti-tumor immunity. Immunol
Rev 276:97–111
de Leeuw RJ, Kost SE, Kakal JA, Nelson BH (2012) The prognostic value of FoxP3+ tumor-
infiltrating lymphocytes in cancer: a critical review of the literature. Clin Cancer Res
18:3022–3029
Di Giacomo A, Ascierto P, Queirolo P, Pilla L, Ridolfi R, Santinami M, Testori A, Simeone E,
Guidoboni M, Maurichi A (2015) Three-year follow-up of advanced melanoma patients who
received ipilimumab plus fotemustine in the Italian Network for Tumor Biotherapy (NIBIT)-M1
phase II study. Ann Oncol 26:798–803
Dolcetti R, Viel A, Doglioni C, Russo A, Guidoboni M, Capozzi E, Vecchiato N, Macrì E,
Fornasarig M, Boiocchi M (1999) High prevalence of activated intraepithelial cytotoxic T
lymphocytes and increased neoplastic cell apoptosis in colorectal carcinomas with microsatellite
instability. Am J Pathol 154:1805–1813
Dunn GP, Old LJ, Schreiber RD (2004) The three Es of cancer immunoediting. Annu Rev Immunol
22:329–360
Eggermont AM, Chiarion-Sileni V, Grob J-J, Dummer R, Wolchok JD, Schmidt H, Hamid O,
Robert C, Ascierto PA, Richards JM (2016) Prolonged survival in stage III melanoma with
ipilimumab adjuvant therapy. N Engl J Med 375:1845–1855
Eggermont AM, Chiarion-Sileni V, Grob J-J, Dummer R, Wolchok JD, Schmidt H, Hamid O,
Robert C, Ascierto PA, Richards JM (2019) Adjuvant ipilimumab versus placebo after complete
resection of stage III melanoma: long-term follow-up results of the European Organisation for
Research and Treatment of Cancer 18071 double-blind phase 3 randomised trial. Eur J Cancer
119:1–10
Felipe De Sousa EM, Wang X, Jansen M, Fessler E, Trinh A, De Rooij LP, De Jong JH, De Boer
OJ, Van Leersum R, Bijlsma MF (2013) Poor-prognosis colon cancer is defined by a molecu-
larly distinct subtype and develops from serrated precursor lesions. Nat Med 19:614
Fleisher AS, Esteller M, Harpaz N, Leytin A, Rashid A, Xu Y, Liang J, Stine OC, Yin J, Zou T-T
(2000) Microsatellite instability in inflammatory bowel disease-associated neoplastic lesions is
associated with hypermethylation and diminished expression of the DNA mismatch repair gene,
hMLH1. Cancer Res 60:4864–4868
Francisco LM, Salinas VH, Brown KE, Vanguri VK, Freeman GJ, Kuchroo VK, Sharpe AH (2009)
PD-L1 regulates the development, maintenance, and function of induced regulatory T cells. J
Exp Med 206:3015–3029
Fraser JH, Rincón M, McCoy KD, Le Gros G (1999) CTLA4 ligation attenuates AP-1, NFAT and
NF-κB activity in activated T cells. Eur J Immunol 29:838–844
Fridman WH, Pagès F, Sautes-Fridman C, Galon J (2012) The immune contexture in human
tumours: impact on clinical outcome. Nat Rev Cancer 12:298–306
Fumet J-D, Isambert N, Hervieu A, Zanetta S, Guion J-F, Hennequin A, Rederstorff E, Bertaut A,
Ghiringhelli F (2018) Phase Ib/II trial evaluating the safety, tolerability and immunological
activity of durvalumab (MEDI4736)(anti-PD-L1) plus tremelimumab (anti-CTLA-4) combined
with FOLFOX in patients with metastatic colorectal cancer. ESMO open 3:e000375
Galon J, Costes A, Sanchez-Cabo F, Kirilovsky A, Mlecnik B, Lagorce-Pagès C, Tosolini M,
Camus M, Berger A, Wind P (2006) Type, density, and location of immune cells within human
colorectal tumors predict clinical outcome. Science 313:1960–1964
Garon EB, Rizvi NA, Hui R, Leighl N, Balmanoukian AS, Eder JP, Patnaik A, Aggarwal C,
Gubens M, Horn L (2015) Pembrolizumab for the treatment of non–small-cell lung cancer. N
Engl J Med 372:2018–2028
Gerrard TL, Cohen DJ, Kaplan AM (1981) Human neutrophil-mediated cytotoxicity to tumor cells.
J Natl Cancer Inst 66:483–488
Giaccone G, Kim C, Thompson J, McGuire C, Kallakury B, Chahine JJ, Manning M, Mogg R,
Blumenschein WM, Tan MT (2018) Pembrolizumab in patients with thymic carcinoma: a
single-arm, single-centre, phase 2 study. Lancet Oncol 19:347–355
Goldszmid RS, Dzutsev A, Trinchieri G (2014) Host immune response to infection and cancer:
unexpected commonalities. Cell Host Microbe 15:295–305
Grivennikov SI, Greten FR, Karin M (2010) Immunity, inflammation, and cancer. Cell
140:883–899
Guinney J, Dienstmann R, Wang X, De Reyniès A, Schlicker A, Soneson C, Marisa L, Roepman P,
Nyamundanda G, Angelino P (2015) The consensus molecular subtypes of colorectal cancer.
Nat Med 21:1350–1356
Haas M, Dimmler A, Hohenberger W, Grabenbauer GG, Niedobitek G, Distel LV (2009) Stromal
regulatory T-cells are associated with a favourable prognosis in gastric cancer of the cardia.
BMC Gastroenterol 9:65
Halama N, Braun M, Kahlert C, Spille A, Quack C, Rahbari N, Koch M, Weitz J, Kloor M, Zoernig
I (2011) Natural killer cells are scarce in colorectal carcinoma tissue despite high levels of
chemokines and cytokines. Clin Cancer Res 17:678–689
Hanahan D, Weinberg RA (2011) Hallmarks of cancer: the next generation. Cell 144:646–674
Hanna MG Jr, Hoover HC Jr, Vermorken JB, Harris JE, Pinedo HM (2001) Adjuvant active specific
immunotherapy of stage II and stage III colon cancer with an autologous tumor cell vaccine: first
randomized phase III trials show promise. Vaccine 19:2576–2582
Hemminki A, Peltomäki P, Mecklin J-P, Järvinen H, Salovaara R, Nyström-Lahti M, de la
Chapelle A, Aaltonen LA (1994) Loss of the wild type MLH1 gene is a feature of hereditary
nonpolyposis colorectal cancer. Nat Genet 8:405–410
Herman JG, Umar A, Polyak K, Graff JR, Ahuja N, Issa J-PJ, Markowitz S, Willson JK, Hamilton
SR, Kinzler KW (1998) Incidence and functional consequences of hMLH1 promoter
hypermethylation in colorectal carcinoma. Proc Natl Acad Sci 95:6870–6875
Idenoue S, Hirohashi Y, Torigoe T, Sato Y, Tamura Y, Hariu H, Yamamoto M, Kurotaki T,
Tsuruma T, Asanuma H (2005) A potent immunogenic general cancer vaccine that targets
survivin, an inhibitor of apoptosis proteins. Clin Cancer Res 11:1474–1482
Intlekofer AM, Thompson CB (2013) At the bench: preclinical rationale for CTLA-4 and PD-1
blockade as cancer immunotherapy. J Leukoc Biol 94:25–39
Jiang X-R, Song A, Bergelson S, Arroll T, Parekh B, May K, Chung S, Strouse R, Mire-Sluis A,
Schenerman M (2011) Advances in the assessment and control of the effector functions of
therapeutic antibodies. Nat Rev Drug Discov 10:101–111
Jiang T, Sun Y, Yin Z, Feng S, Sun L, Li Z (2015) Research progress of indoleamine
2, 3-dioxygenase inhibitors. Future Med Chem 7:185–201
Jobin G, Rodriguez-Suarez R, Betito K (2017) Association between natural killer cell activity and
colorectal cancer in high-risk subjects undergoing colonoscopy. Gastroenterology 153:980–987
Johnson LA, June CH (2017) Driving gene-engineered T cell immunotherapy of cancer. Cell Res
27:38–58
Joyce JA, Fearon DT (2015) T cell exclusion, immune privilege, and the tumor microenvironment.
Science 348:74–80
Joyce JA, Baruch A, Chehade K, Meyer-Morse N, Giraudo E, Tsai F-Y, Greenbaum DC, Hager JH,
Bogyo M, Hanahan D (2004) Cathepsin cysteine proteases are effectors of invasive growth and
angiogenesis during multistage tumorigenesis. Cancer Cell 5:443–453
Katz SC, Burga RA, McCormack E, Wang LJ, Mooring W, Point GR, Khare PD, Thorn M, Ma Q,
Stainken BF (2015) Phase I hepatic immunotherapy for metastases study of intra-arterial
chimeric antigen receptor–modified T-cell therapy for CEA+ liver metastases. Clin Cancer
Res 21:3149–3159
Kim JW, Eder JP (2014) Prospects for targeting PD-1 and PD-L1 in various tumor types. Oncology
28:15
Kim VM, Pan X, Soares KC, Azad NS, Ahuja N, Gamper CJ, Blair AB, Muth S, Ding D, Ladle BH
(2020) Neoantigen-based EpiGVAX vaccine initiates antitumor immunity in colorectal cancer.
JCI Insight 5:e136368
Kimura T, McKolanis JR, Dzubinski LA, Islam K, Potter DM, Salazar AM, Schoen RE, Finn OJ
(2013) MUC1 vaccine for individuals with advanced adenoma of the colon: a cancer
immunoprevention feasibility study. Cancer Prev Res 6:18–26
Kobayashi H, Enomoto A, Woods SL, Burt AD, Takahashi M, Worthley DL (2019) Cancer-
associated fibroblasts in gastrointestinal cancer. Nat Rev Gastroenterol Hepatol 16:282–295
Kochenderfer JN, Dudley ME, Kassim SH, Somerville RP, Carpenter RO, Stetler-Stevenson M,
Yang JC, Phan GQ, Hughes MS, Sherry RM (2015) Chemotherapy-refractory diffuse large
B-cell lymphoma and indolent B-cell malignancies can be effectively treated with autologous T
cells expressing an anti-CD19 chimeric antigen receptor. J Clin Oncol 33:540
Kryczek I, Wu K, Zhao E, Wei S, Vatan L, Szeliga W, Huang E, Greenson J, Chang A, Roliński J
(2011) IL-17+ regulatory T cells in the microenvironments of chronic inflammation and cancer.
J Immunol 186:4388–4395
Latchman Y, Wood CR, Chernova T, Chaudhary D, Borde M, Chernova I, Iwai Y, Long AJ, Brown
JA, Nunes R (2001) PD-L2 is a second ligand for PD-1 and inhibits T cell activation. Nat
Immunol 2:261–268
Leach DR, Krummel MF, Allison JP (1996) Enhancement of antitumor immunity by CTLA-4
blockade. Science 271:1734–1736
Löfroos A-B, Kadivar M, Lindehammer SR, Marsal J (2017) Colorectal cancer-infiltrating T
lymphocytes display a distinct chemokine receptor expression profile. Eur J Med Res 22:40
Lucas C, Barnich N, Nguyen HTT (2017) Microbiota, inflammation and colorectal cancer. Int J Mol
Sci 18:1310
Luke JJ, Bao R, Sweis RF, Spranger S, Gajewski TF (2019) WNT/β-catenin pathway activation
correlates with immune exclusion across human cancers. Clin Cancer Res 25:3074–3083
Luo C, Zhang H (2017) The role of proinflammatory pathways in the pathogenesis of colitis-
associated colorectal cancer. Mediat Inflamm 2017:1
Mahoney KM, Rennert PD, Freeman GJ (2015) Combination cancer immunotherapy and new
immunomodulatory targets. Nat Rev Drug Discov 14:561–584
Marisa L, de Reyniès A, Duval A, Selves J, Gaub MP, Vescovo L, Etienne-Grimaldi M-C,
Schiappa R, Guenot D, Ayadi M (2013) Gene expression classification of colon cancer into
molecular subtypes: characterization, validation, and prognostic value. PLoS Med 10:e1001453
Markman JL, Shiao SL (2015) Impact of the immune system and immunotherapy in colorectal
cancer. J Gastrointest Oncol 6:208
Mármol I, Sánchez-de-Diego C, Pradilla Dieste A, Cerrada E, Rodriguez Yoldi M (2017) Colorec-
tal carcinoma: a general overview and future perspectives in colorectal cancer. Int J Mol Sci
18:197
Maude SL, Frey N, Shaw PA, Aplenc R, Barrett DM, Bunin NJ, Chew A, Gonzalez VE, Zheng Z,
Lacey SF (2014) Chimeric antigen receptor T cells for sustained remissions in leukemia. N Engl
J Med 371:1507–1517
Michalarea V, Fontana E, Garces AI, Williams A, Smyth EC, Picchia S, Rao S, Chau I,
Cunningham D, Bali MA (2019) Pseudoprogression on treatment with immune-checkpoint
inhibitors in patients with gastrointestinal malignancies: case series and short literature review.
Curr Probl Cancer 43:487–494
Miyagi Y, Imai N, Sasatomi T, Yamada A, Mine T, Katagiri K, Nakagawa M, Muto A, Okouchi S,
Isomoto H (2001) Induction of cellular immune responses to tumor cells and peptides in
colorectal cancer patients by vaccination with SART3 peptides. Clin Cancer Res 7:3950–3962
Miyara M, Yoshioka Y, Kitoh A, Shima T, Wing K, Niwa A, Parizot C, Taflin C, Heike T, Valeyre
D (2009) Functional delineation and differentiation dynamics of human CD4+ T cells
expressing the FoxP3 transcription factor. Immunity 30:899–911
Mlecnik B, Bindea G, Angell HK, Maby P, Angelova M, Tougeron D, Church SE, Lafontaine L,
Fischer M, Fredriksen T (2016) Integrative analyses of colorectal cancer show immunoscore is a
stronger predictor of patient survival than microsatellite instability. Immunity 44:698–711
Moulton HM, Yoshihara PH, Mason DH, Iversen PL, Triozzi PL (2002) Active specific immuno-
therapy with a β-human chorionic gonadotropin peptide vaccine in patients with metastatic
colorectal cancer: antibody response is associated with improved survival. Clin Cancer Res
8:2044–2051
Munegowda MA, Deng Y, Mulligan SJ, Xiang J (2011) Th17 and Th17-stimulated CD8+ T cells
play a distinct role in Th17-induced preventive and therapeutic antitumor immunity. Cancer
Immunol Immunother 60:1473
Munn DH, Cheung N (1990) Phagocytosis of tumor cells by human monocytes cultured in
recombinant macrophage colony-stimulating factor. J Exp Med 172:231–237
Munn DH, Mellor AL (2013) Indoleamine 2, 3 dioxygenase and metabolic control of immune
responses. Trends Immunol 34:137–143
Naboush A, Roman CA, Shapira I (2017) Immune checkpoint inhibitors in malignancies with
mismatch repair deficiency: a review of the state of the current knowledge. J Investig Med
65:754–758
Naciute M, Niemi V, Kemp RA, Hook S (2020) Lipid-encapsulated oral therapeutic peptide
vaccines reduce tumour growth in an orthotopic mouse model of colorectal cancer. Eur J
Pharm Biopharm 152:183
Newick K, O'Brien S, Moon E, Albelda SM (2017) CAR T cell therapy for solid tumors. Annu Rev
Med 68:139–152
Ogino S, Nosho K, Irahara N, Meyerhardt JA, Baba Y, Shima K, Glickman JN, Ferrone CR, Mino-
Kenudson M, Tanaka N (2009) Lymphocytic reaction to colorectal cancer is associated with
longer survival, independent of lymph node count, microsatellite instability, and CpG island
methylator phenotype. Clin Cancer Res 15:6412–6420
Ouyang W, O’Garra A (2019) IL-10 family cytokines IL-10 and IL-22: from basic science to
clinical translation. Immunity 50:871–891
Pardoll D (2002) T cells take aim at cancer. Proc Natl Acad Sci 99:15840–15842
Cancer 12:252–264
Parizadeh SM, Jafarzadeh-Esfehani R, Ghandehari M, Rezaei-Kalat A, Parizadeh SM,
Javanbakht A, Hassanian SM, Ferns GA, Khazaei M, Avan A (2019) Personalized peptide-
based vaccination for treatment of colorectal cancer: rational and progress. Curr Drug Targets
20:1486–1495
Parkhurst MR, Yang JC, Langan RC, Dudley ME, Nathan D-AN, Feldman SA, Davis JL, Morgan
RA, Merino MJ, Sherry RM (2011) T cells targeting carcinoembryonic antigen can mediate
regression of metastatic colorectal cancer but induce severe transient colitis. Mol Ther
19:620–626
Perez-Ruiz E, Minute L, Otano I, Alvarez M, Ochoa MC, Belsue V, de Andrea C, Rodriguez-Ruiz

