Rivas 2021 Drug

Archives of Toxicology
https://doi.org/10.1007/s00204-021-03063-7
REVIEW ARTICLE
Cancer drug resistance induced by EMT: novel therapeutic strategies

Javier De Las Rivas1 · Anamaria Brozovic2 · Sivan Izraely3 · Alba Casas‑Pais4,5 · Isaac P. Witz3 · Angélica Figueroa4,5
Received: 5 March 2021 / Accepted: 28 April 2021

© The Author(s) 2021
Abstract
Over the last decade, important clinical benefits have been achieved in cancer patients by using drug-targeting strategies.
Nevertheless, drug resistance is still a major problem in most cancer therapies. Epithelial-mesenchymal plasticity (EMP) and
tumour microenvironment have been described as limiting factors for effective treatment in many cancer types. Moreover,
epithelial-to-mesenchymal transition (EMT) has also been associated with therapy resistance in many different preclinical
models, although limited evidence has been obtained from clinical studies and clinical samples. In this review, we particularly
deepen into the mechanisms of which intermediate epithelial/mesenchymal (E/M) states and its interconnection to microen-
vironment influence therapy resistance. We also describe how the use of bioinformatics and pharmacogenomics will help to
figure out the biological impact of the EMT on drug resistance and to develop novel pharmacological approaches in the future.
Keywords Epithelial plasticity · Cancer · Therapy resistance · Tumour microenvironment
Abbreviations Background
ECM Extracellular matrix
CAFs Cancer-associated fibroblast At present, one of the most important challenges in oncol-
EMT Epithelial-to-mesenchymal transition ogy is to overcome therapy resistance, as it is a persis-
E/M Epithelial/mesenchymal states tent problem for cancer patient management. Frequently,
HIF Hipoxia-iducible factors patients with resistance also develop more metastases, and
MDR Multidrug resistance given that metastasis is the major cause of cancer-related
NSCLC Non-small cell lung cancer deaths in human carcinomas, it is important to overcome
SCLC Small cell lung cancer therapy resistance by using new targeted-therapy strategies.
TAMs Tumour associated macrofges Therapy resistance not only includes the traditionally well-
TFs Transcription factors established innate and acquired tumour drug resistance,
TME Tumour microenvironment but it also includes resistance to treatment such as chemo
or radiotherapy, immune- and targeted-therapies (Burrell
and Swanton 2016; Assaraf et al. 2019; Vasan et al. 2019).
* Angélica Figueroa
angelica.figueroa.conde-valvis@sergas.es Important molecular mechanisms involved in drug resist-
ance have been well determined by the effect of a decreased
1
Bioinformatics and Functional Genomics Group, Cancer drug uptake by altered influx transporters, an increased drug
Research Center (CiC‑IBMCC, CSIC/USAL/IBSAL), efflux by the overexpression of multidrug-resistance (MDR)
Consejo Superior de Investigaciones Científicas (CSIC),
University of Salamanca (USAL), Salamanca, Spain efflux transporters or an altered expression of anti-apoptotic
2
proteins (Assaraf et al. 2019). However, still limited under-
Division of Molecular Biology, Ruđer Bošković Institute,
Bijenička 54, 10000 Zagreb, Croatia
standing of the molecular mechanisms involved in therapy
3
resistance has been elucidated. Epithelial-to-mesenchymal
Shmunis School of Biomedicine and Cancer Research,
George S. Wise Faculty of Life Sciences, Tel-Aviv
transition (EMT) has emerged as a major contributor to ther-
University, Tel Aviv, Israel apy resistance. EMT is a highly conserved cellular program
4
Epithelial Plasticity and Metastasis Group, Instituto de
that allows polarized, immobile epithelial cells to transform
Investigación Biomédica de A Coruña (INIBIC), Complexo into mesenchymal, mobile cells because of the loss of apico-
Hospitalario Universitario de A Coruña (CHUAC), Sergas, basal polarity, the loss of cell–cell contacts, the reorganiza-
Spain tion of the actin cytoskeleton, and the ability to invade the
5
Universidade da Coruña (UDC), Coruña, Spain
13
Vol.:(0123456789)
extracellular matrix as an individual cell. EMT is related to is accompanied by the downregulation of other epithelial
tumour progression, metastasis and mediates resistance to proteins, such as cytokeratins, claudins, and the upregulation
conventional therapies and small-molecule targeted inhib- of mesenchymal markers, such as N-cadherin, Vimentin or
itors (Thiery et al. 2009; Chaffer et al. 2016; Yang et al. Fibronectin (Nieto et al. 2016; Brabletz et al. 2018; Yang
2020). Important studies using tumour cell lines demonstrate et al. 2020). Moreover, several transcription factors (TFs)
the implication of EMT in resistance driven by radio- or are involved in the EMT, as the repressors of E-cadherin pro-
chemotherapy (Inoue et al. 2002; Olmeda et al. 2007). How- moter including the Snail/Slug family, Twist, Zeb1 and Zeb2
ever, insufficient in vivo information is available mainly due (Batlle et al. 2000; Cano et al. 2000). The loss of E-cadherin
to the absence of suitable in vivo models and limited human is also regulated by posttranscriptional regulators (such as
samples analyzed to perform comprehensive studies. On the miR-200 family or RNA-binding proteins) or by posttrans-
other hand, it is important to highlight that intermediate epi- lational regulators (such as CK1 or Hakai) (Park et al. 2008;
thelial and mesenchymal (E/M) phenotypic states coexists Gregory et al. 2008; Sarkar et al. 2010; Wang et al. 2010;
in a carcinoma, therefore different subpopulation are found, Aparicio et al. 2013).
increasing the level of plasticity within the tumour (Yang Although many publications have reported the implica-
et al. 2020). Although the influence of these intermediate tion of EMT on cancer metastasis, important articles support
E/M states on resistance to anticancer therapeutics drugs is that EMT program is dispensable in this process (Arumugam
not fully understood, pharmacogenomics approaches impact et al. 2009; Fischer et al. 2015; Zheng et al. 2015). How-
on this relevant aspect. Moreover, an important link between ever, the relationship between EMT and therapy resistance
EMT and tumour microenvironment has arisen as a state of is increasingly established. Indeed, the link between EMT
the art of research in oncology, highlighting the need of per- and cancer stemness and their influence on drug resistance
sonalized treatments for individual cancer patients (Shibue has been recently reported, therefore this topic will be not
and Weinberg 2017; Maman and Witz 2018; Gupta et al. recapitulated in detail (Koren and Fuchs 2016; Chaffer et al.
2019; Recasens and Munoz 2019; Boumahdi and de Sau- 2016; Shibue and Weinberg 2017; Dongre and Weinberg
vage 2020). Given the recent outstanding contributions pub- 2019). The general mechanism regarding EMT-associated
lished on the importance of tumour microenvironment and drug resistance is related to increased drug efflux, slow cell
EMT in multidrug resistance (MDR), this issue will be not proliferation and avoiding apoptosis signaling pathways.
further discussed (Erin et al. 2020). In this review, we will Moreover, avoiding immune response is another impor-
go in depth into the molecular mechanism by which EMT tant mechanism by which EMT contributes to therapeutic
induce therapy resistance and how the microenvironment resistance, by altering expression of molecules involved in
contribute to this process. Moreover, future perspectives on immunosuppression or immunoevasion (Shibue and Wein-
bioinformatic and pharmacological approaches to overcome berg 2017; Gupta et al. 2019; Dongre and Weinberg 2019).
