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A Ferroptosis-Related Gene Signature Identified as a Novel Prognostic Biomarker for Colon Cancer

BACKGROUND: Colon cancer (CC) is a common gastrointestinal malignant tumor with high heterogeneity in clinical behavior and response to treatment, making individualized survival prediction challenging. Ferroptosis is a newly discovered iron-dependent cell death that plays a critical role in cancer b...

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Autores principales: Qi, Xin, Wang, Rui, Lin, Yuxin, Yan, Donghui, Zuo, Jiachen, Chen, Jiajia, Shen, Bairong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8280527/
https://www.ncbi.nlm.nih.gov/pubmed/34276794
http://dx.doi.org/10.3389/fgene.2021.692426
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author Qi, Xin
Wang, Rui
Lin, Yuxin
Yan, Donghui
Zuo, Jiachen
Chen, Jiajia
Shen, Bairong
author_facet Qi, Xin
Wang, Rui
Lin, Yuxin
Yan, Donghui
Zuo, Jiachen
Chen, Jiajia
Shen, Bairong
author_sort Qi, Xin
collection PubMed
description BACKGROUND: Colon cancer (CC) is a common gastrointestinal malignant tumor with high heterogeneity in clinical behavior and response to treatment, making individualized survival prediction challenging. Ferroptosis is a newly discovered iron-dependent cell death that plays a critical role in cancer biology. Therefore, identifying a prognostic biomarker with ferroptosis-related genes provides a new strategy to guide precise clinical decision-making in CC patients. METHODS: Alteration in the expression profile of ferroptosis-related genes was initially screened in GSE39582 dataset involving 585 CC patients. Univariate Cox regression analysis and LASSO-penalized Cox regression analysis were combined to further identify a novel ferroptosis-related gene signature for overall survival prediction. The prognostic performance of the signature was validated in the GSE17536 dataset by Kaplan-Meier survival curve and time-dependent ROC curve analyses. Functional annotation of the signature was explored by integrating GO and KEGG enrichment analysis, GSEA analysis and ssGSEA analysis. Furthermore, an outcome risk nomogram was constructed considering both the gene signature and the clinicopathological features. RESULTS: The prognostic signature biomarker composed of 9 ferroptosis-related genes accurately discriminated high-risk and low-risk patients with CC in both the training and validation datasets. The signature was tightly linked to clinicopathological features and possessed powerful predictive ability for distinct clinical subgroups. Furthermore, the risk score was confirmed to be an independent prognostic factor for CC patients by multivariate Cox regression analysis (p < 0.05). Functional annotation analyses showed that the prognostic signature was closely correlated with pivotal cancer hallmarks, particularly cell cycle, transcriptional regulation, and immune-related functions. Moreover, a nomogram with the signature was also built to quantify outcome risk for each patient. CONCLUSION: The novel ferroptosis-related gene signature biomarker can be utilized for predicting individualized prognosis, optimizing survival risk assessment and facilitating personalized management of CC patients.
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spelling pubmed-82805272021-07-16 A Ferroptosis-Related Gene Signature Identified as a Novel Prognostic Biomarker for Colon Cancer Qi, Xin Wang, Rui Lin, Yuxin Yan, Donghui Zuo, Jiachen Chen, Jiajia Shen, Bairong Front Genet Genetics BACKGROUND: Colon cancer (CC) is a common gastrointestinal malignant tumor with high heterogeneity in clinical behavior and response to treatment, making individualized survival prediction challenging. Ferroptosis is a newly discovered iron-dependent cell death that plays a critical role in cancer biology. Therefore, identifying a prognostic biomarker with ferroptosis-related genes provides a new strategy to guide precise clinical decision-making in CC patients. METHODS: Alteration in the expression profile of ferroptosis-related genes was initially screened in GSE39582 dataset involving 585 CC patients. Univariate Cox regression analysis and LASSO-penalized Cox regression analysis were combined to further identify a novel ferroptosis-related gene signature for overall survival prediction. The prognostic performance of the signature was validated in the GSE17536 dataset by Kaplan-Meier survival curve and time-dependent ROC curve analyses. Functional annotation of the signature was explored by integrating GO and KEGG enrichment analysis, GSEA analysis and ssGSEA analysis. Furthermore, an outcome risk nomogram was constructed considering both the gene signature and the clinicopathological features. RESULTS: The prognostic signature biomarker composed of 9 ferroptosis-related genes accurately discriminated high-risk and low-risk patients with CC in both the training and validation datasets. The signature was tightly linked to clinicopathological features and possessed powerful predictive ability for distinct clinical subgroups. Furthermore, the risk score was confirmed to be an independent prognostic factor for CC patients by multivariate Cox regression analysis (p < 0.05). Functional annotation analyses showed that the prognostic signature was closely correlated with pivotal cancer hallmarks, particularly cell cycle, transcriptional regulation, and immune-related functions. Moreover, a nomogram with the signature was also built to quantify outcome risk for each patient. CONCLUSION: The novel ferroptosis-related gene signature biomarker can be utilized for predicting individualized prognosis, optimizing survival risk assessment and facilitating personalized management of CC patients. Frontiers Media S.A. 2021-07-01 /pmc/articles/PMC8280527/ /pubmed/34276794 http://dx.doi.org/10.3389/fgene.2021.692426 Text en Copyright © 2021 Qi, Wang, Lin, Yan, Zuo, Chen and Shen. 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
Qi, Xin
Wang, Rui
Lin, Yuxin
Yan, Donghui
Zuo, Jiachen
Chen, Jiajia
Shen, Bairong
A Ferroptosis-Related Gene Signature Identified as a Novel Prognostic Biomarker for Colon Cancer
title A Ferroptosis-Related Gene Signature Identified as a Novel Prognostic Biomarker for Colon Cancer
title_full A Ferroptosis-Related Gene Signature Identified as a Novel Prognostic Biomarker for Colon Cancer
title_fullStr A Ferroptosis-Related Gene Signature Identified as a Novel Prognostic Biomarker for Colon Cancer
title_full_unstemmed A Ferroptosis-Related Gene Signature Identified as a Novel Prognostic Biomarker for Colon Cancer
title_short A Ferroptosis-Related Gene Signature Identified as a Novel Prognostic Biomarker for Colon Cancer
title_sort ferroptosis-related gene signature identified as a novel prognostic biomarker for colon cancer
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8280527/
https://www.ncbi.nlm.nih.gov/pubmed/34276794
http://dx.doi.org/10.3389/fgene.2021.692426
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