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Cancers, Volume 15, Issue 8 (April-2 2023) – 214 articles

Cover Story (view full-size image): Despite recent therapeutic advances, Multiple Myeloma (MM) remains an incurable disease which alternates between remissions and relapses. Recently, novel immunotherapies, such as antibody drug conjugates, bispecific antibodies and chimeric T cell, have made progress that could drastically change future MM patients’ outcomes. Recent clinical trials demonstrated impressive response rates even in challenging settings, such as triple-refractory MM, which has shown disappointing outcomes in real life. However, ultra-high-risk MM remains a challenge for clinicians despite novel drugs, resulting in new risk stratification approaches. Furthermore, minimal residual disease (MRD)-based therapeutic approaches are becoming the principal objective of future trials, in an attempt to better personalize therapies and optimize outcomes. View this paper
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27 pages, 17708 KiB  
Article
Probing the Potential of Defense Response-Associated Genes for Predicting the Progression, Prognosis, and Immune Microenvironment of Osteosarcoma
by Liangkun Huang, Fei Sun, Zilin Liu, Wenyi Jin, Yubiao Zhang, Junwen Chen, Changheng Zhong, Wanting Liang and Hao Peng
Cancers 2023, 15(8), 2405; https://doi.org/10.3390/cancers15082405 - 21 Apr 2023
Cited by 11 | Viewed by 2282
Abstract
Background: The defense response is a type of self-protective response of the body that protects it from damage by pathogenic factors. Although these reactions make important contributions to the occurrence and development of tumors, the role they play in osteosarcoma (OS), particularly in [...] Read more.
Background: The defense response is a type of self-protective response of the body that protects it from damage by pathogenic factors. Although these reactions make important contributions to the occurrence and development of tumors, the role they play in osteosarcoma (OS), particularly in the immune microenvironment, remains unpredictable. Methods: This study included the clinical information and transcriptomic data of 84 osteosarcoma samples and the microarray data of 12 mesenchymal stem cell samples and 84 osteosarcoma samples. We obtained 129 differentially expressed genes related to the defense response (DRGs) by taking the intersection of differentially expressed genes with genes involved in the defense response pathway, and prognostic genes were screened using univariate Cox regression. Least absolute shrinkage and selection operator (LASSO) penalized Cox regression and multivariate Cox regression were then used to establish a DRG prognostic signature (DGPS) via the stepwise method. DGPS performance was examined using independent prognostic analysis, survival curves, and receiver operating characteristic (ROC) curves. In addition, the molecular and immune mechanisms of adverse prognosis in high-risk populations identified by DGPS were elucidated. The results were well verified by experiments. Result: BNIP3, PTGIS, and ZYX were identified as the most important DRGs for OS progression (hazard ratios of 2.044, 1.485, and 0.189, respectively). DGPS demonstrated outstanding performance in the prediction of OS prognosis (area under the curve (AUC) values of 0.842 and 0.787 in the training and test sets, respectively, adj-p < 0.05 in the survival curve). DGPS also performed better than a recent clinical prognostic approach with an AUC value of only 0.674 [metastasis], which was certified in the subsequent experimental results. These three genes regulate several key biological processes, including immune receptor activity and T cell activation, and they also reduce the infiltration of some immune cells, such as B cells, CD8+ T cells, and macrophages. Encouragingly, we found that DGPS was associated with sensitivity to chemotherapeutic drugs including JNK Inhibitor VIII, TGX221, MP470, and SB52334. Finally, we verified the effect of BNIP3 on apoptosis, proliferation, and migration of osteosarcoma cells through experiments. Conclusions: This study elucidated the role and mechanism of BNIP3, PTGIS, and ZYX in OS progression and was well verified by the experimental results, enabling reliable prognostic means and treatment strategies to be proposed for OS patients. Full article
(This article belongs to the Special Issue Biomarkers of Tumor Metastasis and Invasiveness)
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<p>Screening of DEGs related to the defense response. (<b>A</b>) Volcano plot illustrating the DEGs in osteosarcoma and normal groups with the threshold set at |logFC| ≥ 1 and adj-<span class="html-italic">p</span> ≤ 0.05. (<b>B</b>) DEGs are significantly enriched in the GOBP_DEFENSE_RESPONSE pathway. (<b>C</b>) Trend in the number of studies on GOBP_DEFENSE_RESPONSE pathways in recent years. (<b>D</b>) DRGs obtained by taking the intersection of DEGs and GOBP_DEFENSE_RESPONSE pathway genes. (<b>E</b>) Heatmap showing the expression of DRGs in osteosarcoma samples and normal samples.</p>
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<p>Obtaining DRGs associated with osteosarcoma prognosis. (<b>A</b>) Univariate Cox regression analysis for identifying prognostic DRGs. (<b>B</b>) Interaction network diagram of prognosis-related DRGs. (<b>C</b>,<b>D</b>) Lasso–Cox regression analysis was performed to construct prognostic prediction models.</p>
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<p>Evaluation of DGPS. (<b>A</b>) Univariate Cox analysis. Risk score and metastasis were statistically significant. (<b>B</b>) Multivariate Cox analysis. (<b>C</b>) ROC curve of DGPS in training group. (<b>D</b>) ROC demonstrating that the predictive accuracy of DGPS was superior to the other clinical parameters in the training set. (<b>E</b>) Kaplan–Meier curves of overall survival in the training set. (<b>F</b>,<b>G</b>) Distribution of risk scores and distribution of overall survival status and risk score in the training set. Blue: low risk; red: high risk. (<b>H</b>) Heatmap indicating the expression degrees of BNIP3, PTGIS, and ZYX in the training set. ROC curve, receiver operating characteristics curve; AUC, area under the curve; <span class="html-italic">p</span> &lt; 0.05, statistically significant.</p>
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<p>Kaplan–Meier plots depicting subgroup survival analyses stratified by gender, age, and metastasis.</p>
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<p>Verification of DGPS. ROC curve of DGPS in the test set (<b>A</b>) and in the entire cohort (<b>B</b>). ROC demonstrated that the predictive accuracy of DGPS was superior to that of other clinical characteristics in the test set (<b>C</b>) and in the entire cohort (<b>D</b>). Kaplan–Meier curves of overall survival (OS) in the test set (<b>E</b>) and in the entire cohort (<b>F</b>). Survival status of patients with osteosarcoma in the test set (<b>G</b>,<b>I</b>) and in the entire cohort (<b>H</b>,<b>J</b>). Blue: low risk; red: high risk. The heatmap indicates the expression degrees of BNIP3, PTGIS, and ZYX in the test set (<b>K</b>) and in the entire cohort (<b>L</b>).</p>
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<p>PCA plots depicting the distribution of samples based on the expression of model genes (<b>A</b>), DRGs (<b>B</b>), and all genes (<b>C</b>). Differential expression of model genes in the high- and low-risk groups is shown in box plots (<b>D</b>–<b>F</b>).</p>
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<p>Construction and evaluation of a nomogram based on DGPS. Nomogram used to predict prognosis was constructed based on DGPS in the training set (<b>A</b>), test set (<b>E</b>), and entire cohort (<b>I</b>). Calibration curves of the nomogram in the training set (<b>B</b>), test set (<b>F</b>), and entire cohort (<b>J</b>). The C-index curves for assessing the discrimination ability of DGPS and other clinical characteristics at each time point in the training set (<b>C</b>), test set (<b>G</b>), and entire cohort (<b>K</b>). ROC curves of the nomograms at one, three, and five years in the training set (<b>D</b>), test set (<b>H</b>), and entire cohort (<b>L</b>). “*”represented “<span class="html-italic">p</span> &lt; 0.05”, “***”represented “<span class="html-italic">p</span> &lt; 0.001”.</p>
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<p>Exploration of the association of tumor metastasis with BNIP3. (<b>A</b>) Correlations between BNIP3 and osteosarcoma metastasis are displayed in box plots. ROC curve of diagnosis of osteosarcoma metastasis by BNIP3 in the training set (<b>B</b>) and in the entire cohort (<b>C</b>). (<b>D</b>) Relationship between the expression of BNIP3 and the expression of tumor metastasis-related genes MYC, NELL1, SAR1A, PLOD2, TNFAIP8L1, and TRIM22. (<b>E</b>,<b>F</b>) Expression of BNIP3 in different tumors. “*”represented “<span class="html-italic">p</span> &lt; 0.05”.</p>
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<p>Pathway enrichment analysis of the genes most strongly associated with BNIP3. (<b>A</b>) Heatmap showing the 20 genes with the strongest positive or negative correlations with BNIP3 expression. (<b>B</b>,<b>C</b>) Pathway enrichment analysis showing the enrichment of genes in different pathways.</p>
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<p>GO and KEGG pathway enrichment analyses. (<b>A</b>) Bar plot of the top 10 GO enrichment terms. (<b>B</b>) Bar plot of the top 30 KEGG enrichment terms. (<b>C</b>) Bubble chart of the top 10 GO enrichment terms. (<b>D</b>) Bubble chart of the top 30 KEGG enrichment terms. (<b>E</b>) Circle diagram of GO enrichment analysis. (<b>F</b>) Circle diagram of KEGG enrichment analysis. GO enrichment terms include biological process, cellular component, and molecular function.</p>
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<p>Immunoassay showing that DGPS is closely related to the immune system. (<b>A</b>) Analysis of TMB differences between high- and low-risk groups of patients with osteosarcoma. Box plots of the ssGSEA scores of 15 immune checkpoints (<b>B</b>), 13 immune cells (<b>C</b>), and 12 immune-related functions (<b>D</b>) between different risk groups. (<b>E</b>) Heatmap showing the landscape of immune characteristics and the tumor microenvironment in the TARGET cohort determined by the ssGSEA algorithm. “*”represented “<span class="html-italic">p</span> &lt; 0.05”,“**”represented “<span class="html-italic">p</span> &lt; 0.01”,“***”represented “<span class="html-italic">p</span> &lt; 0.001”.</p>
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<p>The association between immune functions and risk scores and immune function scores between different risk subgroups.</p>
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<p>The association between immune cells and risk scores and immune cell scores between different risk subgroups.</p>
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<p>Correlation analysis of immune-related scores and risk scores. (<b>A</b>–<b>C</b>) Analysis of the variability of risk scores among different StromalScore (<b>A</b>), ImmuneScore (<b>B</b>), and ESTIMATEScore (<b>C</b>) subgroups. (<b>D</b>–<b>F</b>) Scatter plots of correlations between risk scores and StromalScore (<b>D</b>), ImmuneScore (<b>E</b>), and ESTIMATEScore (<b>F</b>).</p>
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<p>Drug correlation and sensitivity analyses with JNK Inhibitor VIII, TGX221, MP470, and SB52334.</p>
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<p>BNIP3 regulates the apoptosis of osteosarcoma cells. (<b>A</b>–<b>E</b>) Apoptosis of osteosarcoma cells after knockdown or overexpression of BNIP3. (<b>F</b>) Overexpression of BNIP3 inhibits apoptosis of osteosarcoma cells, while knockdown of BNIP3 promotes apoptosis of osteosarcoma cells. “NS” represented “No significant difference”, “***” represented “<span class="html-italic">p</span> &lt; 0.001”.</p>
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<p>BNIP3 regulates the proliferation of osteosarcoma cells. Knockdown of BNIP3 inhibits the proliferation of osteosarcoma cells, while overexpression of BNIP3 promotes the proliferation of osteosarcoma cells. “NS” represented “No significant difference”, “*” represented “<span class="html-italic">p</span> &lt; 0.05”, “**” represented “<span class="html-italic">p</span> &lt; 0.01”, “***” represented “<span class="html-italic">p</span> &lt; 0.001”.</p>
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<p>BNIP3 regulates the migration ability of osteosarcoma cells; knockdown of BNIP3 inhibits their migration ability, while overexpression of BNIP3 promotes the migration ability of osteosarcoma cells. “NS” represented “No significant difference”, “**” represented “<span class="html-italic">p</span> &lt; 0.01”, “***” represented “<span class="html-italic">p</span> &lt; 0.001”.</p>
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27 pages, 6383 KiB  
Article
Lung Micrometastases Display ECM Depletion and Softening While Macrometastases Are 30-Fold Stiffer and Enriched in Fibronectin
by Maria Narciso, África Martínez, Constança Júnior, Natalia Díaz-Valdivia, Anna Ulldemolins, Massimiliano Berardi, Kate Neal, Daniel Navajas, Ramon Farré, Jordi Alcaraz, Isaac Almendros and Núria Gavara
Cancers 2023, 15(8), 2404; https://doi.org/10.3390/cancers15082404 - 21 Apr 2023
Cited by 4 | Viewed by 2887
Abstract
Mechanical changes in tumors have long been linked to increased malignancy and therapy resistance and attributed to mechanical changes in the tumor extracellular matrix (ECM). However, to the best of our knowledge, there have been no mechanical studies on decellularized tumors. Here, we [...] Read more.