therapies resistance will be also discussed. Although EMT can have an impact on drug resistance in sev-
eral preclinical models (Shibue and Weinberg 2017; Gupta
et al. 2019), the understanding of the molecular mechanism
Epithelial‑to‑mesenchymal transition is poorly understood as recapitulated below. Many publica-
and tumour resistance: evidences in vitro, tions highlight the impact of EMT in vitro, in vivo and in
in vivo and in clinical studies clinical specimens. It is reported the implication of tran-
scriptional or posttranslational EMT-related regulators in
The cancer EMT program is a cellular and molecular process resistance to anticancer therapeutic drugs (Kajita et al. 2004;
by which epithelial tumour cells lose cell–cell contacts and Yauch et al. 2005; Olmeda et al. 2007; Saxena et al. 2011;
apico–basal polarity, acquiring mesenchymal characteris- Shibue and Weinberg 2017; Weng et al. 2019; Dongre and
tics (Brabletz et al. 2018; Yang et al. 2020). Importantly, Weinberg 2019; Boumahdi and de Sauvage 2020). Here, we
EMT is a highly dynamic and reversible process, on which will discuss recent EMT studies in different cancer models.
mesenchymal cells can revert to epithelial phenotype by Perhaps the most controversial studies in this field were
mesenchymal-to-epithelial transition process (MET) (Thiery reported in vivo, using transgenic mice models (Fischer et al.
et al. 2009). Intermediate cellular states, E/M hybrid phe- 2015; Zheng et al. 2015). Using a EMT lineage tracing a
notypes, coexist within the tumour harboring high degree triple transgenic mice of breast cancer, it was demonstrated
of epithelial–mesenchymal plasticity (EMP). The epithelial- that inhibition of EMT by overexpression of miR-200a
to-mesenchymal plasticity is tightly regulated at a transcrip- and, in consequence, the abolition of the EMT-TFs Zeb1
tional, post-transcriptional and post-translational level, with and Zeb2, abrogated chemoresistance to cyclophospha-
important clinical implications (Sabbah et al. 2008; Aparicio mide (Fischer et al. 2015). Additionally, by deleting Snail
et al. 2013, 2015). The loss of expression of E-cadherin pro- or Twist TFs in genetically engineered mouse models of
tein at cell–cell contacts is a hallmark of the EMT, which pancreatic ductal adenocarcinoma resulted in an enhanced
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expression of nucleoside transporters in tumours, which osimertinib (Namba et al. 2019). The molecular mechanism
in turn increased the sensitivity to gemcitabine treatment proposed for this therapy resistance is the participation of
(Zheng et al. 2015). Although both studies were very con- cell stem characteristics, the repression of the proapoptotic
troversial as the contribution of EMT on cancer metastasis protein Bcl-2-like protein 11 or the chromatin remodeling
was not supported, this affirmation was later argued (Aiello driven by EMT-TFs (Sayan et al. 2009; Song et al. 2018).
et al. 2017; Ye et al. 2017). However, the involvement of Moreover, MET-driven EMT has also been demonstrated to
the EMT in drug resistance was very well demonstrated in induce chemoresistance. On the one hand, cisplatin-resistant
these two in vivo preclinical models, and the implication of NSCLC cell lines showed MET overexpression compared
EMT in chemoresistance underscored the potential benefit to parental ones, which is accompanied by and increased
of combining EMT inhibition with chemotherapy for the expression of N-cadherin, Vimentin, Zeb1 and Snail, and
cancer treatment. a decreased expression of E-cadherin. On the other hand,
Apart from these two important contributions using trans- mir-206-mediated MET downregulation not only reversed
genic mice models, the majority of data linking EMT to EMT but also sensitized resistant NSCLC cells to cisplatin
chemoresistance is supported by in vitro studies, xenograft (Chen et al. 2016).
tumours using athymic mice, and in clinical specimens. Per- In breast cancer, it was described that the overexpres-
haps, lung cancer is one the best type of cancer on which sion TFs such as Twist, Snail, and FOXC2 increases the
the link between EMT and resistance to therapy is well promoter activity of ABC transporters, indicating that EMT
documented. It has been demonstrated that targeting FGFR inducers are novel regulators of ABC transporters. Therefore
prevents the development of EMT-mediated resistance in EMT-TFs are proposed as novel strategies to treat metasta-
EGFR mutant NSCLC (Raoof et al. 2019). On the other sis and the associated drug resistance (Saxena et al. 2011).
hand, epigenetic silencing of miR-483-3p has been reported Importantly, it has been elucidated that intermediate E/M
to promote acquired gefitinib resistance and EMT in EGFR- phenotypes in breast cancer cells are more effective in devel-
mutant NSCLC (Yue et al. 2018). Many publications under- oping drug resistance and metastasis than when a complete
score the implication of EMT-TFs in drug resistance (Fig. 1). mesenchymal state has occurred (Jolly et al. 2019). One of
For instance, the overexpression of Snail and Slug has been the molecular mechanisms proposed for this resistance in
reported to induce gefitinib resistance in EGFR-mutant lung mesenchymal-like triple-negative breast cancer cells is due
cancer cell lines (Lee et al. 2017a). Moreover, PAX6 has to the expression of ITGB4 + in intermediate states, regu-
been demonstrated to induce EMT and cisplatin resistance lated by Zeb1 through its repression on Tap63α expression, a
through the regulation of Zeb2 expression (Wu et al. 2019a). protein that promotes ITGB4 expression (Bierie et al. 2017).
The upregulation of the EMT-associated gene AXL, has Another important example of the implication of EMT-TFs
been described to predict acquired resistance to EGFR-TKI in drug resistance was reported in normal and transformed
Fig. 1 Targeting cancer epithelial tumour plasticity to overcome lial/mesenchymal marker proteins in cancer cells with partial E/M
resistance. Tumour cells with epithelial phenotype can undergo hybrid phenotype is associated with increased cellular plasticity and
epithelial-to-mesenchymal transition program at primary tumour stemness. Several transcription factors, post-trasncriptional and post-
site. Epithelial cells loose cell–cell contacts and aquiere invasive translational regulators of the EMT are implicated in therapy resist-
and migratory capabilities. The existence of intermediate epithe- ance
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human mammary epithelial on which induction of Twist Boumahdi and de Sauvage 2020). This study not only under-
overexpression or E-cadherin inhibition confer resistance to scores the implication of the posttranslational regulators of
paclitaxel and doxorubicin. On the other hand, Snail confers the EMT in gefitinib-resistance (beyond EGFR mutations
resistance to docetaxel and gemcitabine in basal-like breast per se), but also draws the attention for therapeutic target-
cancer MDA-MB-231 cells. However, breast cancer cells ing of Hakai to block EMT and overcome chemoresistance
with mesenchymal characteristics are sensitive to paclitaxel. in combination with chemotherapy. In fact, a recent study
Indeed, it has been demonstrated that induction of EMT acti- identified Hakin-1 as a novel specific small-molecule inhibi-
vates PERK-eIF2α and sensitizes cells to agents that perturb tor against Hakai, emerging as an effective therapeutic agent
endoplasmic reticulum function, which shows a new vulner- for EMT inhibition (Martinez-Iglesias et al. 2020). Given
ability of cancer cells that undergo EMT, consisting in the the mechanism of action of Hakai, it is expected that differ-
sensitivity to endoplasmic reticulum stress (Olmeda et al. ent types of carcinomas, such as colorectal cancer or lung
2007; Gupta et al. 2009; Feng et al. 2014). Importantly, by cancer, may benefit with this therapy (Figueroa et al. 2009;
using in vitro and in xenograft models, the link between Aparicio et al. 2015; Castosa et al. 2018). Another important
EMT and endocrine therapy resistance in luminal breast can- posttranslational mechanism that may impact therapy resist-
cer has been reported. Indeed, when estrogen receptor alpha ance, is described in colorectal cancer (Díaz and de Herreros
gene (ESR1) fusion proteins is expressed in breast cancer 2016; Li et al. 2019). The transcription factor Zeb2 is a sub-
cell lines it promotes an estrogen-independent activation of strate for the F-Box E3 ubiquitin-ligase FBXW7 in intesti-
EMT by Snail upregulation and E-cadherin downregulation nal stem cells upon GSK3β phosphorylation. In mouse and
(Lei et al. 2018). Other examples of the link between EMT human colorectal cancer cell lines, the axis Zeb2/FBXW7
and therapy resistance have been shown in prostate and ovar- induces EMT and metastasis, and it is linked to chemore-
ian cancer. Indeed, prostate tumour resistance to cabazitaxel sistance (Díaz and de Herreros 2016; Li et al. 2019). Other
can be overcome by antiandrogen-mediated EMT-MET in important proteins involved in ubiquitin–proteasome path-
androgen-sensitive tumours but not in metastatic castration- way was recently reported to be involved in breast and pan-
resistant prostate cancer patients, who frequently develop creatic cancer cells (Lambies et al. 2019). It was shown that
therapeutic resistance to taxane chemotherapy and antian- TGF-β-induced EMT activates the deubiquitinase USP27X,
drogens. On the other hand, Lysyl oxidase-like 2 (LOXL2), a which stabilize Snail protein. In the absence of USP27X,
protein that induces EMT, is involved in radiotherapy resist- Snail is degraded and the sensitivity to cisplatin is increased,
ance in prostate cancer cells and in xenografts mice model opening new therapeutic strategies to overcome chemoresist-
(Cano et al. 2012; Martin et al. 2016). In ovarian cancer, the ance (Lambies et al. 2019).
