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Integrated Analysis of Immunity- and Ferroptosis-Related Biomarker Signatures to Improve the Prognosis Prediction of Hepatocellular Carcinoma
BACKGROUND: Hepatocellular carcinoma (HCC) is a common malignant tumor with high mortality and poor prognoses around the world. Ferroptosis is a new form of cell death, and some studies have found that it is related to cancer immunotherapy. The aim of our research was to find immunity- and ferroptos...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775557/ https://www.ncbi.nlm.nih.gov/pubmed/33391356 http://dx.doi.org/10.3389/fgene.2020.614888 |
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author | Du, Xuanlong Zhang, Yewei |
author_facet | Du, Xuanlong Zhang, Yewei |
author_sort | Du, Xuanlong |
collection | PubMed |
description | BACKGROUND: Hepatocellular carcinoma (HCC) is a common malignant tumor with high mortality and poor prognoses around the world. Ferroptosis is a new form of cell death, and some studies have found that it is related to cancer immunotherapy. The aim of our research was to find immunity- and ferroptosis-related biomarkers to improve the treatment and prognosis of HCC by bioinformatics analysis. METHODS: First, we obtained the original RNA sequencing (RNA-seq) expression data and corresponding clinical data of HCC from The Cancer Genome Atlas (TGCA) database and performed differential analysis. Second, we used immunity- and ferroptosis-related differentially expressed genes (DEGs) to perform a computational difference algorithm and Cox regression analysis. Third, we explored the potential molecular mechanisms and properties of immunity- and ferroptosis-related DEGs by computational biology and performed a new prognostic index based on immunity- and ferroptosis-related DEGs by multivariable Cox analysis. Finally, we used HCC data from International Cancer Genome Consortium (ICGC) data to perform validation. RESULTS: We obtained 31 immunity (p < 0.001)- and 14 ferroptosis (p < 0.05)-related DEGs correlated with overall survival (OS) in the univariate Cox regression analysis. Then, we screened five immunity- and two ferroptosis-related DEGs (HSPA4, ISG20L2, NRAS, IL17D, NDRG1, ACSL4, and G6PD) to establish a predictive model by multivariate Cox regression analysis. Receiver operating characteristic (ROC) and Kaplan–Meier (K–M) analyses demonstrated a good performance of the seven-biomarker signature. Functional enrichment analysis including Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed that the seven-biomarker signature was mainly associated with HCC-related biological processes such as nuclear division and the cell cycle, and the immune status was different between the two risk groups. CONCLUSION: Our results suggest that this specific seven-biomarker signature may be clinically useful in the prediction of HCC prognoses beyond conventional clinicopathological factors. Moreover, it also brings us new insights into the molecular mechanisms of HCC. |
format | Online Article Text |
id | pubmed-7775557 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-77755572021-01-02 Integrated Analysis of Immunity- and Ferroptosis-Related Biomarker Signatures to Improve the Prognosis Prediction of Hepatocellular Carcinoma Du, Xuanlong Zhang, Yewei Front Genet Genetics BACKGROUND: Hepatocellular carcinoma (HCC) is a common malignant tumor with high mortality and poor prognoses around the world. Ferroptosis is a new form of cell death, and some studies have found that it is related to cancer immunotherapy. The aim of our research was to find immunity- and ferroptosis-related biomarkers to improve the treatment and prognosis of HCC by bioinformatics analysis. METHODS: First, we obtained the original RNA sequencing (RNA-seq) expression data and corresponding clinical data of HCC from The Cancer Genome Atlas (TGCA) database and performed differential analysis. Second, we used immunity- and ferroptosis-related differentially expressed genes (DEGs) to perform a computational difference algorithm and Cox regression analysis. Third, we explored the potential molecular mechanisms and properties of immunity- and ferroptosis-related DEGs by computational biology and performed a new prognostic index based on immunity- and ferroptosis-related DEGs by multivariable Cox analysis. Finally, we used HCC data from International Cancer Genome Consortium (ICGC) data to perform validation. RESULTS: We obtained 31 immunity (p < 0.001)- and 14 ferroptosis (p < 0.05)-related DEGs correlated with overall survival (OS) in the univariate Cox regression analysis. Then, we screened five immunity- and two ferroptosis-related DEGs (HSPA4, ISG20L2, NRAS, IL17D, NDRG1, ACSL4, and G6PD) to establish a predictive model by multivariate Cox regression analysis. Receiver operating characteristic (ROC) and Kaplan–Meier (K–M) analyses demonstrated a good performance of the seven-biomarker signature. Functional enrichment analysis including Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed that the seven-biomarker signature was mainly associated with HCC-related biological processes such as nuclear division and the cell cycle, and the immune status was different between the two risk groups. CONCLUSION: Our results suggest that this specific seven-biomarker signature may be clinically useful in the prediction of HCC prognoses beyond conventional clinicopathological factors. Moreover, it also brings us new insights into the molecular mechanisms of HCC. Frontiers Media S.A. 2020-12-18 /pmc/articles/PMC7775557/ /pubmed/33391356 http://dx.doi.org/10.3389/fgene.2020.614888 Text en Copyright © 2020 Du and Zhang. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Du, Xuanlong Zhang, Yewei Integrated Analysis of Immunity- and Ferroptosis-Related Biomarker Signatures to Improve the Prognosis Prediction of Hepatocellular Carcinoma |
title | Integrated Analysis of Immunity- and Ferroptosis-Related Biomarker Signatures to Improve the Prognosis Prediction of Hepatocellular Carcinoma |
title_full | Integrated Analysis of Immunity- and Ferroptosis-Related Biomarker Signatures to Improve the Prognosis Prediction of Hepatocellular Carcinoma |
title_fullStr | Integrated Analysis of Immunity- and Ferroptosis-Related Biomarker Signatures to Improve the Prognosis Prediction of Hepatocellular Carcinoma |
title_full_unstemmed | Integrated Analysis of Immunity- and Ferroptosis-Related Biomarker Signatures to Improve the Prognosis Prediction of Hepatocellular Carcinoma |
title_short | Integrated Analysis of Immunity- and Ferroptosis-Related Biomarker Signatures to Improve the Prognosis Prediction of Hepatocellular Carcinoma |
title_sort | integrated analysis of immunity- and ferroptosis-related biomarker signatures to improve the prognosis prediction of hepatocellular carcinoma |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775557/ https://www.ncbi.nlm.nih.gov/pubmed/33391356 http://dx.doi.org/10.3389/fgene.2020.614888 |
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