Genomics and prognosis analysis of epithelial-mesenchymal transition in colorectal cancer patients

Zhang, Zizhen; Zheng, Shu; Lin, Yaowang; Sun, Jiawei; Ding, Ning; Chen, Jingyu; Zhong, Jing; Shi, Liuhong; Xue, Min

doi:10.1186/s12885-020-07615-5

Cited by 26 publications

(14 citation statements)

References 44 publications

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“…ERGs were attained from a previous study of EMT-related signatures for CRC (8). ERG expression data and clinical features of 522 EC patients and 23 normal samples were downloaded from The Cancer Genome Atlas (TCGA), and the transcriptome data files were "FPKM".…”

Section: Public Data Sourcesmentioning

confidence: 99%

Establishing a Prognostic Signature Based on Epithelial–Mesenchymal Transition-Related Genes for Endometrial Cancer Patients

et al. 2022

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BackgroundsEpithelial–mesenchymal transition (EMT) is a sequential process where tumor cells develop from the epithelial state to the mesenchymal state. EMT contributes to various tumor functions including initiation, propagating potential, and resistance to therapy, thus affecting the survival time of patients. The aim of this research is to set up an EMT-related prognostic signature for endometrial cancer (EC).MethodsEMT-related gene (ERG) expression and clinical data were acquired from The Cancer Genome Atlas (TCGA). The entire set was randomly divided into two sets, one for contributing the risk model (risk score) and the other for validating. Univariate and multivariate Cox proportional hazards regression analyses were applied to the training set to select the prognostic ERGs. The expression of 10 ERGs was confirmed by qRT-PCR in clinical samples. Then, we developed a nomogram predicting 1-/3-/5-year survival possibility combining the risk score and clinical factors. The entire set was stratified into the high- and low-risk groups, which was used to analyze the immune infiltrating, tumorigenesis pathways, and response to drugs.ResultsA total of 220 genes were screened out from 1,316 ERGs for their differential expression in tumor versus normal. Next, 10 genes were found to be associated with overall survival (OS) in EC, and the expression was validated by qRT-PCR using clinical samples, so we constructed a 10-ERG-based risk score to distinguish high-/low-risk patients and a nomogram to predict survival rate. The calibration plots proved the predictive value of our model. Gene Set Enrichment Analysis (GSEA) discovered that in the low-risk group, immune-related pathways were enriched; in the high-risk group, tumorigenesis pathways were enriched. The low-risk group showed more immune activities, higher tumor mutational burden (TMB), and higher CTAL4/PD1 expression, which was in line with a better response to immune checkpoint inhibitors. Nevertheless, response to chemotherapeutic drugs turned out better in the high-risk group. The high-risk group had higher N6-methyladenosine (m6A) RNA expression, microsatellite instability level, and stemness indices.ConclusionWe constructed the ERG-related signature model to predict the prognosis of EC patients. What is more, it might offer a reference for predicting individualized response to immune checkpoint inhibitors and chemotherapeutic drugs.

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Section: Public Data Sourcesmentioning

confidence: 99%

Establishing a Prognostic Signature Based on Epithelial–Mesenchymal Transition-Related Genes for Endometrial Cancer Patients

et al. 2022

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“…MET is characterized by loss of mesenchymal markers (i.e., SNAIL-1 and TWIST-1) and, in turn, enhancement of epithelial markers (i.e., E-CADHERIN). [55] During the EMT, the cells lose their epithelial characteristics, like cell polarity and cell-cell contacts, and gain mesenchymal traits such as increased motility. [56] The transient nature of the EMT events allows mesenchymal cells to revert to an epithelial shape when signals driving the EMT decrease.…”

Section: Evaluation Of Met Induced By Dnps-aunps-ly@gel In Crc Cellsmentioning

confidence: 99%

SERS Quantification of Galunisertib Delivery in Colorectal Cancer Cells by Plasmonic‐Assisted Diatomite Nanoparticles