EMT-TFs Snail and Slug drive chemo and radioresistance
through the p53-driven apoptosis and regulation of stem
properties (Kurrey et al. 2009). In colorectal cancer, miR- Regulation of the epithelial‑to‑mesenchymal
128-3p reverses oxaliplatin resistance in colorectal cancer transition by tumour microenvironment
through the downregulation of Bmi1 and MRP5, two genes
involved in oxaliplatin-induced EMT (Liu et al. 2019). Solid tumours are a cellular ecosystem termed tumour
The involvement of the post-translational EMT regulators microenvironment (TME). In addition to tumour cells the
in drug resistance has been described (Fig. 1). It was demon- cellular content of the TME is composed of resident and
strated that early stages of EMT involve a post-translational infiltrating non-tumour cells including endothelial cells,
downregulation of E-cadherin, whereas loss of E-cadherin fibroblasts, various types of lymphatic cells such as T, B
via transcriptional repression is a late event in EMT (Janda and NK cells; myeloid cells such as macrophages and granu-
et al. 2006). As previously mentioned, the E3 ubiquitin- locytes and others. A major component of the acellular frac-
ligase Hakai is a posttranslational regulator of E-cadherin tion of the TME is the extra cellular matrix (ECM), a net-
stability (Fujita et al. 2002; Aparicio et al. 2012). Hakai is work of multiple categories of macromolecules. Other TME
upregulated in gefitinib-resistant NSCLC cells that acquired constituents are soluble products of the microenvironmental
EMT characteristics. Moreover, an increase of Hakai and a cells such enzymes, cytokines, chemokines and antibodies.
decrease in E-cadherin expression is also detected in gefi- The metabolome of the TME very often differs from the
tinib-resistant clinical cancer samples and lung cell lines. corresponding normal organ and hypoxia characterizes the
This event was reversed by the dual action of histone dea- TME of most solid tumours. Drugs may also be present in
cetylase (HDAC) and 3-hydroxy-3-methylglutaryl coenzyme the TME of treated tumour bearers (Maman and Witz 2018).
A reductase (HMGR) inhibitor, JMF3086. Indeed, JMF3086 The TME is an arena for dynamic and constant interactions
inhibited the Src/Hakai and Hakai/E-cadherin interaction between tumour cells, their molecular products and host-
reverting E-cadherin expression and reducing Vimentin and derived cells and molecules. The reciprocal tumour-host
stemness to restore gefitinib sensitivity (Weng et al. 2019; interactions lead to an evolving phenotype reprograming of
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both interaction partners and may culminate in metastasis superfamily, VEGF, HGF, HIFs, Notch and Wnt, ECM
and therapy resistance (Dalton 1999; Morin 2003; Correia components and microRNAs to mention but a few (Thiery
and Bissell 2012; Maman and Witz 2018). et al. 2009; Lindsey and Langhans 2014; Mudduluru et al.
The survival, propagation and the progression of cancer 2015; Ye and Weinberg 2015; Zhang et al. 2016; Dongre and
cells towards metastasis depend on intrinsic properties of Weinberg 2019). These, sometimes converging, signaling
the cancer cells as well as on cross-talk with their microen- pathways upregulate several EMT-transcription factors such
vironment (Klein-Goldberg et al. 2014; Maman and Witz as Twist, Zeb1 and Snail (Cano et al. 2000; Peinado et al.
2018). The spread of cancer cells from the primary site to 2007; Taube et al. 2010).
secondary organ sites and then the establishment of new These EMT-regulated factors act in concert to alter cel-
cancer lesions in these sites is a sequential multistep process. lular morphology, promote motility, reprogram ECM, and
Each step of the metastatic cascade is jointly controlled by downregulate tight junctions (Peinado et al. 2007; Wheelock
tumour-intrinsic factors as well as by those originating in the et al. 2008). Importantly, during EMT process distinct inter-
TME (Klein-Goldberg et al. 2014; Maman and Witz 2018). mediate stages are found, existing tumour subpopulations
One of the initial phases of the metastatic cascade is driven expressing phenotypes ranging from a complete epithelial
by the activation of the EMT program that confers to tumour to a complete mesenchymal one may co-inhabit single solid
cells the capacity to invade neighboring tissues. Then, cells tumours. The microenvironmental host cells associated with
reach the circulation, spread throughout the body and subse- different tumour subpopulations may also vary (Pastushenko
quently metastasize to specific organs. EMT program is trig- et al. 2018). Moreover, it should also be remembered that
gered in response to TME-derived paracrine signals emit- the mesenchymal-tumour cells generated by the EMT pro-
ted from resident or infiltrating non-tumour cells such as cess exert various effects on microenvironmental cells that
fibroblasts, macrophages or immunocytes (Lamouille et al. could impact tumour progression and drug resistance (Nas-
2014; Brabletz et al. 2018; Yang et al. 2020). The molecu- sar and Blanpain 2016; Dongre and Weinberg 2019). The
lar program that drives EMT functions via miocroenviron- main microenvironmental drivers of EMT will be discussed
mental multi-signaling pathways that cooperate and cross below (Fig. 2).
talk to each other. Among these are members of the TGF
Fig. 2 Microenvironment drivers of the EMT as potential therapeutic hypoxic conditions, inflammatory and immune cells are EMT-drivers.
target to overcome therapy resistance. Several microenvironment fac- These cells activate several signaling pathways such as TNF-α, TGF-
tors such as tumour associated macrophages (TAMs), cancer associ- β, IL-1β, IL-6, VEGF, HGF, HIFs, NOTCH and WNT, inducing
ated fibroblasts (CAFs), alterations in the extracellular matrix (ECM), EMT-transcription factors
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Hypoxia The inflammatory and immune microenvironment
Hypoxia, characterizing the microenvironment of essentially Tumour promoting and tumour suppressive immunocytes
all solid tumours, is a major driver of EMT. The hypoxia- and inflammatory cells as well as their molecular products
mediated effects are exerted by Hypoxia-Inducible Factors are abundantly present in the TME (Maman and Witz 2018).