ME, Perez-Gracia JL, Marquez-Rodas I (2019) Prophylactic TNF blockade uncouples efficacy
and toxicity in dual CTLA-4 and PD-1 immunotherapy. Nature 569:428–432
Perkins D, Wang Z, Donovan C, He H, Mark D, Guan G, Wang Y, Walunas T, Bluestone J,
Listman J (1996) Regulation of CTLA-4 expression during T cell activation. J Immunol
156:4154–4159
Perrella A, D'Antonio A, Sbreglia C, Sorrentino P, Conca P, Atripaldi L, Conti P, Perrella O (2014)
CD4+/CD25+ T cells suppress autologous CD4+/CD25 lymphocytes and secrete granzyme B
during acute and chronic hepatitis C. Pathog Dis 72:124–130
Phillips S, Banerjea A, Feakins R, Li S, Bustin S, Dorudi S (2004) Tumour-infiltrating lymphocytes
in colorectal cancer with microsatellite instability are activated and cytotoxic. Br J Surg
91:469–475
Plitas G, Konopacki C, Wu K, Bos PD, Morrow M, Putintseva EV, Chudakov DM, Rudensky AY
(2016) Regulatory T cells exhibit distinct features in human breast cancer. Immunity
45:1122–1134
Poon E, Mullins S, Watkins A, Williams GS, Koopmann J-O, Di Genova G, Cumberbatch M,
Veldman-Jones M, Grosskurth SE, Sah V (2017) The MEK inhibitor selumetinib complements
CTLA-4 blockade by reprogramming the tumor immune microenvironment. J Immunother
Cancer 5:63
Postow MA, Callahan MK, Wolchok JD (2015) Immune checkpoint blockade in cancer therapy. J
Clin Oncol 33:1974
Purdy AK, Campbell KS (2009) Natural killer cells and cancer: regulation by the killer cell Ig-like
receptors (KIR). Cancer Biol Ther 8:2209–2218
Qian B-Z, Li J, Zhang H, Kitamura T, Zhang J, Campion LR, Kaiser EA, Snyder LA, Pollard JW
(2011) CCL2 recruits inflammatory monocytes to facilitate breast-tumour metastasis. Nature
475:222–225
Robert C, Thomas L, Bondarenko I, O'Day S, Weber J, Garbe C, Lebbe C, Baurain J-F, Testori A,
Grob J-J (2011) Ipilimumab plus dacarbazine for previously untreated metastatic melanoma. N
Engl J Med 364:2517–2526
Roepman P, Schlicker A, Tabernero J, Majewski I, Tian S, Moreno V, Snel MH, Chresta CM,
Rosenberg R, Nitsche U (2014) Colorectal cancer intrinsic subtypes predict chemotherapy
benefit, deficient mismatch repair and epithelial-to-mesenchymal transition. Int J Cancer
134:552–562
Rosenberg SA, Restifo NP (2015) Adoptive cell transfer as personalized immunotherapy for human
cancer. Science 348:62–68
Rotte A (2019) Combination of CTLA-4 and PD-1 blockers for treatment of cancer. J Exp Clin
Cancer Res 38:255
Rotte A, Jin J, Lemaire V (2018) Mechanistic overview of immune checkpoints to support the
rational design of their combinations in cancer immunotherapy. Ann Oncol 29:71–83
Ruella M, Kalos M (2014) Adoptive immunotherapy for cancer. Immunol Rev 257:14–38
Sadanandam A, Lyssiotis CA, Homicsko K, Collisson EA, Gibb WJ, Wullschleger S, Ostos LCG,
Lannon WA, Grotzinger C, Del Rio M (2013) A colorectal cancer classification system that
associates cellular phenotype and responses to therapy. Nat Med 19:619
Saito T, Nishikawa H, Wada H, Nagano Y, Sugiyama D, Atarashi K, Maeda Y, Hamaguchi M,
Ohkura N, Sato E (2016) Two FOXP3+ CD4+ T cell subpopulations distinctly control the
prognosis of colorectal cancers. Nat Med 22:679
Sasada T, Kimura M, Yoshida Y, Kanai M, Takabayashi A (2003) CD4+ CD25+ regulatory T cells
in patients with gastrointestinal malignancies: possible involvement of regulatory T cells in
disease progression. Cancer 98:1089–1099
Schlicker A, Beran G, Chresta CM, McWalter G, Pritchard A, Weston S, Runswick S, Davenport S,
Heathcote K, Castro DA (2012) Subtypes of primary colorectal tumors correlate with response
to targeted treatment in colorectal cell lines. BMC Med Genet 5:66
Schneider H, Valk E, Leung R, Rudd CE (2009) Correction: CTLA-4 activation of

phosphatidylinositol 3-kinase (PI 3-K) and protein kinase B (PKB/AKT) sustains T-cell anergy
without cell death. PLoS One 4. https://doi.org/10.1371/annotation/5f36e0a6-8e8b-4b33-8e96-
a2d53d5c1e46
Schumacher TN, Schreiber RD (2015) Neoantigens in cancer immunotherapy. Science 348:69–74
Shang B, Liu Y, Jiang S (2015) Prognostic value of tumor-infiltrating FoxP3 (+) regulatory T cells
in cancers: a systematic review and meta-analysis. Sci Rep 5:15179
Shimizu Y, Yoshikawa T, Kojima T, Shoda K, Nosaka K, Mizuno S, Wada S, Fujimoto Y,
Sasada T, Kohashi K (2019) Heat shock protein 105 peptide vaccine could induce antitumor
immune reactions in a phase I clinical trial. Cancer Sci 110:3049
Shum T, Kruse RL, Rooney CM (2018) Strategies for enhancing adoptive T-cell immunotherapy
against solid tumors using engineered cytokine signaling and other modalities. Expert Opin Biol
Ther 18:653–664
Siegel RL, Miller KD, Jemal A (2020) Cancer statistics, 2020. CA Cancer J Clin 70:7–30
Speetjens FM, Kuppen PJ, Welters MJ, Essahsah F, Lantrua MGK, Valentijn ARP, Oostendorp J,
Fathers LM, Nijman HW, Drijfhout JW (2009) Induction of p53-specific immunity by a p53
synthetic long peptide vaccine in patients treated for metastatic colorectal cancer. Clin Cancer
Res 15:1086–1095
Spill F, Reynolds DS, Kamm RD, Zaman MH (2016) Impact of the physical microenvironment on
tumor progression and metastasis. Curr Opin Biotechnol 40:41–48
Spranger S, Bao R, Gajewski TF (2015) Melanoma-intrinsic β-catenin signalling prevents anti-
tumour immunity. Nature 523:231–235
Sugiura D, Maruhashi T, Okazaki I-m, Shimizu K, Maeda TK, Takemoto T, Okazaki T (2019)
Restriction of PD-1 function by cis-PD-L1/CD80 interactions is required for optimal T cell
responses. Science 364:558–566
Sugiyama D, Nishikawa H, Maeda Y, Nishioka M, Tanemura A, Katayama I, Ezoe S, Kanakura Y,
Sato E, Fukumori Y (2013) Anti-CCR4 mAb selectively depletes effector-type FoxP3+ CD4+
regulatory T cells, evoking antitumor immune responses in humans. Proc Natl Acad Sci
110:17945–17950
Sun J, Kato I (2016) Gut microbiota, inflammation and colorectal cancer. Genes Dis 3:130–143
Sun Q, Burton RL, Lucas KG (2002) Cytokine production and cytolytic mechanism of CD4+
cytotoxic T lymphocytes in ex vivo expanded therapeutic Epstein-Barr virus–specific T-cell
cultures. Blood 99:3302–3309
Teng MW, Swann JB, Koebel CM, Schreiber RD, Smyth MJ (2008) Immune-mediated dormancy:
an equilibrium with cancer. J Leukoc Biol 84:988–993
Topalian SL, Drake CG, Pardoll DM (2015) Immune checkpoint blockade: a common denominator
approach to cancer therapy. Cancer Cell 27:450–461
Topalian SL, Taube JM, Anders RA, Pardoll DM (2016) Mechanism-driven biomarkers to guide
immune checkpoint blockade in cancer therapy. Nat Rev Cancer 16:275
Van Pel A, Boon T (1982) Protection against a nonimmunogenic mouse leukemia by an immuno-
genic variant obtained by mutagenesis. Proc Natl Acad Sci 79:4718–4722
Veluchamy JP, Spanholtz J, Tordoir M, Thijssen VL, Heideman DA, Verheul HM, de Gruijl TD,
van der Vliet HJ (2016) Combination of NK cells and cetuximab to enhance anti-tumor
responses in RAS mutant metastatic colorectal cancer. PLoS One 11:e0157830
Veluchamy JP, Lopez-Lastra S, Spanholtz J, Bohme F, Kok N, Heideman DA, Verheul HM, Di
Santo JP, de Gruijl TD, van der Vliet HJ (2017) In vivo efficacy of umbilical cord blood stem
cell-derived NK cells in the treatment of metastatic colorectal cancer. Front Immunol 8:87
Villamil BP, Lopez AR, Prieto SH, Campos GL, Calles A, Asenjo JAL, Ortega JS, Perez CF,
Sastre J, Alfonso R (2012) Colon cancer molecular subtypes identified by expression profiling
and associated to stroma, mucinous type and different clinical behavior. BMC Cancer 12:260
Walker LS (2013) Treg and CTLA-4: two intertwining pathways to immune tolerance. J
Autoimmun 45:49–57
Wang S, Fu Y, Ma K, Liu C, Jiao X, Du W, Zhang H, Wu X (2014) The significant increase and