Mechanical changes in tumors have long been linked to increased malignancy and therapy resistance and attributed to mechanical changes in the tumor extracellular matrix (ECM). However, to the best of our knowledge, there have been no mechanical studies on decellularized tumors. Here, we studied the biochemical and mechanical progression of the tumor ECM in two models of lung metastases: lung carcinoma (CAR) and melanoma (MEL). We decellularized the metastatic lung sections, measured the micromechanics of the tumor ECM, and stained the sections for ECM proteins, proliferation, and cell death markers. The same methodology was applied to MEL mice treated with the clinically approved anti-fibrotic drug nintedanib. When compared to healthy ECM (~0.40 kPa), CAR and MEL lung macrometastases produced a highly dense and stiff ECM (1.79 ± 1.32 kPa, CAR and 6.39 ± 3.37 kPa, MEL). Fibronectin was overexpressed from the early stages (~118%) to developed macrometastases (~260%) in both models. Surprisingly, nintedanib caused a 4-fold increase in ECM-occupied tumor area (5.1 ± 1.6% to 18.6 ± 8.9%) and a 2-fold in-crease in ECM stiffness (6.39 ± 3.37 kPa to 12.35 ± 5.74 kPa). This increase in stiffness strongly correlated with an increase in necrosis, which reveals a potential link between tumor hypoxia and ECM deposition and stiffness. Our findings highlight fibronectin and tumor ECM mechanics as attractive targets in cancer therapy and support the need to identify new anti-fibrotic drugs to abrogate aberrant ECM mechanics in metastases. Full article
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<p>Schematic representation of the methodology followed in this work.</p>
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<p>Structure and mechanics of the decellularized ECM of lung carcinoma (LC) and melanoma (MEL) lung metastases. (<b>A</b>,<b>B</b>) Lung carcinoma and melanoma decellularized metastases, respectively. Different ECM structures are marked with different coloured selections: green—ECM-rich regions; blue—ECM capsule; black—ECM-poor regions; purple—tumor-infiltration area (TIA); orange—micrometastases. (<b>C</b>) Young’s modulus (kPa) of each ECM structure of LC and MEL metastases, measured by atomic force microscopy. (<b>D</b>) ECM deposition measured by the area tumor area occupied by the ECM-rich areas, where the total tumor area was normalized to 100%. (<b>E</b>) Relationship between Young’s modulus (kPa) and estimated volume (mm<sup>3</sup>) of metastases. <span class="html-italic">p</span>-values were obtained using a two-way analysis of variance (ANOVA) with Tukey post hoc multiple comparisons. (ns, * <span class="html-italic">p</span>-value &gt; 0.05, <span class="html-italic">p</span>-value &lt; 0.05, ****, <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Frequency dependent loss (E′) and storage (E″) modulus as measured by dynamic mechanical analysis (DMA) of the ECM of healthy lung and the ECM-rich regions of (<b>A</b>) lung carcinoma (CAR) and (<b>B</b>) melanoma (MEL) lung macrometastasis. Solid lines represent the fits of the two-power law model. Arrows indicate the transition frequency. Fit parameters and transition frequency are detailed in table (<b>C</b>).</p>
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<p>ECM protein staining and quantification of CAR and MEL macrometastases. (<b>A</b>) Representative fluorescent images of acellular tumor sections (20 µm) after immunostaining of laminin (yellow), collagen IV (green), collagen I (blue), and fibronectin (red). Healthy lung ECM is represented in the left column. ECM-rich areas (%r, white selections) were traced using a phase contrast image and then applied to the corresponding fluorescent image. (<b>B</b>,<b>C</b>) ECM proteins’ fluorescent signal quantification of the total tumor (%t) and tumor ECM-rich areas (%r). Healthy lung ECM signal was normalized to 100% (green line). Statistical analysis was performed using unpaired parametric student’s <span class="html-italic">t</span>-tests (**, <span class="html-italic">p</span>-value &lt; 0.01, ***, <span class="html-italic">p</span>-value &lt; 0.001). If nothing else is indicated, the relationship between two variables was found to be insignificant (<span class="html-italic">p</span> &gt; 0.05). Scale bar = 500 µm.</p>
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<p>ECM protein staining and quantification of early-stage invasion areas in CAR metastases (tumor-infiltrated areas, TIA (<b>D</b>–<b>F</b>)) and MEL metastases (micrometastases (<b>A</b>–<b>C</b>)). Representative phase contrast (<b>A</b>,<b>D</b>) and corresponding fluorescent images (<b>B</b>,<b>E</b>) of acellular tumor sections (20 µm) after fibronectin immunostaining (red). The regions of interest were traced on the phase contrast images (yellow selection) and applied to the corresponding fluorescent image (white selection), and the signal was quantified. This quantification was performed for fibronectin, collagen I and IV, and laminin in micrometastases ECM (<b>C</b>) and TIA (<b>F</b>). The intensity of healthy lung ECM was normalized to 100% (green line).</p>
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<p>(<b>A.1</b>,<b>A.2</b>) Tumor necrosis (TUNEL) and (<b>B.1</b>,<b>B.2</b>) proliferation (Ki67) of CAR and MEL macrometastases. TUNEL+ and Ki67+ areas were selected and quantified by normalizing the total tumor area to 100% ((<b>A.3</b>,<b>B.3</b>), respectively). Scale bar = 500 µm.</p>
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<p>Nintedanib effects on structure and microscale mechanics of melanoma lung metastases. (<b>A</b>) Atomic force microscopy (AFM) measurements of the Young’s modulus (kPa) of each ECM structure of MEL metastases that either received no treatment or treatment with NTD. <span class="html-italic">p</span>-values were obtained using a two-way analysis of variance (ANOVA) with a Tukey post hoc multiple comparisons. (<b>B</b>) ECM deposition of ECM-rich regions of MEL macrometastases with and without NTD treatment. Measured by the tumor area occupied by the ECM-rich areas, where the total tumor area was normalized to 100%. Statistical analysis was performed using unpaired parametric student’s <span class="html-italic">t</span>-tests (***, <span class="html-italic">p</span>-value &lt; 0.001). (<b>C</b>) Frequency dependent loss (E′) and storage (E″) modulus as measured by dynamic mechanical analysis (DMA) of the ECM of ECM-rich regions of MEL lung macrometastasis in NTD treated and non-treated mice. Solid lines represent the fits of the two-power law model. Arrows indicate the transition frequency. Fit parameters and transition frequency are detailed in table (<b>D</b>).</p>
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<p>Effects of Nintedanib on the ECM composition, proliferation, and tumor necrosis of MEL macrometastases. (<b>A.1</b>) Representative fluorescent images of acellular tumor sections (20 µm) after immunostaining of laminin (yellow), collagen IV (green), collagen I (blue), and fibronectin (red). Healthy lung ECM is represented in the left column. ECM-rich areas (%r, white selections) were traced using a phase contrast image and then applied to the corresponding fluorescent image. (<b>A.2</b>,<b>A.3</b>) ECM proteins’ fluorescent signal quantification of the total tumor (%t) and tumor ECM-rich areas (%r). Healthy lung ECM signal was normalized to 100% (green line). (<b>B</b>) Effect of Nintedanib treatment on tumor necrosis (TUNEL) (<b>B.1</b>–<b>B.4</b>) and proliferation (Ki67) (<b>B.5</b>,<b>B.6</b>). TUNEL+ and Ki67+ areas were quantified in (<b>B.3</b>,<b>B.5</b>), respectively. (<b>B.4</b>,<b>B.6</b>) Fibronectin enrichment in (<b>B.4</b>) TUNEL+ areas and (<b>B.6</b>) Ki67+ areas 100% corresponds to the total tumor measurement. Statistical analysis was performed using unpaired parametric student’s <span class="html-italic">t</span>-tests (ns, <span class="html-italic">p</span>-value &gt; 0.05 *, <span class="html-italic">p</span>-value &lt; 0.05, ****, <span class="html-italic">p</span> &lt; 0.0001). Scale bar = 500 µm.</p>
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<p>Correlation analysis of ECM-rich area (%rECM), tumor necrosis (TUNEL+), and the stiffness of the ECM-rich areas (E(kPa)) in melanoma macrometastases that received no treatment (triangles, −) and received nintedanib treatment (squares, +NTD) for 10 days after initial cancer cell injection. (<b>A</b>) Correlation analysis between tumor necrosis and ECM production. (<b>B</b>) Correlation analysis between tumor necrosis and ECM stiffness of ECM-rich areas. (<b>C</b>) Correlation analysis between ECM-rich stiffness and relative tumor area. <span class="html-italic">p</span>-values (<span class="html-italic">p</span>) and correlation coefficient (<span class="html-italic">r</span>) were obtained by computing the Pearson correlation.</p>
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12 pages, 3310 KiB  
Article
Immunomorphological Patterns of Chaperone System Components in Rare Thyroid Tumors with Promise as Biomarkers for Differential Diagnosis and Providing Clues on Molecular Mechanisms of Carcinogenesis
by Letizia Paladino, Radha Santonocito, Giuseppa Graceffa, Calogero Cipolla, Alessandro Pitruzzella, Daniela Cabibi, Francesco Cappello, Everly Conway de Macario, Alberto J. L. Macario, Fabio Bucchieri and Francesca Rappa
Cancers 2023, 15(8), 2403; https://doi.org/10.3390/cancers15082403 - 21 Apr 2023
Cited by 1 | Viewed by 1629
Abstract
Hurthle cell (HC), anaplastic (AC), and medullary (MC) carcinomas are low frequency thyroid tumors that pose several challenges for physicians and pathologists due to the scarcity of cases, information, and histopathological images, especially in the many areas around the world in which sophisticated [...] Read more.
Hurthle cell (HC), anaplastic (AC), and medullary (MC) carcinomas are low frequency thyroid tumors that pose several challenges for physicians and pathologists due to the scarcity of cases, information, and histopathological images, especially in the many areas around the world in which sophisticated molecular and genetic diagnostic facilities are unavailable. It is, therefore, cogent to provide tools for microscopists to achieve accurate diagnosis, such as histopathological images with reliable biomarkers, which can help them to reach a differential diagnosis. We are investigating whether components of the chaperone system (CS), such as the molecular chaperones, can be considered dependable biomarkers, whose levels and distribution inside and outside cells in the tumor tissue could present a distinctive histopathological pattern for each tumor type. Here, we report data on the chaperones Hsp27, Hsp60, and Hsp90. They presented quantitative levels and distribution patterns that were different for each tumor and differed from those of a benign thyroid pathology, goiter (BG). Therefore, the reported methodology can be beneficial when the microscopist must differentiate between HC, AC, MC, and BG. Full article
(This article belongs to the Special Issue Thyroid Cancer: New Advances from Diagnosis to Therapy)
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<p>Classification of thyroid cancers (TCs). Thyroid tumors of follicular origin can be of two main subtypes: differentiated and undifferentiated. Papillary (PC) thyroid tumors are the most common type (80–85%) of well differentiated thyroid tumors and have the best prognosis. Follicular thyroid carcinoma (FC) accounts for about 10% of epithelial cancers and lacks diagnostic molecular features. Thyroidal oncocytic follicular cells can give origin to Hurthle cell carcinoma (HC), which constitute about 3% of all TC cancers. Among the undifferentiated subtype, anaplastic thyroid cancer (AC) is a rare and lethal form of TC, which probably derives from follicular cells, resulting from dedifferentiation, in patients with long-standing goiter. In addition to tumors derived from follicular cells, the thyroid gland also develops tumors from parafollicular cells, or C cells, such as the medullary thyroid carcinoma (MC), characterized by an elevated level of calcitonin [<a href="#B4-cancers-15-02403" class="html-bibr">4</a>]. Routinely, diagnosis and staging are carried out using fine-needle aspiration (FNA): cancer cells usually look different from normal cells, so the type of TC is determined by microscopic examination of thyroid cells found in nodules. In addition, molecular tests, such as those for RAS and BRAF mutations, can be used to help make a diagnosis when the result of a fine needle biopsy is uncertain [<a href="#B5-cancers-15-02403" class="html-bibr">5</a>].</p>
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<p>Hsp27 immunohistochemistry. Representative images of immunohistochemical results for Hsp27 in benign goiter (<b>A</b>,<b>B</b>), Hurthle cell carcinoma (<b>C</b>,<b>D</b>), medullary carcinoma (<b>E</b>,<b>F</b>) and anaplastic carcinoma (<b>G</b>,<b>H</b>). (<b>A</b>,<b>C</b>,<b>E</b>,<b>G</b>): magnification 200×, scale bar 50 µm; (<b>B</b>,<b>D</b>,<b>F</b>,<b>H</b>): magnification 400×; scale bar 20 µm.</p>
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<p>Statistical analysis of Hsp27 results. The histogram shows the results for the immunohistochemical evaluation of Hsp27 in benign goiter (BG), Hurthle cell carcinoma (HC), medullary carcinoma (MC), and anaplastic carcinoma (AC). Data are presented as arithmetic mean ± standard deviation. * <span class="html-italic">p</span> ≤ 0.05 vs. BG and MC # <span class="html-italic">p</span> ≤ 0.05 vs. BG, HC and MC.</p>
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<p>Hsp60 immunohistochemistry. Representative images of immunohistochemical results for Hsp60 in benign goiter (<b>A</b>,<b>B</b>), Hurthle cell carcinoma (<b>C</b>,<b>D</b>), medullary carcinoma (<b>E</b>,<b>F</b>), and anaplastic carcinoma (<b>G</b>,<b>H</b>). (<b>A</b>,<b>C</b>,<b>E</b>,<b>G</b>): magnification 200×, scale bar 50 µm; (<b>B</b>,<b>D</b>,<b>F</b>,<b>H</b>): magnification 400×, scale bar 20 µm.</p>
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<p>Statistical analysis of Hsp60 results. The histogram shows statistical results for the immunohistochemical evaluation of Hsp60 in benign goiter (BG), Hurthle cell carcinoma (HC), medullary carcinoma (MC), and anaplastic carcinoma (AC). Data are presented as arithmetic mean ± standard deviation. * <span class="html-italic">p</span> ≤ 0.05 vs. BG and MC; # <span class="html-italic">p</span> ≤ 0.05 vs. BG, and MC.</p>
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<p>Hsp90 immunohistochemistry. Representative images of immunohistochemical results for Hsp90 in benign goiter (<b>A</b>,<b>B</b>), Hurthle cell carcinoma (<b>C</b>,<b>D</b>), medullary carcinoma (<b>E</b>,<b>F</b>), and anaplastic carcinoma (<b>G</b>,<b>H</b>). (<b>A</b>,<b>C</b>,<b>E</b>,<b>G</b>): magnification 200×, scale bar 50 µm; (<b>B</b>,<b>D</b>,<b>F</b>,<b>H</b>): magnification 400×, scale bar 20 µm.</p>
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<p>Statistical analysis of Hsp90 results. The histogram shows results for the immunohistochemical evaluation of Hsp90 in benign goiter (BG), Hurthle cell carcinoma (HC), medullary carcinoma (MC), and anaplastic carcinoma (AC). Data are presented as mean ± standard deviation. * <span class="html-italic">p</span> ≤ 0.05 vs. BG, MC, and AC; # <span class="html-italic">p</span> ≤ 0.05 vs. BG, HC, and MC.</p>
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15 pages, 28043 KiB  
Article
Application of Indocyanine Green Fluorescence Imaging in Assisting Biopsy of Musculoskeletal Tumors
by Siyuan He, Ang Zhong, Jun Lei, Zhouming Deng, Xiaobin Zhu, Renxiong Wei, Huayi Huang, Zhenyi Chen, Lin Cai and Yuanlong Xie
Cancers 2023, 15(8), 2402; https://doi.org/10.3390/cancers15082402 - 21 Apr 2023
Viewed by 1661
Abstract
(1) Background: Biopsies are the gold standard for the diagnosis of musculoskeletal tumors. In this study, we aimed to explore whether indocyanine green near-infrared fluorescence imaging can assist in the biopsy of bone and soft tissue tumors and improve the success rate of [...] Read more.
(1) Background: Biopsies are the gold standard for the diagnosis of musculoskeletal tumors. In this study, we aimed to explore whether indocyanine green near-infrared fluorescence imaging can assist in the biopsy of bone and soft tissue tumors and improve the success rate of biopsy. (2) Method: We recruited patients with clinically considered bone and soft tissue tumors and planned biopsies. In the test group, indocyanine green (0.3 mg/kg) was injected. After identifying the lesion, a near-infrared fluorescence camera system was used to verify the ex vivo specimens of the biopsy in real time. If the biopsy specimens were not developed, we assumed that we failed to acquire lesions, so the needle track and needle position were adjusted for the supplementary biopsy, and then real-time imaging was performed again. Finally, we conducted a pathological examination. In the control group, normal biopsy was performed. (3) Results: The total diagnosis rate of musculoskeletal tumors in the test group was 94.92% (56/59) and that in the control group was 82.36% (42/51). In the test group, 14 cases were not developed, as seen from real-time fluorescence in the core biopsy, and then underwent the supplementary biopsy after changing the puncture direction and the location of the needle channel immediately, of which 7 cases showed new fluorescence. (4) Conclusions: Using the near-infrared fluorescence real-time development technique to assist the biopsy of musculoskeletal tumors may improve the accuracy of core biopsy and help to avoid missed diagnoses, especially for some selected tumors. Full article
(This article belongs to the Section Clinical Research of Cancer)
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<p>Research and design technology roadmap of the test group.</p>
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<p>The flowchart of this trial.</p>
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<p>Thirty-two-year-old male suspected to have malignant tumors of the lower limb soft tissue. (<b>A</b>) Under the guidance of B-ultrasound, the biopsy needle was implanted into the lesion (red arrow). (<b>B</b>–<b>D</b>) The naked-eye view of the biopsy lesions, the green fluorescence, and original fluorescence of the real-time fluorescence development of the biopsy lesions. (<b>E</b>) The histopathologic biopsy results (hematoxylin and eosin, original magnification 100×) confirmed the bone lesion as a non-Hodgkin’s lymphoma. (<b>F</b>–<b>I</b>) Medical imaging before biopsy for the diagnosis of soft tissue tumors (yellow arrow). (<b>J</b>) The pathological results (non-Hodgkin’s lymphoma) after surgical resection of the humeral tumor were consistent with the pathological results of the biopsy (hematoxylin and eosin, original magnification 40×).</p>
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<p>A 35-year-old male suspected to have malignant tumors of the right pelvis and surrounding soft tissue. (<b>A</b>–<b>D</b>) Medical imaging before biopsy for the diagnosis of pelvic malignant tumors (yellow arrow). (<b>E</b>) Under the guidance of CT, the biopsy needle was implanted into the lesion (red arrow). (<b>F</b>–<b>H</b>) Naked-eye view of biopsy lesions and real-time fluorescence imaging of lesion specimens (no fluorescence imaging). (<b>I</b>) Pathological results of the first biopsy (necrotic lesions, inflammatory tissues). (<b>J</b>) The position and direction of the puncture channel were immediately adjusted, the supplementary biopsy was performed (under the guidance of CT), and then real-time fluorescence imaging was performed again after the lesions were obtained (red arrow). (<b>K</b>–<b>M</b>) The naked-eye view of the biopsy lesions, the green fluorescence, and original fluorescence of the real-time fluorescence development of the supplementary biopsy lesions. (<b>N</b>) The histopathologic biopsy results (hematoxylin and eosin, original magnification 100×) confirmed the bone lesion as a fibrosarcoma.</p>
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<p>(<b>A</b>) Under the guidance of CT, the biopsy needle was implanted into the lesion (red arrow). (<b>B</b>–<b>D</b>) The naked-eye view of the biopsy lesions and real-time fluorescence imaging of the lesion specimens (no fluorescence imaging). (<b>E</b>) Pathological results of the first biopsy (necrotic tissue). (<b>F</b>) The direction and position of the needle track were adjusted immediately, and the focus was obtained again. After the end of the biopsy, the specimen was developed with real-time fluorescence. In the picture, the biopsy needle was implanted into the lesion (red arrow). (<b>G</b>–<b>I</b>) The naked-eye view of the biopsy lesions, the green fluorescence, and original fluorescence of the real-time fluorescence development of the supplementary biopsy lesions. (<b>J</b>) The pathological results of the supplementary biopsy (osteosarcoma). (<b>K</b>–<b>M</b>) Imaging data before biopsy (yellow arrow). (<b>N</b>) The pathological results (osteosarcoma) after surgical resection of the humeral tumor were consistent with the pathological results of the biopsy.</p>
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16 pages, 4233 KiB  
Article
Pterostilbene and Probiotic Complex in Chemoprevention of Putative Precursor Lesions for Colorectal Cancer in an Experimental Model of Intestinal Carcinogenesis with 1,2-Dimethylhydrazine
by Márcio Alencar Barreira, Márcio Wilker Soares Campelo, Conceição da Silva Martins Rebouças, Antoniella Souza Gomes Duarte, Maria Lucianny Lima Barbosa, Said Gonçalves da Cruz Fonseca, Raphaela Ribeiro Queiroz, Érica Uchoa Holanda, Ana Beatriz Aragão de Vasconcelos, Vitória Jannyne Guimarães de Sousa Araújo, Gabriel Maia Diniz, Reinaldo Barreto Oriá and Paulo Roberto Leitão de Vasconcelos
Cancers 2023, 15(8), 2401; https://doi.org/10.3390/cancers15082401 - 21 Apr 2023
Cited by 1 | Viewed by 1789
Abstract
Dietary supplementation with pterostilbene (PS) and/or a probiotic (PRO) may ameliorate the intestinal microbiota in disease conditions. This study aims to evaluate PS and PRO for the chemoprevention of putative precursor lesions for colorectal cancer (CRC) in an experimental model of intestinal carcinogenesis [...] Read more.
