A novel survival model based on a Ferroptosis-related gene signature for predicting overall survival in bladder cancer

Yingchun Liang; Fangdie Ye; Chenyang Xu; Lujia Zou; Yun Hu; Jimeng Hu; Haowen Jiang

doi:10.1186/s12885-021-08687-7

A novel survival model based on a Ferroptosis-related gene signature for predicting overall survival in bladder cancer

BMC Cancer. 2021 Aug 21;21(1):943. doi: 10.1186/s12885-021-08687-7.

Authors

Yingchun Liang^#^{1

2}, Fangdie Ye^#^{1

2}, Chenyang Xu^{1

2}, Lujia Zou^{1

2}, Yun Hu^{1

2}, Jimeng Hu^{3

4}, Haowen Jiang^{5

6

7}

Affiliations

¹ Departments of Urology, Huashan Hospital, Fudan University, No. 12 WuLuMuQi Middle Road, Shanghai, 200040, China.
² Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China.
³ Departments of Urology, Huashan Hospital, Fudan University, No. 12 WuLuMuQi Middle Road, Shanghai, 200040, China. jmhu14@fudan.edu.cn.
⁴ Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China. jmhu14@fudan.edu.cn.
⁵ Departments of Urology, Huashan Hospital, Fudan University, No. 12 WuLuMuQi Middle Road, Shanghai, 200040, China. haowj_sh@fudan.edu.cn.
⁶ Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China. haowj_sh@fudan.edu.cn.
⁷ National Clinical Research Center for Aging and Medicine, Fudan University, Shanghai, China. haowj_sh@fudan.edu.cn.

^# Contributed equally.

Abstract

Background: The effective treatment and prognosis prediction of bladder cancer (BLCA) remains a medical problem. Ferroptosis is an iron-dependent form of programmed cell death. Ferroptosis is closely related to tumour occurrence and progression, but the prognostic value of ferroptosis-related genes (FRGs) in BLCA remains to be further clarified. In this study, we identified an FRG signature with potential prognostic value for patients with BLCA.

Methods: The corresponding clinical data and mRNA expression profiles of BLCA patients were downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression was used to extract FRGs related to survival time, and a Cox regression model was used to construct a multigene signature. Both principal component analysis (PCA) and single-sample gene set enrichment analysis (ssGSEA) were performed for functional annotation.

Results: Clinical traits were combined with FRGs, and 15 prognosis-related FRGs were identified by Cox regression. High expression of CISD1, GCLM, CRYAB, SLC7A11, TFRC, ACACA, ZEB1, SQLE, FADS2, ABCC1, G6PD and PGD was related to poor survival in BLCA patients. Multivariate Cox regression was used to construct a prognostic model with 7 FRGs that divided patients into two risk groups. Compared with that in the low-risk group, the overall survival (OS) of patients in the high-risk group was significantly lower (P < 0.001). In multivariate regression analysis, the risk score was shown to be an independent predictor of OS (HR = 1.772, P < 0.01). Receiver operating characteristic (ROC) curve analysis verified the predictive ability of the model. In addition, the two risk groups displayed different immune statuses in ssGSEA and different distributed patterns in PCA.

Conclusion: Our research suggests that a new gene model related to ferroptosis can be applied for the prognosis prediction of BLCA. Targeting FRGs may be a treatment option for BLCA.

Keywords: Bladder cancer; Ferroptosis; Gene signature; Prognostic model; The Cancer genome atlas (TCGA).

MeSH terms

Biomarkers, Tumor / genetics*
Ferroptosis*
Follow-Up Studies
Gene Expression Profiling
Humans
Nomograms*
Prognosis
ROC Curve
Retrospective Studies
Risk Factors
Survival Rate
Urinary Bladder Neoplasms / genetics
Urinary Bladder Neoplasms / mortality*
Urinary Bladder Neoplasms / pathology

Substances

Biomarkers, Tumor