dynamic changes of the myeloid-derived suppressor cells percentage with chemotherapy in
advanced NSCLC patients. Clin Transl Oncol 16:616–622
Weiner LM, Murray JC, Shuptrine CW (2012) Antibody-based immunotherapy of cancer. Cell
148:1081–1084
Whitehead GS, Wilson RH, Nakano K, Burch LH, Nakano H, Cook DN (2012) IL-35 production
by inducible costimulator (ICOS)–positive regulatory T cells reverses established IL-17–depen-
dent allergic airways disease. J Allergy Clin Immunol 129:207–215. e205
Willett CG, Chang DT, Czito BG, Meyer J, Wo J, Cancer Genome Atlas Network (2012)
Comprehensive molecular characterization of human colon and rectal cancer. Nature 487
(7407):330, International Journal of Radiation Oncology Biology Physics, 86 (2013)
Yeku OO, Brentjens RJ (2016) Armored CAR T-cells: utilizing cytokines and pro-inflammatory
ligands to enhance CAR T-cell anti-tumour efficacy. Biochem Soc Trans 44:412–418
Zamai L, Ponti C, Mirandola P, Gobbi G, Papa S, Galeotti L, Cocco L, Vitale M (2007) NK cells
and cancer. J Immunol 178:4011–4016
Zeng ZS, Huang Y, Cohen AM, Guillem JG (1996) Prediction of colorectal cancer relapse and
survival via tissue RNA levels of matrix metalloproteinase-9. J Clin Oncol 14:3133–3140
Zhang B, Wang Z, Wu L, Zhang M, Li W, Ding J, Zhu J, Wei H, Zhao K (2013) Circulating and
tumor-infiltrating myeloid-derived suppressor cells in patients with colorectal carcinoma. PLoS
One 8:e57114
Zhang C, Wang Z, Yang Z, Wang M, Li S, Li Y, Zhang R, Xiong Z, Wei Z, Shen J (2017) Phase I
escalating-dose trial of CAR-T therapy targeting CEA+ metastatic colorectal cancers. Mol Ther
25:1248–1258
Chapter 13
Applications of Computational Biology
in Gastrointestinal Malignancies
Manoj Kumar Gupta and Ramakrishna Vadde
Abstract Gastrointestinal cancers (GICs) are the most common cancers of the
digestive tract system in humans. Earlier several techniques have been utilized to
understand the molecular mechanism and identification of the key gene or protein–
protein interaction that is responsible for causing GICs. Nevertheless, detecting key
genes and protein–protein interaction through experimental equipment necessitates
huge capital and time. Recently developed computational methods provide a distinct
way to address such problems in a short interval of time with less cost. Thus, in the
present chapter authors attempted to understand how computational approaches may
help us in detecting key genes and protein associated with GICs. Information
obtained revealed that several studies have employed computational methods to
identify key hub genes, including COL4A1 and SERPINH1, transcription factors
(e.g., MYC and MAZ), and miRNAs (e.g., miRNA-133b and miRNA-99a) that play a
key role in the gastric cancer development. Computational studies have also detected
key hub genes (e.g., AMBP and APOB) and miRNAs (e.g., miRNA-7 and miRNA-
141) that play a key role in the development of colorectal cancer. However, all these
studies performed analysis on the bulk cell level, which in turn provides less
information about gene expression at the cellular level, which might be the reason
for ineffective treatment and low survival of GICs patients. Thus, there is an urgent
requirement to understand gene expression in GICs at the cellular level. In the near
future, the information present in the present chapter will be highly valuable for
cancer biologists and immunologists toward the treatment of GICs.
Keywords Gastric cancer · Computational approach · Key genes · Drugs

Pradesh, India
https://doi.org/10.1007/978-981-15-6487-1_13
232 M. K. Gupta and R. Vadde
13.1 Introduction
Cancer is clinically characterized by malignant tumors. The tumor is an abnormal

proliferation of cells and may be either “benign” (remains confined to its original
location) or “malignant” (invades nearby healthy tissue and spreads throughout the
body by lymphatic or circulatory systems (“metastasis”)). As tumors can be formed
via any cell type, numerous types of cancer differ significantly in their behavior as
well as response to treatment (Cooper 2000). Cancer is one of the foremost death
cause globally, with 14 million new cases and ~eight million deaths per year
worldwide. Though it is well established that residents of developed countries are
more prone to cancer, in 2008, more than 70% of cancer death and more than 60% of
new cases were reported from developing countries (Shams and Haug 2017).
Recently, the incidence of cancer has increased dramatically. In 2019, 606,880
cancer deaths and 1,762,450 new cancer cases were reported to occur in the United
States alone (Siegel et al. 2019). In men, bronchus, prostate, colorectal, and lungs
cancer account for ~42% of all cancer cases. In women, colorectal, lung, and breast
cancer account for ~50% of all cancer cases. However, in women, breast cancer
solely constitutes ~30% of all new cases. Additionally, the incident of cancer in men
is higher than women, which might be due to differences in endogenous hormones
and exposure to numerous biotic and abiotic factors, for instance, cigarette smoking
(Siegel et al. 2019). Out of all forms of cancer, gastrointestinal cancers (GICs) are the
most common cancers of the digestive tract system in both men as well as women
globally. Colorectal cancer, esophageal cancer, gallbladder carcinoma, gastric can-
cer, hepatocellular carcinoma, and pancreatic cancer are the most common cancer of
GICs. Earlier studies have reported that GICs alone count for 30% of the total cancer
cases (Ge et al. 2018). Though profound progress has been made toward cancer
diagnosis as well as treatment, still the outcome of GICs treatment is unsatisfactory.
This might be due to resistance against drugs and lack of information about the
complete mechanism associated with pathogenesis, cell differentiation, and origin of
the disease (Wu et al. 2012). Therefore, continuous research and effective methods
are urgently required for the treatment of GICs patients.
With continuous research suggesting interaction amongst genes, as well as pro-
teins, play a significant role in molecular cancer mechanisms, it highly necessary for
introducing computational approaches in cancer research (Gupta et al. 2019a, b;
Vemula et al. 2019). Additionally, screening genes and its associated variants
responsible for causing various diseases by laboratory approaches take both huge
investment and time. However, high screening via a computational methodology
saves both money and time (Gupta et al. 2017, 2019c, d; Donde et al. 2019; Gupta
and Vadde 2019a; Gouda et al. 2020). Re-analysis of genetic information present in
International Consortia like the “International HapMap project,” “1000 genomes
project,” “Simons Genome Diversity Project,” and “Exome Aggregation Consor-
tium” (ExAC) utilizing more modern statistical tools will enable us to screen genes
along with its variants associated with various diseases or traits. Three-dimension
structure for both synthetic drugs and phytochemicals present in the publically
13 Applications of Computational Biology in Gastrointestinal Malignancies 233
available databases, for instance, TIPdb database (Lin et al. 2013), can be also
utilized for identifying novel drug or phytochemicals against gene responsible for
causing any disease or trait. These ADMET (Absorption, Distribution, Metabolism,
Excretion and Toxicity) and “Lipinski’s rule of 5s” passed natural/synthetic drug
molecules will have less or no side effect (Gola et al. 2006; Lagorce et al. 2017) and
hence, in future, these phytochemicals/drugs may function as good contestants for
the treatment of various human diseases, after further laboratory investigation.
Earlier, Tang and the team employed computational approaches to understand the
complex network of known 84 T2D genes based on protein–protein interactions as
well as localization. Obtained results revealed that amongst 84 genes, 14 genes
(AKT2, UBC, IRS1, IGF2BP2, HNF4A, IRS2, HNF1A, PPARG, HMGA1,
MAPK8IP1, HNF1B, NEUROD1, TCF7L2, and GCK) play a vital role in the T2D
complex network (Tang et al. 2016). Recently, Latek and team employed computa-
tional approach for understanding glucose homeostasis disturbance and reported that
drugs with least binding energy are more capable of stimulating GIPR as well as
GLP1R and/or inhibiting GCGR, that in turn enhance insulin secretion and reduce
hepatic glucose production, thereby controlling T2D (Latek et al. 2019). Bharti and
team confirmed anti-diabetic property of Withania coagulans fruit via both in-vivo
as well as in silico approaches (Bharti et al. 2015). Kaur and the team also identified
anti-diabetic property of Theaflavin-3,30 -di-O-gallate and rutin via computational
methods (Kaur et al. 2018). Menakha and the team identified the anti-diabetic
property of phytochemical quercetin (obtained from Ipomoea sepiaria) via compu-
tational approaches (Menakha et al. 2018). In 2011, Sawey and the team performed
genomic analysis of human cellular carcinoma and reported that an oncogene,
namely, FGF19, is co-amplified with CCND1 in human tumors. They also reported
that FGF19 inhibition via RNAi restricts clonal growth as well as tumorigenicity of
human HCC cells harboring the “FGF19/CCND1” amplicon (Sawey et al. 2011).
Thus, computational investigation of varied data produced from high-throughput
sequencing technologies, for instance, RNA sequencing, provides a unique “ontol-
ogy-based solution for querying distributed databases over service-oriented, model-
driven infrastructures by integrating pathology,” clinical molecular, and radiology
data effectively (González-Beltrán et al. 2012). Besides saving time and money,
computational approaches also hasten the process of drug discovery. Considering all
this important information, recently, our laboratory has also employed computa-
tional approach toward predicting the three-dimensional structure of the “γ-secretase
activating protein” (GSAP), an Alzheimer’s disease therapeutic target, through
comparative modeling approaches and studied its structure as well as function via
simulation studies. Docking studies of GSAP with 4153 phytochemicals identified
GSAP is having a better binding affinity with “monachosorin B,” “(E)-1-
[2,4-dihydroxy-3-(3-methylbut-2-enyl) phenyl]-3-(2,2-dimethyl-8-hydroxy-2H-
benzopyran-6-yl)prop-2-en-1-one,” and “macaflavanone C” in comparison to
“imatinib” (the standard drugs). Subsequently, the molecular dynamics analysis
revealed that only two phytochemicals, namely, “macaflavanone C” and “(E)-1-
[2,4-dihydroxy-3-(3-methylbut-2-enyl)phenyl]-3-(2,2-dimethyl-8-hydroxy-2H-
benzopyran-6-yl)prop-2-en-1-one)” significantly disrupt the original property of
GSAP; thereby supporting that these two phytochemicals may be utilized in future
for curing Alzheimer’s disease (Gupta and Vadde 2019b). Thus, in this chapter
authors attempted to understand how computational approaches have revolutionized
the cancer research, especially GICs. In the near future, the information in the
present review will be highly utilized in the GICs treatment.
13.2 Methods for Detecting Cancer
Till date, numerous researcher has employed various computational approaches to

detect key gene and associated factors that are responsible for causing GICs.
However, in comparison to other GICs, very few computational studies have been
performed in the context of gallbladder carcinoma. These factors along with key
genes may serve as an important target during drug development against GICs.
13.2.1 Identification of Key Genes and Protein Responsible

for Causing GICs
A most important aim in public health research is the identification and development
of the best pharmacotherapies for treating disease. The generation and availability of
publicly available high-throughput genomic and proteomic datasets provide us with
a unique opportunity to scan key candidate gene(s) which can serve as a therapeutic
target toward the treatment of any diseases with less cost in short interval of time
(Ferguson et al. 2018). To date, numerous approaches have been developed toward
in silico drug design and development to examine how drugs interact with key
candidate genes and how they modulate the molecular process toward the prevention
or treatment of diseases (Table 13.1).
13.2.1.1 Colorectal Cancer
Recently, several independent computational studies have identified six (Wnt,

