Integrated bioinformatics analysis identifies a Ferroptosis-related gene signature as prognosis model and potential therapeutic target of bladder cancer

Zonglai Liu; Dan Du; Shizhong Zhang

doi:10.1093/toxres/tfae010

Integrated bioinformatics analysis identifies a Ferroptosis-related gene signature as prognosis model and potential therapeutic target of bladder cancer

Toxicol Res (Camb). 2024 Jan 27;13(1):tfae010. doi: 10.1093/toxres/tfae010. eCollection 2024 Feb.

Authors

Zonglai Liu^{1

2

3}, Dan Du³, Shizhong Zhang^{1

2}

Affiliations

¹ Hubei Key Laboratory of Tumor Microenvironment and Immunotherapy, China Three Gorges University, No. 8, University Avenue, Yichang 443002, Hubei Province, China.
² Medical College, China Three Gorges University, No. 8, University Avenue, Yichang 443002, Hubei Province, China.
³ Department of Urology, The Second People's Hospital of China Three Gorges University, The Second People's Hospital of Yichang, No. 21, Xiling 1st Road, Yichang 443008, Hubei Province, China.

PMID: 38292893
PMCID: PMC10822837 (available on 2025-01-27)
DOI: 10.1093/toxres/tfae010

Abstract

Background: Bladder cancer (BLCA) is one of the most prevalent cancers worldwide. Ferroptosis is a newly discovered form of non-apoptotic cell death that plays an important role in tumors. However, the prognostic value of ferroptosis-related genes (FRGs) in BLCA has not yet been well studied.

Method and materials: In this study, we performed consensus clustering based on FRGS and categorized BLCA patients into 2 clusters (C1 and C2). Immune cell infiltration score and immune score for each sample were computed using the CIBERSORT and ESTIMATE methods. Functional annotation of differentially expressed genes were performed by Gene Ontology (GO) and KEGG pathway enrichment analysis. Protein expression validation were confirmed in Human Protein Atlas. Gene expression validation were performed by qPCR in human bladder cancer cell lines lysis samples.

Result: C2 had a significant survival advantage and higher immune infiltration levels than C1. Additionally, C2 showed substantially higher expression levels of immune checkpoint markers than C1. According to the Cox and LASSO regression analyses, a novel ferroptosis-related prognostic signature was developed to predict the prognosis of BLCA effectively. High-risk and low-risk groups were divided according to risk scores. Kaplan-Meier survival analyses showed that the high-risk group had a shorter overall survival than the low-risk group throughout the cohort. Furthermore, a nomogram combining risk score and clinical features was developed. Finally, SLC39A7 was identified as a potential target in bladder cancer.

Discussion: In conclusion, we identified two ferroptosis-clusters with different prognoses using consensus clustering in BLCA. We also developed a ferroptosis-related prognostic signature and nomogram, which could indicate the outcome.

Keywords: Bladder cancer; Consensus clustering; Ferroptosis; Prognostic prediction model; Risk score.