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Ferroptosis-Related Hub Genes in Hepatocellular Carcinoma: Prognostic Signature, Immune-Related, and Drug Resistance Analysis

Background: Hepatocellular carcinoma (HCC) is the most prevalent type of primary liver cancer with a high fatality rate and dismal prognosis because of frequent recurrence and lack of efficient therapies. Ferroptosis is a recently recognized iron-dependent cell death distinct from necroptosis and ap...

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Autores principales: Wang, Wei, Pan, Fan, Lin, Xinrong, Yuan, Jiakai, Tao, Chunyu, Wang, Rui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9355705/
https://www.ncbi.nlm.nih.gov/pubmed/35938001
http://dx.doi.org/10.3389/fgene.2022.907331
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author Wang, Wei
Pan, Fan
Lin, Xinrong
Yuan, Jiakai
Tao, Chunyu
Wang, Rui
author_facet Wang, Wei
Pan, Fan
Lin, Xinrong
Yuan, Jiakai
Tao, Chunyu
Wang, Rui
author_sort Wang, Wei
collection PubMed
description Background: Hepatocellular carcinoma (HCC) is the most prevalent type of primary liver cancer with a high fatality rate and dismal prognosis because of frequent recurrence and lack of efficient therapies. Ferroptosis is a recently recognized iron-dependent cell death distinct from necroptosis and apoptosis. The relationship between ferroptosis-related hub gene expression and prognosis in HCC remains to be further elucidated. Methods: Ferroptosis-related genes from the FerrDb database and the mRNA sequencing data and clinical information of HCC patients were obtained from The Cancer Genome Atlas (TCGA) database. The least absolute shrinkage and selection operator (LASSO) Cox regression was applied to identify a prognostic signature consisting of five ferroptosis-related hub genes in the TCGA cohort. The International Cancer Genome Consortium (ICGC) database was utilized to validate the reliability of the signature. Functional enrichment and immune-related analysis, including single-sample gene set enrichment analysis (ssGSEA), immune checkpoints, TIP-related genes, tumor stemness, and m6A-related genes, were performed to analyze the underlying mechanism. Additionally, the correlations between ferroptosis and drug resistance were evaluated using the NCI-60 database. Results: A 5–hub-gene signature associated with ferroptosis was constructed by multivariate Cox regression analysis to stratify patients into two risk groups. Patients with high risk had worse prognosis than those with low risk. Multivariate Cox regression analysis uncovered that the risk score was an independent prognostic indicator. We also proved the signature’s predictive capacity using the Kaplan–Meier method and receiver operating characteristic (ROC) curve analysis. Functional analysis showed that nuclear division and the cell cycle were enriched. Immune-related analysis revealed that the signature was enriched in immune-related pathways. Moreover, the risk signature was significantly associated with immune cell infiltration, immune checkpoints, TIP-related genes, tumor stem cells, as well as m6A-related genes. Furthermore, these genes were crucial regulators of drug resistance. Conclusion: We identified and validated a novel hub gene signature that is closely associated with ferroptosis as a new and efficient biomarker with favorable potential for predicting the prognosis of HCC patients. In addition, it also offers new insights into the molecular mechanisms of HCC and provides an effective approach for the treatment of HCC. Further studies are necessary to validate the results of our study.
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spelling pubmed-93557052022-08-06 Ferroptosis-Related Hub Genes in Hepatocellular Carcinoma: Prognostic Signature, Immune-Related, and Drug Resistance Analysis Wang, Wei Pan, Fan Lin, Xinrong Yuan, Jiakai Tao, Chunyu Wang, Rui Front Genet Genetics Background: Hepatocellular carcinoma (HCC) is the most prevalent type of primary liver cancer with a high fatality rate and dismal prognosis because of frequent recurrence and lack of efficient therapies. Ferroptosis is a recently recognized iron-dependent cell death distinct from necroptosis and apoptosis. The relationship between ferroptosis-related hub gene expression and prognosis in HCC remains to be further elucidated. Methods: Ferroptosis-related genes from the FerrDb database and the mRNA sequencing data and clinical information of HCC patients were obtained from The Cancer Genome Atlas (TCGA) database. The least absolute shrinkage and selection operator (LASSO) Cox regression was applied to identify a prognostic signature consisting of five ferroptosis-related hub genes in the TCGA cohort. The International Cancer Genome Consortium (ICGC) database was utilized to validate the reliability of the signature. Functional enrichment and immune-related analysis, including single-sample gene set enrichment analysis (ssGSEA), immune checkpoints, TIP-related genes, tumor stemness, and m6A-related genes, were performed to analyze the underlying mechanism. Additionally, the correlations between ferroptosis and drug resistance were evaluated using the NCI-60 database. Results: A 5–hub-gene signature associated with ferroptosis was constructed by multivariate Cox regression analysis to stratify patients into two risk groups. Patients with high risk had worse prognosis than those with low risk. Multivariate Cox regression analysis uncovered that the risk score was an independent prognostic indicator. We also proved the signature’s predictive capacity using the Kaplan–Meier method and receiver operating characteristic (ROC) curve analysis. Functional analysis showed that nuclear division and the cell cycle were enriched. Immune-related analysis revealed that the signature was enriched in immune-related pathways. Moreover, the risk signature was significantly associated with immune cell infiltration, immune checkpoints, TIP-related genes, tumor stem cells, as well as m6A-related genes. Furthermore, these genes were crucial regulators of drug resistance. Conclusion: We identified and validated a novel hub gene signature that is closely associated with ferroptosis as a new and efficient biomarker with favorable potential for predicting the prognosis of HCC patients. In addition, it also offers new insights into the molecular mechanisms of HCC and provides an effective approach for the treatment of HCC. Further studies are necessary to validate the results of our study. Frontiers Media S.A. 2022-07-22 /pmc/articles/PMC9355705/ /pubmed/35938001 http://dx.doi.org/10.3389/fgene.2022.907331 Text en Copyright © 2022 Wang, Pan, Lin, Yuan, Tao and Wang. https://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
Wang, Wei
Pan, Fan
Lin, Xinrong
Yuan, Jiakai
Tao, Chunyu
Wang, Rui
Ferroptosis-Related Hub Genes in Hepatocellular Carcinoma: Prognostic Signature, Immune-Related, and Drug Resistance Analysis
title Ferroptosis-Related Hub Genes in Hepatocellular Carcinoma: Prognostic Signature, Immune-Related, and Drug Resistance Analysis
title_full Ferroptosis-Related Hub Genes in Hepatocellular Carcinoma: Prognostic Signature, Immune-Related, and Drug Resistance Analysis
title_fullStr Ferroptosis-Related Hub Genes in Hepatocellular Carcinoma: Prognostic Signature, Immune-Related, and Drug Resistance Analysis
title_full_unstemmed Ferroptosis-Related Hub Genes in Hepatocellular Carcinoma: Prognostic Signature, Immune-Related, and Drug Resistance Analysis
title_short Ferroptosis-Related Hub Genes in Hepatocellular Carcinoma: Prognostic Signature, Immune-Related, and Drug Resistance Analysis
title_sort ferroptosis-related hub genes in hepatocellular carcinoma: prognostic signature, immune-related, and drug resistance analysis
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9355705/
https://www.ncbi.nlm.nih.gov/pubmed/35938001
http://dx.doi.org/10.3389/fgene.2022.907331
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