Dataset Information

A Novel Epithelial-Mesenchymal Transition Gene Signature Correlated With Prognosis, and Immune Infiltration in Hepatocellular Carcinoma.

ABSTRACT: Background: Although many genes related to epithelial-mesenchymal transition (EMT) have been explored in hepatocellular carcinoma (HCC), their prognostic significance still needs further analysis. Methods: Differentially expressed EMT-related genes were obtained through the integrated analysis of 4 Gene expression omnibus (GEO) datasets. The univariate Cox regression and Lasso Cox regression models are utilized to determine the EMT-related gene signature. Based on the results of multivariate Cox regression, a predictive nomogram is established. Time-dependent ROC curve and calibration curve are used to show the distinguishing ability and consistency of the nomogram. Finally, we explored the correlation between EMT risk score and immune immunity. Results: We identified a nine EMT-related gene signature to predict the survival outcome of HCC patients. Based on the EMT risk score's median, HCC patients in each dataset were divided into high and low-risk groups. The survival outcomes of HCC patients in the high-risk group were significantly worse than those in the low-risk group. The prediction nomogram based on the EMT risk score has better distinguishing ability and consistency. High EMT risk score was related to immune infiltration. Conclusion: The nomogram based on the EMT risk score can reliably predict the survival outcome of HCC patients, thereby providing benefits for medical decisions.

SUBMITTER: Kong W

PROVIDER: S-EPMC9065556 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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A Novel Epithelial-Mesenchymal Transition Gene Signature Correlated With Prognosis, and Immune Infiltration in Hepatocellular Carcinoma.

Kong Weihao W Mao Zhongxiang Z Han Chen C Ding Zhenxing Z Yuan Qianqian Q Zhang Gaosong G Li Chong C Wu Xuesheng X Chen Jia J Guo Manyu M Hong Shaocheng S Yu Feng F Liu Rongqiang R Wang Xingyu X Zhang Jianlin J

Frontiers in pharmacology 20220420

<b>Background:</b> Although many genes related to epithelial-mesenchymal transition (EMT) have been explored in hepatocellular carcinoma (HCC), their prognostic significance still needs further analysis. <b>Methods:</b> Differentially expressed EMT-related genes were obtained through the integrated analysis of 4 Gene expression omnibus (GEO) datasets. The univariate Cox regression and Lasso Cox regression models are utilized to determine the EMT-related gene signature. Based on the results of mu ...[more]

PMID: 35517787

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Project description:BackgroundTumor metastasis is one of the leading reasons of the dismal prognosis of hepatocellular carcinoma (HCC). Epithelial-mesenchymal transition (EMT) is closely associated with tumor metastasis including HCC. The purpose of this study is to construct and validate an EMT-related gene signature for predicting the prognosis of HCC patients.MethodsGene expression data of HCC patients was downloaded from The Cancer Genome Atlas (TCGA) database. Gene set enrichment analysis (GSEA) was performed to found the EMT-related gene sets which were obviously distinct between normal samples and paired HCC samples. Cox regression analysis was used to develop an EMT-related prognostic signature, and the performance of the signature was evaluated by Kaplan-Meier curves and time-dependent receiver operating characteristic (ROC) curves. A nomogram incorporating the independent predictors was established. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the expression levels of the hub genes in HCC cell lines, and the role of PDCD6 in the metastasis of HCC was determined by functional experiments.ResultsAn EMT-related 5-gene signature (PDCD6, TCOF1, TRIM28, EZH2 and FAM83D) was constructed using univariate and multivariate Cox regression analysis. Based on the signature, the HCC patients were classified into high- and low-risk groups, and patients in high-risk group had a poor prognosis. Time-dependent ROC and Cox regression analyses suggested that the signature could predict HCC prognosis exactly and independently. The predictive capacity of the signature was also validated in two external cohorts. GSEA results showed that many cancer-related signaling pathways such as PI3K/Akt/mTOR pathway and TGF-β/SMAD pathway were enriched in high-risk group. The result of qRT-PCR revealed that PDCD6, TCOF1 and FAM83D were highly expressed in HCC cancer cells. Among them, PDCD6 were found to promote cell migration and invasion.ConclusionThe EMT-related 5-gene signature can serve as a promising prognostic biomarker for HCC patients and may provide a novel mechanism of HCC metastasis.