TGF-β, PI3K, MAPK, RAS, and p53) (Falzone et al. 2018), ten (ALB, AMBP, F2,
APOB, APOH, PLG, APOA1, SERPINC1, AHSG, and APOC3) (Zhang et al. 2019),
and six (COL1A1, TIMP1, CXCL5, SPP1, GNG4, and LPAR1) (Yang et al. 2018)
key genes that play vital role in colorectal cancer development. These key genes are
mainly involved in significant pathways, namely, extracellular matrix organization,
G protein-coupled receptors signaling pathway, and gastrin-CREB signaling path-
way through PKC and MAPK (Yang et al. 2018). Another computational study
identified three (DYNC1H1, GRM1, and GRIN2A), four (IGF1R, DSP, SPTA1, and
CPS1), and three (GSK3B, EIF2B5, and GGT1) key genes that are associated with
Table 13.1 GICs associated genes and miRNAs identified through computational approaches
Cancer Genes/miRNAs References
Colorectal Genes AHSG, ALB, AMBP, APOA1, Falzone et al. (2018), Zhang
cancer APOB, APOC3, APOH, et al. (2019), and Yang et al.
COL1A1, CPS1, CXCL5, DSP, (2018)
DYNC1H1, EIF2B5, F2, GGT1,
GNG4, GRIN2A, GRM1,
GSK3B, IGF1R, LPAR1, MAPK,
p53, PI3K, PLG, RAS,
SERPINC1, SPP1, SPTA1,
TGF-β, TIMP1, Wnt
miRNAs miRNA-128, miRNA-4777, Falzone et al. (2018), Zhang
miRNA-141, miRNA-143, et al. (2019), Jiang et al. (2017),
miRNA-14, miRNA-182, Ma et al. (2018), Su et al.
miRNA-183-5p, miRNA-200a, (2019), and Chen et al. (2019)
miRNA-21-5p, miRNA-4638,
miRNA-6510, miRNA-659,
miRNA-675, miRNA-7, miRNA-
195-5p, miRNA-200c, miRNA-
885, miRNA-200b, miRNA-19b-
3p
Gastric cancer Genes ACTA2, ADCY7, ADCY9, Li et al. (2018a), Liu et al.
ADHFE1, AHR, AKR1C1, BGN, (2019a), Wang et al. (2015),
BMP2, BRMS1, CALML5, Dai et al. (2018), Zheng et al.
CCNB1, CCNB2, CDKN3, (2019), Wu et al. (2019a), Zeng
CEP55, COL1A1, COL1A2, et al. (2018), Liu et al. (2014,
COL3A1, COL4A1, COL4A2, 2018a, 2019b), and Saberi
COL6A3, CTNNB1, CYP1A1, Anvar et al. (2018)
EGR1,JUN, ERBB2, ERPINH1,
FGFR4, FN1, FOS, FOSL1,
FYN, GIF, GNAS, GNG7,
GPER, GRB2, GSTP1, HSPA4,
IGF2, ITCH, ITGA5, JAK3,
KDR, MMP2, MMP9, MYH11,
ND6, NDC80, NID2, NPY,
OLFML2B, PIK3R1, PLCB1,
PTGDR, SERPINH1, SRXN1,
SST, TGFB1, THBS1, THBS2,
TIMP, TIMP1, TMEM59,
TOP2A, TPX2, VCAN, WNT7B,
XBP1
miRNAs Let-7i-5p, miRNA-21, miRNA- Su et al. (2019), Ribeiro-dos-
203, miRNA-212, miRNA-1, Santos et al. (2010), Deng et al.
miRNA-100, miRNA-368, (2013), Pan et al. (2013), Zhang
miRNA-101-3p, miRNA-107, et al. (2015), Baghaei et al.
miRNA-10a, miRNA-124a, (2017), Gu et al. (2018a),
miRNA-125b, miRNA-129, Hwang et al. (2018), Zhang
miRNA-204-5p, miRNA-135b, et al. (2018), Yuan et al. (2019),
miRNA-137, miRNA-139, and Hu et al. (2018)
miRNA-145, miRNA-148a,
(continued)

miRNA-10b, miRNA-154,
miRNA-15b, miRNA-15b-5p,
miRNA-181a*, miRNA-133a,
miRNA-181c, miRNA-18a*,
miRNA-18b, miRNA-195,
miRNA-196b, miRNA-19b,
miRNA-200A-3p, miRNA-200c,
miRNA-218, miRNA-133b,
miRNA-18a, miRNA-369-3p,
miRNA-26a, miRNA-29a,
miRNA-29b, miRNA-29c,
miRNA-300, miRNA-302c,
miRNA-30e-5p, miRNA-31,
miRNA-329, miRNA-34b/c,
miRNA-551b, miRNA-574-3p,
miRNA-664a, miRNA-767-3p,
miRNA-9, miRNA-9*, miRNA-
512, miRNA-93-5p, miRNA-96,
miRNA-99a, miRNA-125b,
miRNA-205-5p
Esophageal Genes ACSL1, BCL6, BUB1, BUB1B, He et al. (2017, 2018), Chen
cancer CCNA2, CD19, CD226, CD27, et al. (2018), Yue et al. (2017),
CD28, CD37, CD38, CD5, Dai et al. (2017), and Dong
CD74, CD83, CFL1, CHEK1, et al. (2018)
COL11A1, E2F4, FAM46A,
IL1A, IL2, IRF6, JUN, KRT14,
KRT5, LAMA3, MME, NDC1,
NUP107, NUP155, RAB15,
SFN, SLC20A1, SLURP-1, TTK,
VEGFA
miRNAs miRNA-1, miRNA-105-5p, Dai et al. (2017), Xu et al.
miRNA-1246, miRNA-21-5p, (2013), Chong et al. (2014), Liu
miRNA-1290, miRNA-375, et al. (2015), Lau et al. (2018),
miRNA-206, miRNA-208b-3p, and Cai et al. (2018)
miRNA-21-3p, miRNA-503
Pancreatic Genes Albumin, COL1A1, COL1A2,
cancer COL3A1, ECT2, epidermal
(continued)

growth factor, fibronectin1, Gupta et al. (2019a), Li et al.
integrin subunitα 2, ITGA2, (2018b), Lv et al. (2019), and
MMP2, MMP7, MMP9, NR5A2, Liu et al. (2018b)
NRP2, TGFBI, TIMP1
miRNAs miRNA-125a, miRNA-126, Ma et al. (2013), Liang et al.
miRNA-222, miRNA-100, (2018), and Tan et al. (2018)
miRNA-454 miRNA-29b,
miRNA-375, miRNA-193a-3p,
miRNA-23a, miRNA-31,
miRNA-34a, miRNA-376b,
miRNA-376c, miRNA-502-3p,
miRNA-664a
Hepatocellular Genes ABCB1, ACACB, ADH1A, Gao et al. (2018), Wu et al.
carcinoma ADH1C, AURKA, CCNB1, (2019b), Tu et al. (2019), Liu
CCNB2, CDK1, CDKN3, et al. (2019c), and Yan and Liu
CENPF, CXCR4, EHHADH, (2019)
ENO3, ESR1, IGF1, MAD2L1,
MAP2K1, NCAPG, NDC80,
PLK1, PRC1, PRCC, PRPF4,
PSMA7, RACGAP1, RIPK4,
RRM2, TLR4, TOP2A, TTK,
UBE2C, ZWINT
miRNAs miRNA-1296, miRNA-221, Yan and Liu (2019), Ji et al.
miRNA-23c, miRNA-300, (2018), Mei et al. (2018), Lou
miRNA-381-3p, miRNA-494-3p, et al. (2018), and Pan et al.
miRNA-95, miRNA-149, (2019)
miRNA-15b-5p, miRNA-29c,
miRNA-126-3p
stage-II, III, and IV progression in colorectal cancer, respectively (Palaniappan et al.

2016).
13.2.1.2 Gastric Cancer
Recently, Li and team re-analyzed three microarray datasets, namely, GSE27342,

GSE33335, GSE29272, present in the GEO database and identified seven novel
genes, namely, COL4A1, THBS2, VCAN, COL1A2, TIMP1, COL6A3, and
SERPINH1 that are associated with worse overall survival of gastric cancer in
human (Li et al. 2018a). Several other studies identified one (OLFML2B) (Liu
et al. 2019a), two (CCNB1 and CCNB2) (Wang et al. 2015), two (XBP1 and GIF)
(Dai et al. 2018), three (ND6, BRMS1, and SRXN1), three (NID2, COL4A2, and
COL4A1), six (ERPINH1, PTGDR, NPY, ADHFE1, AKR1C1, and GPER) (Zheng
et al. 2019), six (IGF2, SST, GSTP1, TMEM59, MYH11, and ERBB2) (Wu et al.
2019a), seven (FOS, AHR, EGR1, JUN, WNT7B, CYP1A1, and FOSL1) (Zeng et al.
2018), nine (TOP2A, TIMP, TPX2, COL3A1, COL1A2, CEP55, NDC80, CDKN3,
and COL1A1) (Liu et al. 2018a), ten (GNG7, PLCB1, JAK3, KDR, GNAS, FGFR4,
GRB2, ADCY9, ADCY7, and CALML5) (Liu et al. 2019b), and fifteen (CTNNB1,
FN1, FYN, MMP9, COL1A1, ITCH, TGFB1, THBS1, MMP2, ACTA2, ITGA5,
BMP2, BGN, HSPA4, and PIK3R1) keys genes associated with gastric cancer via
bioinformatics approaches. Anvar and the team identified three vital proteins,
namely, HNF4A, TAF1, and TP53 that play a crucial role in gastric cancer formation
via system biology approaches (Saberi Anvar et al. 2018). In 2014, Liu and the team
identified six clusters of proteins responsible for cell-cycle, protein degradation,
immunoreaction, and protein trafficking during gastric cancer. Out of all, COPS5
(COP9 Subunit 5) is the critical protein of all the largest cluster (module 1). They
also detected two key transcription factors, namely, MAZ (Myc-associated zinc-
finger protein) and MYC in module 1 (Liu et al. 2014). These genes may serve as key
target molecules during drug discovery against gastric cancer.
13.2.1.3 Esophageal Cancer
In 2017, He and the team identified four essential genes, namely, CHEK1, CCNA2,
COL11A1, and MME that are mainly related to cell-cycle modulation and play a vital
role in the development of esophageal cancer (He et al. 2017). In another study,
Chen and the team reported that downregulation of SLURP-1 causes esophageal
cancer (Chen et al. 2018). In another study, two sets of genes, BUB1B, BUB1, &
TTK and NDC1, NUP107, & NUP155, were identified to play an essential role in
esophageal cancer. While BUB1B, BUB1, and TTK affect the chemotherapy, NDC1,
NUP107, and NUP155 modulate the function of the RNA transport pathway during
gastric cancer. However, when combined, these six genes do not play an essential
role in the development of esophageal cancer (He et al. 2018). Yue and team
suggested that dysfunction of PTK2, MAPK signaling pathway, PI3K-Akt signaling
pathway, p53 signaling pathway, and MET plays a vital role in the development of
esophageal cancer (Yue et al. 2017). In 2017, Dai and the team suggested that
immune-related genes, namely, CD5, CD226, CD38, CD19, CD27, CD83, BCL6,
IL2, CD37, CD74, and CD28, are highly expressed in subtype I “oesophageal
squamous cell carcinoma” (OSCC). Other essential pathways associated with
subtype I are drug metabolism, chemokine signaling, and calcium signaling. On
the contrary, genes related to epithelium development, for instance, JUN, E2F4,
VEGFA, CFL1, SFN, KRT14, LAMA3, KRT5, and IRF6, are highly expressed in the
subtype II OSCC. These genes are mainly associated with numerous biological
processes, including focal adhesion, actin cytoskeleton modulation, MAPK path-
way, cell-cycle regulation, development of epithelium, glycolysis, programmed cell
death, apoptosis (Dai et al. 2017). Another study identified five genes, namely,
FAM46A, RAB15, SLC20A1, IL1A, and ACSL1 that are associated with the overall
survival or relapse-free survival in OSCC (Dong et al. 2018).
13.2.1.4 Pancreatic Cancer
Earlier computational studies have identified two (MMP7 and ITGA2) (Li et al.
2018b), ten (MMP9, COL1A2, COL1A1, COL3A1, TIMP1, MMP2, albumin, epi-
dermal growth factor, fibronectin 1, and integrin subunit α 2) (Lv et al. 2019), and
two (ITGA2 and MMP7) (Li et al. 2018b) key hub genes that are associated with
pancreatic cancer via computational approaches. Both MMP7 and ITGA2 are asso-
ciated with modulating the tumor microenvironment, i.e., tumor proliferation, pro-
gression, migration as well as metastasis (Li et al. 2018b). In another study,
researchers identified four key genes, namely, TGFBI, ECT2, NR5A2, and NRP2
that are responsible for the poor survival of pancreatic cancer patients (Liu et al.
2018b). For detail information about the usage of computational biology in the
pancreatic cancer treatment, the reader can refer to our earlier published review
article (Gupta et al. 2019a).
13.2.1.5 Hepatocellular Carcinoma
In 2017, we employed bioinformatics approaches to identify four key genes