(HIFs), a family of transcriptional regulators that control The inflammatory cells as well as their secretome have the
functions involved in tumour progression such as extracel- capacity to induce, drive and maintain EMT (Yan et al.
lular matrix (ECM) remodeling, cell survival and prolif- 2018; Fedele and Melisi 2020). Tumour-associated mac-
eration, metabolism, inflammation and angiogenesis. HIFs rophages (TAMs) are the largest non-tumour cell popula-
also play pivotal functions in the EMT process and drug tion in the TME. These cells promote tumour progression
resistance (Rohwer and Cramer 2011; Balamurugan 2016; by secreting the angiogenic cytokine VEGF, and by activat-
Schito and Rey 2017; Joseph et al. 2018). HIF-1, a member ing inflammatory pathways via pro-inflammatory cytokines
of the HIF family, upregulates the expression and activity (Noy and Pollard 2014; Ségaliny et al. 2015; Mantovani
of several EMT-inducing transcription factors including et al. 2017). TAMs also play a crucial role in the induction
Twist, Zeb1 and Snail. Each of these factors alone has the and maintenance of EMT (Song et al. 2017), for example by
capacity to induce EMT (Yang et al. 2008). These factors secreting pro-inflammatory cytokines such as TNF-α, TGF-
repress the expression by tumour cells of epithelial-specific β, IL-1β, IL-6, CCL5 and CCL18. TAMs are involved in
proteins such as E-cadherin while inducing the acquisition the activation of the EMT process by using various modes
of a mesenchymal phenotype in these cells. HIF-1 may exert of action (Suarez-Carmona et al. 2017; Dominguez et al.
its influence by functioning in concert with other factors. For 2017). Other myeloid cells such as granulocytes or myeloid-
example, HIF-1 engages in a crosstalk with members of the derived suppressor cells also induce EMT (Toh et al. 2011;
TGF-β family, being themselves strong inducers of EMT Mayer et al. 2016; Sangaletti et al. 2016). Tumour infiltrating
(the role of TGF-β family members in EMT is discussed lymphocytes such as regulatory T cells (Kudo-Saito et al.
separately). These 2 interaction partners cooperatively sup- 2009) are also involved in the activation of EMT mainly via
port EMT (Copple 2010). secretion of pro-inflammatory and other tumour-promoting
cytokines. The cross talk between tumour and NK cells tak-
ing place in the microenvironment induces a skewed phe-
The extracellular matrix notype in NK cells becoming drivers rather than inhibitors
of metastasis. This metastasis-promoting function is imple-
The extracellular matrix (ECM), a three-dimensional net- mented via the activation of EMT. The tumour infiltrating
work that surround the cells in a certain microenviron- NK cells secrete pro-inflammatory cytokines such as IL-6
ment, is an important constituent of the TME that provides and activate various matrix metalloproteinases that facilitate
structural and biochemical support to such cells. Its main tumour invasion (Cantoni et al., 2016; Lee et al. 2017b).
functions are to support cell adhesion and inter cellular EMT may induce immune suppressive properties in cancer
communication (Hynes and Naba 2012). The ECM is com- cells (Ricciardi et al. 2015; Terry et al. 2017) or modify their
posed of macromolecules, such as integrins, collagen, gly- immunogenicity resulting either in escape from anti-tumour
coproteins, glycosaminoglycans and enzymes to name but a immune responses or in the generation of new tumour-asso-
few. A review by Tzanakakis provides a detailed account of ciated epitopes (Chockley and Keshamouni 2016; Poggi and
the ECM constituents that interact with EMT components Giuliani 2016).
thereby regulating this process (Tzanakakis et al. 2018).
Deregulated ECM remodeling, induced by matricellular pro- Cancer‑associated fibroblasts
teins, reactive oxygen species, by hypoxia or by proteases,
has a meaningful impact on tumour progression especially Cancer-Associated Fibroblasts (CAFs) together with mye-
by being both affected by this process as well as influencing loid-derived cells (mostly macrophages) and to lesser degree
it. ECM remodeling involves alterations in the expression of endothelial cells are the most abundant non-tumour cells
proteoglycans, a reorganization of the collagen interactome, in the TME. CAFs are generated as a response to activa-
proteolysis of macromolecules and activation of integrins. tion signals delivered to fibroblasts from tumour and non-
These alterations in ECM structure and function drive EMT tumour cells in the TME. Such signals which mediate their
(Catalano et al. 2013; Nieberler et al. 2017; Paolillo and function by contact between tumour cells and fibroblast or
Schinelli 2019; Brassart-Pasco et al. 2020; Gerarduzzi et al. by soluble factors such as IL-1 or IL-6, induce the CAF
2020). phenotype characterized by the expression of α-smooth
muscle actin (α-SMA) (Sahai et al. 2020). CAFs promote
cancer progression by EMT facilitating functions such as
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reprograming of ECM and of the phenotype of tumour and EMT (Vincent et al. 2009; Kim et al. 2016; Yu et al. 2016;
of other TME-residing cells. These functions are mediated Yeh et al. 2018; Tong et al. 2020). TGF-β can also induce
by cellular contacts between CAFs and tumour cells or other EMT by altering the mechanical architecture (cytoskeletal
stromal cells or by soluble factors (Choe et al. 2013; Yu et al. remodeling) of cancer cells to a motile phenotype (Gladilin
2014; Chen and Song 2019). Among the EMT-enhancing et al. 2019). This Smad-independent process involves the
factors released from CAFs are TGF-β and proinflammatory activation of ERK (Lee et al. 2007). Similarly to the TGF-β/
cytokines (Yu et al. 2014; Fang et al. 2018). HIF-1 cooperation (Copple 2010) TGF-β collaborates with
other EMT inducers such as Wnt or Notch to co-stimulate
MicroRNAs EMT thereby promoting an invasive and pro-metastatic phe-
notype of tumour cells (Murillo-Garzón et al. 2018).
MicroRNAs (miRNAs) are small non-coding RNAs that
extensively regulate gene expression by binding mRNA
thereby inhibiting its translation. This capacity enables Microenvironmental regulation of EMT:
miRNAs to function as potent regulators of normal cel- influence on drug resistance
lular physiology and when aberrantly expressed, also of
pathological processes such as cancer progression (Fabian Tumour microenvironment, as an important regulator of the
et al. 2010; Markopoulos et al. 2017). EMT is regulated by EMT, has an impact on therapy resistance. Many publica-
miRNAs. These molecules downregulate EMT-associated tions have highlighted that signals such as growth factors
transcription factors, or alternatively act as their functional or cytokines originated from tumour stroma may regulate
mediators in the regulation of the EMT process (Abba et al. EMT-related drug resistance (Shibue and Weinberg 2017).