Dietary supplementation with pterostilbene (PS) and/or a probiotic (PRO) may ameliorate the intestinal microbiota in disease conditions. This study aims to evaluate PS and PRO for the chemoprevention of putative precursor lesions for colorectal cancer (CRC) in an experimental model of intestinal carcinogenesis with 1,2-dimethylhydrazine (1,2-DMH). Sixty male Wistar rats were equally divided into five groups: Sham, 1,2-DMH, 1,2-DMH + PS, 1,2-DMH + PRO, and 1,2-DMH + PS + PRO. PRO (5 × 107/mL) was offered in water, and PS (300 ppm) was provided in the diet ad libitum. 1,2-DMH (20 mg/kg/week) was administered for 15 consecutive weeks. In the 25th week, proctocolectomy was conducted. PRO alone and PRO combined with PS were the best intervention strategies to improve experimental 1,2-DMH-induced CRC regarding several parameters of carcinogenesis. Our findings may contribute to the development of novel preventive strategies for CRC and may help to identify novel modulators of colon carcinogenesis. Full article
(This article belongs to the Section Cancer Epidemiology and Prevention)
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<p>Experiment design.</p>
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<p>Histopathology of the experimental groups. Photos 2 (<b>A</b>–<b>E</b>) and 2 (<b>K</b>–<b>O</b>) were under 20× objective magnification (scale bar 100 μm) and the longitudinal section. Photos 2 (<b>F</b>–<b>J</b>) and 2 (<b>P</b>–<b>T</b>) were under 40× objective magnification (scale bar 50 μm) and the cross-section. Black arrow—the presence of an aggregate of ACF with more intense staining due to nuclear enlargement and mucin depletion.</p>
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<p>Analysis of oxidative damage by measuring MDA and GSH levels in the distal colon segment. (<b>A</b>) MDA and GSH (<b>B</b>) levels in the distal colon segment. The values are presented as the mean ± SEM. # <span class="html-italic">p</span> &lt; 0.05 vs. Sham and * <span class="html-italic">p</span> &lt; 0.05 vs. 1,2-DMH group. For statistical analysis, the one-way ANOVA test was used followed by Tukey’s post-test.</p>
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<p>Immunoexpression of iNOS, NF-kB, TNF-α, and IL1β proteins in the distal colon segment. (<b>A</b>) Representative histology of iNOS, NF-kB, TNF-α, and IL1β immunolabeling in the experimental groups. The graphs (<b>B</b>–<b>E</b>) represent the mean ± SEM of the percentage of the immunopositive area for iNOS, NF-kB, TNF-α, and IL1β in relation to the total area. # <span class="html-italic">p</span> &lt; 0.05 vs. Sham and * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. 1,2-DMH group. (<b>B</b>,<b>D</b>) The data were analyzed using the Kruskal–Wallis test followed by the Dunn’s post-test. (<b>C</b>,<b>E</b>) The data were analyzed by the one-way ANOVA test followed by Tukey’s post-test.</p>
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<p>Immunoexpression of Ki67, P53, β-catenin, and Wnt-3a proteins in the distal colon. (<b>A</b>) Representative histology of Ki67, P53, β-catenin, and Wnt-3a protein immunolabeling in the experimental groups. The graphs (<b>B</b>–<b>E</b>) represent the mean ± SEM of the percentage of the immunopositive area for Ki67, P53, β-catenin, and Wnt-3a in relation to the total area. # <span class="html-italic">p</span> &lt; 0.05 vs. Sham and * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. 1,2-DMH group. (<b>B</b>,<b>C</b>) The data were analyzed using the Kruskal–Wallis test followed by the Dunn’s post-test. (<b>D</b>,<b>E</b>) The data were analyzed by the one-way ANOVA test followed by the Tukey’s post-test.</p>
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<p>The outcome of PRO and/or PS supplementation in an experimental model of CRC development with 1,2-DMH. 1,2-DMH increased histopathological scores, OS (elevated MDA and reduced GSH), and selected inflammatory and tumorigenesis markers (Ki67, β-catenin, Wnt3a, p53, NF-kB, iNOS, IL1-β, and TNF- α). 1,2-DMH + PRO and 1,2-DMH + PS + PRO reduced histopathological scores, and selected inflammatory and tumorigenesis markers (Ki67, β-catenin, Wnt3a, p53, NF-kB, iNOS, IL1-β, and TNF- α) and improved OS (MDA). 1,2-DMH + PS + PRO also increased intestinal GSH levels. 1,2-DMH + PS reduced p53, Ki67, IL1-β and TNF-α tissue expression, but without improving OS and histopathological scores. ↑, increased; ↓, decreased.</p>
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14 pages, 302 KiB  
Review
The Role of AI in Breast Cancer Lymph Node Classification: A Comprehensive Review
by Josip Vrdoljak, Ante Krešo, Marko Kumrić, Dinko Martinović, Ivan Cvitković, Marko Grahovac, Josip Vickov, Josipa Bukić and Joško Božic
Cancers 2023, 15(8), 2400; https://doi.org/10.3390/cancers15082400 - 21 Apr 2023
Cited by 8 | Viewed by 2548
Abstract
Breast cancer is a significant health issue affecting women worldwide, and accurately detecting lymph node metastasis is critical in determining treatment and prognosis. While traditional diagnostic methods have limitations and complications, artificial intelligence (AI) techniques such as machine learning (ML) and deep learning [...] Read more.
Breast cancer is a significant health issue affecting women worldwide, and accurately detecting lymph node metastasis is critical in determining treatment and prognosis. While traditional diagnostic methods have limitations and complications, artificial intelligence (AI) techniques such as machine learning (ML) and deep learning (DL) offer promising solutions for improving and supplementing diagnostic procedures. Current research has explored state-of-the-art DL models for breast cancer lymph node classification from radiological images, achieving high performances (AUC: 0.71–0.99). AI models trained on clinicopathological features also show promise in predicting metastasis status (AUC: 0.74–0.77), whereas multimodal (radiomics + clinicopathological features) models combine the best from both approaches and also achieve good results (AUC: 0.82–0.94). Once properly validated, such models could greatly improve cancer care, especially in areas with limited medical resources. This comprehensive review aims to compile knowledge about state-of-the-art AI models used for breast cancer lymph node metastasis detection, discusses proper validation techniques and potential pitfalls and limitations, and presents future directions and best practices to achieve high usability in real-world clinical settings. Full article
(This article belongs to the Section Cancer Informatics and Big Data)
13 pages, 610 KiB  
Review
Optimizing Treatment Options for Newly Diagnosed Acute Myeloid Leukemia in Older Patients with Comorbidities
by Gaku Oshikawa and Koji Sasaki
Cancers 2023, 15(8), 2399; https://doi.org/10.3390/cancers15082399 - 21 Apr 2023
Cited by 1 | Viewed by 2257
Abstract
Traditionally, the goal of AML therapy has been to induce remission through intensive chemotherapy, maintain long-term remission using consolidation therapy, and achieve higher rates of a cure by allogeneic transplantation in patients with a poor prognosis. However, for the elderly patients and those [...] Read more.
Traditionally, the goal of AML therapy has been to induce remission through intensive chemotherapy, maintain long-term remission using consolidation therapy, and achieve higher rates of a cure by allogeneic transplantation in patients with a poor prognosis. However, for the elderly patients and those with comorbidities, the toxicity often surpasses the therapeutic benefits of intensive chemotherapy. Consequently, low-intensity therapies, such as the combination of a hypomethylating agent with venetoclax, have emerged as promising treatment options for elderly patients. Given the rise of low-intensity therapies as the leading treatment option for the elderly, it is increasingly important to consider patients’ age and comorbidities when selecting a treatment option. The recently proposed comorbidity-based risk stratification for AML allows prognosis stratification not only in patients undergoing intensive chemotherapy, but also in those receiving low-intensity chemotherapy. Optimizing treatment intensity based on such risk stratification is anticipated to balance treatment efficacy and safety, and will ultimately improve the life expectancy for patients with AML. Full article
(This article belongs to the Special Issue Actionable Vulnerabilities in Hematological Malignancies)
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<p>Predicted 5-year overall survival probability using European Risk Score (ESS70+; modified) [<a href="#B45-cancers-15-02399" class="html-bibr">45</a>].</p>
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12 pages, 1452 KiB  
Article
Protective Effects of Influenza Vaccine against Colorectal Cancer in Populations with Chronic Kidney Disease: A Nationwide Population-Based Cohort Study
by Chun-Chao Chen, Wen-Rui Hao, Hong-Jye Hong, Kuan-Jie Lin, Chun-Chih Chiu, Tsung-Yeh Yang, Yu-Ann Fang, William Jian, Ming-Yao Chen, Min-Huei Hsu, Shih-Chun Lu, Yu-Hsin Lai, Tsung-Lin Yang and Ju-Chi Liu
Cancers 2023, 15(8), 2398; https://doi.org/10.3390/cancers15082398 - 21 Apr 2023
Viewed by 2065
Abstract
Chronic kidney disease (CKD) is associated with malignancy, including colorectal cancer, via the potential mechanism of chronic inflammation status. This study aimed to determine whether influenza vaccines can reduce the risk of colorectal cancer in patients with CKD. Our cohort study enrolled 12,985 [...] Read more.
Chronic kidney disease (CKD) is associated with malignancy, including colorectal cancer, via the potential mechanism of chronic inflammation status. This study aimed to determine whether influenza vaccines can reduce the risk of colorectal cancer in patients with CKD. Our cohort study enrolled 12,985 patients older than 55 years with a diagnosis of CKD in Taiwan from the National Health Insurance Research Database at any time from 1 January 2001 to 31 December 2012. Patients enrolled in the study were divided into a vaccinated and an unvaccinated group. In this study, 7490 and 5495 patients were unvaccinated and vaccinated, respectively. A propensity score was utilized to reduce bias and adjust the results. Cox proportional hazards regression was used to estimate the correlation between the influenza vaccine and colorectal cancer in patients with CKD. The results showed that the influenza vaccine exerted a protective effect against colorectal cancer in populations with CKD. The incidence rate of colon cancer in the vaccinated group was significantly lower than in the unvaccinated group, with an adjusted hazard rate (HR) of 0.38 (95% CI: 0.30–0.48, p < 0.05). After the propensity score was adjusted for Charlson comorbidity index, age, sex, dyslipidemia, hypertension, diabetes, monthly income, and level of urbanization, the dose-dependent effect was found, and it revealed adjusted HRs of 0.74 (95% CI: 0.54–1.00, p < 0.05), 0.41 (95% CI: 0.30–0.57, p < 0.001), 0.16 (95% CI: 0.11–0.25, p < 0.001) for one, two to three, and four or more vaccinations, respectively. In summary, the influenza vaccine was found to be associated with a reduced risk of colorectal cancer in CKD patients. This study highlights the potential chemopreventive effect of influenza vaccination among patients with CKD. Future studies are required to determine whether the aforementioned relationship is a causal one. Full article
(This article belongs to the Section Cancer Epidemiology and Prevention)
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<p>Data selection process.</p>
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<p>Free of colon cancer survival rate in vaccinated and unvaccinated group.</p>
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<p>Free of colon cancer survival rate in different numbers of vaccination.</p>
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14 pages, 3585 KiB  
Article
Partial Hepatic Vein Occlusion and Venous Congestion in Liver Exploration Using a Hyperspectral Camera: A Proposal for Monitoring Intraoperative Liver Perfusion
by Simone Famularo, Elisa Bannone, Toby Collins, Elisa Reitano, Nariaki Okamoto, Kohei Mishima, Pietro Riva, Yu-Chieh Tsai, Richard Nkusi, Alexandre Hostettler, Jacques Marescaux, Eric Felli and Michele Diana
Cancers 2023, 15(8), 2397; https://doi.org/10.3390/cancers15082397 - 21 Apr 2023
Viewed by 1879
Abstract
Introduction. The changes occurring in the liver in cases of outflow deprivation have rarely been investigated, and no measurements of this phenomenon are available. This investigation explored outflow occlusion in a pig model using a hyperspectral camera. Methods. Six pigs were enrolled. The [...] Read more.
Introduction. The changes occurring in the liver in cases of outflow deprivation have rarely been investigated, and no measurements of this phenomenon are available. This investigation explored outflow occlusion in a pig model using a hyperspectral camera. Methods. Six pigs were enrolled. The right hepatic vein was clamped for 30 min. The oxygen saturation (StO2%), deoxygenated hemoglobin level (de-Hb), near-infrared perfusion (NIR), and total hemoglobin index (THI) were investigated at different time points in four perfused lobes using a hyperspectral camera measuring light absorbance between 500 nm and 995 nm. Differences among lobes at different time points were estimated by mixed-effect linear regression. Results. StO2% decreased over time in the right lateral lobe (RLL, totally occluded) when compared to the left lateral (LLL, outflow preserved) and the right medial (RML, partially occluded) lobes (p < 0.05). De-Hb significantly increased after clamping in RLL when compared to RML and LLL (p < 0.05). RML was further analyzed considering the right portion (totally occluded) and the left portion of the lobe (with an autonomous draining vein). StO2% decreased and de-Hb increased more smoothly when compared to the totally occluded RLL (p < 0.05). Conclusions. The variations of StO2% and deoxy-Hb could be considered good markers of venous liver congestion. Full article
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<p>Example of the ROI positioning to extract the indexes.</p>
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<p>Examples of the photos acquired with the hyperspectral camera at different time points. In the first line, the near-infrared perfusion index window was controlled; in the second, the real appearance of the pig liver at different time points; in the third line, the window to check the oxygen saturation is evident.</p>
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<p>Trends of each index during time in the different liver lobes. (<b>A</b>) Oxygen saturation, (<b>B</b>) deoxygenated hemoglobin, (<b>C</b>) near-infrared perfusion index, (<b>D</b>) total hemoglobin index, (<b>E</b>) lactates.</p>
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18 pages, 6709 KiB  
Article
Cross-Dataset Single-Cell Analysis Identifies Temporal Alterations in Cell Populations of Primary Pancreatic Tumor and Liver Metastasis
by Daowei Yang, Rohan Moniruzzaman, Hua Wang, Huamin Wang and Yang Chen
Cancers 2023, 15(8), 2396; https://doi.org/10.3390/cancers15082396 - 21 Apr 2023
Cited by 5 | Viewed by 3684
Abstract
Pancreatic ductal adenocarcinoma (PDAC) has a unique tumor microenvironment composed of various cell populations such as cancer cells, cancer-associated fibroblasts (CAFs), immune cells, and endothelial cells. Recently, single-cell RNA-sequencing analysis (scRNA-seq) has systemically revealed the genomic profiles of these cell populations in PDAC. [...] Read more.