Project description:ObjectiveColorectal cancer (CRC) is a commonly diagnosed human malignancy worldwide. Both epithelial-mesenchymal transition (EMT) and N6-methyladenosine (m6A) modification play a crucial role in CRC development. This study aimed to construct a prognostic signature based on the genes related to EMT and m6A modification.MethodFirstly, the mRNA expression profiling of CRC tissues was analyzed using TCGA and GEO databases. The prognostic hub genes related to EMT and m6A modification were selected using weighted correlation network and cox regression analysis. The prognostic signature was constructed based on hub genes, followed by validation in three external cohorts. Finally, the expression of the representative hub gene was detected in clinical samples, and its biological role was investigated using assays in vivo and in vitro.ResultsA prognostic signature was constructed using the following genes: YAP1, FAM3C, NUBPL, GLO1, JARID2, NFKB1, CDKN1B, HOOK1, and GIPC2. The signature effectively stratified the clinical outcome of CRC patients in the training cohort and two validation cohorts. The subgroup analysis demonstrated the signature could identify high-risk population from CRC patients within stage I-II or III-IV, female, male and elder patients. The signature was correlated with the infiltration of some immune cells (such as macrophage and regulatory T cells) and gene mutation counts. Finally, the hub gene GIPC2 was found to be downregulated in CRC tissues and most CRC cells lines. GIPC2 overexpression inhibited the malignant characteristics of CRC cells in vitro and in vivo through upregulating E-cadherin and downregulating N-cadherin, Vimentin, and Snail, while the opposite results were observed for GIPC2 knockdown in CRC cells.ConclusionOur present study for the first time constructed a novel prognostic signature related to EMT, m6A modification, and immune infiltration for CRC risk stratification. In addition, GIPC2 is identified as a promising clinical biomarker or therapeutical target for CRC.

Project description:Background: Epithelial-mesenchymal transition (EMT) is closely associated with cancer cell metastasis. Colon adenocarcinoma (COAD) is one of the most common malignancies in the world, and its metastasis leading to poor prognosis remains a challenge for clinicians. The purpose of this study was to explore the prognostic value of EMT-related genes (EMTRGs) by bioinformatics analysis and to develop a new EMTRGs prognostic signature for COAD. Methods: The TCGA-COAD dataset was downloaded from the TCGA portal as the training cohort, and the GSE17538 and GSE29621 datasets were obtained from the GEO database as the validation cohort. The best EMTRGs prognostic signature was constructed by differential expression analysis, Cox, and LASSO regression analysis. Gene set enrichment analysis (GSEA) is used to reveal pathways that are enriched in high-risk and low-risk groups. Differences in tumor immune cell levels were analyzed using microenvironmental cell population counter and single sample gene set enrichment analysis. Subclass mapping analysis and Genomics of Drug Sensitivity in Cancer were applied for prediction of immunotherapy response and chemotherapy response, respectively. Results: A total of 77 differentially expressed EMTRGs were identified in the TCGA-COAD cohort, and they were significantly associated with functions and pathways related to cancer cell metastasis, proliferation, and apoptosis. We constructed EMTRGs prognostic signature with COMP, MYL9, PCOLCE2, SCG2, and TIMP1 as new COAD prognostic biomarkers. The high-risk group had a poorer prognosis with enhanced immune cell infiltration. The GSEA demonstrated that the high-risk group was involved in "ECM Receptor Interaction," "WNT Signaling Pathway" and "Colorectal Cancer." Furthermore, patients with high risk scores may respond to anti-CTLA4 therapy and may be more resistant to targeted therapy agents BI 2536 and ABT-888. Conclusion: Together, we developed a new EMTRGs prognostic signature that can be an independent prognostic factor for COAD. This study has guiding implications for individualized counseling and treatment of COAD patients.

Dataset Information

A Novel Epithelial-Mesenchymal Transition Gene Signature Correlated With Prognosis, and Immune Infiltration in Hepatocellular Carcinoma.

Publications

A Novel Epithelial-Mesenchymal Transition Gene Signature Correlated With Prognosis, and Immune Infiltration in Hepatocellular Carcinoma.

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