(CXCR4, ABCB1, ADH1C, and ADH1A) that play a crucial role in the development
of hepatocellular carcinoma (HC). Several other studies have also employed com-
putational approaches to detect eight (CDK1, CCNB2, CCNB1, ACACB, MAD2L1,
TOP2A, IGF1, and EHHADH) (Gao et al. 2018), twelve (TTK, AURKA, NCAPG,
ZWINT, CCNB1, PRC1, CDK1, TOP2A, UBE2C, CDKN3, RRM2, and RACGAP1)
(Wu et al. 2019b), four (PLK1, PRPF4, PRCC, and PSMA7) (Tu et al. 2019), five
(ACACB, TLR4, IGF1, RIPK4, and MAP 2 K1), and six (NDC80, ZWINT, ESR1,
ENO3, NCAPG, and CENPF) (Liu et al. 2019c) key genes that are responsible for
causing HC. These key genes are mainly involved in protein processing in the
endoplasmic reticulum and metabolism, the p53 signaling pathway, cell-cycle reg-
ulation DNA replication, and oocyte meiosis (Tu et al. 2019; Liu et al. 2019c; Yan
and Liu 2019).
13.2.2 Identification of mRNA–Micro RNA (miRNA)

Interaction
Earlier several studies have reported that miRNA plays a vital role in the post-
transcriptional modulation of genes involved in the development and cellular func-
tion, and their dysfunction causes initiation, progression, invasion, and metastasis in
GICs. However, the complete mechanism of how miRNA module GICs remains
elusive to date. Thus there is an urgent need to elucidate the biological role of
miRNA in gastric cancer (Pereira et al. 2019). To date, several computational
approaches have been performed to detect mRNA–miRNA interaction during GICs.
13.2.2.1 Colorectal Cancer
Recently, Falzone and team reported that upregulation of miRNA-21-5p and miRNA-
183-5p and downregulation of miRNA-195-5p and miRNA-497-5p are directly
associated with colorectal cancer development via interaction with the “Mismatch
Repair” pathway (Falzone et al. 2018). In another study, Zhang and team reported
that miRNA-885 initiates colorectal cancer via cell migration by partly reducing the
expression of vWF and IGFBP5 (Zhang et al. 2019). miRNA-182, miRNA-128, and
miRNA-143 are reported to play a crucial role in colorectal cancer (Su et al. 2019).
miRNA-19b-3p is reported to initiate colon cancer proliferation as well as
oxaliplatin-based chemoresistance via targeting SMAD4 (Jiang et al. 2017). In
another study, Ma and the team conveyed that five miRNAs (miRNA-200b,
miRNA-200c, miRNA-7, miRNA-200a, and miRNA-141) get upregulated during
colon cancer (Ma et al. 2018). Another team of researchers reported that miRNA-
4777, miRNA-659, miRNA-6501, miRNA-6510, miRNA-4638, and miRNA-675 are
associated with better survival of colorectal cancer patients. However, the associa-
tion between miRNA-328 and miRNA-891a with the overall survival of the patient is
relatively lower (Chen et al. 2019). In another study, miRNA-128, miRNA-143, and
miRNA-182 play a key role in the initiation and development of colorectal cancer.
13.2.2.2 Gastric Cancer
Gu and team performed a microarray analysis of miRNA expression profiles present

in the GEO database and suggested that Hippo and p53 signaling pathways are
significantly enriched during gastric cancer and one circular RNA, namely,
hsa_circRNA_101504, played a key role in the network associated with gastric
cancer (Gu et al. 2018b). Earlier numerous studies have also reported about silencing
of several miRNAs, including miRNA-137, miRNA-1, miRNA-9, miRNA-196b,
miRNA-512, miRNA-10b, miRNA-129, miRNA-516a, miRNA-34b/c, miRNA-152,
miRNA-18b, miRNA-124a, miRNA-212, miRNA-148a, miRNA-181c, and miRNA-
203, during gastric cancer via aberrant DNA methylation of their promoter regions
(Pan et al. 2013). Downregulation of six miRNAs, namely, miRNA-451, miRNA-
148a, miRNA-19b, miRNA-29c, miRNA-31, and miRNA-29b, during gastric cancer,
was discovered in another study (Ribeiro-dos-Santos et al. 2010).
Baghaei and team identified downregulation of four tumor-suppressive miRNA,
namely, miRNA-194-5p, miRNA-101-3p, miRNA-205-5p, and miRNA-200A-3p dur-
ing gastric cancer. The downregulation of miRNA-194-5p and miRNA-101-3p plau-
sibly causes the upregulation of WDR72 in gastric cancer (Baghaei et al. 2017).
Recently, Pereira and the team identified ten miRNAs, namely, miRNA-9a, miRNA-
135b, miRNA-664a, miRNA-21, miRNA-148a, miRNA-204, miRNA-150, miRNA-
483, and miRNA-215 that are upregulated in gastric cancer (Pereira et al. 2019).
Hwang and the team identified 42 aberrantly expressed miRNAs during early gastric
cancer. Out of these 42, five miRNAs, namely, miRNA-375, miRNA-26a, miRNA-
574-3p, miRNA-15b, and miRNA-145, experienced reduced expression since ade-
noma. Six miRNAs, namely, miRNA-601, miRNA-18a, miRNA-300, miRNA-370,
miRNA-107, and miRNA-96, were upregulated, while two miRNAs, namely,
miRNA-29a and miRNA-200c, were downregulated during gastric cancer (Hwang
et al. 2018). Recently, Zhang and team reported that miRNA-329, miRNA-133b,
miRNA-129, miRNA-196a, miRNA-376a, miRNA-368, miRNA-204, miRNA-302c,
miRNA-145, miRNA-143, miRNA-29c, miRNA-497, miRNA-133a, miRNA-99a,
miRNA-381, miRNA-604, miRNA-767-3p, miRNA-148a, miRNA-139, miRNA-218,
miRNA-154, miRNA-1, miRNA-363, miRNA-30e-5p, miRNA-125b, miRNA-100,
miRNA-195, miRNA-375, miRNA-586, miRNA-328, and miRNA-551b get
upregulated, while miRNA-18a*, miRNA-523, miRNA-611, miRNA-196b, miRNA-
9*, miRNA-135b, miRNA-514, miRNA-369-3p, miRNA-550, miRNA-181a*, and
miRNA-224 get downregulated during gastric cancer (Zhang et al. 2018).
Three independent studies reported that miRNA-15b-5p, let-7i-5p, miRNA-93-5p,
and miRNA-204-5p (Yuan et al. 2019), miRNA-17 (Hu et al. 2018), and miRNA-125b
(Zhang et al. 2015) play a key role in the development of gastric cancer. In another
study, Deng and the team reported that miRNA-195 is significantly downregulated in
gastric cancer (Deng et al. 2013). Thus, identified key genes and miRNAs can serve
as a biomarker in the gastric cancer treatment in humans.
13.2.2.3 Esophageal Cancer
In 2017, Dai and the team suggested that upregulation of miRNA-105-5p, miRNA-
21-3p, and miRNA-21-5p and downregulation of miRNA-206, miRNA-208b-3p, and
miRNA-375 cause the development of OSCC (Dai et al. 2017). Upregulation of
miRNA-503, miRNA-1290, miRNA-21-5p, and miRNA-1246 is also found to be
associated with OSCC (Lau et al. 2018). Interestingly miRNA-503 is generally
downregulated in most cancer types; for instance, cervical cancer and hepatocellular
carcinoma (Xu et al. 2013; Chong et al. 2014; Liu et al. 2015). Another study
reported that miRNA-203 modulates the function of eight upregulated genes, namely,
PXDN, AHR, NRCAM, EIF5A2, FMNL2, GLI3, GREM1, and FSL1, and miRNA-1
modulates the function of five upregulated genes, namely, MMD, PTPRG, BICD1,
SEMA6D, and SDC2 during esophageal cancer (Cai et al. 2018).
13.2.2.4 Pancreatic Cancer
Earlier, Ma and the team identified pancreatic cancer-associated three downregulated

(miRNA-217, miRNA-148a, and miRNA-375) and seven upregulated (miRNA-31,
miRNA-143, miRNA-100, miRNA-21, miRNA-155, miRNA-23a, and miRNA-221)

miRNAs (Ma et al. 2013). Liang and team identified 10 pancreatic cancer-associated
novel miRNAs, namely, miRNA-1301, miRNA-376c, miRNA-328, miRNA-125a,
miRNA-454, miRNA-376b, miRNA-29b, miRNA-126, miRNA-664a, and miRNA-
3613 (Liang et al. 2018). Tang and team detected pancreatic cancer related two
upregulated (miRNA-193a-3p and miRNA-34a) and four downregulated (miRNA-
502-3p, miRNA-221, miRNA-484, and miRNA-222) miRNAs (Tan et al. 2018).
13.2.2.5 Hepatocellular Carcinoma
Yan and the team suggested that miRNA-300 and miRNA-381-3p co-regulate the
function of CCNA2, UBE2C, and AURKA during liver cancer (Yan and Liu 2019).
Earlier other computational studies have reported that four (miRNA-1296,
miRNA-149, miRNA-23c, and miRNA-95) (Mei et al. 2018), two (miRNA-221 and
miRNA-29c) (Lou et al. 2018), one (miRNA-15b-5p) (Pan et al. 2019), and two
(miRNA-126-3p and miRNA-494-3p) miRNAs also play significant roles in the
modulation of transcription, cell proliferation as well as live cancer-associated
pathways (Ji et al. 2018). It is pertinent to note that miRNA-126-3p and miRNA-
494-3p were also found to be significantly downregulated and upregulated in HC
cell lines, respectively (Lou et al. 2018).
13.2.3 Identification of Drug Toward the Treatment