Pancreatic ductal adenocarcinoma (PDAC) has a unique tumor microenvironment composed of various cell populations such as cancer cells, cancer-associated fibroblasts (CAFs), immune cells, and endothelial cells. Recently, single-cell RNA-sequencing analysis (scRNA-seq) has systemically revealed the genomic profiles of these cell populations in PDAC. However, the direct comparison of cell population composition and genomic profile between primary tumors (at both early- and late-stage) and metastatic tumors of PDAC is still lacking. In this study, we combined and analyzed recent scRNA-seq datasets of transgenic KPC mouse models with autochthonous PDAC and matched liver metastasis, revealing the unique tumor ecosystem and cell composition of liver metastasis in contrast to primary PDAC. Metastatic PDAC tumors harbor distinct cancer cell subpopulations from primary tumors. Several unique markers, including HMGA1, were identified for metastasis-enriched cancer cell subpopulations. Furthermore, metastatic tumors reveal significantly enriched granulocytic myeloid-derived suppressor cells (G-MDSCs), mature neutrophils, and granulocyte-myeloid progenitors (GMPs). A common GMP population across primary tumors, liver metastases, and healthy bone marrow was identified as the putative cell origin of tumor-associated neutrophils/granulocytes. Full article
(This article belongs to the Special Issue Neoadjuvant Therapies in Pancreatic Cancer)
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<p>Single-cell RNA-sequencing (scRNA-seq) analysis identifies distinct compositions of cell populations between primary tumors and liver metastases of pancreatic cancer. (<b>A</b>,<b>B</b>) scRNA-seq analysis of unfractionated live cell mixture from primary pancreatic tumors and liver metastases of <span class="html-italic">LSL-Kras<sup>G12D/+</sup></span>;<span class="html-italic">Trp53<sup>R172H/+</sup></span>;<span class="html-italic">Pdx1-Cre</span> (KPC) mice, as published by previous datasets (GSE198815 and GSE165534). The major cell clusters are shown in UMAP plot (<b>A</b>). Expression profile of indicated marker genes among defined cell clusters is shown in dot plot with the normalized expression levels of indicated genes (<b>B</b>). (<b>C</b>) UMAP plot comparison of the distinct cell compositions across three groups of KPC mice (<span class="html-italic">n</span> = 3 per group): early-stage primary tumors (KPC-Early), late-stage primary tumors (KPC-Late), and late-stage liver metastatic tumors (KPC-Late-Met). The KPC-Early group contains 6204 cells from 3 individual early-stage KPC mice. The KPC-Late group contains 5878 cells from 3 individual late-stage KPC mice. The KPC-Late-Met group (3406 cells) was derived from the liver metastases from the same three mice of the KPC-Late group. (<b>D</b>) The abundance (%) of indicated cell populations across KPC-Early, KPC-Late, and KPC-Late-Met groups. DC, dendritic cell; pDC, plasmacytoid dendritic cell; G-MDSC, granulocytic myeloid-derived suppressor cell; Gran-Mo progenitor, granulocyte-monocyte progenitor cell.</p>
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<p>Liver metastases reveal different cancer cell subpopulation compositions from primary tumors. (<b>A</b>–<b>C</b>) Cancer cells from primary tumors and liver metastases of KPC-Early, KPC-Late, and KPC-Late-Met groups are stratified into three distinct subclusters in UMAP plot (<b>A</b>), based on the various expression profiles of signature genes shown in violin plot (<b>B</b>) and dot plot (<b>C</b>). (<b>D</b>) UMAP plot comparison of the distinct cancer cell subcluster compositions in the primary tumors and liver metastases of KPC-Early, KPC-Late, and KPC-Late-Met groups. The temporal alterations in cancer cell subcluster compositions among three groups are also shown in pie chart plot. (<b>E</b>) The cancer cell subclusters were examined for the expression profiles of genes associated with the classical and basal-like cancer cell subtype definition, as shown in dot plot.</p>
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<p>Liver metastases reveal different trajectories of cancer cell subpopulations from primary tumors. (<b>A</b>–<b>C</b>) Pseudotime trajectory of cancer cell subpopulations, as revealed by the Monocle3 inference analysis. The distributions of cancer cell subpopulations among KPC-Early, KPC-Late, and KPC-Late-Met groups are compared in (<b>A</b>). The transitional trajectory of cell subpopulations (defined by Monocle3 as the pseudotime clusters 1–9) is shown in (<b>B</b>). Cluster 1 in this Monocle3 trajectory plot represents the previously defined cancer cell CC-1 subcluster as the starting point of the pseudotime trajectory. Cluster 2 represents the previously defined CC-2 subcluster. Clusters 3–9 represent the previously defined CC-3 subcluster. The expression profiles of representative genes for the previously defined CC-1, CC-2, and CC-3 are shown in (<b>C</b>). (<b>D</b>) Differentially expressed genes (DEGs) were calculated by comparing cancer cells from liver metastasis with cancer cells from matched primary tumors. The metastasis-upregulated genes were defined as the DEGs that were expressed by cancer cells of liver metastases at significantly higher levels than cancer cells of late-stage primary tumors. The expression profiles of indicated metastasis-upregulated genes are shown in dot plot.</p>
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<p>The expression level of HMGA1 is upregulated in cancer cells of liver metastases. (<b>A</b>,<b>B</b>) HMGA1 immunohistochemistry staining on tumor tissue sections from KPC mice at various stages of PDAC progression (<span class="html-italic">n</span> = 5 mice per group). The representative images (<b>A</b>) and quantitative results (<b>B</b>) of HMGA1 staining are shown. **, <span class="html-italic">p</span> &lt; 0.01; ***, <span class="html-italic">p</span> &lt; 0.001. (<b>C</b>,<b>D</b>) HMGA1 immunohistochemistry staining on tumor tissue arrays from human PDAC patients. The representative images (<b>C</b>) and quantitative results (<b>D</b>) of HMGA1 staining are shown. *, <span class="html-italic">p</span> &lt; 0.05; ***, <span class="html-italic">p</span> &lt; 0.001. (<b>E</b>) Survival of pancreatic adenocarcinoma patients from TCGA dataset correlated with <span class="html-italic">HMGA1</span> expression level. Log-rank (Mantel–Cox) test was used. Patients with available survival data and RNA-seq data (<span class="html-italic">n</span> = 179) were stratified into two groups based on the average <span class="html-italic">HMGA1</span> expression level as the cut-off value. Scatterplot illustrating the distribution of <span class="html-italic">HMGA1</span> gene expression levels among PDAC patients is also shown. *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Cell compositions of subclusters of endothelial cells and fibroblasts in primary tumors and liver metastases. (<b>A</b>–<b>C</b>) Endothelial cells from primary tumors and liver metastases are characterized in UMAP plot (<b>A</b>) and compared across KPC-Early, KPC-Late, and KPC-Late-Met groups (<b>B</b>). The signature genes of endothelial cells from primary tumors or endothelial cells from liver metastases are shown in violin plot (<b>C</b>). (<b>D</b>,<b>E</b>) Various subpopulations of cancer-associated fibroblasts (CAFs) from primary tumors and liver metastases are characterized in UMAP plot (<b>D</b>) and compared across KPC-Early, KPC-Late, and KPC-Late-Met groups<sup>©</sup>.</p>
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<p>Subpopulation compositions of T cells and B cells in primary tumors and liver metastases. (<b>A</b>–<b>C</b>) T cells and B cells from primary tumors and liver metastases are stratified into indicated subclusters in UMAP plot (<b>A</b>) based on the various expression profiles of signature genes shown in dot plot (<b>B</b>). The temporal alteration of T cell and B cell compositions are compared across KPC-Early, KPC-Late, and KPC-Late-Met groups (<b>C</b>). (<b>D</b>) The abundance (%) of indicated T and B cell subpopulations across KPC-Early, KPC-Late, and KPC-Late-Met groups.</p>
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<p>Distinct compositions of myeloid cells and dendritic cells in liver metastases. (<b>A</b>–<b>C</b>) Myeloid cells and dendritic cells (DCs) from primary tumors and liver metastases are characterized in UMAP plot (<b>A</b>) and compared across KPC-Early, KPC-Late, and KPC-Late-Met groups (<b>B</b>). The signature genes of myeloid cells and DCs in primary tumors and liver metastases are shown in dot plot (<b>C</b>). (<b>D</b>) The expression profiles of indicated signature genes of myeloid cell subpopulations in primary tumors and liver metastases are shown in UMAP plot.</p>
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<p>The similarity and difference of granulocyte/neutrophil subclusters across primary tumors, liver metastases, and normal bone marrow. (<b>A</b>,<b>B</b>) Cross-comparison of scRNA-seq datasets of KPC-Early, KPC-Late, and KPC-Late-Met groups compared with normal bone marrow of background-matched healthy mice (<span class="html-italic">n</span> = 2; total cell number 2241), as published by previous datasets (GSE184360). The major cell clusters were defined using the same threshold used in <a href="#cancers-15-02396-f001" class="html-fig">Figure 1</a>, as shown in UMAP plot (<b>A</b>). The cell population compositions are compared across KPC-Early, KPC-Late, KPC-Late-Met, and bone marrow groups (<b>B</b>). (<b>C</b>,<b>D</b>) Expression profile of indicated marker genes among defined granulocyte/neutrophil subpopulations is shown in dot plot with the normalized expression levels of indicated signature genes (<b>C</b>). Granulocyte/neutrophil subpopulations from primary tumors, liver metastases, and normal bone marrow are characterized in UMAP plot and compared across KPC-Early, KPC-Late, KPC-Late-Met, and bone marrow groups (<b>D</b>). G-MDSC, granulocytic myeloid-derived suppressor cell; Gran-Mo progenitor, granulocyte-monocyte progenitor cell.</p>
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11 pages, 575 KiB  
Article
Lung Adenocarcinoma Diagnosed at a Younger Age Is Associated with Advanced Stage, Female Sex, and Ever-Smoker Status, in Patients Treated with Lung Resection
by Tommaso A. Dragani, Thomas Muley, Marc A. Schneider, Sonja Kobinger, Martin Eichhorn, Hauke Winter, Hans Hoffmann, Mark Kriegsmann, Sara Noci, Matteo Incarbone, Davide Tosi, Sara Franzi and Francesca Colombo
Cancers 2023, 15(8), 2395; https://doi.org/10.3390/cancers15082395 - 21 Apr 2023
Cited by 1 | Viewed by 1422
Abstract
To date, the factors which affect the age at diagnosis of lung adenocarcinoma are not fully understood. In our study, we examined the relationships of age at diagnosis with smoking, pathological stage, sex, and year of diagnosis in a discovery (n = 1694) [...] Read more.
To date, the factors which affect the age at diagnosis of lung adenocarcinoma are not fully understood. In our study, we examined the relationships of age at diagnosis with smoking, pathological stage, sex, and year of diagnosis in a discovery (n = 1694) and validation (n = 1384) series of lung adenocarcinoma patients who had undergone pulmonary resection at hospitals in the Milan area and at Thoraxklinik (Heidelberg), respectively. In the discovery series, younger age at diagnosis was associated with ever-smoker status (OR = 1.5, p = 0.0035) and advanced stage (taking stage I as reference: stage III OR = 1.4, p = 0.0067; stage IV OR = 1.7, p = 0.0080), whereas older age at diagnosis was associated with male sex (OR = 0.57, p < 0.001). Analysis in the validation series confirmed the ever versus never smokers’ association (OR = 2.9, p < 0.001), the association with highest stages (stage III versus stage I OR = 1.4, p = 0.0066; stage IV versus stage I OR = 2.0, p = 0.0022), and the male versus female sex association (OR = 0.78, p = 0.032). These data suggest the role of smoking in affecting the natural history of the disease. Moreover, aggressive tumours seem to have shorter latency from initiation to clinical detection. Finally, younger age at diagnosis is associated with the female sex, suggesting that hormonal status of young women confers risk to develop lung adenocarcinoma. Overall, this study provided novel findings on the mechanisms underlying age at diagnosis of lung adenocarcinoma. Full article
(This article belongs to the Special Issue World Lung Cancer Awareness Month)
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<p>Distributions of age at diagnosis (upper panel) and year of diagnosis (lower panel) in the discovery (<b>A</b>,<b>C</b>) and validation (<b>B</b>,<b>D</b>) series.</p>
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10 pages, 671 KiB  
Article
Characterization of Tumor and Immune Tumor Microenvironment of Primary Tumors and Metastatic Sites in Advanced Renal Cell Carcinoma Patients Based on Response to Nivolumab Immunotherapy: Preliminary Results from the Meet-URO 18 Study
by Sara Elena Rebuzzi, Matteo Brunelli, Francesca Galuppini, Valerio Gaetano Vellone, Alessio Signori, Fabio Catalano, Alessandra Damassi, Gabriele Gaggero, Pasquale Rescigno, Marco Maruzzo, Sara Merler, Francesca Vignani, Alessia Cavo, Umberto Basso, Michele Milella, Olimpia Panepinto, Manlio Mencoboni, Marta Sbaraglia, Angelo Paolo Dei Tos, Veronica Murianni, Malvina Cremante, Miguel Angel Llaja Obispo, Michele Maffezzoli, Giuseppe Luigi Banna, Sebastiano Buti and Giuseppe Fornariniadd Show full author list remove Hide full author list
Cancers 2023, 15(8), 2394; https://doi.org/10.3390/cancers15082394 - 21 Apr 2023
Cited by 3 | Viewed by 1919
Abstract
Background: Prognostic and predictive factors for patients with metastatic renal cell carcinoma (mRCC) treated with immunotherapy are highly warranted, and the immune tumor microenvironment (I-TME) is under investigation. Methods: The Meet-URO 18 was a multicentric retrospective study assessing the I-TME in mRCC patients [...] Read more.
Background: Prognostic and predictive factors for patients with metastatic renal cell carcinoma (mRCC) treated with immunotherapy are highly warranted, and the immune tumor microenvironment (I-TME) is under investigation. Methods: The Meet-URO 18 was a multicentric retrospective study assessing the I-TME in mRCC patients treated with ≥2nd-line nivolumab, dichotomized into responders and non-responders according to progression-free survival (≥12 months and ≤3 months, respectively). The primary objective was to identify differential immunohistochemical (IHC) patterns between the two groups. Lymphocyte infiltration and the expressions of different proteins on tumor cells (CD56, CD15, CD68, and ph-mTOR) were analyzed. The expression of PD-L1 was also assessed. Results: A total of 116 tumor tissue samples from 84 patients (59% were primary tumors and 41% were metastases) were evaluated. Samples from responders (N = 55) were significantly associated with lower expression of CD4+ T lymphocytes and higher levels of ph-mTOR and CD56+ compared with samples from non-responders (N = 61). Responders also showed a higher CD3+ expression (p = 0.059) and CD8+/CD4+ ratio (p = 0.084). Non-responders were significantly associated with a higher percentage of clear cell histology and grading. Conclusions: Differential IHC patterns between the tumors in patients who were responders and non-responders to nivolumab were identified. Further investigation with genomic analyses is planned. Full article
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<p>IHC assessment of CD4+ T lymphocytes and CD56 and ph-mTOR in TCs. Representative hematoxylin and eosin staining of clear cell renal cell carcinoma (<b>A</b>). CD4 (<b>B</b>,<b>C</b>), CD56 (<b>D</b>,<b>E</b>), and ph-mTOR (<b>F</b>,<b>G</b>) expression between <span class="html-italic">responders</span> (<b>B</b>,<b>D</b>,<b>F</b>) and <span class="html-italic">non-responders</span> (<b>C</b>,<b>E</b>,<b>G</b>).</p>
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25 pages, 410 KiB  
Review
Triple-Negative Breast Cancer: Basic Biology and Immuno-Oncolytic Viruses
by Michael L. Monaco, Omer A. Idris and Karim Essani
Cancers 2023, 15(8), 2393; https://doi.org/10.3390/cancers15082393 - 21 Apr 2023
Cited by 5 | Viewed by 3588
Abstract
Triple-negative breast cancer (TNBC) is the most lethal subtype of breast cancer. TNBC diagnoses account for approximately one-fifth of all breast cancer cases globally. The lack of receptors for estrogen, progesterone, and human epidermal growth factor 2 (HER-2, CD340) results in a lack [...] Read more.
Triple-negative breast cancer (TNBC) is the most lethal subtype of breast cancer. TNBC diagnoses account for approximately one-fifth of all breast cancer cases globally. The lack of receptors for estrogen, progesterone, and human epidermal growth factor 2 (HER-2, CD340) results in a lack of available molecular-based therapeutics. This increases the difficulty of treatment and leaves more traditional as well as toxic therapies as the only available standards of care in many cases. Recurrence is an additional serious problem, contributing substantially to its higher mortality rate as compared to other breast cancers. Tumor heterogeneity also poses a large obstacle to treatment approaches. No driver of tumor development has been identified for TNBC, and large variations in mutational burden between tumors have been described previously. Here, we describe the biology of six different subtypes of TNBC, based on differential gene expression. Subtype differences can have a large impact on metastatic potential and resistance to treatment. Emerging antibody-based therapeutics, such as immune checkpoint inhibitors, have available targets for small subsets of TNBC patients, leading to partial responses and relatively low overall efficacy. Immuno-oncolytic viruses (OVs) have recently become significant in the pursuit of effective treatments for TNBC. OVs generally share the ability to ignore the heterogeneous nature of TNBC cells and allow infection throughout a treated tumor. Recent genetic engineering has allowed for the enhancement of efficacy against certain tumor types while avoiding the most common side effects in non-cancerous tissues. In this review, TNBC is described in order to address the challenges it presents to potential treatments. The OVs currently described preclinically and in various stages of clinical trials are also summarized, as are their strategies to enhance therapeutic potential. Full article
(This article belongs to the Special Issue Systems Biology of Tumor Immune Microenvironment and Immuno-Oncology)
10 pages, 1346 KiB  
Article
Analysis of Local Recurrence Risk in Ductal Carcinoma In Situ and External Validation of the Memorial Sloan Kettering Cancer Center Nomogram
by Gabriela Oses, Eduard Mension, Claudia Pumarola, Helena Castillo, León Francesc, Inés Torras, Isaac Cebrecos, Xavier Caparrós, Sergi Ganau, Belén Ubeda, Xavier Bargallo, Blanca González, Esther Sanfeliu, Sergi Vidal-Sicart, Reinaldo Moreno, Montserrat Muñoz, Gorane Santamaría and Meritxell Mollà
Cancers 2023, 15(8), 2392; https://doi.org/10.3390/cancers15082392 - 21 Apr 2023
Cited by 3 | Viewed by 2507
Abstract
Background: Adjuvant radiotherapy and hormonotherapy after breast-conserving surgery (BCS) in ductal carcinoma in situ (DCIS) have been shown to reduce the risk of local recurrence. To predict the risk of ipsilateral breast tumor relapse (IBTR) after BCS, the Memorial Sloan Kettering Cancer Center [...] Read more.