Managò

Tramontano

Cave

et al. 2021

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therapies for CRC treatment, like systemic chemotherapy and immunotherapy, are expensive and invasive since they fail to target cancer cells selectively, causing severe toxicity on normal tissues besides side effects. [2][3][4][5] The epithelial-to-mesenchymal transition (EMT) is a dynamic multistep process involved in several physiological and pathological conditions, including cancer. [6] Notably, EMT in CRC is associated with an invasive, metastatic, and chemoresistant phenotype. [7] In contrast, the mesenchymal-to-epithelial transition (MET), is the reverse program of EMT in metastases and is characterized by the upregulation of epithelial adhesive proteins such as E-CADHERIN, and downregulation of mesenchymal proteins, such as SNAIL-1 and TWIST-1. Slowing EMT or even reversing the process in metastases inducing a MET program not only is a powerful therapeutic approach alone, but can also assist in increasing the efficacy of other anticancer treatments. Among the molecular pathways promoting tumorigenesis in CRC, the transforming growth factor-β (TGF-β) is described as a crucial factor in EMT induction. [8] Fighting the CRC with the TGF-β receptor I-specific inhibitor Galunisertib (LY2157299, LY) has been proposed as a powerful strategy to reduce tumor growth and the risk of relapse. [8] However, LY is cleared predominantly by cytochrome P450 3A4 (CYP3A4) oxidative metabolism in the The small molecule Galunisertib (LY2157299, LY) shows multiple anticancer activities blocking the transforming growth factor-β1 receptor, responsible for the epithelial-to-mesenchymal transition (EMT) by which colorectal cancer (CRC) cells acquire migratory and metastatic capacities. However, frequent dosing of LY can produce highly toxic metabolites. Alternative strategies to reduce drug side effects can rely on nanoscale drug delivery systems that have led to a medical revolution in the treatment of cancer, improving drug efficacy and lowering drug toxicity. Here, a hybrid nanosystem (DNP-AuNPs-LY@Gel) made of a porous diatomite nanoparticle decorated with plasmonic gold nanoparticles, in which LY is retained by a gelatin shell, is proposed. The multifunctional capability of the nanosystem is demonstrated by investigating the efficient LY delivery, the enhanced EMT reversion in CRCs and the intracellular quantification of drug release with a sub-femtogram resolution by surface-enhanced Raman spectroscopy (SERS). The LY release trigger is the pH sensitivity of the gelatin shell to the CRC acidic microenvironment. The drug release is real-time monitored at single-cell level by analyzing the SERS signals of LY in CRC cells. The higher efficiency of LY delivered by the DNP-AuNPs-LY@Gel complex paves the way to an alternative strategy for lowering drug dosing and consequent side effects.

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“…EMT-based gene signatures have been developed in bladder cancer [23], glioma [24], and colorectal cancer [25]. EMT is determined to be closely associated with gastric cancer progression and prognosis.…”

Section: Discussionmentioning

confidence: 99%

Discovery and Validation of an Epithelial-Mesenchymal Transition-Based Signature in Gastric Cancer by Genomics and Prognosis Analysis

Wan

Zhu

et al. 2021

BioMed Research International

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Objective. Epithelial-mesenchymal transition (EMT) exerts a key function in cancer initiation and progression. Herein, we aimed to develop an EMT-based prognostic signature in gastric cancer. Methods. The gene expression profiles of gastric cancer were obtained from TCGA dataset as a training set and GSE66229 and GSE84437 datasets as validation sets. By LASSO regression and Cox regression analyses, key prognostic EMT-related genes were screened for developing a risk score (RS) model. Potential small molecular compounds were predicted by the CMap database based on the RS model. GSEA was employed to explore signaling pathways associated with the RS. ESTIMATE and seven algorithms (TIMER, CIBERSORT, CIBERSORT-ABS, QUANTISEQ, MCPCOUNTER, XCELL, and EPIC) were applied to assess the RS and immune microenvironment. Results. This study developed an EMT-related gene signature comprised of SERPINE1, PCOLCE2, MATN3, and DKK1. High-RS patients displayed poorer survival outcomes than those with low RS. ROC curves demonstrated the robustness of the model in predicting the prognosis. After external validation, the RS model was an independent risk factor for gastric cancer. Several compounds were predicted for gastric cancer treatment based on the RS model. ECM receptor interaction, focal adhesion, pathway in cancer, TGF-beta, and WNT pathways were distinctly activated in high-RS samples. Also, high RS was significantly associated with increased stromal and immune scores and increased infiltration of CD4+ T cell, CD8+ T cell, cancer-associated fibroblast, and macrophage in gastric cancer tissues. Conclusion. Our findings suggested that the EMT-related gene model may robustly predict gastric cancer prognosis, which could improve the efficacy of personalized therapy.

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Genomics and prognosis analysis of epithelial-mesenchymal transition in colorectal cancer patients

Cited by 26 publications

References 44 publications

Establishing a Prognostic Signature Based on Epithelial–Mesenchymal Transition-Related Genes for Endometrial Cancer Patients

Establishing a Prognostic Signature Based on Epithelial–Mesenchymal Transition-Related Genes for Endometrial Cancer Patients

SERS Quantification of Galunisertib Delivery in Colorectal Cancer Cells by Plasmonic‐Assisted Diatomite Nanoparticles

Discovery and Validation of an Epithelial-Mesenchymal Transition-Based Signature in Gastric Cancer by Genomics and Prognosis Analysis

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