Cargando…

An epithelial-mesenchymal transition-related 5-gene signature predicting the prognosis of hepatocellular carcinoma patients

BACKGROUND: Tumor 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 signatur...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhu, Gongmin, Xia, Hongwei, Tang, Qiulin, Bi, Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7953549/
https://www.ncbi.nlm.nih.gov/pubmed/33712026
http://dx.doi.org/10.1186/s12935-021-01864-5
_version_ 1783663940075520000
author Zhu, Gongmin
Xia, Hongwei
Tang, Qiulin
Bi, Feng
author_facet Zhu, Gongmin
Xia, Hongwei
Tang, Qiulin
Bi, Feng
author_sort Zhu, Gongmin
collection PubMed
description BACKGROUND: Tumor 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. METHODS: Gene 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. RESULTS: An 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. CONCLUSION: The EMT-related 5-gene signature can serve as a promising prognostic biomarker for HCC patients and may provide a novel mechanism of HCC metastasis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-021-01864-5.
format Online
Article
Text
id pubmed-7953549
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-79535492021-03-12 An epithelial-mesenchymal transition-related 5-gene signature predicting the prognosis of hepatocellular carcinoma patients Zhu, Gongmin Xia, Hongwei Tang, Qiulin Bi, Feng Cancer Cell Int Primary Research BACKGROUND: Tumor 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. METHODS: Gene 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. RESULTS: An 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. CONCLUSION: The EMT-related 5-gene signature can serve as a promising prognostic biomarker for HCC patients and may provide a novel mechanism of HCC metastasis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-021-01864-5. BioMed Central 2021-03-12 /pmc/articles/PMC7953549/ /pubmed/33712026 http://dx.doi.org/10.1186/s12935-021-01864-5 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Primary Research
Zhu, Gongmin
Xia, Hongwei
Tang, Qiulin
Bi, Feng
An epithelial-mesenchymal transition-related 5-gene signature predicting the prognosis of hepatocellular carcinoma patients
title An epithelial-mesenchymal transition-related 5-gene signature predicting the prognosis of hepatocellular carcinoma patients
title_full An epithelial-mesenchymal transition-related 5-gene signature predicting the prognosis of hepatocellular carcinoma patients
title_fullStr An epithelial-mesenchymal transition-related 5-gene signature predicting the prognosis of hepatocellular carcinoma patients
title_full_unstemmed An epithelial-mesenchymal transition-related 5-gene signature predicting the prognosis of hepatocellular carcinoma patients
title_short An epithelial-mesenchymal transition-related 5-gene signature predicting the prognosis of hepatocellular carcinoma patients
title_sort epithelial-mesenchymal transition-related 5-gene signature predicting the prognosis of hepatocellular carcinoma patients
topic Primary Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7953549/
https://www.ncbi.nlm.nih.gov/pubmed/33712026
http://dx.doi.org/10.1186/s12935-021-01864-5
work_keys_str_mv AT zhugongmin anepithelialmesenchymaltransitionrelated5genesignaturepredictingtheprognosisofhepatocellularcarcinomapatients
AT xiahongwei anepithelialmesenchymaltransitionrelated5genesignaturepredictingtheprognosisofhepatocellularcarcinomapatients
AT tangqiulin anepithelialmesenchymaltransitionrelated5genesignaturepredictingtheprognosisofhepatocellularcarcinomapatients
AT bifeng anepithelialmesenchymaltransitionrelated5genesignaturepredictingtheprognosisofhepatocellularcarcinomapatients
AT zhugongmin epithelialmesenchymaltransitionrelated5genesignaturepredictingtheprognosisofhepatocellularcarcinomapatients
AT xiahongwei epithelialmesenchymaltransitionrelated5genesignaturepredictingtheprognosisofhepatocellularcarcinomapatients
AT tangqiulin epithelialmesenchymaltransitionrelated5genesignaturepredictingtheprognosisofhepatocellularcarcinomapatients
AT bifeng epithelialmesenchymaltransitionrelated5genesignaturepredictingtheprognosisofhepatocellularcarcinomapatients