Background: Adjuvant radiotherapy and hormonotherapy after breast-conserving surgery (BCS) in ductal carcinoma in situ (DCIS) have been shown to reduce the risk of local recurrence. To predict the risk of ipsilateral breast tumor relapse (IBTR) after BCS, the Memorial Sloan Kettering Cancer Center (MSKCC) developed a nomogram to analyze local recurrence (LR) risk in our cohort and to assess its external validation. Methods: A historical cohort study using data from 296 patients treated for DCIS at the Hospital Clínic of Barcelona was carried out. Patients who had had a mastectomy were excluded from the analysis. Results: The mean age was 58 years (42–75), and the median follow-up time was 10.64 years. The overall local relapse rate was 13.04% (27 patients) during the study period. Actuarial 5- and 10-year IBTR rates were 5.8 and 12.9%, respectively. The external validation of the MSKCC nomogram was performed using a multivariate logistic regression analysis on a total of 207 patients, which did not reach statistical significance in the studied population for predicting LR (p = 0.10). The expression of estrogen receptors was significantly associated with a decreased risk of LR (OR: 0.25; p = 0.004). Conclusions: In our series, the LR rate was 13.4%, which was in accordance with the published series. The MSKCC nomogram did not accurately predict the IBTR in this Spanish cohort of patients treated for DCIS (p = 0.10). Full article
(This article belongs to the Special Issue Medical Complications and Supportive Care in Patients with Cancer)
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<p>Historical cohort flowchart.</p>
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11 pages, 288 KiB  
Article
Robotic versus Video-Assisted Thoracic Surgery for Lung Cancer: Short-Term Outcomes of a Propensity Matched Analysis
by Savvas Lampridis, Alessandro Maraschi, Corinne Le Reun, Tom Routledge and Andrea Billè
Cancers 2023, 15(8), 2391; https://doi.org/10.3390/cancers15082391 - 21 Apr 2023
Cited by 5 | Viewed by 1971
Abstract
Robot-assisted thoracic surgery (RATS) has gained popularity for the treatment of lung cancer, but its quality outcome measures are still being evaluated. The purpose of this study was to compare the perioperative outcomes of lung cancer resection using RATS versus video-assisted thoracic surgery [...] Read more.
Robot-assisted thoracic surgery (RATS) has gained popularity for the treatment of lung cancer, but its quality outcome measures are still being evaluated. The purpose of this study was to compare the perioperative outcomes of lung cancer resection using RATS versus video-assisted thoracic surgery (VATS). To achieve this aim, we conducted a retrospective analysis of consecutive patients who underwent lung cancer surgery between July 2015 and December 2020. A propensity-matched analysis was performed based on patients’ performance status, forced expiratory volume in 1 s% of predicted, diffusing capacity of the lungs for carbon monoxide% of predicted, and surgical procedure (lobectomy or segmentectomy). Following propensity matching, a total of 613 patients were included in the analysis, of which 328 underwent RATS, and 285 underwent VATS, with satisfactory performance indicators. The results of the analysis indicated that RATS had a significantly longer operating time than VATS (132.4 ± 37.3 versus 122.4 ± 27.7 min; mean difference of 10 min 95% CI [confidence interval], 4.2 to 15.9 min; p = 0.001). On the other hand, VATS had a significantly higher estimated blood loss compared to RATS (169.7 ± 237.2 versus 82.2 ± 195.4 mL; mean difference of 87.5 mL; 95% CI, 48.1 to 126.8 mL; p < 0.001). However, there were no significant differences between the groups in terms of the duration of chest tubes, length of hospital stay, low- and high-grade complications, as well as readmissions and mortality within 30 days after surgery. Moreover, the number of dissected lymph-node stations was significantly higher with VATS than RATS (5.9 ± 1.5 versus 4.8 ± 2.2; mean difference of 1.2; 95% CI, 0.8 to 1.5; p = 0.001). Nonetheless, the percentage of patients who were upstaged after histopathological analysis of the resected lymph nodes was similar between the two groups. In conclusion, RATS and VATS yielded comparable results for most of the short-term outcomes assessed. Further research is needed to validate the implementation of RATS and identify its potential benefits over VATS. Full article
35 pages, 1850 KiB  
Review
Reviewing the Prospective Pharmacological Potential of Isothiocyanates in Fight against Female-Specific Cancers
by Shoaib Shoaib, Farheen Badrealam Khan, Meshari A. Alsharif, M. Shaheer Malik, Saleh A. Ahmed, Yahya F. Jamous, Shahab Uddin, Ching Siang Tan, Chrismawan Ardianto, Saba Tufail, Long Chiau Ming, Nabiha Yusuf and Najmul Islam
Cancers 2023, 15(8), 2390; https://doi.org/10.3390/cancers15082390 - 20 Apr 2023
Cited by 5 | Viewed by 3330
Abstract
Gynecological cancers are the most commonly diagnosed malignancies in females worldwide. Despite the advancement of diagnostic tools as well as the availability of various therapeutic interventions, the incidence and mortality of female-specific cancers is still a life-threatening issue, prevailing as one of the [...] Read more.
Gynecological cancers are the most commonly diagnosed malignancies in females worldwide. Despite the advancement of diagnostic tools as well as the availability of various therapeutic interventions, the incidence and mortality of female-specific cancers is still a life-threatening issue, prevailing as one of the major health problems worldwide. Lately, alternative medicines have garnered immense attention as a therapeutic intervention against various types of cancers, seemingly because of their safety profiles and enhanced effectiveness. Isothiocyanates (ITCs), specifically sulforaphane, benzyl isothiocyanate, and phenethyl isothiocyanate, have shown an intriguing potential to actively contribute to cancer cell growth inhibition, apoptosis induction, epigenetic alterations, and modulation of autophagy and cancer stem cells in female-specific cancers. Additionally, it has been shown that ITCs plausibly enhance the chemo-sensitization of many chemotherapeutic drugs. To this end, evidence has shown enhanced efficacy in combinatorial regimens with conventional chemotherapeutic drugs and/or other phytochemicals. Reckoning with these, herein, we discuss the advances in the knowledge regarding the aspects highlighting the molecular intricacies of ITCs in female-specific cancers. In addition, we have also argued regarding the potential of ITCs either as solitary treatment or in a combinatorial therapeutic regimen for the prevention and/or treatment of female-specific cancers. Hopefully, this review will open new horizons for consideration of ITCs in therapeutic interventions that would undoubtedly improve the prognosis of the female-specific cancer clientele. Considering all these, it is reasonable to state that a better understanding of these molecular intricacies will plausibly provide a facile opportunity for treating these female-specific cancers. Full article
(This article belongs to the Special Issue Advances in Anticancer Drugs and Pharmacotherapy of Cancer)
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<p>Representative figure highlighting the schematic illustration of the plausible mechanisms of action of ITCs against female-specific cancers. ITCs (SFN, BITC, and PEITC) effectively participate in inhibition of cell survival, migration, invasion, angiogenesis, and histone deacetylation, and lead to cell cycle arrest, apoptosis induction, and modulation of autophagy and cancer stem cells. The image was created in BioRender software (biorender.com).</p>
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18 pages, 1913 KiB  
Review
Inflammation-Driven Colorectal Cancer Associated with Colitis: From Pathogenesis to Changing Therapy
by Olga Maria Nardone, Irene Zammarchi, Giovanni Santacroce, Subrata Ghosh and Marietta Iacucci
Cancers 2023, 15(8), 2389; https://doi.org/10.3390/cancers15082389 - 20 Apr 2023
Cited by 22 | Viewed by 5379
Abstract
Patients affected by inflammatory bowel disease (IBD) have a two-fold higher risk of developing colorectal cancer (CRC) than the general population. IBD-related CRC follows a different genetic and molecular pathogenic pathway than sporadic CRC and can be considered a complication of chronic intestinal [...] Read more.
Patients affected by inflammatory bowel disease (IBD) have a two-fold higher risk of developing colorectal cancer (CRC) than the general population. IBD-related CRC follows a different genetic and molecular pathogenic pathway than sporadic CRC and can be considered a complication of chronic intestinal inflammation. Since inflammation is recognised as an independent risk factor for neoplastic progression, clinicians strive to modulate and control disease, often using potent therapy agents to achieve mucosal healing and decrease the risk of colorectal cancer in IBD patients. Improved therapeutic control of inflammation, combined with endoscopic advances and early detection of pre-cancerous lesions through surveillance programs, explains the lower incidence rate of IBD-related CRC. In addition, current research is increasingly focused on translating emerging and advanced knowledge in microbiome and metagenomics into personalised, early, and non-invasive CRC screening tools that guide organ-sparing therapy in IBD patients. This review aims to summarise the existing literature on IBD-associated CRC, focusing on new insights into the alteration of the intestinal barrier and the interactions with the gut microbiome as the initial promoter. In addition, the role of OMIC techniques for precision medicine and the impact of the available IBD therapeutic armamentarium on the evolution to CRC will be discussed. Full article
(This article belongs to the Special Issue Chronic Intestinal Inflammation and Cancers)
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<p><b>Pathogenic pathway of sporadic colorectal cancer and IBD-related colorectal cancer.</b> The figure shows the different molecular pathways related to sporadic and IBD-related colorectal cancer (CRC). The sporadic CRC prevails in the adenoma-to-carcinoma sequence, while the inflammation–dysplasia–carcinoma cascade characterises the colitis related-CRC. In addition, the main gene mutations determining the progression of the two tumour phenotypes are reported with emphasis on the earliest mutations in the two processes. Namely, these entail APC loss of function, the WNT-beta catenin pathway activation for sporadic CRC (see zoom circle at left), and p53 mutations with consequent impacts on cell cycle, DNA repair, and cell viability for IBD-related CRC (see zoom circle at right). Finally, high-definition white light endoscopic images and virtual chromoendoscopic images (obtained through the Narrow Band Imaging technology) are provided for each phenotype of tumours. Created with “Biorender.com”. <span class="html-italic">Abbreviations: CRC, colorectal cancer; IBD, inflammatory bowel disease</span>.</p>
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<p><b>Multi—OMICs and its impact on inflammatory bowel disease and colorectal cancer.</b> This figure schematically represents the main OMIC techniques available to date: genomics—the study of the genetic or epigenetic sequence information; transcriptomics—the evaluation of RNA transcripts; proteomics—the investigation of the structure and function of proteins; metabolomics—the identification and quantification of metabolites; metaomics—the application of the previously described techniques to the gut microbiome. The multiple and integrated application of these techniques, so-called multi-OMICs, will offer a great chance to fill knowledge gaps in inflammatory bowel disease (IBD) and colorectal cancer (CRC). In more detail, the application of multi-OMICs will provide (as specified in figure squares) the discovery of novel biological mechanisms below IBD and CRC pathogenesis, the detection of new clinically relevant biomarkers, the definition of integrated signatures able to stratify patients, and the enhancement of physician ability to establish disease prediction, establish a prognosis, and treat patients appropriately. Created with “Biorender.com”. <span class="html-italic">Abbreviations: CRC, colorectal cancer; IBD, inflammatory bowel disease</span>.</p>
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<p><b>Intestinal inflammation and evolution to cancer in IBD</b>. The impairment of the mucus layer and epithelial barrier, associated with dysbiosis, determines the inflammatory response, leading to IBD disease development and possible cancer evolution. Bile acids and small-chain fatty acids participate in initiating this process. In the lamina propria, dendritic cells and macrophages, after their interaction with intestinal microbes, determine the activation of innate immune cells through the release of numerous cytokines (neutrophils, eosinophils, etc.) and trigger the adaptative (Th1 and Th17) immune cells differentiation in mesenteric lymph nodes. Activated T cells, through a vascular homing mediated by the alfa4-beta7–MAdCAM-1 pathway, reach the intestinal lamina propria and spread the inflammatory process. The persistence of inflammation can lead to carcinogenesis and metastasis. Proteins involved in maintaining gut barrier function, such as intestinal fatty acid binding protein and tight junction proteins (shown in the dotted-line circle box in the upper left corner of the figure), have been proposed as potential biomarkers for cancer detection. Created with “Biorender.com”. <span class="html-italic">Abbreviations: E. coli, Escherichia coli; ETBF, Enterotoxigenic Bacteroides fragilis; iFABP, intestinal fatty acid binding protein; IFN, interferon; IL, interleukin; JAM, junctional adhesion molecule; MAdCAM, mucosal vascular addressin cell adhesion molecule; pks+, polyketide synthase productor; SCFA, small chain fatty acid; TNF, tumour necrosis factor</span>.</p>
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13 pages, 481 KiB  
Review
A Historical Overview on the Role of Hepatitis B and C Viruses as Aetiological Factors for Hepatocellular Carcinoma
by Tommaso Stroffolini and Giacomo Stroffolini
Cancers 2023, 15(8), 2388; https://doi.org/10.3390/cancers15082388 - 20 Apr 2023
Cited by 13 | Viewed by 3083
Abstract
Hepatitis B virus (HBV) and hepatitis C virus (HCV) are the leading cause of hepatocellular carcinoma (HCC) worldwide. Currently, HBV-related HCC predominates in Sub-Saharan Africa and South-East-Asia, while HCV-related HCC predominates in northern Africa and in the western world. Liver cirrhosis is the [...] Read more.
Hepatitis B virus (HBV) and hepatitis C virus (HCV) are the leading cause of hepatocellular carcinoma (HCC) worldwide. Currently, HBV-related HCC predominates in Sub-Saharan Africa and South-East-Asia, while HCV-related HCC predominates in northern Africa and in the western world. Liver cirrhosis is the underlying condition in most HBV cases and in nearly all HCV cases. Several cofactors, viral and non-viral, play a role in the progression toward HCC: dual HBV/HCV infection, HDV, HIV, alcohol intake, smoking, diabetes mellitus, obesity, and NAFLD/NASH. HBV vaccine is effective in preventing both infection and HCC; antiviral drugs may suppress HBV replication and eradicate HCV infection, halting progression to HCC. Inequalities exist between high- and low-income countries with respect to vaccine availability and access to antivirals. These factors represent barriers to the control of HCC incidence. Lack of an effective vaccine against HCV is also a serious barrier to HCV elimination and HCC prevention. The most crucial steps and knowledge that have arisen over time on the association between the two major hepatotropic viruses and HCC are discussed in this historical review. Full article
(This article belongs to the Special Issue Viruses in Cancer Etiology)
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<p>Temporal trends of the proportion (%) of anti-HCV positivity and hepatitis viruses negativity among HCC patients in Italy, 1996–2014. Adapted from Reference 68. (X<sup>2</sup> for linear trend = <span class="html-italic">p</span> &lt; 0.001).</p>
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15 pages, 10500 KiB  
Article
Biomarkers of Tumor Heterogeneity in Glioblastoma Multiforme Cohort of TCGA
by Garrett Winkelmaier, Brandon Koch, Skylar Bogardus, Alexander D. Borowsky and Bahram Parvin
Cancers 2023, 15(8), 2387; https://doi.org/10.3390/cancers15082387 - 20 Apr 2023
Cited by 1 | Viewed by 2389
Abstract
Tumor Whole Slide Images (WSI) are often heterogeneous, which hinders the discovery of biomarkers in the presence of confounding clinical factors. In this study, we present a pipeline for identifying biomarkers from the Glioblastoma Multiforme (GBM) cohort of WSIs from TCGA archive. The [...] Read more.