2016). As noted above TGF-β, Notch, and Wnt signaling Between them, one of the extracellular matrix factors
pathways are intimately linked to the EMT process. The dis- secreted by CAFs are TGF-β1 and hyaluronan. The first evi-
covery of a signature of 30 miRNAs, each regulating all of dence showing the properties of hyaluronan in cancer resist-
these 3 pathways and of the target genes of these miRNAs, ance was reported in a model of naked rat mole fibroblasts
demonstrated the occurrence of an EMT-promoting cross secreting high molecular mass hyaluronan, that hyper sen-
talk between these pathways (Zoni et al. 2015). Multiple sitize cells to contact inhibition and cell cycle arrest (Tian
miRNAs including miR-200, miR-34, miR-338-3p and oth- et al. 2013, 2015). Those CAFs maintaining high autocrine
ers are involved in the regulation of EMT (Park et al. 2008; production of hyaluronan are more motile, whereas CAFs
Li et al. 2016; Nie et al. 2019). Members of the miR-200 with fewer motile characteristics synthesized higher TGF-
family may serve as prototypes for miRNAs that influence β1. TGF-β1 did not stimulate motility but enhance inva-
EMT. These miRNAs have been extensively studied for their sion and EMT markers, indicating different mechanisms to
role as master regulators (suppressors) of EMT. drive carcinoma progression (Costea et al. 2013). Moreo-
ver, colorectal cancer subtypes with poor prognosis share
TGF‑β a gene program driven by TGF-β secreted by tumour stro-
mal cells, suggesting its association to treatment resistance
TGF-β is a multifunctional cytokine produced by tumour (Calon et al. 2015). On the other hand, it has been reported
as well as by host-derived cells within the TME (Izraely that IL-6 from CAFs enhanced TGF-β-induced EMT in
et al. 2017; Ahmadi et al. 2019). TGF-β regulates various non-small lung cancer cells (NSCLS). Treatment with cis-
functions of tumour cells and of host-derived cells within platin increased TGF-β expression, and the conditioned
the TME by employing TGF-β type I and type II receptors media from cancer cells activated fibroblasts and increased
(Heldin and Moustakas 2016). TGF-β can be regarded as a their IL-6 production, concluding that IL-6 contribute to
prototype of molecules that exert yin-yang functions with induce a paracrine loop that intercommunicated CAFs and
respect to tumourigenesis and tumour progression (Witz NSCLS, resulting in chemoresistance (Abulaiti et al. 2013;
2008). In early phases of tumour progression TGF-β usu- Shintani et al. 2016). Moreover, oncostatin M (OSM), an
ally functions as a tumour suppressor whereas in later phases IL6 cytokine family member, induced the expression of
it promotes malignancy (Yang et al. 2010; Suriyamurthy Zeb1, Snail (SNAI1), and OSM receptor (OSMR), inducing
et al. 2019) mainly by acting as the main inducer and driver the regulation of EMT program and conferring resistance
of EMT, leading to tumour progression towards metastasis to gemcitabine, a current first-line therapy for pancreatic
(Hao et al. 2019). Complexes of TGF-β and its kinase recep- ductal adenocarcinoma (Smigiel et al. 2017). Moreover,
tors activate the intracellular transcriptional effectors Smad. as previously mentioned hypoxia is a hallmark of solid
These, in turn, regulate the expression of EMT-mediating tumours’ microenvironment and is associated to therapeu-
genes Twist, Zeb1 and Snail. Following are some selected tic resistance. The hypoxia-induced gene, procollagen-lysine
studies documenting the role of Smad in TGF-β-mediated 2-oxoglutarate 5-dioxygenase 2 (PLOD2), was induced by
13
hypoxia conditions in biliary tract cancer cell and influence survival. Indeed, the EMT-transcriptional score in different
gemcitabine resistance through EMT (Okumura et al. 2018). tumour subtypes result in a better response to immunother-
HIF-1 has also been associated to therapy resistance. Indeed, apy of those patients presenting luminal phenotype (more
gemcitabine resistance is associated with EMT and induc- epithelial phenotype), than those presenting basal phenotype
tion of HIF-1α in pancreatic cancer cells (Wang et al. 2014), (mesenchymal phenotype). Importantly, different response
leading to the pharmacologic manipulation of HIF-1α as to therapeutic administration with or without paclitaxel was
novel therapeutic approach to overcome resistance. It is also observed while comparing epithelial- and mesenchymal-like
important to mention that exosomes are also responsible of phenotype in ovarian cancers, showing that mesenchymal-
therapy resistance as they contain molecules that influence like tumours do not always show resistance to chemotherapy
tumour progression. Indeed, tumour-derived exosomes may (Choi et al. 2014; Tan et al. 2014). Additionally, high score
favor therapy resistance in the tumour microenvironment and of EMT markers is related to immune expression markers,
induces EMT (Steinbichler et al. 2019). Indeed, exosomal such as PDL-1 in lung adenocarcinomas or head and neck
miR-155 is linked to the development of drug resistance in squamous cell carcinoma (Mak et al. 2016; Ock et al. 2016;
several types of cancers via EMT, such as cisplatin resist- Lou et al. 2016). Future investigations are required to under-
ance in oral cancer cells and in paclitaxel-resistance in gas- stand the molecular mechanism by which the microenviron-
tric cancer cells (Wang et al. 2019a; Steinbichler et al. 2019; ment may influence EMT and therapy resistance. In this con-
Kirave et al. 2020). text, multidisciplinary approaches including bioinformatics
The interactions between cancer cells and immune micro- and pharmacology are important strategies to investigate the
environment also play a crucial role on EMT and therapy impact of EMT-induced therapeutic resistance.
resistance. Cancer cells produce chemokines and cytokines
which recruit immune cells such as T and B lympho-
cytes, macrophages, neutrophils, between others (Maman Bioinformatic investigation in drug
and Witz 2018). For instance, in lung cancer, it has been resistance and in EMT
recently reported that epigenetic suppression by Snail of
the ubiquitin specific protease 4 (USP4) expression is an Bioinformatic and pharmacogenomics for drug
underlying mechanism to contribute to inflammation and and target optimization and for drug resistance
therapeutic resistance by tumour-associated macrophages detection
(Lai et al. 2020). Importantly, immunotherapy has emerged
as a promising therapeutic strategy to treat cancer. Particu- In the future, bioinformatic approaches will importantly
larly, the use of immune-inhibitors targeting the interaction benefit the understanding of clinical relevant phenotypic
between PD-1 and PDL-1 or CTLA-4 have proved important programs to develop better-targeted therapies. It is becom-
benefit in cancer patients (Sharma et al. 2017; Havel et al. ing increasingly apparent that the use of bioinformatics and
2019). Although future investigations are required to deeply patient samples will help to study the biological impact of
understand the molecular mechanism of the immune scape EMT depending on the transition dynamics, as well as to
mechanisms, important contribution of EMT to immune elucidate the role of EMT in drug resistance (Celià-Terrassa
escape has started to come out as well as it has been eluci- et al. 2018). Important publications have used mathemati-
dated the potential use of EMT markers for immune therapy cal or computational methods to study EMT and its poten-
selection. The co-expression of the N-cadherin and Vimentin tial implication in drug resistance. For instance, the use of
EMT markers together with PDL-1 was detected in CTCs of RACIPE mathematical modeling has shown a significant
recurrent patients treated with nivulumab, a PD-L1 inhibi- negative correlation between Twist1 and E-cadherin, and a
tor. This evidence suggests that EMT and PDL-1 may serve positive correlation between Twist1 and Vimentin. Moreo-
to identify patients that do not respond to immunotherapy ver, Twist1 overexpression enhances genome instability in
(Raimondi et al. 2017). Moreover, immunosuppression the context of EMT, thus contributing to cellular hetero-
of CD8 + tumour-infiltrating lymphocytes (TIL) is linked geneity and potentially influencing chemoresistance (Khot
to EMT. In this sense, microRNA-200 (miR-200) targets et al. 2020). On the other hand, a computational approach
PD-L1. The TF Zeb1 activates EMT and transcription- named MAGIC (Markov affinity-based graph imputation of
ally repressed miR-200, which in consequence attenuated cells) was developed for recovering missing gene expres-
miR-200 repression of PD-L1 on tumour cells, leading to sion in single-cell data. MAGIC reveals that the majority of
CD8 + T-cell immunosuppression. This important work sug- cells that reside in an intermediate E/M state display stem-
gests that patients on whom tumour progression is driven like characteristics (van Dijk et al. 2018). Importantly, drug
by EMT activators may respond to PD-L1 inhibitors (Chen resistance in carcinoma cells seems to be maximal at an
et al. 2014). Moreover, EMT transcriptional scoring is a intermediate level of EMT-program activation (Shibue and
very promising strategy to determine treatment response and Weinberg 2017). Foroutan et al. performed a comprehensive
13
bioinformatics approach to show that TGFβ-driven EMT failure because they replace the EGRF function (Gillis and
presents a low mutational burden across the TGFβ signal- McLeod 2016).