of Gastric Cancer
As stated above, the key hub gene or protein identified through computational
approaches may serve as a therapeutic target toward the GICs treatment. For
instance, in our laboratory, we have employed computational approaches to scan
novel phytochemicals against diabetes (Gupta and Vadde 2019c) and Alzheimer
(Gupta and Vadde 2019b). Similarly, several computational studies have been
performed to identify the most plausible drug for the GICs treatment. To the best
of our knowledge, only a few computational studies have been able to identify drugs
against gastric cancer, esophageal cancer, colorectal cancer, gallbladder carcinoma,
pancreatic cancer, and hepatocellular carcinoma. Two independent computational
studies identified three cycloprotoberberines, and sesame lignans against RAF
kinases and β-catenin, important targets for colorectal cancer treatment, respectively
(Kaboli et al. 2018; Cavuturu et al. 2019). Earlier two studies utilized both compu-
tational as well as experimental approaches and suggested that trifluoperazine
(Santofimia-Castaño et al. 2019) and trifluoperazine dihydrochloride (Neira et al.
2017) have a strong affinity toward NUPR1 (intrinsically disordered proteins that are
responsible for causing pancreatic cancer) and inhibit tumor growth. Nevertheless,
trifluoperazine has a side effect on the central nervous system (Santofimia-Castaño

et al. 2019).
In 2017, Babu and the team identified anti-Helicobacter pylori and urease
inhibitory activities of three flavonoids, namely, kaempferol-3-O-b-D-
glucopyranoside, 5-hydroxy-7,40-dimethoxy-6,8-di-C-methylflavone, and
kaempferol-3-O-a-L-rhamnopyranoside of Syzygium alternifolium fruits by
employing both experimental and computational approaches (Babu et al. 2017). In
another study, Shi and the team identified Nonoxynol-9 and Benzonatate as an
inhibitor of HER2 protein, a common gene for ovarian cancer, breast cancer, prostate
cancer, and gastric cancer (Shi et al. 2016). In another study, Junaid and the team
identified CHEMBL17319 and CHEMBL1183979 as anti-Helicobacter pylori mol-
ecules (Junaid et al. 2019). Another approach, namely, the drug repositioning
approach, is becoming one of the most essential pillars of personalized medicine
(Luciano et al. 2019). This approach helps us in identifying drugs whose tolerability
and safety have already been examined earlier, which in turn hasten development as
well as delivery of novel therapies with less cost. Transcriptomic data associated
with drug perturbations, for instance, the “Connectivity Map” (CMap), have been
extensively analyzed to scan the most plausible novel indications via matching
similar signatures of diseases as well as drugs on the basis of gene expression
modification (Chan et al. 2019). These approaches are designed on the presumption
that the pattern of gene expression associated with any disease or trait can be
modulated via drugs. In this context, earlier researchers examined numerous
approaches for restoring physiological markers in dyslipidemia mouse model
study. Efficacy of treatments was found to be correlated with their reversal of gene
expression abnormalities to normal levels; thereby suggesting that treatment which
reverses transcriptomic effects could possibly cure a disease (Chan et al. 2019).
Earlier several studies have utilized drug repositioning approach to identify drugs,
namely, chloroquine (Sasaki et al. 2010), dehydroepiandrosterone (DHEA) (Osawa
et al. 2002), pantoprazole (Zeng et al. 2016), orlistat (Kridel et al. 2004), raloxifene
(Luciano et al. 2019), and sodium dichloroacetate (Khan et al. 2016), that may be
used for treating gastric cancer.
13.2.4 Mathematical Modeling
Earlier several studies have reported that there is a continuous interaction between
the human body and environment for the normal function of the human body. For
instance, our body intakes essential nutrient from food present in the digestive tract
and imposes organ-specific function. However, irregular and imbalanced nutrient
may result in numerous organ or system-specific disorder (Trusov et al. 2016). Thus,
there is an urgent requirement to understand the “dose-dependent” effect of any
nutrient on the normal function of any organ. Considering this, numerous statistical
approaches, as well as mathematical models, have been developed to understand
both normal and abnormal function of respiratory, cardiovascular, digestive as well
as other systems (Trusov et al. 2016). These model either work at “macro-level” or
“micro-level.” “Macro-level” interaction amongst systems and organs is estimated
via ordinary differential systems that describe the evolution of damage. Zero desig-
nates no functional disorder in any organ, while one designates complete function
fails. All these “macro models” consider natural (self-restoration and aging), medical
treatment, the impact of non-normative environmental as well as preventive mea-
sures. However, all these “macro-model” fails to capture complete mechanisms
associated with any body function or human disease at the cellular level. Hence, in
the near future, it is highly required to develop “micro-models” which may capture
events at the cellular level (Trusov et al. 2016).
Recent developed single-cell RNA sequencing (scRNA-seq) technique provides
a unique to capture event at cellular level. For the first time, in 2009, transcriptomic
data was estimated at the single-cell level by Tang and the team (Tang et al. 2009).
Since then the technique associated with scRNA-seq has experienced an explosive
development. In comparison to bulk-based methods, scRNA-seq provides more
detailed insights into cellular heterogeneity, which in turn helps us in bringing
remarkable new discoveries in biology (Tang et al. 2011; Zeisel et al. 2015). For
instance, Deng and the team identified the stochastic expression of monoallelic
genes within mammalian cells (Deng et al. 2014). Earlier Xin & team (Xin et al.
2016) and Segerstolpe & team (Segerstolpe et al. 2016) reported expression
heterogeneity of human islet cells (for instance, β-cells, α-cells, and δ-cells) using
scRNA-seq techniques. They also investigated the modifications in patterns of gene
expression and the enriched signaling pathways in T2D in comparison with healthy
people. Hence, mathematical models designed based on information obtained from
the single-cell RNA-sequencing technology can provide detailed insight about the
molecular mechanisms associated with any disease or trait by capturing gene
expression at the inter-cell level.
Additionally, several other mathematical models have been proposed to under-
stand cancer progression, giving more emphasis on patient-specific models
(Cumsille et al. 2019). However, because of the complex process associated with
any cancer, it very hard to predict the absolute model describing a complete
mechanism related to all stages of neoplastic growth. Hence, the main objective of
most of these mathematical models developed to date is to capture the maximum
phenomenon associated with any cancer progression. For developing any mathe-
matical model, parameter estimation is an important step and parameter estimation
requires sensible experimental design as well as clinical data collection. Though
most of the mathematical models associated with GI-cancer are confined to metas-
tasis to the liver, a mathematical model describing growth as well as therapy failure
due to drug resistance is also available. However, these models failed to describe
growth as well as therapy failure quantitatively (Cumsille et al. 2019). Additionally,
the mathematical model employed for clinical application in GI-cancer does not
consider the spatial aspect of tumor growth. Parameter of these models is generally
estimated via using statistical methods and may provide tumor diagnosis in the
context of other essential elements (Cumsille et al. 2015). Considering this, recently,
Cumsille and the team developed patient-specific models that detect the evolution of
tumor metastasis and also describe growth and therapy failure because of drug
resistance quantitatively. Clinically, disease progression was mainly detected
through CT scans. Later, observation from each CT scan was extracted via hybrid
approaches and employed for generating patient-specific mathematical models that
describe growth and therapy failure in terms of drug resistance quantitatively
(Cumsille et al. 2015). Thus, these mathematical model along with key genes and
protein may be utilized in the treatment of GICs.
13.3 Conclusion and Future Perspective
In conclusion GICs are the most common cancers of the digestive tract system in
both men as well as women. Though chemotherapy is widely employed for the GICs
treatment, to date overall survival rate of GICs is very less. Thus, there is an urgent
requirement of the new approaches to identify key genes responsible for causing
GICs in humans, which in turn will help us in designing effective treatment and
drugs against GICs. Recently developed computational approaches provide us a
unique way to identify key genes and drug—using publicly available genomic and
proteomic datasets in a short interval of time with less cost. However, earlier
developed experimental as well as computational approaches performed analysis
on bulk cell, which in turn provide less information about gene expression at the
cellular level. Author believes that estimation of gene expression at cellular level by
integrating both experimental, for instance, single-cell RNA (scRNA) sequencing
technique, and computational approaches together, we will address a timely and
urgent need to link genetic and proteomic data to distinguished tumor heterogeneity
in GICs at the genomic, transcriptomic, and metabolomic levels that offer, for some,
new therapeutic opportunities. In the near future, the information present in the
present chapter will be highly valuable for cancer biologists and immunologists
toward the GICs treatment.
Conflicts of Interest None
References
Babu TMC, Rajesh SS, Bhaskar BV, Devi S, Rammohan A, Sivaraman T et al (2017) Molecular
docking, molecular dynamics simulation, biological evaluation and 2D QSAR analysis of
flavonoids from Syzygium alternifolium as potent anti-Helicobacter pylori agents. RSC Adv 7
(30):18277–18292
Baghaei K, Hosseinkhan N, Aghdaei HA, Zali MR (2017) Investigation of a common gene
expression signature in gastrointestinal cancers using systems biology approaches. Mol BioSyst
13(11):2277–2288
Bharti SK, Krishnan S, Sharma NK, Kumar A, Prakash O, Gupta AK et al (2015) In vivo and in
silico investigation of antidiabetic activity of fruit of Withania coagulans Dunal. Curr Hypertens
Rev 11(2):143–158
Cai X, Yang X, Jin C, Li L, Cui Q, Guo Y et al (2018) Identification and verification of differentially
expressed microRNAs and their target genes for the diagnosis of esophageal cancer. Oncol Lett
16(3):3642–3650
Cavuturu BM, Bhandare VV, Ramaswamy A, Arumugam N (2019) Molecular dynamics of
interaction of Sesamin and related compounds with the cancer marker β-catenin: an in silico
study. J Biomol Struct Dyn 37(4):877–891
Chan J, Wang X, Turner JA, Baldwin NE, Gu J (2019) Breaking the paradigm: Dr Insight
empowers signature-free, enhanced drug repurposing. Bioinformatics 35(16):2818–2826
Chen X, Cai S, Li B, Zhang X, Li W, Linag H et al (2018) Identification of key genes and pathways
for esophageal squamous cell carcinoma by bioinformatics analysis. Exp Ther Med 16
(2):1121–1130
Chen F, Li Z, Zhou H (2019) Identification of prognostic miRNA biomarkers for predicting overall
survival of colon adenocarcinoma and bioinformatics analysis: a study based on The Cancer
Genome Atlas database. J Cell Biochem 120(6):9839–9849
Chong Y, Zhang J, Guo X, Li G, Zhang S, Li C et al (2014) MicroRNA-503 acts as a tumor
suppressor in osteosarcoma by targeting L1CAM. PLoS One 9(12):e114585
Cooper GM (2000) The development and causes of cancer. In: The cell: a molecular approach, 2nd
edn. [cited 2018 Nov 16]. https://www.ncbi.nlm.nih.gov/books/NBK9963/
Cumsille P, Coronel A, Conca C, Quiñinao C, Escudero C (2015) Proposal of a hybrid approach for
tumor progression and tumor-induced angiogenesis. Theor Biol Med Model 12:13
Cumsille P, Godoy M, Gerdtzen ZP, Conca C (2019) Parameter estimation and mathematical
modeling for the quantitative description of therapy failure due to drug resistance in gastroin-
testinal stromal tumor metastasis to the liver. PLoS One 14(5):e0217332. [cited 2019 Aug 15].
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6542538/
Dai F, Mei L, Meng S, Ma Z, Guo W, Zhou J et al (2017) The global expression profiling in
esophageal squamous cell carcinoma. Genomics 109(3):241–250
Dai W, Li Q, Liu B-Y, Li Y-X, Li Y-Y (2018) Differential networking meta-analysis of gastric
cancer across Asian and American racial groups. BMC Syst Biol 12(4):51
Deng H, Guo Y, Song H, Xiao B, Sun W, Liu Z et al (2013) MicroRNA-195 and microRNA-378
mediate tumor growth suppression by epigenetical regulation in gastric cancer. Gene 518
(2):351–359
Deng Q, Ramsköld D, Reinius B, Sandberg R (2014) Single-cell RNA-seq reveals dynamic,
random monoallelic gene expression in mammalian cells. Science 343(6167):193–196
Donde R, Gupta MK, Gouda G, Kumar J, Vadde R, Sahoo KK et al (2019) Computational
characterization of structural and functional roles of DREB1A, DREB1B and DREB1C in
enhancing cold tolerance in rice plant. Amino Acids 51(5):839–853
Dong Z, Wang J, Zhan T, Xu S (2018) Identification of prognostic risk factors for esophageal
adenocarcinoma using bioinformatics analysis. OncoTargets Ther 11:4327–4337
Falzone L, Scola L, Zanghì A, Biondi A, Di Cataldo A, Libra M et al (2018) Integrated analysis of
colorectal cancer microRNA datasets: identification of microRNAs associated with tumor
development. Aging 10(5):1000–1014
Ferguson LB, Harris RA, Mayfield RD (2018) From gene networks to drugs: systems pharmacol-
ogy approaches for AUD. Psychopharmacology 235(6):1635–1662
Gao X, Wang X, Zhang S (2018) Bioinformatics identification of crucial genes and pathways
associated with hepatocellular carcinoma. Biosci Rep 38(6):BSR20181441. [cited 2019 Sep
11]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6239270/
Ge H, Yan Y, Guo L, Tian F, Wu D (2018) Prognostic role of HSPs in human gastrointestinal
cancer: a systematic review and meta-analysis. OncoTargets Ther 11:351–359
Gola J, Obrezanova O, Champness E, Segall M (2006) ADMET property prediction: the state of the
art and current challenges. QSAR Comb Sci 25(12):1172–1180
González-Beltrán A, Tagger B, Finkelstein A (2012) Federated ontology-based queries over cancer