Tumor Whole Slide Images (WSI) are often heterogeneous, which hinders the discovery of biomarkers in the presence of confounding clinical factors. In this study, we present a pipeline for identifying biomarkers from the Glioblastoma Multiforme (GBM) cohort of WSIs from TCGA archive. The GBM cohort endures many technical artifacts while the discovery of GBM biomarkers is challenged because “age” is the single most confounding factor for predicting outcomes. The proposed approach relies on interpretable features (e.g., nuclear morphometric indices), effective similarity metrics for heterogeneity analysis, and robust statistics for identifying biomarkers. The pipeline first removes artifacts (e.g., pen marks) and partitions each WSI into patches for nuclear segmentation via an extended U-Net for subsequent quantitative representation. Given the variations in fixation and staining that can artificially modulate hematoxylin optical density (HOD), we extended Navab’s Lab method to normalize images and reduce the impact of batch effects. The heterogeneity of each WSI is then represented either as probability density functions (PDF) per patient or as the composition of a dictionary predicted from the entire cohort of WSIs. For PDF- or dictionary-based methods, morphometric subtypes are constructed based on distances computed from optimal transport and linkage analysis or consensus clustering with Euclidean distances, respectively. For each inferred subtype, Kaplan–Meier and/or the Cox regression model are used to regress the survival time. Since age is the single most important confounder for predicting survival in GBM and there is an observed violation of the proportionality assumption in the Cox model, we use both age and age-squared coupled with the Likelihood ratio test and forest plots for evaluating competing statistics. Next, the PDF- and dictionary-based methods are combined to identify biomarkers that are predictive of survival. The combined model has the advantage of integrating global (e.g., cohort scale) and local (e.g., patient scale) attributes of morphometric heterogeneity, coupled with robust statistics, to reveal stable biomarkers. The results indicate that, after normalization of the GBM cohort, mean HOD, eccentricity, and cellularity are predictive of survival. Finally, we also stratified the GBM cohort as a function of EGFR expression and published genomic subtypes to reveal genomic-dependent morphometric biomarkers. Full article
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<p>Eash WSI is represented in the context of tumor heterogeneity for biomarker discovery: (<b>a</b>) a WSI is partitioned to patches of 224-by-224, where each patch is analyzed for pen marks or other aberrations; (<b>b</b>) nuclei are segmented in patches; (<b>c</b>) H&amp;E optical density is normalized in each patch; (<b>d</b>) nuclei organization is quantified in each patch; (<b>e</b>,<b>f</b>) computed indices from nuclei and their organizations are used for the dictionary- and PDF-based representations. (<b>g</b>) Predictive morphometric indices of survival are identified.</p>
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<p>H&amp;E stain is heterogeneous between patients. Two patches from two WSIs indicate a diverse staining signature. They are normalized for quantifying HOD and visualized in the RGB space.</p>
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<p>Dictionary-based learning identified two and three subpopulation (e.g., clusters) of patients based on cellularity and eccentricity indices, respectively. (top row): Computed similarity matrices; (middle row) the cumulative Density Function (CDF) of similarity matrices shows the quality of the number of clusters for each index (e.g., a flat horizontal line indicates a low number of misclassified samples between clusters). (bottom row) Silhouette plots of 800,000 randomly sampled nuclei show the similarity of patients within a cluster (e.g., a silhouette score less than 1) and a red dashed indicating the average silhouette score.</p>
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<p>Representative patches showing low, medium, and high eccentricities corresponding to clusters 1, 2, and 3 from the dictionary-based method.</p>
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<p>Representative patches showing low, and high cellularities corresponding to clusters 1 and 2 from the dictionary-method.</p>
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<p>Steps in the dictionary-based method for representing heterogeneity: (<b>a</b>) each WSI is partitioned into patches; (<b>b</b>) each patch is quantified in terms of nuclear indices and organization; (<b>c</b>) each computed index (e.g., HOD content, nuclear size) is aggregated across the entire cohort for dictionary-based learning (e.g., alphabets, which are four in this example); and (<b>d</b>) each WSI is then represented as a composition of learned alphabets.</p>
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<p>Optimal transport identifies subpopulations of patients, based on PDF representation, for survival analysis. Top row: similarity matrices identified by linkage analysis; Bottom row: Kaplan–Meier plots, hazard ratio, and computed <span class="html-italic">p</span>-values for three computed morphometric indices of nuclear size, solidity, and total chromatin.</p>
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<p>The forest plot indicates biomarkers associated with the subpopulation at risk using the PDF-based representation without any genomic preconditioning. The asterisks **, ***, and **** denote the number of stratifications per morphometric index.</p>
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<p>Using the PDF method, pre-conditioned on the classical subtype, the forest plot indicates the subpopulation at risk. The asterisks **, ***, and **** denote the number of stratifications per morphometric index.</p>
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<p>Using the PDF method, pre-conditioned on a high EGFR expression, the forest plot indicates the subpopulation at risk. For example, Area cluster two has an 52% decreased risk of death compared to Area cluster zero. The asterisks **** denote the number of stratifications per morphometric index.</p>
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16 pages, 709 KiB  
Systematic Review
Plasma Device Functions and Tissue Effects in the Female Pelvis—A Systematic Review
by Nick J. van de Berg, Gatske M. Nieuwenhuyzen-de Boer, Xu Shan Gao, L. Lucia Rijstenberg and Heleen J. van Beekhuizen
Cancers 2023, 15(8), 2386; https://doi.org/10.3390/cancers15082386 - 20 Apr 2023
Viewed by 2007
Abstract
Medical use of (non-)thermal plasmas is an emerging field in gynaecology. However, data on plasma energy dispersion remain limited. This systematic review presents an overview of plasma devices, fields of effective application, and impact of use factors and device settings on tissues in [...] Read more.
Medical use of (non-)thermal plasmas is an emerging field in gynaecology. However, data on plasma energy dispersion remain limited. This systematic review presents an overview of plasma devices, fields of effective application, and impact of use factors and device settings on tissues in the female pelvis, including the uterus, ovaries, cervix, vagina, vulva, colon, omentum, mesenterium, and peritoneum. A search of the literature was performed on 4 January 2023 in the Medline Ovid, Embase, Cochrane, Web of Science, and Google Scholar databases. Devices were classified as plasma-assisted electrosurgery (ES) using electrothermal energy, neutral argon plasma (NAP) using kinetic particle energy, or cold atmospheric plasma (CAP) using non-thermal biochemical reactions. In total, 8958 articles were identified, of which 310 were scanned, and 14 were included due to containing quantitative data on depths or volumes of tissues reached. Plasma-assisted ES devices produce a thermal effects depth of <2.4 mm. In turn, NAP effects remained superficial, <1.0 mm. So far, the depth and uniformity of CAP effects are insufficiently understood. These data are crucial to achieve complete treatment, reduce recurrence, and limit damage to healthy tissues (e.g., prevent perforations or preserve parenchyma). Upcoming and potentially high-gain applications are discussed, and deficits in current evidence are identified. Full article
(This article belongs to the Special Issue Gynecologic Oncology: Prevention, Screening and Treatment Innovations)
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<p>PRISMA flowchart indicating the selection of articles for this systematic review.</p>
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29 pages, 1599 KiB  
Review
The Ubiquitin–Proteasome System in Tumor Metabolism
by Jie Wang, Yuandi Xiang, Mengqi Fan, Shizhen Fang and Qingquan Hua
Cancers 2023, 15(8), 2385; https://doi.org/10.3390/cancers15082385 - 20 Apr 2023
Cited by 7 | Viewed by 3472
Abstract
Metabolic reprogramming, which is considered a hallmark of cancer, can maintain the homeostasis of the tumor environment and promote the proliferation, survival, and metastasis of cancer cells. For instance, increased glucose uptake and high glucose consumption, known as the “Warburg effect,” play an [...] Read more.
Metabolic reprogramming, which is considered a hallmark of cancer, can maintain the homeostasis of the tumor environment and promote the proliferation, survival, and metastasis of cancer cells. For instance, increased glucose uptake and high glucose consumption, known as the “Warburg effect,” play an essential part in tumor metabolic reprogramming. In addition, fatty acids are harnessed to satisfy the increased requirement for the phospholipid components of biological membranes and energy. Moreover, the anabolism/catabolism of amino acids, such as glutamine, cystine, and serine, provides nitrogen donors for biosynthesis processes, development of the tumor inflammatory environment, and signal transduction. The ubiquitin–proteasome system (UPS) has been widely reported to be involved in various cellular biological activities. A potential role of UPS in the metabolic regulation of tumor cells has also been reported, but the specific regulatory mechanism has not been elucidated. Here, we review the role of ubiquitination and deubiquitination modification on major metabolic enzymes and important signaling pathways in tumor metabolism to inspire new strategies for the clinical treatment of cancer. Full article
(This article belongs to the Special Issue Cancer Metabolomic Analysis)
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<p>The process of the ubiquitin–proteasome system. Ubiquitination conjugation is initiated by activating enzyme E1, with ATP-dependent hydrolysis. Then, ubiquitin is transferred to E2, and E3 ligase cooperates with the E2 ligase ubiquitin complex onto the target substrates; the ubiquitins can covalently attach to each other by forming various linear or branched ubiquitin chains on the target substrates, forming mono-ubiquitination, multi-ubiquitination, and poly-ubiquitination ways of modification on substrates. Among them, the mono-ubiquitinated proteins cannot be degraded by proteasomes, and the substrates with at least four ubiquitins attached can be degraded by proteasomes. Then, the labelled substrates are recognized by the 26S proteasome and degraded. Deubiquitination enzymes (DUBs) can deconjugate ubiquitin from substrates to stabilize the protein levels of substrates and keep the balance of the ubiquitin pool in the human body. Ub, ubiquitin; DUB: deubiquitination enzymes.</p>
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<p>The ubiquitination and deubiquitination of the essential enzymes in tumor glucose metabolism and fatty acid metabolism. Glucose metabolism can produce large amounts of raw materials for the synthesis of many biological macromolecules for tumor cells, and fatty acid metabolism contributes to the tumor cell membrane and transmission of secondary messengers. The ligands bind to cell surface receptors and initiate signal transduction cascades; essential enzymes of these two kinds of metabolism reprograming are highlighted in red, pyruvate is a bridge between them, and the ubiquitination enzyme (red) and DUB (blue) control the balance of key enzymes that regulate tumor cell proliferation and chemotherapy resistance as described in the text. Transcription factors mTOR, KRAS, HIF, and c-Myc regulate the tumor glucose and fatty acid metabolism. HK2, Hexokinase 2; PFK2, Phosphofructokinase 2; PKM2, Pyruvate kinase M2; Glucose-6-P, Glucose-6-phosphate; Fructose-6-P, fructose-6-phosphate; Fructose-1,6-2P,fructose-1,6-bisphosphate; 3PG, 3-phosphoglycerate; PKM2, Pyruvate kinase M2; PEP, phosphoenolpyruvate; LDH, lactate dehydrogenase; NADH, Nicotinamide Adenine Dinucleotide; Ribose-5-P, ribose-5-phosphate; ACC1, Acetyl-coenzyme A carboxylase 1; FASN, Fatty acid synthase; ACLY, ATP citrate lyase; PPARγ, Peroxisome proliferator-activated receptor gamma; α-KG, ketoglutarate; IDH2, isocitrate dehydrogenase2; Ac-CoA, acetyl-coenzyme A; TCA cycle, Tricarboxylic acid cycle.</p>
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<p>The ubiquitination and deubiquitination of the essential enzymes in tumor amino acid metabolism. “Glutamine addition” in tumor cells provides carbon and nitrogen to replenish the tricarboxylic acid cycle (TCA) and maintain mitochondrial ATP production. The essential enzymes of amino acid metabolism reprogramming are highlighted in blue. The ubiquitin enzymes (red) and DUBs (blue) negatively or positively regulate the activity of the key enzymes; among them, PHGDH, ASCT2, SLC7A11, and ASS1 were the frequently UPS-modified enzymes, and the glycolysis intermediate 3-PG can be used to the synthesis of serine. Transcription factors mTOR, KRAS, HIF, c-Myc, and YAP/TAZ regulate the tumor amino acid metabolism. GLS, glutaminase; GLUD, glutamate dehydrogenase; α-KG: α-ketoglutarate; 3-PG, 3-phosphoglycerate; OAA, oxaloacetate; GOT2; Glutamic-oxaloacetic transaminase 2; PHGDH,3-phosphoglycerate dehydrogenase; PSPH, phosphoserine phosphatase; ASS1, argininosuccinate synthase1; GSH, glutathione; GSSG, glutathione disulfide; ROS, reactive oxygen species; SAM, S-adenosylmethionine.</p>
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28 pages, 486 KiB  
Review
Locoregional Therapy for Intrahepatic Cholangiocarcinoma
by Mackenzie Owen, Mina S. Makary and Eliza W. Beal
Cancers 2023, 15(8), 2384; https://doi.org/10.3390/cancers15082384 - 20 Apr 2023
Cited by 15 | Viewed by 2511
Abstract
Intrahepatic cholangiocarcinoma (ICC) has a poor prognosis, and surgical resection (SR) offers the only potential for cure. Unfortunately, only a small proportion of patients are eligible for resection due to locally advanced or metastatic disease. Locoregional therapies (LRT) are often used in unresectable [...] Read more.
Intrahepatic cholangiocarcinoma (ICC) has a poor prognosis, and surgical resection (SR) offers the only potential for cure. Unfortunately, only a small proportion of patients are eligible for resection due to locally advanced or metastatic disease. Locoregional therapies (LRT) are often used in unresectable liver-only or liver-dominant ICC. This review explores the role of these therapies in the treatment of ICC, including radiofrequency ablation (RFA), microwave ablation (MWA), transarterial chemoembolization (TACE), transarterial radioembolization (TARE), external beam radiotherapy (EBRT), stereotactic body radiotherapy (SBRT), hepatic arterial infusion (HAI) of chemotherapy, irreversible electroporation (IE), and brachytherapy. A search of the current literature was performed to examine types of LRT currently used in the treatment of ICC. We examined patient selection, technique, and outcomes of each type. Overall, LRTs are well-tolerated in the treatment of ICC and are effective in improving overall survival (OS) in this patient population. Further studies are needed to reduce bias from heterogenous patient populations and small sample sizes, as well as to determine whether certain LRTs are superior to others and to examine optimal treatment selection. Full article
(This article belongs to the Special Issue New Insights in Biliary Tract Cancers Therapy)
27 pages, 1326 KiB  
Review
Immunotherapy for Peritoneal Carcinomatosis: Challenges and Prospective Outcomes
by Mefotse Saha Cyrelle Ornella, Narayanasamy Badrinath, Kyeong-Ae Kim, Jung Hee Kim, Euna Cho, Tae-Ho Hwang and Jae-Joon Kim
Cancers 2023, 15(8), 2383; https://doi.org/10.3390/cancers15082383 - 20 Apr 2023
Cited by 9 | Viewed by 6960
Abstract
Peritoneal metastasis, also known as peritoneal carcinomatosis (PC), is a refractory cancer that is typically resistant to conventional therapies. The typical treatment for PC is a combination of cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC). Recently, research in this area has seen [...] Read more.
Peritoneal metastasis, also known as peritoneal carcinomatosis (PC), is a refractory cancer that is typically resistant to conventional therapies. The typical treatment for PC is a combination of cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC). Recently, research in this area has seen significant advances, particularly in immunotherapy as an alternative therapy for PC, which is very encouraging. Catumaxomab is a trifunctional antibody intraperitoneal (IP) immunotherapy authorized in Europe that can be used to diminish malignant ascites by targeting EpCAM. Intraperitoneal (IP) immunotherapy breaks immunological tolerance to treat peritoneal illness. Increasing T-cell responses and vaccination against tumor-associated antigens are two methods of treatment. CAR-T cells, vaccine-based therapeutics, dendritic cells (DCs) in combination with pro-inflammatory cytokines and NKs, adoptive cell transfer, and immune checkpoint inhibitors are promising treatments for PC. Carcinoembryonic antigen-expressing tumors are suppressed by IP administration of CAR-T cells. This reaction was strengthened by anti-PD-L1 or anti-Gr1. When paired with CD137 co-stimulatory signaling, CAR-T cells for folate receptor cancers made it easier for T-cell tumors to find their way to and stay alive in the body. Full article
(This article belongs to the Section Cancer Immunology and Immunotherapy)
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<p>The development of peritoneal carcinomatosis: (<b>a</b>) The cancer cells dissociate from the main tumor and (<b>b</b>) penetrate the epithelial tissue. Cancer cells that have exfoliated invade the underlying basal lamina and stroma. (<b>c</b>) Stromal cancer cells defy apoptosis and entice growth substances that stimulate proliferation and angiogenesis. (<b>d</b>) After breaking through the endothelial cells that border the vessels, cancer cells spread to other parts of the body. (<b>e</b>) Blood vessels in close proximity to a tumor facilitate the development of distant metastases. (<b>f</b>) At a future metastatic site, cancer cells adhere to and invade the endothelium to form a new metastasis.</p>
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<p>Cells in the ascites tumor microenvironment (TME). The peritoneal carcinomatosis microenvironment is formed of malignant ascites and solid tumor tissue. Under the influence of the ascites, which exchange O2 and nutrients with the circulatory system, cells actively communicate with each other through molecules they produce (cytokines, chemokines, DAMPs, etc.) and receptors they express (MHC, PD-1). The TME may re-polarize the same set of cells or move cell components to other locations. The growth or shrinkage of a tumor site is controlled by a complex network of cells and molecules in the TME.</p>
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14 pages, 1030 KiB  
Article
First- versus Third-Generation EGFR Tyrosine Kinase Inhibitors in EGFR-Mutated Non-Small Cell Lung Cancer Patients with Brain Metastases
by Vineeth Tatineni, Patrick J. O’Shea, Ahmad Ozair, Atulya A. Khosla, Shreya Saxena, Yasmeen Rauf, Xuefei Jia, Erin S. Murphy, Samuel T. Chao, John H. Suh, David M. Peereboom and Manmeet S. Ahluwalia
Cancers 2023, 15(8), 2382; https://doi.org/10.3390/cancers15082382 - 20 Apr 2023
Cited by 6 | Viewed by 2626
Abstract
Introduction: Up to 50% of non-small cell lung cancer (NSCLC) harbor EGFR alterations, the most common etiology behind brain metastases (BMs). First-generation EGFR-directed tyrosine kinase inhibitors (EGFR-TKI) are limited by blood-brain barrier penetration and T790M tumor mutations, wherein third-generation EGFR-TKIs, like Osimertinib, have [...] Read more.