ing pathway. Moreover, a significant variation was detected A key challenge that can be also addressed using pharma-
in the response of high scoring cell lines to some common cogenomics is the frequent problem of ineffective response
cancer drugs. This scoring was applied to pan-cancer data to drugs (Relling and Evans 2015; Wang and Weinshilboum
from The Cancer Genome Atlas, showing that tumour types 2019). The complexity drug interactions (due to the exist-
with high scores had significantly lower survival rates than ence of multiple drug-targets, drug-drug cross reactions,
those with low scores and carried a lower mutational burden target-to-target interferences, etc.) and the effect of mul-
in the TGFβ pathway. The pan-drug analysis also showed tiple environmental factors can significantly contribute to
that there was no general drug resistance associated with drug inefficiency, which often also is associated to specific
TGFβ-induced EMT, thus reinforcing the idea of a drug- individual variability. In this regard, genetic factors (such
specific effect (Foroutan et al. 2017). as inherited variability of drug targets, drug metabolizing
Pharmacogenomics is a rapidly growing field framed enzymes, and/or drug transporters) also appear to have a
within genome-wide studies that aims to elucidate how major impact on drug resistance (Roden et al. 2019; Che-
human gene products (i.e. proteins) affect the response to noweth et al. 2020). In fact, specific individual resistance
drugs and pharmacological treatments (Roden et al. 2019). may be associated, for example, with the multi-drug resist-
This relatively new field combines pharmacology and ance proteins (MRPs). These proteins present genetic poly-
genomics to develop effective, safe medications and doses morphisms that cause large differences in their expression
that can be tailored for specific tumour subtypes and spe- and activity level from some individuals to others, and they
cific patient risk factors (Harper and Topol 2012). It is well are key factors in the development of resistance to differ-
known that drugs can have multiple molecular targets inside ent classes of anticancer drugs (Yu et al. 2007; Zhang et al.
our body and that the specific molecular interaction of many 2015).
drugs is often unknown and can be quite variable from one
individual to another. Genome and proteome-wide informa- Cancer drug resistance: inherited or acquired
tion associated to the drugs activity in human cells is essen-
tial to generate better maps of the molecular targets of each Focusing on cancer therapy, the success of target-driven
drug (De Las Rivas et al. 2018). Construction of this type of anticancer drugs is usually limited by the development of
drug-target interaction mapping has been successful in the several types of resistance (Rueff and Rodrigues 2016): (i)
field of cancer genomics thanks to the possibility of testing inherited resistance (sometimes defined as primary resist-
the activity of hundreds of cancer drugs in multiple human ance) and (ii) acquired resistance (defined as secondary
cancer cell lines (Arroyo et al. 2020). Similar studies using resistance). In both cases, resistance emerges in the context
genomic data combined with drugs activity are needed to of cancer heterogeneity, either heterogeneity reflected by
elucidate at molecular level the genetic and somatic basis inter-individual differences within the same type of tumours,
for inter-individual differences in drug response. The dis- or heterogeneity reflected by intra-tumoural differences that
covery of specific genetic factors that modulate the reactiv- reveal the phenotypic diversity of cancer cells co-inhabiting
ity or resistance of a patient with cancer to a drug is one a single tumour mass (Shibue and Weinberg 2017). The first
of the main objectives of pharmacogenomics, knowing that type of cancer heterogeneity (inter-individual) is often cor-
these factors can be critical to understand the safety, toxicity related with inherited primary drug resistance. The second
and efficacy of drugs in individual patients or in groups of type of cancer heterogeneity (intra-tumour) usually cor-
patients (Lee et al. 2005; Chenoweth et al. 2020). An exam- responds to secondary drug resistance, which is acquired
ple of this is the discovery of multiple genetic polymorphism throughout the process of tumour evolution. In both cases,
in gene CYP2D6, that encodes a cytochrome P450, and it pharmacogenomic studies help elucidate the molecular
is responsible for the metabolism of 25% of all drugs cur- origin of resistance to specific anticancer drugs. For exam-
rently on the market. This gene presents polymorphism that ple, resistance to small-molecule tyrosine kinase inhibitors
significantly affect drug action. In fact, in breast cancer it has (TKIs, such as imatinib, erlotinib, gefitinib, and sorafenib),
been shown that the allelic variations in CYP2D6 is a very is usually acquired and shows a very different evolution in
important determinant of tamoxifen’s activity and toxicity different individuals. Also genome-wide studies have shown
(Huang and Ratain 2009). Another example of how pharma- that resistant individuals, compared to non-resistant, com-
cogenomics can reveal resistance mechanisms is the detec- monly harbor acquired somatic point mutations detected
tion, in tumours treated with EGRF inhibitors (erlotinib, in genes NTRK1, KDR, TGFBR2 and PTPN11 and copy
gefetinib, afatinib), of the upregulation or amplification of number alterations in CDK4, CDKN2B and ERBB2 (Gillis
other genes such as MET and HER2 that cause treatment et al. 2017).
13
EMT‑induced drug resistance data) what brought us to the thinking that possible strategy
to overcome or slow down the disease progression could be
EMT-induced drug resistance can be associated in most targeting those specific states by targeting their regulators.
cases with the second type of cancer heterogeneity, intra- There are several great review papers which are discussing
tumour, described above. Moreover, the phenotypic diversity in details therapeutic targets, small-molecule inhibitors of
of neoplastic cells within a tumour is considered a major tumour plasticity as well as natural compounds which could
driver of the development of resistance to therapy. In this be used for targeting tumour metastasis (Kotiyal and Bhat-
context, one of the critical cell subpopulations playing a tacharya 2014; Varghese et al. 2018; Yang et al. 2019; Feng
major role in the generation of drug resistance corresponds et al. 2020). Furthermore, very nicely presented literature
to the tumour cells that undergo EMT. Large-scale pharma- overview was given in a context of compounds and drugs,
cogenomics have been used to unravel how EMT can drive which target microenvironmental-induced EMT (Gao and
resistance to chemotherapeutic drugs (Hong et al. 2018). Mittal 2012; Maman and Witz 2018). It is also known that
In this respect, overexpression of several genes (like inte- many of EMT drivers are epigenetically regulated, by DNA
grin beta-3, ITGB3 also called CD61; and integrin beta-4, methylation, histone modifications and etc., pointing out the
ITGB4), which promote EMT, have been directly related epigenetic regulators could also be interesting therapeutic
with chemoresistance (Li et al. 2017; Hong et al. 2018). This targets for overcoming EMT (Mishra and Johnsen 2014).
resistance has been linked to the activation of EMT tran- As mentioned above, EMT is regulated by various mediators
scription factors Snail (SNAI1) and Slug (SNAI2) in several such as transcription factors, microenvironmental factors,
types of cancer (Haslehurst et al. 2012). Overexpression of signaling pathways, RNA‐binding proteins and miRNAs. In
other EMT-inducing genes, such as Zeb1 have also been a line with this, there are several possible targets to over-
shown to closely correlate with resistance to gemcitabine, come EMT induced drug resistance. The detailed discus-
5-fluorouracil, and cisplatin (Arumugam et al. 2009). sion on all the targets is not possible within the limits of
The specific mechanisms of how EMT induces drug this review but the one investigated lately in the context of
resistance are still under study and may vary in different EMT induced drug resistance particularly are displayed in
types of cancer. For example, some results observed in lung Table 1. Briefly, transcription factors such as Snail, Twist,
cancer (Chae et al. 2018), indicate that EMT causes a change Zeb or Stat3 are activated early in EMT process (Lamouille
in tumours that move them from a hot to a cold state, increas- et al. 2014). Due to their importance in regulation of EMT,
ing the resistance of tumours to immunotherapy. In fact, it the inhibition of their expression or activation may be one
has been shown in non-small cell lung cancer (NSCLC) that of the ways to block EMT. Many signaling pathways, such
an EMT signature is inversely associated with T-cell infiltra- as TGF‐β1, NF‐κB, Wnt, Akt, peroxisome proliferator
tion (Chae et al. 2018). It has also been shown that revers- activated receptor (PPAR), and Notch pathways, and the
ing EMT causes an increase in anticancer drug sensitivity renin‐angiotensin system (RAS) contribute to the EMT.
