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Development and validation of epithelial mesenchymal transition-related prognostic model for hepatocellular carcinoma

Epithelial cell transformation (EMT) plays an important role in the pathogenesis and metastasis of hepatocellular carcinoma (HCC). We aimed to establish a genetic risk model to evaluate HCC prognosis based on the expression levels of EMT-related genes. The data of HCC patients were collected from TC...

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Autores principales: Wang, Xuequan, Xing, Ziming, Xu, Huihui, Yang, Haihua, Xing, Tongjing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8202896/
https://www.ncbi.nlm.nih.gov/pubmed/33929972
http://dx.doi.org/10.18632/aging.202976
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author Wang, Xuequan
Xing, Ziming
Xu, Huihui
Yang, Haihua
Xing, Tongjing
author_facet Wang, Xuequan
Xing, Ziming
Xu, Huihui
Yang, Haihua
Xing, Tongjing
author_sort Wang, Xuequan
collection PubMed
description Epithelial cell transformation (EMT) plays an important role in the pathogenesis and metastasis of hepatocellular carcinoma (HCC). We aimed to establish a genetic risk model to evaluate HCC prognosis based on the expression levels of EMT-related genes. The data of HCC patients were collected from TCGA and ICGC databases. Gene expression differential analysis, univariate analysis, and lasso combined with stepwise Cox regression were used to construct the prognostic model. Kaplan–Meier curve, receiver operating characteristic (ROC) curve, calibration analysis, Harrell’s concordance index (C-index), and decision curve analysis (DCA) were used to evaluate the predictive ability of the risk model or nomogram. GO and KEGG were used to analyze differently expressed EMT genes, or genes that directly or indirectly interact with the risk-associated genes. A 10-gene signature, including TSC2, ACTA2, SLC2A1, PGF, MYCN, PIK3R1, EOMES, BDNF, ZNF746, and TFDP3, was identified. Kaplan–Meier survival analysis showed a significant prognostic difference between high- and low-risk groups of patients. ROC curve analysis showed that the risk score model could effectively predict the 1-, 3-, and 5-year overall survival rates of patients with HCC. The nomogram showed a stronger predictive effect than clinical indicators. C-index, DCA, and calibration analysis demonstrated that the risk score and nomogram had high accuracy. The single sample gene set enrichment analysis results confirmed significant differences in the types of infiltrating immune cells between patients in the high- and low-risk groups. This study established a new prediction model of risk gene signature for predicting prognosis in patients with HCC, and provides a new molecular tool for the clinical evaluation of HCC prognosis.
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spelling pubmed-82028962021-06-15 Development and validation of epithelial mesenchymal transition-related prognostic model for hepatocellular carcinoma Wang, Xuequan Xing, Ziming Xu, Huihui Yang, Haihua Xing, Tongjing Aging (Albany NY) Research Paper Epithelial cell transformation (EMT) plays an important role in the pathogenesis and metastasis of hepatocellular carcinoma (HCC). We aimed to establish a genetic risk model to evaluate HCC prognosis based on the expression levels of EMT-related genes. The data of HCC patients were collected from TCGA and ICGC databases. Gene expression differential analysis, univariate analysis, and lasso combined with stepwise Cox regression were used to construct the prognostic model. Kaplan–Meier curve, receiver operating characteristic (ROC) curve, calibration analysis, Harrell’s concordance index (C-index), and decision curve analysis (DCA) were used to evaluate the predictive ability of the risk model or nomogram. GO and KEGG were used to analyze differently expressed EMT genes, or genes that directly or indirectly interact with the risk-associated genes. A 10-gene signature, including TSC2, ACTA2, SLC2A1, PGF, MYCN, PIK3R1, EOMES, BDNF, ZNF746, and TFDP3, was identified. Kaplan–Meier survival analysis showed a significant prognostic difference between high- and low-risk groups of patients. ROC curve analysis showed that the risk score model could effectively predict the 1-, 3-, and 5-year overall survival rates of patients with HCC. The nomogram showed a stronger predictive effect than clinical indicators. C-index, DCA, and calibration analysis demonstrated that the risk score and nomogram had high accuracy. The single sample gene set enrichment analysis results confirmed significant differences in the types of infiltrating immune cells between patients in the high- and low-risk groups. This study established a new prediction model of risk gene signature for predicting prognosis in patients with HCC, and provides a new molecular tool for the clinical evaluation of HCC prognosis. Impact Journals 2021-04-30 /pmc/articles/PMC8202896/ /pubmed/33929972 http://dx.doi.org/10.18632/aging.202976 Text en Copyright: © 2021 Wang et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Wang, Xuequan
Xing, Ziming
Xu, Huihui
Yang, Haihua
Xing, Tongjing
Development and validation of epithelial mesenchymal transition-related prognostic model for hepatocellular carcinoma
title Development and validation of epithelial mesenchymal transition-related prognostic model for hepatocellular carcinoma
title_full Development and validation of epithelial mesenchymal transition-related prognostic model for hepatocellular carcinoma
title_fullStr Development and validation of epithelial mesenchymal transition-related prognostic model for hepatocellular carcinoma
title_full_unstemmed Development and validation of epithelial mesenchymal transition-related prognostic model for hepatocellular carcinoma
title_short Development and validation of epithelial mesenchymal transition-related prognostic model for hepatocellular carcinoma
title_sort development and validation of epithelial mesenchymal transition-related prognostic model for hepatocellular carcinoma
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8202896/
https://www.ncbi.nlm.nih.gov/pubmed/33929972
http://dx.doi.org/10.18632/aging.202976
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