Introduction: Up to 50% of non-small cell lung cancer (NSCLC) harbor EGFR alterations, the most common etiology behind brain metastases (BMs). First-generation EGFR-directed tyrosine kinase inhibitors (EGFR-TKI) are limited by blood-brain barrier penetration and T790M tumor mutations, wherein third-generation EGFR-TKIs, like Osimertinib, have shown greater activity. However, their efficacy has not been well-studied in later therapy lines in NSCLC patients with BMs (NSCLC-BM). We sought to compare outcomes of NSCLC-BM treated with either first- or third-generation EGFR-TKIs in first-line and 2nd-to-5th-line settings. Methods: A retrospective review of NSCLC-BM patients diagnosed during 2010–2019 at Cleveland Clinic, Ohio, US, a quaternary-care center, was performed and reported following ‘strengthening the reporting of observational studies in epidemiology’ (STROBE) guidelines. Data regarding socio-demographic, histopathological, molecular characteristics, and clinical outcomes were collected. Primary outcomes were median overall survival (mOS) and progression-free survival (mPFS). Multivariable Cox proportional hazards modeling and propensity score matching were utilized to adjust for confounders. Results: 239 NSCLC-BM patients with EGFR alterations were identified, of which 107 received EGFR-TKIs after diagnosis of BMs. 77.6% (83/107) received it as first-line treatment, and 30.8% (33/107) received it in later (2nd–5th) lines of therapy, with nine patients receiving it in both settings. 64 of 107 patients received first-generation (erlotinib/gefitinib) TKIs, with 53 receiving them in the first line setting and 13 receiving it in the 2nd–5th lines of therapy. 50 patients received Osimertinib as third-generation EGFR-TKI, 30 in first-line, and 20 in the 2nd–5th lines of therapy. Univariable analysis in first-line therapy demonstrated mOS of first- and third-generation EGFR-TKIs as 18.2 and 19.4 months, respectively (p = 0.57), while unadjusted mPFS of first- and third-generation EGFR-TKIs was 9.3 and 13.8 months, respectively (p = 0.14). In 2nd–5th line therapy, for first- and third-generation EGFR-TKIs, mOS was 17.3 and 11.9 months, (p = 0.19), while mPFS was 10.4 and 6.08 months, respectively (p = 0.41). After adjusting for age, performance status, presence of extracranial metastases, whole-brain radiotherapy, and presence of leptomeningeal metastases, hazard ratio (HR) for OS was 1.25 (95% CI 0.63–2.49, p = 0.52) for first-line therapy. Adjusted HR for mOS in 2nd-to-5th line therapy was 1.60 (95% CI 0.55–4.69, p = 0.39). Conclusions: No difference in survival was detected between first- and third-generation EGFR-TKIs in either first or 2nd-to-5th lines of therapy. Larger prospective studies are warranted reporting intracranial lesion size, EGFR alteration and expression levels in primary tumor and brain metastases, and response rates. Full article
(This article belongs to the Special Issue Updates on Molecular Targeted Therapies for CNS Tumors)
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<p>Flow diagram of the current study.</p>
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<p>Kaplan-Meier curves for overall survival, with results of first-line therapy in (<b>A</b>) and outcomes of later-line therapy in (<b>B</b>).</p>
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<p>Kaplan-Meier curves for progression-free survival, with results of first-line therapy in (<b>A</b>) and outcomes of later-line therapy in (<b>B</b>).</p>
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13 pages, 1069 KiB  
Review
Non-Invasive Imaging Modalities in Intravesical Murine Models of Bladder Cancer
by Sydney Relouw, George J. Dugbartey and Alp Sener
Cancers 2023, 15(8), 2381; https://doi.org/10.3390/cancers15082381 - 20 Apr 2023
Cited by 2 | Viewed by 1757
Abstract
Bladder cancer (BCa) is the sixth most prevalent cancer in men and seventeenth most prevalent cancer in women worldwide. Current treatment paradigms have limited therapeutic impact, suggesting an urgent need for the investigation of novel therapies. To best emulate the progression of human [...] Read more.
Bladder cancer (BCa) is the sixth most prevalent cancer in men and seventeenth most prevalent cancer in women worldwide. Current treatment paradigms have limited therapeutic impact, suggesting an urgent need for the investigation of novel therapies. To best emulate the progression of human BCa, a pre-clinical intravesical murine model is required in conjunction with existing non-invasive imaging modalities to detect and evaluate cancer progression. Non-invasive imaging modalities reduce the number of required experimental models while allowing for longitudinal studies of novel therapies to investigate long-term efficacy. In this review, we discuss the individual and multi-modal use of non-invasive imaging modalities; bioluminescence imaging (BLI), micro-ultrasound imaging (MUI), magnetic resonance imaging (MRI), and positron emission tomography (PET) in BCa evaluation. We also provide an update on the potential and the future directions of imaging modalities in relation to intravesical murine models of BCa. Full article
(This article belongs to the Special Issue Multidisciplinary Approaches in Bladder Cancer)
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<p>Bioluminescence imaging (BLI) method in an intravesical murine model of BCa, where a BCa cell line is transfected with a luciferase vector that is subsequently inoculated into the bladder wall of the murine model. The D-luciferin substrate is administered via intravascular or intraperitoneal injection 10–18 min prior to visualization to stimulate the reporter system. Visualization occurs using an in vivo imaging system that detects the emission of green light when luciferase converts D-luciferin to oxyluciferin. Figure prepared with BioRender (<a href="http://biorender.com" target="_blank">biorender.com</a>, accessed on 1 February 2023).</p>
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<p>Micro-ultrasound imaging (MUI) method in an intravesical model of BCa where the abdomen is shaved, depilatory cream is applied to remove fine hairs, and high viscosity ultrasound gel is utilized during imaging to enhance the image resolution. Subsequent studies administered microbubbles via intravenous injection prior to imaging for visualization and quantification of the superficial tumor vasculature. Figure prepared with BioRender (<a href="http://biorender.com" target="_blank">biorender.com</a>, accessed on 1 February 2023).</p>
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<p>Positron emission tomography (PET) method in an intravesical murine model of BCa in which EGFR-expressing BCa cells are inoculated into the mouse bladder wall. Antibodies are conjugated and radiolabeled producing [<sup>89</sup>Zr] Zr DFO-panitumumab, which was administered intravenously, and mice were imaged 72 h later. Figure prepared with BioRender (<a href="http://biorender.com" target="_blank">biorender.com</a>, accessed on 1 February 2023).</p>
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14 pages, 1235 KiB  
Article
Cyclooxygenase and Lipoxygenase Gene Expression in the Inflammogenesis of Colorectal Cancer: Correlated Expression of EGFR, JAK STAT and Src Genes, and a Natural Antisense Transcript, RP11-C67.2.2
by Brian M. Kennedy and Randall E. Harris
Cancers 2023, 15(8), 2380; https://doi.org/10.3390/cancers15082380 - 20 Apr 2023
Cited by 4 | Viewed by 2057
Abstract
We examined the expression of major inflammatory genes, cyclooxygenase-1, 2 (COX1, COX2), arachidonate-5-lipoxygenase (ALOX5), and arachidonate-5-lipoxygenase activating protein (ALOX5AP) among 469 tumor specimens of colorectal cancer in The Cancer Genome Atlas (TCGA). Among 411 specimens without mutations in mismatch repair (MMR) genes, the [...] Read more.
We examined the expression of major inflammatory genes, cyclooxygenase-1, 2 (COX1, COX2), arachidonate-5-lipoxygenase (ALOX5), and arachidonate-5-lipoxygenase activating protein (ALOX5AP) among 469 tumor specimens of colorectal cancer in The Cancer Genome Atlas (TCGA). Among 411 specimens without mutations in mismatch repair (MMR) genes, the mean expression of each of the inflammatory genes ranked above the 80th percentile, and the overall mean cyclooxygenase expression (COX1+COX2) ranked in the upper 99th percentile of all genes. Similar levels were observed for 58 cases with MMR mutations. Pearson correlation coefficients exceeding r = 0.70 were observed between COX and LOX mRNA levels with genes of major cell-signaling pathways involved in tumorigenesis (Src, JAK STAT, MAPK, PI3K). We observed a novel association (r = 0.78) between ALOX5 expression and a natural antisense transcript (NAT), RP11-67C2.2, a long non-coding mRNA gene, 462 base pairs in length that is located within the terminal intron of the ALOX5 gene on chromosome 10q11.21. Tumor-promoting genes highly correlated with the expression of COX1, COX2, ALOX5 and ALOX5AP are known to increase mitogenesis, mutagenesis, angiogenesis, cell survival, immunosuppression and metastasis in the inflammogenesis of colorectal cancer. These genes and the novel NAT, RP1167C2.2 are potential molecular targets for chemoprevention and therapy of colorectal cancer. Full article
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<p>Violin density plots of the genetic expression of COX1, COX2, ALOX5 and ALOX5AP in invasive colorectal cancer. Means and standard deviations are indicated by horizontal bars and box plots, respectively. Prostaglandin Synthetase-1, PTSG1 (Cyclooxygenase-1, COX1). Prostaglandin Synthetase-2, PTSG2 (Cyclooxygenase-2, COX2). Arachidonate 5-Lipoxygenase (ALOX5). Arachidonate 5-Lipoxygenase Activating Protein (ALOX5AP). RP11-67C2.2: Novel Natural Antisense Transcript Gene, RP11-67C2.2 nested within the terminal region of the ALOX5 gene on chromosome 10q11.21.</p>
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<p>Violin density plots of the expression of inflammation-correlated genes of the Src and JAK STAT signaling pathways. (<b>a</b>) Src Genes; (<b>b</b>) JAK STAT Genes.</p>
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<p>Violin density plots of the expression of EGFR and other inflammation-correlated tumor response genes.</p>
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<p>Inflammogenesis model of colorectal carcinogenesis. Genes and pathways in the model. Arachidonic Acid biosynthesis: Phospholipase A2: PLA2, Acyl-CoA synthetase: ACSLl; Prostaglandin biosynthesis: Cyclooxygenase-1, 2 (COX1, COX2), Leukotriene biosynthesis: ALOX5 arachidonate 5-lipoxygenase, RP 11 67C2.2 long noncoding natural antisense transcript of ALOX5, ALOX5AP (FLAP) arachidonate 5-lipoxygenase activating protein; Prostaglandin E receptors: PTGER1, PTGER2, PTGER3, PTGER4, PTGFR; Leukotriene receptors: LTB4R, CysLTR1, CysLTR2; Colony Stimulating Factor receptors: CSFR1, CSFR2B, CSFR3; Transforming Growth Factor: TGF; Janus Kinase Transduction and Transcription cell signaling: JAK STAT; Receptor Tyrosine Kinase: RTK; Epidermal Growth Factor Receptor: EGFR; Mitogen Activated Protein Kinase cell signaling: MAPK; Phosphoinositide 3 Kinase cell signaling: PI3K; Src Tyrosine Kinase cell signaling: Src; TEK Receptor Tyrosine Kinase: TEK; Oncostatin Tyrosine Kinase Membrane Receptor: OSMR; Interleukin 6: IL6; Interleukin 1B: IL1B; CXC Motif Chemokine Ligands 5 and 8: CXCL5, CXCL8; ATPase Phospholipid Transporting 8B2: ATP8B2; Disheveled Activator of Morphogenesis 1: DAAM1; Signaling Lymphocytic Activation Molecule Family 8: SLAMF8; Serglycin: SRGN; Bruton’s Tyrosine Kinase: BTK; Feline Gardner–Rasheed proto-oncogene: FGR; Hematopoietic Cytokinase: HCK; Lysosomal Activating Transmembrane Protein-5: LAPTM5; Carcinoembryonic antigen-related cell adhesion molecules: CEACAM 1, 5, 6; Mismatch Repair Genes: PMS2, MLH 1, 5, 6; Suppressor of Cytokine Signaling: SOCS3; Alpha 2 Macroglobulin (Protease Inhibitor): A2M; Death Associated Protein Kinase: DAPK1; Ras Associated Family: RAASF8.</p>
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14 pages, 4238 KiB  
Article
Non-Inflamed Tumor Microenvironment and Methylation/Downregulation of Antigen-Presenting Machineries in Cholangiocarcinoma
by Naoshi Nishida, Tomoko Aoki, Masahiro Morita, Hirokazu Chishina, Masahiro Takita, Hiroshi Ida, Satoru Hagiwara, Yasunori Minami, Kazuomi Ueshima and Masatoshi Kudo
Cancers 2023, 15(8), 2379; https://doi.org/10.3390/cancers15082379 - 20 Apr 2023
Cited by 8 | Viewed by 1839
Abstract
Cholangiocarcinoma (CCA) is a refractory cancer; a majority of CCAs represents a non-inflamed tumor phenotype that should be resistant to treatment, including immune checkpoint inhibitors (ICIs). In this study, we aimed to understand the molecular characteristics associated with non-inflamed CCAs. The genetic/epigenetic status [...] Read more.
Cholangiocarcinoma (CCA) is a refractory cancer; a majority of CCAs represents a non-inflamed tumor phenotype that should be resistant to treatment, including immune checkpoint inhibitors (ICIs). In this study, we aimed to understand the molecular characteristics associated with non-inflamed CCAs. The genetic/epigenetic status of 36 CCAs was obtained from the Cancer Genome Atlas (PanCancerAtlas). CCAs were classified based on immune class using hierarchical clustering analysis of gene expressions related to tumor-infiltrating lymphocytes. The associations between immune class and genetic/epigenetic events were analyzed. We found that the tumors with alterations in FGFR2 and IDH1/2 had a “non-inflamed” tumor phenotype. A significant association was observed between the non-inflamed group and the downregulation of genes involved in antigen presentation (p = 0.0015). The expression of antigen-presenting machineries was inversely correlated with their DNA methylation levels, where 33.3% of tumors had an upregulation/low-methylation pattern, and 66.7% of tumors had a downregulation/high-methylation pattern. All tumors in the “inflamed” group exhibited an upregulation/low-methylation pattern. In contrast, 24 of 30 tumors in the non-inflamed group represent the downregulation/high-methylation pattern (p = 0.0005). Methylation with downregulation of antigen-presenting machineries is associated with the “non-inflamed” tumor phenotype of CCAs. This evidence provides important insights for developing new strategies for treating CCA. Full article
(This article belongs to the Collection Primary Liver Cancer)
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<p>Hierarchical clustering analysis using z-scores of mRNA levels related to tumor-infiltrated lymphocytes. The color map (<span class="html-italic">red-gray-blue</span>): <span class="html-italic">red</span>, degree of increased mRNA expression; <span class="html-italic">blue</span>, degree of decreased mRNA expression. For clustering analysis, z-scores of mRNA levels of the following genes were used: CD2, CD3D, CD8A, CD8B, CD48, CD52, and CD53 as T-cell surface markers; FYB1, IFNG, LAPTM5, LCP2, PTPRC, and SLA as T-cell signaling and activation-related markers; CCL5, CXCL9, CXCL10, CXCL11, and CXCR4 as lymphocyte chemotactic markers; GZMA, GZMB, GZMK, GZMH, and GZMM as T-cell-related cytolytic factors; CTLA4, LAG3, TIGIT, CD274, PDCD1, and HAVCR4 as immune checkpoint molecules. Among the 36 cases, 6 (17%) formed a cluster and were considered to belong to the inflamed class because of the high expression of genes related to tumor-infiltrated lymphocytes. The remaining 30 cases were classified as non-inflamed. Of these, seventeen formed a cluster with low expression of these markers and were defined as non-inflamed A; thirteen cases with a mild expression of markers were defined as non-inflamed B.</p>
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<p>Correlation between methylation level and expression of the genes involved in antigen-presenting machineries. Negative correlations are observed between expression and methylation levels in HLA-B, HLA-C, HLA-E, B2M, TAP1, and CIITA. Pearson’s correlation coefficients are shown for each correlation.</p>
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<p>Hierarchical clustering analysis using z-scores of mRNA expression and methylation levels of antigen-presenting machineries. The color map (<span class="html-italic">red-gray-blue</span>): <span class="html-italic">red</span>, degree of increased mRNA expression or methylation density; <span class="html-italic">blue</span>, degree of decreased mRNA expression or methylation density. CCAs in the cluster with high expression (red rectangle) and low methylation levels (blue rectangle) were considered upregulation/low-methylation pattern, and those with low expression (blue rectangle) and high methylation levels (red rectangle) were determined as downregulation/high-methylation pattern, respectively. Tumors classified as inflamed group, which are indicated in <a href="#cancers-15-02379-f001" class="html-fig">Figure 1</a>, are shown with red squares. Similarly, tumors harboring FGFR2 alterations and mutations in IDH1/2 are shown as black squares. All six tumors considered to have an inflamed tumor phenotype showed upregulation and low-methylation pattern in the genes involved in antigen presentation, whereas 24 of 30 tumors with a non-inflamed tumor phenotype showed downregulation with high-methylation pattern (<span class="html-italic">p</span> = 0.0005). All seven tumors carrying mutations in the IDH genes and six of the seven tumors carrying FGFR2 alterations were classified into the downregulation/high-methylation pattern group (<span class="html-italic">p</span> = 0.0704 and 0.3839 for mutations in the IDH genes and alterations in the FGFR2 genes, respectively).</p>
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<p>Comparisons of mRNA expression and DNA methylation level between inflamed and non-inflamed cholangiocarcinoma. mRNA expressions of the genes involved in antigen presentation are significantly higher in inflamed group than in non-inflamed group for all comparisons (<b>a</b>). Similarly, their DNA methylation levels are significantly lower in inflamed group than in non-inflamed group for all comparisons (<b>b</b>). Red boxes and whisker plots denote 75% and 95% distribution, respectively, and the red lines in the boxes show the median values. <span class="html-italic">p</span> values by non-parametric Wilcoxon rank-sum test are shown.</p>
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<p>Comparisons of mRNA expression and DNA methylation level between inflamed and non-inflamed cholangiocarcinoma. mRNA expressions of the genes involved in antigen presentation are significantly higher in inflamed group than in non-inflamed group for all comparisons (<b>a</b>). Similarly, their DNA methylation levels are significantly lower in inflamed group than in non-inflamed group for all comparisons (<b>b</b>). Red boxes and whisker plots denote 75% and 95% distribution, respectively, and the red lines in the boxes show the median values. <span class="html-italic">p</span> values by non-parametric Wilcoxon rank-sum test are shown.</p>
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<p>Schematic representation of the role of methylation and downregulation of genes involved in antigen presentation. In cholangiocarcinomas (CCAs), the phenotype of “inflamed” and “non-inflamed” classes, determined by the transcriptome of tumor-infiltrated lymphocytes, is strongly associated with the methylation and downregulation of genes related to antigen-presenting machinery. Consequently, lack of antigen-presenting machinery for the presentation of tumor-specific neoantigen result in the failure of attracting cytotoxic T lymphocytes (CTLs) into tumor. Some driver mutations unique to CCAs, such as mutations in the <span class="html-italic">IDH1</span>/<span class="html-italic">2</span> genes and alterations in the <span class="html-italic">FGFR2</span> gene, may be associated with these methylation and downregulation events.</p>
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21 pages, 15648 KiB  
Article
Ursolic Acid Alleviates Cancer Cachexia and Prevents Muscle Wasting via Activating SIRT1
by Weili Tao, Ze Ouyang, Zhiqi Liao, Lu Li, Yujie Zhang, Jiali Gao, Li Ma and Shiying Yu
Cancers 2023, 15(8), 2378; https://doi.org/10.3390/cancers15082378 - 20 Apr 2023
Cited by 9 | Viewed by 3142
Abstract
Skeletal muscle wasting is the most remarkable phenotypic feature of cancer cachexia that increases the risk of morbidity and mortality. However, there are currently no effective drugs against cancer cachexia. Ursolic acid (UA) is a lipophilic pentacyclic triterpene that has been reported to [...] Read more.