(Huang and Huang 2016). Another relevant discovery in this Different compounds are described as possible inhibitors of
context is that EMT often generates cells with properties of these signaling pathways for overcoming EMT (Feng et al.
stem cells (Mani et al. 2009), which are more resistant to 2020). Recently, many miRNAs have been found to promote
apoptosis and other types of programmed death, improving or suppress EMT in tumours and sensitize tumour cells to
the capacity for self-renewal. Finally, as explained above chemotherapeutics (Zhang and Ma 2012; Brozovic et al.
therapeutic resistance is in many cases linked to an hybrid 2015; Brozovic 2017). Moreover, post-translational EMT-
epithelial-to-mesenchymal phenotype (Williams et al. 2019). regulators, such as Hakai, FBXW7 or USP27X have been
emerged as new therapeutic strategies to overcome therapy
resistance (Aparicio et al. 2012, 2015; Díaz and de Herre-
Pharmacological approaches for therapies ros 2016; Castosa et al. 2018; Lambies et al. 2019; Li et al.
of EMT induced drug resistance 2019; Martinez-Iglesias et al. 2020).
Some novel mediators specifically involved in EMT-
Due to the fact that EMT is implicated in cancer metastasis induced drug resistance are also shown in Table 1. Inhibitor
and induction of drug resistance, targeting EMT may have of apoptosis-stimulating protein of p53 (iASPP), which was
a therapeutic value (Malek et al. 2017). As previously men- previously confirmed as EMT inducer, promotes miR-20a
tioned, interesting findings have been obtained about the expression in a p53-dependent manner. MiR-20 upregula-
correlation between either epithelial or mesenchymal status tion induces EMT and cisplatin resistance via F-box and
of the cell with drug resistance (Miow et al. 2014; Biddle leucine rich repeat protein 5/BTG anti-proliferation factor 3
et al. 2016). There are on-going investigations about the pos- (FBXL5/BTG3) signaling in cervical cancer HeLa and SiHa
sibility that the specific state of these two phenomena could cell lines (Dong et al. 2016; Xiong et al. 2017). Forkhead
be reversible, among them also ours (Brozovic, unpublished box protein C2 (FOXC2) was shown to promote resistance
13
Table 1 Potential new targets to overcome EMT-induced drug resistance

EMT inducer Proposed targets Developed resistance Tumour/tumour cell type Reference
Snail (SNAI1)⇑ Snail Cisplatin Head and neck Ota et al. (2016)
Twist (TWIST1) ⇑ Twist Erlotinib Non-small cell lung Yochum et al. (2019)
Osimertinib
Hakai (CBLL1) Hakai Gefitinib /cisplatin Lung Liu et al. (2018); Weng et al.
(2019); Martinez-Iglesias
et al. (2020)
FBXW7 FBXW7 Cisplatin Colorectal Li et al. (2019)
CAFs ANXA2, EGFRi Non-small cell lung Yi et al. (2018)
HGF/IGF-1/ANXA2
CAFs IL-6 Paclitaxel Ovary Wang et al. (2018)
IL-1β⇑ AKR1C1 Cisplatin Bladder Matsumoto et al. (2016)
IGF-1⇑ SPHK1 Paclitaxel Lung Wu et al. (2019b)
OSM&IL-6 (tumour OSM/OSMR Gemcitabine Pancreas Smigiel et al. (2017)
microenvironment)⇑
+ TIPACF7⇑ HECTD1 Cisplatin Breast Duhamel et al. (2018)
TGF-β1 miR-134/-487b/-655 cluster Gefitinib Lung adenocarcinoma Kitamura et al. (2014)
MAGI2
TGF-β1 MCL-1 Cisplatin Non-small cell lung Toge et al. (2015)
TGF-β1 CXCR7 Cisplatin Lung Wu et al. (2016)
Etoposide
TGF-β1 TGF-β1 Oxaliplatin Colorectal Mao et al. (2017)
TGF-β PHD3 (- EMT regulator) Erlotinib Lung Dopeso et al. (2018)
TGF-β1 ST3GAL1 Paclitaxel Ovary Wu et al. (2018)
TGF-β USP27X, Snail Cisplatin Breast and pancreas Lambies et al. (2019)
TGF-β1 WDR5 Paclitaxel Breast Punzi et al. (2019)
Hypoxia HIF-1 (HIF1A) Cisplatin Head and neck squamous Wiechec et al. (2017)
Cetuximab
Dasatinib
Hypoxia PLOD2 Gemcitabine Biliary tract Okumura et al. (2018)
Tumour-derived exosomes miR-155 Cisplatin Oral cancer Kirave et al. (2020)
iASPP⇑ miR-20, FBXL5/BTG3 Cisplatin Cervical Xiong et al. (2017)
CD73⇑ CD73 Trastuzumab Lung Turcotte et al. (2017)
FOXC2⇑ FOXC2, AKT/GSK3β Cisplatin Non-small cell lung He et al. (2018)
KPNA3⇑ KPNA3, AKT/ERK Sorafenib Hepatocellular Hu et al. (2019)
PRRX1⇑ SIRT1-PRRX1-KLF4-ALDH1 Paclitaxel Breast Shi et al. (2018)
Sema4C⇑ Sema4C, miR-31-3p Cisplatin Cervical Jing et al. (2019)
SNHG3⇑ miR-128/CD151 Sorafenib Hepatocellular Zhang et al. (2019)
TYRO3⇑ Snail Paclitaxel Colon Chien et al. (2016)
Oxalilatin
5-fluorouracil
miR-93⇑ PTEN Doxorubicin Breast Chu et al. (2017)
miR-296-3p⇑ PRKCA-FAK-RAS-cMYC Cisplatin Lung adenocarcinoma Fu et al. (2017)
miR-216a/-217⇑ PTEN, SMAD Sorafenib Liver Xia et al. (2013)
miR-574-3p⇓ Zeb1 Cisplatin Gastric Wang et al. (2019b)
miR-509 and miR-1243⇓ CDH1 Gemcitabine Pancreas Hiramoto et al. (2017)
AKR1C1, aldo–keto reductase family 1 member C1; ANXA2, annexin A2; CBF1, centromere-binding protein 1; CDH1, E-cadherin; COX-2,
cyclooxygenase-2; CXCR7, C-X-C chemokine receptor type 7; FAK, focal adhesion kinase; FBXW7, F-Box E3 ubiquitin-ligase; Hakai, HYB
domain E3 ubiquitin, ligase; HectD1, E3 ubiquitin-ligase; HGF, hepatocyte growth factor. IGF-1, insulin like growth factor 1; MCL-1, myeloid
leukemia cell differentiation protein; Oct4, octamer-binding transcription factor 4; OSM/OSMR, oncostatin-M/oncostatin M receptor; PARP3,
poly(ADP-Ribose) polymerase family member 3; PHD3, prolyl-4-hydroxylase domain 3; PLOD2, procollagen-lysine,2-oxoglutarate 5-diox-
ygenase 2; PRKCA, protein kinase C alpha; PTEN, phosphatase and tensin homolog; Ras, rous sarcoma virus; SHKBP1, SH3KBP1 binding
protein 1; SMAD, mothers against decapentaplegic homolog 1; SOX2, sex determining region Y-box 2 (or SRY); SphK1, sphingosine kinase
1; ST3GAL1, ST3 beta-galactoside alpha-2; USP27X, X-linked ubiquitin carboxyl-terminal hydrolase 27, deubiquitinase; WDR5, WD repeat
domain
13
to the same drug by induction of EMT in non-small cell lung been proposed to overcome therapy resistance. The devel-
cancer A549 cells by activating v-akt murine thymoma viral opment of plasticity inhibitors may have a great potential
oncogene homolog 1/ Glycogen synthase kinase 3 (AKT/ in cancer treatment as this type of drugs may prevent both
GSK3) signaling pathway and increased expression of Snail drug resistance and cancer metastasis. Compounds targeting
(He et al. 2018). Cisplatin resistance was also induced by regulators of this plasticity could also work well with chem-
Sema4C, and upregulation of miR-31-3p which reversed otherapy or targeted therapy drugs improving in that way the
EMT-mediated biological functions in human cervical can- clinical outcomes of cancer patients. The integration of bio-
cer HeLa, Caski, Siha and C33a cell lines (Jing et al. 2019). informatics, pharmacogenomics and chemical genomic data
It was proposed that depleting sirtuin 1 (SIRT1) accelerates will be crucial to identify both therapeutic targets and novel
the degradation of paired related homeobox 1 (PRRX1) and chemosensitizing drugs to overcome resistance to multiple
disinhibits kruppel-like factor 4 (KLF4) transcription, lead- chemotherapies. A wide range of targets associated with
ing to a partial MET, occurrence of aldehyde dehydrogenase EMT is expected to be elucidated in the future, thus allow-
1 (ALDH1)-positive cancer stem cells, distant metastases ing to overcome therapy resistance. This will allow paving
and resistance to paclitaxel. Reduced nuclear level of SIRT1- an alternative path for drug discovery even for proteins that
PRRX1 axis is positively correlated with lung metastasis cannot be pharmacological targeted nowadays.