data. BMC Bioinf 13(1):S9
Gouda G, Gupta MK, Donde R, Kumar J, Vadde R, Mohapatra T et al (2020) Computational
approach towards understanding structural and functional role of cytokinin oxidase/dehydroge-
nase 2 (CKX2) in enhancing grain yield in rice plant. J Biomol Struct Dyn 38:1158–1167
Gu W, Sun Y, Zheng X, Ma J, Hu X-Y, Gao T et al (2018a) Identification of gastric cancer-related
circular RNA through microarray analysis and bioinformatics analysis. Biomed Res Int
2018:2381680
Gu W, Sun Y, Zheng X, Ma J, Hu X-Y, Gao T et al (2018b) Identification of gastric cancer-related
circular RNA through microarray analysis and bioinformatics analysis. BioMed Res Int 2018:1.
[cited 2019 Sep 10]. https://www.hindawi.com/journals/bmri/2018/2381680/
Gupta MK, Vadde R (2019a) Identification and characterization of differentially expressed genes in
type 2 diabetes using in silico approach. Comput Biol Chem 79:24. [cited 2019 Jan 27]. http://
www.sciencedirect.com/science/article/pii/S1476927118302238
Gupta MK, Vadde R (2019b) In silico identification of natural product inhibitors for γ-secretase
activating protein, a therapeutic target for Alzheimer’s disease. J Cell Biochem 120:10323
Gupta MK, Vadde R (2019c) Insights into the structure-function relationship of both wild and
mutant Zinc transporter ZnT8 in human: a computational structural biology approach. J Biomol
Struct Dyn 11:1–22
Gupta MK, Behera SK, Dehury B, Mahapatra N (2017) Identification and characterization of
differentially expressed genes from human microglial cell samples infected with Japanese
encephalitis virus. J Vector Borne Dis 54(2):131–138
Gupta MK, Sarojamma V, Reddy MR, Shaik JB, Vadde R (2019a) Computational biology: toward
early detection of pancreatic cancer. Crit Rev Oncog 24(2):191. [cited 2019 Nov 21]. http://
www.dl.begellhouse.com/journals/439f422d0783386a,4e35fd64043789bc,3d24f17d426f6f57.
html
Gupta MK, Sarojamma V, Vadde R (2019b. [cited 2019 Nov 30]. p. 35–51) Diabetes and pancreatic
cancer: a bidirectional relationship perspective. In: Nagaraju GP, Reddy ABM (eds) Exploring
pancreatic metabolism and malignancy. Springer, Singapore. https://doi.org/10.1007/978-981-
32-9393-9_3
Gupta MK, Vadde R, Donde R, Gouda G, Kumar J, Nayak S et al (2019c) Insights into the
structure–function relationship of brown plant hopper resistance protein, Bph14 of rice plant: a
computational structural biology approach. J Biomol Struct Dyn 37:1649–1665
Gupta MK, Vadde R, Gouda G, Donde R, Kumar J, Behera L (2019d) Computational approach to
understand molecular mechanism involved in BPH resistance in Bt- rice plant. J Mol Graph
Model 88:209–220
He Y, Liu J, Zhao Z, Zhao H (2017) Bioinformatics analysis of gene expression profiles of
esophageal squamous cell carcinoma. Dis Esophagus 30(5):1–8
He W, Chen L, Yuan K, Zhou Q, Peng L, Han Y (2018) Gene set enrichment analysis and meta-
analysis to identify six key genes regulating and controlling the prognosis of esophageal
squamous cell carcinoma. J Thorac Dis 10(10):5714–5726
Hu G, Lv Q, Yan J, Chen L, Du J, Zhao K et al (2018) MicroRNA-17 as a promising diagnostic
biomarker of gastric cancer: an investigation combining TCGA, GEO, meta-analysis, and
bioinformatics. FEBS Open Bio 8(9):1508–1523
Hwang J, Min B-H, Jang J, Kang SY, Bae H, Jang SS et al (2018) MicroRNA expression profiles in
gastric carcinogenesis. Sci Rep 8(1):1–8
Ji J, Chen H, Liu X-P, Wang Y-H, Luo C-L, Zhang W-W et al (2018) A miRNA combination as
promising biomarker for hepatocellular carcinoma diagnosis: a study based on bioinformatics
analysis. J Cancer 9(19):3435–3446
Jiang T, Ye L, Han Z, Liu Y, Yang Y, Peng Z et al (2017) miR-19b-3p promotes colon cancer
proliferation and oxaliplatin-based chemoresistance by targeting SMAD4: validation by bioin-
formatics and experimental analyses. J Exp Clin Cancer Res 36(1):131
Junaid M, Li C-D, Shah M, Khan A, Guo H, Wei D-Q (2019) Extraction of molecular features for
the drug discovery targeting protein-protein interaction of Helicobacter pylori CagA and tumor
suppressor protein ASSP2. Proteins Struct Funct Bioinf 87(10):837–849
Kaboli PJ, Ismail P, Ling K-H (2018) Molecular modeling, dynamics simulations, and binding
efficiency of berberine derivatives: a new group of RAF inhibitors for cancer treatment. PLoS
One 13(3):e0193941
Kaur J, Singla R, Jaitak V (2018) In silico study of flavonoids as DPP-4 and α-glucosidase
inhibitors. Lett Drug Des Discovery 15(6):634–642. [cited 2019 Apr 23]. https://www.
ingentaconnect.com/contentone/ben/lddd/2018/00000015/00000006/art00009
Khan A, Andrews D, Blackburn AC (2016) Long-term stabilization of stage 4 colon cancer using
sodium dichloroacetate therapy. World J Clin Cases 4(10):336–343
Kridel SJ, Axelrod F, Rozenkrantz N, Smith JW (2004) Orlistat is a novel inhibitor of fatty acid
synthase with antitumor activity. Cancer Res 64(6):2070–2075
Lagorce D, Douguet D, Miteva MA, Villoutreix BO (2017) Computational analysis of calculated
physicochemical and ADMET properties of protein-protein interaction inhibitors. Sci Rep
7:46277
Latek D, Rutkowska E, Niewieczerzal S, Cielecka-Piontek J (2019) Drug-induced diabetes type 2:
in silico study involving class B GPCRs. PLoS One 14(1):e0208892
Lau KW, Zeng H, Liang H, Su X, Ma J, Wen S et al (2018) Bioinformatics-based identification of
differentiated expressed microRNA in esophageal squamous cell carcinoma. Transl Cancer Res
7(6):1366–1375
Li T, Gao X, Han L, Yu J, Li H (2018a) Identification of hub genes with prognostic values in gastric
cancer by bioinformatics analysis. World J Surg Oncol 16(1):114
Li C, Zeng X, Yu H, Gu Y, Zhang W (2018b) Identification of hub genes with diagnostic values in
pancreatic cancer by bioinformatics analyses and supervised learning methods. World J Surg
Oncol 16(1):223
Liang L, Liang L, Wei D-M, Wei D-M, Li J-J, Li J-J et al (2018) Prognostic microRNAs and their
potential molecular mechanism in pancreatic cancer: a study based on The Cancer Genome
Atlas and bioinformatics investigation. Mol Med Rep 17(1):939–951
Lin Y-C, Wang C-C, Chen I-S, Jheng J-L, Li J-H, Tung C-W (2013) TIPdb: a database of
anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in Taiwan.
Sci World J 2013:1. [cited 2017 Aug 30]. https://www.hindawi.com/journals/tswj/2013/
736386/
Liu N, Liu X, Zhou N, Wu Q, Zhou L, Li Q (2014) Gene expression profiling and bioinformatics
analysis of gastric carcinoma. Exp Mol Pathol 96(3):361–366
Liu L, Qu W, Zhong Z (2015) Down-regulation of miR-503 expression predicate advanced
mythological features and poor prognosis in patients with NSCLC. Int J Clin Exp Pathol 8
(5):5609–5613
Liu X, Wu J, Zhang D, Bing Z, Tian J, Ni M et al (2018a) Identification of potential key genes
associated with the pathogenesis and prognosis of gastric cancer based on integrated bioinfor-
matics analysis. Front Genet 9:265. [cited 2019 May 23]. https://www.ncbi.nlm.nih.gov/pmc/
articles/PMC6056647/
Liu B, Yang H, Taher L, Denz A, Grützmann R, Pilarsky C et al (2018b) Identification of
prognostic biomarkers by combined mRNA and miRNA expression microarray analysis in
pancreatic cancer. Transl Oncol 11(3):700–714
Liu J, Liu Z, Zhang X, Gong T, Yao D (2019a) Bioinformatic exploration of OLFML2B
overexpression in gastric cancer base on multiple analyzing tools. BMC Cancer 19(1):227
Liu J-B, Jian T, Yue C, Chen D, Chen W, Bao T-T et al (2019b) Chemo-resistant gastric cancer
associated gene expression signature: bioinformatics analysis based on gene expression omni-
bus. Anticancer Res 39(4):1689–1698
Liu Z-K, Zhang R-Y, Yong Y-L, Zhang Z-Y, Li C, Chen Z-N et al (2019c) Identification of crucial
genes based on expression profiles of hepatocellular carcinomas by bioinformatics analysis.
PeerJ 7:e7436
Lou W, Chen J, Ding B, Chen D, Zheng H, Jiang D et al (2018) Identification of invasion-

