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

被引:20
|
作者
Qi, Xin [1 ]
Wang, Rui [1 ]
Lin, Yuxin [2 ]
Yan, Donghui [1 ]
Zuo, Jiachen [1 ]
Chen, Jiajia [1 ]
Shen, Bairong [3 ]
机构
[1] Suzhou Univ Sci & Technol, Sch Chem & Life Sci, Suzhou, Peoples R China
[2] Soochow Univ, Dept Urol, Affiliated Hosp 1, Suzhou, Peoples R China
[3] Sichuan Univ, West China Hosp, Inst Syst Genet, Chengdu, Peoples R China
基金
中国国家自然科学基金;
关键词
colon cancer; ferroptosis; prognostic biomarker; gene signature; outcome risk nomogram; COLORECTAL-CANCER; DEATH; EXPRESSION; TXNIP;
D O I
10.3389/fgene.2021.692426
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
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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页数:14
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