Skeletal muscle wasting is the most remarkable phenotypic feature of cancer cachexia that increases the risk of morbidity and mortality. However, there are currently no effective drugs against cancer cachexia. Ursolic acid (UA) is a lipophilic pentacyclic triterpene that has been reported to alleviate muscle atrophy and reduce muscle decomposition in some disease models. This study aimed to explore the role and mechanisms of UA treatment in cancer cachexia. We found that UA attenuated Lewis lung carcinoma (LLC)-conditioned medium-induced C2C12 myotube atrophy and muscle wasting of LLC tumor-bearing mice. Moreover, UA dose-dependently activated SIRT1 and downregulated MuRF1 and Atrogin-1. Molecular docking results revealed a good binding effect on UA and SIRT1 protein. UA rescued vital features wasting without impacting tumor growth, suppressed the elevated spleen weight, and downregulated serum concentrations of inflammatory cytokines in vivo. The above phenomena can be attenuated by Ex-527, an inhibitor of SIRT1. Furthermore, UA remained protective against cancer cachexia in the advanced stage of tumor growth. The results revealed that UA exerts an anti-cachexia effect via activating SIRT1, thereby downregulating the phosphorylation levels of NF-κB and STAT3. UA might be a potential drug against cancer cachexia. Full article
(This article belongs to the Special Issue Advances in Cancer Cachexia)
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Figure 1

Figure 1
<p>UA alleviates TCM-induced myotube atrophy in vitro. (<b>A</b>) The chemical structure of UA. (<b>B</b>) Effects of different concentrations of UA on the viability of C2C12 myotubes. C2C12 myotubes were cultured in different concentrations of UA (0, 0.5, 1.0, 2.5, 5.0 μM for 24, 48, and 72 h), and the viability of myotubes was detected by the CCK8 assay. Myotubes were cultured in various concentrations of UA under stimulation of TCM for 48 h. (<b>C</b>) Representative images of immunofluorescence staining for MyHC (green) are displayed (left) with different concentrations of UA. Scale bars = 50 μm. The relative fiber widths of each experiment were measured and calculated (right). mRNA levels of MuRF1 (<b>D</b>) and Atrogin-1 (<b>E</b>) in C2C12 myotubes were analyzed by real-time PCR and normalized to GAPDH. (<b>F</b>) Western blot was used to determine the expression of indicated proteins. The band intensities were quantified and normalized to GAPDH. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 versus control, ns: not significant, <span class="html-italic">n</span> = 3.</p>
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<p>UA alleviates muscle wasting and prevents cancer cachexia in vivo. (<b>A</b>) Schematic illustration of the animal experimental design. The effects of UA on the main features of cachexia were examined, including (<b>B</b>,<b>C</b>) tumor-free body weight, (<b>D</b>) tumor weight, (<b>E</b>–<b>G</b>) gastrocnemius and tibialis anterior muscle mass, (<b>J</b>) epididymal fat mass, (<b>K</b>–<b>M</b>) heart, kidney, and spleen mass (BW: body weight). (<b>H</b>) Gastrocnemius muscle was observed histologically by H&amp;E staining. Scale bars = 100 μm. The cross-sectional areas of approximately 210 myofibers per group were determined. <span class="html-italic">n</span> = 3 mice/group. (<b>I</b>) The protein expression of MuRF1 and Atrogin-1 in gastrocnemius muscles was detected with Western blot. The band intensities were quantified and normalized to GAPDH. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 versus control, ns: not significant, <span class="html-italic">n</span> = 10 mice/group.</p>
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<p>UA upregulates SIRT1 expression and inhibits the expression of NOX4, FOXO1, and FOXO3a in vitro and in vivo. (<b>A</b>) Molecular docking analysis of the interaction between UA and SIRT1 domain. (<b>B</b>) The mRNA expression of SIRT1 and NOX4 in the C2C12 myotube model was analyzed by real-time PCR and normalized to GAPDH. The expression levels of SIRT1, NOX4, FOXO1, and FOXO3a (<b>C</b>) in the C2C12 myotube model and (<b>D</b>) in the gastrocnemius muscles of the animal model were determined by Western blot. The band intensities were quantified by densitometry, and GAPDH was used as a control. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 versus control, ns: not significant, <span class="html-italic">n</span> = 3 in vitro and <span class="html-italic">n</span> = 10 mice/group in vivo.</p>
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<p>UA downregulates phosphorylation of STAT3 and p65 in vitro and in vivo and reverses elevated serum cytokines in the cancer cachectic model. The expression levels of indicated proteins (<b>A</b>) in the C2C12 myotube model and (<b>B</b>) in the gastrocnemius muscles of the animal model were determined by Western blot. The band intensities were quantified by densitometry, and the densities were quantified and normalized to GAPDH or the non-phosphorylated protein forms. The levels of pro-inflammatory cytokines (<b>C</b>) TNF-α, (<b>D</b>) IL-1β, and (<b>E</b>) IL-6 in the serum of the cancer cachectic model were detected by ELISA assay. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 versus control, ns: not significant, <span class="html-italic">n</span> = 3 in vitro and <span class="html-italic">n</span> = 10 mice/group in vivo.</p>
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<p>UA relieves TCM-induced myotube wasting through SIRT1 activation. C2C12 myotubes were pretreated with Ex-527 (0.1 μM) for 30 min and then stimulated by UA (5.0 μM) and TCM for 48 h. (<b>A</b>) Representative images of immunofluorescence staining for MyHC (green) are shown (left) with UA and Ex-527 treatment. Scale bars = 50 μm. The relative fiber widths of each experiment were measured and calculated (right). The mRNA expression levels of (<b>B</b>) MuRF1 and Atrogin-1 and (<b>C</b>) SIRT1 and NOX4 in the C2C12 myotube model were analyzed by real-time PCR and normalized to GAPDH. (<b>D</b>–<b>F</b>) Western blot was used to detect the expression of indicated proteins. The band intensities were quantified and normalized to GAPDH or the non-phosphorylated protein forms. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 versus control, ns: not significant, <span class="html-italic">n</span> = 3.</p>
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<p>UA improves muscle wasting and prevents cancer cachexia in LLC tumor-bearing mice through SIRT1 activation. (<b>A</b>) Schematic illustration of the animal experimental design. The effects of UA on the main features of cachexia were examined, including (<b>B</b>) tumor weight, (<b>C</b>) tumor-free body weight, (<b>D</b>–<b>F</b>) tibialis anterior and gastrocnemius muscle mass, and (<b>I</b>) epididymal fat mass. (<b>G</b>) The expression of MuRF1 and Atrogin-1 in the gastrocnemius muscles of the cancer cachectic model was determined by Western blot. The band intensities were quantified by densitometry and normalized to GAPDH. (<b>H</b>) Gastrocnemius muscle was shown histologically by H&amp;E staining. Scale bars = 100 μm. The cross-sectional areas were analyzed. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 versus control, ns: not significant, <span class="html-italic">n</span> = 10 mice/group.</p>
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<p>UA improves muscle wasting and prevents cancer cachexia in LLC tumor-bearing mice after Ex-527 (SIRT1 inhibitor) treatment. (<b>A</b>,<b>B</b>) Western blot was used to detect the expression of indicated proteins. The band intensities were quantified and normalized to GAPDH or the non-phosphorylated protein forms. The levels of pro-inflammatory cytokines (<b>C</b>) TNF-α, (<b>D</b>) IL-1β, and (<b>E</b>) IL-6 were detected by ELISA assay. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 versus control, <span class="html-italic">n</span> = 3.</p>
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<p>Effects of delaying treatment with UA until advanced stages of tumor and cachexia progression in LLC tumor-bearing mice. (<b>A</b>) Schematic illustration of the animal experimental design. The effects of UA on the main features of cachexia were examined, including (<b>B</b>) tumor weight, (<b>C</b>) tumor-free body weight, (<b>D</b>) spleen mass, (<b>E</b>) tibialis anterior and gastrocnemius muscle mass, and (<b>G</b>) epididymal fat mass. (<b>F</b>) Gastrocnemius muscle was shown histologically by H&amp;E staining. Scale bars = 100 μm. The cross-sectional areas were analyzed. The levels of pro-inflammatory cytokines (<b>H</b>) TNF-α, (<b>I</b>) IL-1β, and (<b>J</b>) IL-6 in the serum of the cancer cachectic model were detected by ELISA assay. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 versus control, ns: not significant, <span class="html-italic">n</span> = 10 mice/group.</p>
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<p>Effects of delaying treatment with UA until advanced stages of tumor and cachexia progression in LLC tumor-bearing mice on the expression of relevant molecules in the gastrocnemius muscle. (<b>A</b>–<b>C</b>) Western blot was used to detect the expression of indicated proteins. The band intensities were quantified and normalized to GAPDH or the non-phosphorylated protein forms. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 versus control, ns: not significant, <span class="html-italic">n</span> = 3.</p>
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11 pages, 245 KiB  
Review
Role for Neoadjuvant Systemic Therapy for Potentially Resectable Pancreatic Cancer
by Brandon G. Smaglo
Cancers 2023, 15(8), 2377; https://doi.org/10.3390/cancers15082377 - 19 Apr 2023
Cited by 6 | Viewed by 1760
Abstract
Despite aggressive adjuvant management, a high percentage of patients who undergo appropriate surgical resection for pancreatic cancer will see their cancer recur and thus will not be cured. An important paradigm shift to achieve better outcomes has been therapy sequence, with neoadjuvant chemotherapy [...] Read more.
Despite aggressive adjuvant management, a high percentage of patients who undergo appropriate surgical resection for pancreatic cancer will see their cancer recur and thus will not be cured. An important paradigm shift to achieve better outcomes has been therapy sequence, with neoadjuvant chemotherapy preceding surgery. Patients with a borderline resectable cancer, or patients with a resectable cancer but who have other high-risk features, are ideal candidates to consider for neoadjuvant chemotherapy. Among the high-risk features, a baseline elevated CA 19-9 concentration can be particularly useful, as its response trend during neoadjuvant chemotherapy can offer important insights into the prognosis after surgery. When selecting a neoadjuvant chemotherapy regimen, response data available for the use of FOLFIRINOX and gemcitabine and nabpaclitaxel in the metastatic setting support their use in this space. FOLFIRINOX is perhaps the preferred regimen, given its proven adjuvant benefit and possibly its superior tumor response rate; still, patient tolerance and thus ability to complete recommended treatment must be carefully considered. This review presents the evidence supporting neoadjuvant chemotherapy for resectable pancreatic cancer, the factors to consider when making such a recommendation, the selection of specific regimens, and our institutional approach using these tools. Full article
(This article belongs to the Special Issue Neoadjuvant Therapies in Pancreatic Cancer)
15 pages, 1118 KiB  
Review
Targeting Angiogenesis in the Era of Biliary Tract Cancer Immunotherapy: Biological Rationale, Clinical Implications, and Future Research Avenues
by Annalisa Schirizzi, Giampiero De Leonardis, Vincenza Lorusso, Rossella Donghia, Alessandro Rizzo, Simona Vallarelli, Carmela Ostuni, Laura Troiani, Ivan Roberto Lolli, Gianluigi Giannelli, Angela Dalia Ricci, Rosalba D’Alessandro and Claudio Lotesoriere
Cancers 2023, 15(8), 2376; https://doi.org/10.3390/cancers15082376 - 19 Apr 2023
Cited by 5 | Viewed by 2202
Abstract
Although biliary tract cancers are traditionally considered rare in Western countries, their incidence and mortality rates are rising worldwide. A better knowledge of the genomic landscape of these tumor types has broadened the number of molecular targeted therapies, including angiogenesis inhibitors. The role [...] Read more.
Although biliary tract cancers are traditionally considered rare in Western countries, their incidence and mortality rates are rising worldwide. A better knowledge of the genomic landscape of these tumor types has broadened the number of molecular targeted therapies, including angiogenesis inhibitors. The role of immune checkpoint inhibitors (ICIs) could potentially change the first-line therapeutic approach, but monotherapy with ICIs has shown disappointing results in CCA. Several clinical trials are evaluating combination strategies that include immunotherapy together with other anticancer agents with a synergistic activity. The tumor microenvironment (TME) composition plays a pivotal role in the prognosis of BTC patients. The accumulation of immunosuppressive cell types, such as tumor-associated macrophages (TAMs) and regulatory T-cells, together with the poor infiltration of cytotoxic CD8+ T-cells, is known to predispose to a poor prognosis owing to the establishment of resistance mechanisms. Likewise, angiogenesis is recognized as a major player in modulating the TME in an immunosuppressive manner. This is the mechanistic rationale for combination treatment schemes blocking both immunity and angiogenesis. In this scenario, this review aims to provide an overview of the most recent completed or ongoing clinical trials combining immunotherapy and angiogenesis inhibitors with/without a chemotherapy backbone. Full article
(This article belongs to the Special Issue Drug Resistance in Gastrointestinal Cancer)
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Figure 1
<p>Schematic figure representing biliary tract cancer anatomical subgroups. Abbreviations: eCCA, extrahepatic cholangiocarcinoma; dCCA, distal cholangiocarcinoma; pCCA, perihilar cholangiocarcinoma; iCCA, intrahepatic cholangiocarcinoma; GBC, gallbladder cancer; ICI, immunocheckpoint inhibitors.</p>
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<p>Schematic representation of the effects of antiangiogenic therapies on the conversion of an immunosuppressive (in blue) into an immunopermissive tumor microenvironment (in yellow). The immunosuppressive environment is characterized by fenestrated (<b>above</b>) and highly disorganized vessels (<b>middle</b>) and high levels of TAM, T-reg, Tie-2, Ang2, VEGFA, VEGFC, and VEGFR2 and low levels of T, T-helper, and dendritic cells (<b>bottom</b>), while the immunopermissive environment is characterized by the normalization of vessels and the inversion of expression levels of the same factors. This switch makes immunotherapy effective in highly vascularized BTCs. Abbreviations: TAM, tumor-associated macrophages; BTCs, biliary tract cancers; TME, tumor microenvironment.</p>
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