metastasis-associated microRNAs in hepatocellular carcinoma based on bioinformatic analysis
and experimental validation. J Transl Med 16(1):266
Luciano A, Malizia F, Menacho MM (2019) Modern strategies in cancer study: drug repositioning
in colorectal cancer treatment. Nov Approaches Cancer Study 2(4):1–5
Lv K, Yang J, Sun J, Guan J (2019) Identification of key candidate genes for pancreatic cancer by
bioinformatics analysis. Exp Ther Med 18(1):451–458
Ma M-Z, Kong X, Weng M-Z, Cheng K, Gong W, Quan Z-W et al (2013) Candidate microRNA
biomarkers of pancreatic ductal adenocarcinoma: meta-analysis, experimental validation and
clinical significance. J Exp Clin Cancer Res 32:71
Ma Q, Song J, Chen Z, Li L, Wang B, He N (2018) Identification of potential gene and microRNA
biomarkers for colon cancer by an integrated bioinformatical approach. Transl Cancer Res 7
(1):17–29
Mei Y, You Y, Xia J, Gong J-P, Wang Y-B (2018) Identifying differentially expressed microRNAs
between cirrhotic and non-cirrhotic hepatocellular carcinoma and exploring their functions
using bioinformatic analysis. Cell Physiol Biochem 48(4):1443–1456
Menakha M, Sangeetha M, Mani P, AlAboody M, Vijayakumar R (2018) In silico prediction of
drug molecule from Ipomoea sepiaria against Type 2 Diabetes. Prog Med Sci 3(1):9
Neira JL, Bintz J, Arruebo M, Rizzuti B, Bonacci T, Vega S et al (2017) Identification of a drug
targeting an intrinsically disordered protein involved in pancreatic adenocarcinoma. Sci Rep
7:39732
Osawa E, Nakajima A, Yoshida S, Omura M, Nagase H, Ueno N et al (2002) Chemoprevention of
precursors to colon cancer by dehydroepiandrosterone (DHEA). Life Sci 70(22):2623–2630
Palaniappan A, Ramar K, Ramalingam S (2016) Computational identification of novel stage-
specific biomarkers in colorectal cancer progression. PLoS One 11(5):e0156665
Pan H-W, Li S-C, Tsai K-W (2013) MicroRNA dysregulation in gastric cancer. Curr Pharm Des 19
(7):1273–1284
Pan W-Y, Zeng J-H, Wen D-Y, Wang J-Y, Wang P-P, Chen G et al (2019) Oncogenic value of
microRNA-15b-5p in hepatocellular carcinoma and a bioinformatics investigation. Oncol Lett
17(2):1695–1713
Pereira AL, Magalhães L, Moreira FC, Reis-das-Mercês L, Vidal AF, Ribeiro-dos-Santos AM et al
(2019) Epigenetic field cancerization in gastric cancer: microRNAs as promising biomarkers. J
Cancer 10(6):1560–1569
Ribeiro-dos-Santos Â, Khayat AS, Silva A, Alencar DO, Lobato J, Luz L et al (2010) Ultra-deep
sequencing reveals the microRNA expression pattern of the human stomach. PLoS One 5(10):
e13205
Saberi Anvar M, Minuchehr Z, Shahlaei M, Kheitan S (2018) Gastric cancer biomarkers; a systems
biology approach. Biochem Biophys Rep 13:141–146
Santofimia-Castaño P, Xia Y, Lan W, Zhou Z, Huang C, Peng L et al (2019) Ligand-based design
identifies a potent NUPR1 inhibitor exerting anticancer activity via necroptosis. J Clin Invest
129(6):2500–2513
Sasaki K, Tsuno NH, Sunami E, Tsurita G, Kawai K, Okaji Y et al (2010) Chloroquine potentiates
the anti-cancer effect of 5-fluorouracil on colon cancer cells. BMC Cancer 10:370
Sawey ET, Chanrion M, Cai C, Wu G, Zhang J, Zender L et al (2011) Identification of a therapeutic
strategy targeting amplified FGF19 in liver cancer by Oncogenomic screening. Cancer Cell 19
(3):347–358
Segerstolpe Å, Palasantza A, Eliasson P, Andersson E-M, Andréasson A-C, Sun X et al (2016)
Single-cell transcriptome profiling of human pancreatic islets in health and type 2 diabetes. Cell
Metab 24(4):593–607
Shams AZ, Haug U (2017) Strategies for prevention of gastrointestinal cancers in developing
countries: a systematic review. J Glob Health 7(2):020405
Shi Z, Yu T, Sun R, Wang S, Chen X-Q, Cheng L-J et al (2016) Discovery of novel human
epidermal growth factor receptor-2 inhibitors by structure-based virtual screening. Pharmacogn
Mag 12(46):139
Siegel RL, Miller KD, Jemal A (2019) Cancer statistics, 2019. CA Cancer J Clin 69(1):7–34
Su Y, Zhang M, Zhang L, Chen S, Zhang D, Zhang X (2019) Construction of an miRNA–mRNA
regulatory network in colorectal cancer with bioinformatics methods. Anti-Cancer Drugs 30
(6):588
Tan X, Zhou L, Wang H, Yang Y, Sun Y, Wang Z et al (2018) Differential expression profiles of
microRNAs in highly and weakly invasive/metastatic pancreatic cancer cells. Oncol Lett 16
(5):6026–6038
Tang F, Barbacioru C, Wang Y, Nordman E, Lee C, Xu N et al (2009) mRNA-Seq whole-
transcriptome analysis of a single cell. Nat Methods 6(5):377–382
Tang F, Lao K, Surani MA (2011) Development and applications of single-cell transcriptome
analysis. Nat Methods 8(4s):S6–S11
Tang X, Hu X, Yang X, Fan Y, Li Y, Hu W et al (2016) Predicting diabetes mellitus genes via
protein-protein interaction and protein subcellular localization information. BMC Genomics 17
(4):433
Trusov PV, Zaitseva NV, Kamaltdinov MR (2016) A multiphase flow in the antroduodenal portion
of the gastrointestinal tract: a mathematical model. Comput Math Methods Med 2016:1. [cited
2019 Aug 16]. https://www.hindawi.com/journals/cmmm/2016/5164029/
Tu J, Chen J, He M, Tong H, Liu H, Zhou B et al (2019) Bioinformatics analysis of molecular
genetic targets and key pathways for hepatocellular carcinoma. OncoTargets Ther
12:5153–5162
Vemula S, Gupta MK, Arva Tatireddygari VR, Vadde R (2019) Chapter 12. Pancreatic cancer
chemoprevention: a review on molecular pathways involved in carcinogenesis and targeting
with terpenoids, and new potential antitumor drugs. In: Nagaraju GP, Ahmad S (eds)
Theranostic approach for pancreatic cancer. Academic Press, Amsterdam. [cited 2020 Jan
4]. p. 245–61. http://www.sciencedirect.com/science/article/pii/B9780128194577000128
Wang D-G, Chen G, Wen X-Y, Wang D, Cheng Z-H, Sun S-Q (2015) Identification of biomarkers
for diagnosis of gastric cancer by bioinformatics. Asian Pac J Cancer Prev 16(4):1361–1365
Wu D, Rice CM, Wang X (2012) Cancer bioinformatics: a new approach to systems clinical
medicine. BMC Bioinf 13(1):71
Wu J, Gu Y, Xiao Y, Xia C, Li H, Kang Y et al (2019a) Characterization of DNA methylation
associated gene regulatory networks during stomach cancer progression. Front Genet 9:711.
[cited 2019 Sep 10]. https://www.frontiersin.org/articles/10.3389/fgene.2018.00711/full#h5
Wu M, Liu Z, Zhang A, Li N (2019b) Identification of key genes and pathways in hepatocellular
carcinoma: a preliminary bioinformatics analysis. Medicine (Baltimore) 98(5):e14287
Xin Y, Kim J, Okamoto H, Ni M, Wei Y, Adler C et al (2016) RNA sequencing of single human
islet cells reveals type 2 diabetes genes. Cell Metab 24(4):608–615
Xu Y-Y, Wu H-J, Ma H-D, Xu L-P, Huo Y, Yin L-R (2013) MicroRNA-503 suppresses prolifer-
ation and cell-cycle progression of endometrioid endometrial cancer by negatively regulating
cyclin D1. FEBS J 280(16):3768–3779
Yan G, Liu Z (2019) Identification of differentially expressed genes in hepatocellular carcinoma by
integrated bioinformatic analysis. bioRxiv:570846. https://doi.org/10.1101/570846
Yang W, Ma J, Zhou W, Li Z, Zhou X, Cao B et al (2018) Identification of hub genes and outcome
in colon cancer based on bioinformatics analysis. Cancer Manag Res 11:323–338
Yuan C, Zhang Y, Tu W, Guo Y (2019) Integrated miRNA profiling and bioinformatics analyses
reveal upregulated miRNAs in gastric cancer. Oncol Lett 18(2):1979–1988
Yue Y, Song M, Qiao Y, Li P, Yuan Y, Lian J et al (2017) Gene function analysis and underlying
mechanism of esophagus cancer based on microarray gene expression profiling. Oncotarget 8
(62):105222–105237
Zeisel A, Muñoz-Manchado AB, Codeluppi S, Lönnerberg P, La Manno G, Juréus A et al (2015)

Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science 347
(6226):1138–1142
Zeng X, Liu L, Zheng M, Sun H, Xiao J, Lu T et al (2016) Pantoprazole, an FDA-approved proton-
pump inhibitor, suppresses colorectal cancer growth by targeting T-cell-originated protein
kinase. Oncotarget 7(16):22460–22473
Zeng Y, Shen Z, Gu W, Wu M (2018) Bioinformatics analysis to identify action targets in NCI-N87
gastric cancer cells exposed to quercetin. Pharm Biol 56(1):393–398
Zhang X, Peng Y, Jin Z, Huang W, Cheng Y, Liu Y et al (2015) Integrated miRNA profiling and
bioinformatics analyses reveal potential causative miRNAs in gastric adenocarcinoma.
Oncotarget 6(32):32878–32889
Zhang C, Liang Y, Ma M-H, Wu K-Z, Zhang C-D, Dai D-Q (2018) Downregulation of microRNA-
376a in gastric cancer and association with poor prognosis. Cell Physiol Biochem 51
(5):2010–2018
Zhang T, Guo J, Gu J, Wang Z, Wang G, Li H et al (2019) Identifying the key genes and
microRNAs in colorectal cancer liver metastasis by bioinformatics analysis and in vitro exper-
iments. Oncol Rep 41(1):279–291
Zheng S, Yang L, Dai Y, Jiang L, Wei Y, Wen H et al (2019) Screening and survival analysis of hub
genes in gastric cancer based on bioinformatics. J Comput Biol 26:1316. [cited 2019 Sep 10].
https://www.liebertpub.com/doi/abs/10.1089/cmb.2019.0119

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Diagnostics and Therapeutic Advances in GI Malignancies

Series Editor: Ganji Purnachandra Nagaraju

Editorial Board Members

More information about this series at http://www.springer.com/series/16343

ISSN 2662-2688 ISSN 2662-2696 (electronic)

Gastrointestinal malignancies are the most common cancers diagnosed worldwide,

Kadapa, Andhra Pradesh, India Ramakrishna Vadde

1 Tumor Heterogeneity: Challenges and Perspectives for

10 Association Between IL6 Gene Polymorphisms and Gastric Cancer

Ramakrishna Vadde is an Assistant Professor at the

Ganji Purnachandra Nagaraju is a faculty member at

serves as an editorial board member for numerous aca-

Manoj Kumar Gupta, Gayatri Gouda, Ravindra Donde,

Abstract Cancer is clinically characterized via the uncontrolled proliferation of

Keywords Cancer · Heterogeneity · Clonal evolution model · Cancer stem cell

M. K. Gupta · R. Vadde (*)

Recent advancements in high throughput sequencing technologies have provided us

1.2 Heterogeneity Type

Heterogeneity is a Greek word, which means “different kinds,” thereby representing

1.2.1 Inter-Tumor Heterogeneity

Inter-tumor heterogeneity refers to the alteration in the phenotype as well as geno-

Intra-tumor heterogeneity denotes the intrinsic temporal–spatial variances amongst

1.2.2.1 The Clonal Evolution Model

reported ampliﬁcation of three distinct receptor tyrosine kinases, namely, EGFR,

1.2.2.2 The Cancer Stem Cell Model

1.2.2.3 The Plasticity Model

1.2.2.4 The Big Bang Model

1.3 Approaches to Explore Tumor Heterogeneity

that ROS1 deletions and ampliﬁcations are heterogeneous in non-small-cell lung

Bockerstett and the team employed scRNA-seq and identiﬁed a population of

Conﬂict of Interests None.

Deng Q, Ramsköld D, Reinius B, Sandberg R (2014) Single-cell RNA-seq reveals dynamic,

Mekapogu Madakka, Nambi Rajesh, and Jinka Rajeswari

Keywords Lamina propria · GALT · Mucosal immunity · Mucosal tolerance ·

M. Madakka (*) · N. Rajesh

2.1.1 Gastrointestinal Tract Architecture

Gastrointestinal (GI) tract plays an important role in uptaking nutrients, digestion. GI

2.2 Immune System of Gut

The mucosal membrane of the GIT comprised of single layer of absorptive

2.3 Intestinal Epithelial Barrier

Intestinal epithelium consists of intestinal epithelial cells (IECs) further modiﬁed

2.4 Specialised Secretory IECs

2.5 Lamina Propria

2.6 Peyer’s Patches

2.7 Follicle-Associated Epithelium (FAE)

2.8 Mesenteric Lymph Nodes

2.9 Antigen Sampling by M Cells

2.10 Mucosal Vaccination

There is great interest in exploiting the transcytotic activity of M cells in the

2.11 Pattern Recognition Receptors

2.12 Toll-Like Receptors

TLRs are evolutionarily conserved type 1 transmembrane proteins with leucine-rich

2.13 Nod1 and Nod2

2.14 RIG-Like Helicases

2.15 Gastrointestinal Immune System and Inﬂammatory

Lim JS, Na HS, Lee HC et al (2009) Caveolae-mediated entry of Salmonella typhimurium in a

Terahara K, Yoshida M, Igarashi O et al (2008) Comprehensive gene expression proﬁling of

Ravikiran Tekupalli, Santosh Anand, Sowbhagya Ramachandregowda,

Keywords Immunomarkers · Esophageal cancer · Gastric cancer · Colorectal