of breast cancer (Shi et al. 2018). Tyrosine-protein kinase
receptor TYRO3 is overexpressed in the early stage of colon Acknowledgements This article was performed as a collaborative
effort of the authors within the framework of Action CA17104, STRA
cancer development and aberrant expression of TYRO3 pro- TAGEM: “New diagnostic and therapeutic tools against multidrug
motes tumourigenesis and induces EMT through the reg- resistant tumours”; supported by COST (European Cooperation in
ulation of SNAI1. Blocking TYRO3 signaling by human Science and Technology, www.cost.eu).
anti-TYRO3 antibody ameliorates cancer malignancy and
increased sensitivity to paclitaxel, oxaliplatin and 5-fluoro- Author contributions AF conceived the review. JDLR, AB, SF, AC-P,
IPW and AF wrote the first version of the review. AF and JDLR
uracil in different colon cancer cell lines (Chien et al. 2016). revised the manuscript. All the authors approved the final version of
Expression of ectonucleotidase CD73 by tumour, stromal the manuscript.
and immune cells is associated with immune suppression
(Allard et al. 2017). But it was shown that expression of Funding AF group has been supported by Plan Estatal I + D + i
CD73 is associated with extracellular matrix organization, 2013 − 2016, co-funded by the Instituto de Salud Carlos III (ISCIII,
Spain) under grant agreements PI13/00250 and PI18/00121 by Fondo
TGF-β genes, EMT, hypoxia-inducible factor-1 (HIF-1) as Europeo de Desarrollo Regional (FEDER) “A way of Making Europe”;
well and is mediating resistance to trastuzumab in human by “la Caixa” Foundation (ID 100010434) under the agreement (LCF/
breast cancer (Turcotte et al. 2017). A novel KPNA3-AKT- TR/CI19/52460016); by PRIS3 project from ACIS and Consolidation
ERK-TWIST signaling cascade that promotes EMT and of Competitive Research (IN607B2020/14) from GAIN, both from
Xunta de Galicia and by I.M.Q. San Rafael Foundation (A Coruña).
mediates sorafenib resistance was described in human hepa- The studies of IPW are supported by the Dr. Miriam and Sheldon G.
tocellular cell lines Huh7 and HepG2 cells (Hu et al. 2019). Adelson Medical Research Foundation (Needham, MA, USA), the Sara
Moreover, sorafenib resistance was induced by SNHG3 and Natan Blutinger Foundation (West Orange, NJ, USA), the Fred
overexpression in several human hepatocellular cells PLC/ August and Adele Wolpers Charitable Fund (Clifton, NJ, USA) and
the James and Rita Leibman Endowment Fund for Cancer Research
PRF/5, Hep3B, HepG2, MHCC97L, Huh7, SMMC‐7721, (New York, NY, USA). AB group is supported by the Croatian Sci-
and HCCLM3 EMT via miR-128/CD151 cascade activation ence Foundation (CSF, Project No. IP-2016–06-1036). JDLR group is
(Zhang et al. 2019). funded by the Instituto de Salud Carlos III (ISCIII, AES, Spain) with
grants PI18/00591 and PT17/0009/0008, co-financed by the European
Regional Development Fund (FEDER).
Conclusions Availability of data and materials All the data obtained and/or analyzed
during the current study were available from the corresponding authors
The heterogeneity and plasticity of EMT phenotype are fea- on reasonable request.
tures not only involved in metastasis, but also in drug resist-
ance. In recent years, new molecular insights have come out Declarations
with the implication of EMT in drug resistance thanks to the
in vitro and in vivo studies in preclinical tumour models and Conflict of interest The authors declare that they have no conflict of
interest.
clinical settings. The knowledge of intermediate E/M states,
that represent more properly the reality within the tumour, Consent for publication All authors give consent for the publication of
together with the influence of tumour microenvironment and manuscript in Molecular Cancer.
cellular stemness, has opened new understanding regarding
Author details A.F. is group leader of the Epithelial Plasticity and
to the impact of the EMT to therapy resistance. Moreover, Metastasis Group at the Instituto de Investigación Biomédica de A
new therapeutic strategies based on epithelial plasticity have
13
Coruña (INIBIC), Complexo Hospitalario Universitario de A Coruña Arroyo MM, Berral-González A, Bueno-Fortes S et al (2020) Mining
(CHUAC), Sergas, Universidade da Coruña (UDC), Spain. Expert in drug-target associations in cancer: analysis of gene expression
epithelial-mesenchymal transition in cancer metastasis and drug resist- and drug activity correlations. Biomolecules. https://doi.org/10.
ance. J.D.L.R is head of the Bioinformatics and Functional Genom- 3390/biom10050667
ics Group at the Cancer Research Center (CiC-IBMCC, CSIC/USAL/ Arumugam T, Ramachandran V, Fournier KF et al (2009) Epithelial to
IBSAL), Consejo Superior de Investigaciones Cientificas (CSIC) and mesenchymal transition contributes to drug resistance in pancre-
University of Salamanca (USAL), Salamanca. Vice Chair of STRA atic cancer. Cancer Res 69:5820–5828. https://doi.org/10.1158/
TAGEM “New diagnostic and therapeutic tools against multidrug 0008-5472.CAN-08-2819
resistant tumours”, a European COST action (European Cooperation Assaraf YG, Brozovic A, Gonçalves AC et al (2019) The multi-factorial
in Science and Technology). Expert in Bioinformatics and Functional nature of clinical multidrug resistance in cancer. Drug Resist
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Shmunis School of Biomedicine and Cancer Research, George S. Wise tion, and cancer. Int J Cancer 138:1058–1066. https://doi.org/
Faculty of Life Sciences, Tel-Aviv University, Tel Aviv, Israel. Expert 10.1002/ijc.29519
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ment. A.B. is senior research associate and group leader in Division of is a repressor of E-cadherin gene expression in epithelial tumour
Molecular Biology, Ruđer Bošković Institute, Zagreb, Croatia. Expert cells. Nat Cell Biol 2:84–89. https://doi.org/10.1038/35000034
in molecular mechanisms of drug resistance and drug-induced epithe- Biddle A, Gammon L, Liang X et al (2016) Phenotypic plasticity
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as you give appropriate credit to the original author(s) and the source, E2346. https://doi.org/10.1073/pnas.1618298114
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Archives of Toxicology

Cancer drug resistance induced by EMT: novel therapeutic strategies

Received: 5 March 2021 / Accepted: 28 April 2021

Keywords Epithelial plasticity · Cancer · Therapy resistance · Tumour microenvironment

Hypoxia The inflammatory and immune microenvironment

Table 1 Potential new targets to overcome EMT-induced drug resistance

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