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Research Paper|Volume 14, Issue 22|pp 9037—9055

Development and validation of a novel model for predicting the survival of bladder cancer based on ferroptosis-related genes

Lianjun Li1, Leizuo Zhao2, Bin Li1, Tengteng Wang1, Weiting Kang1, Zilian Cui1, Dongjian Liu2, Da Gu3
  • 1Department of Urology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250021, China
  • 2Department of Urology, Dongying People’s Hospital, Dongying, Shandong 257091, China
  • 3Department of Plastic Surgery, Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250013, China
Received: June 24, 2022Accepted: November 7, 2022Published: November 17, 2022
https://doi.org/10.18632/aging.204385

Copyright: © 2022 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

The role of ferroptosis, a new form of cell death, in bladder cancer (BC) has not been sufficiently studied. This study aimed to establish a prognostic prediction model for BC patients based on the expression profile of ferroptosis-related genes (FRG). The expression profiles of BC samples with clinical information were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). A total of 80 differentially expressed genes (DEGs) related to FRG were identified among which 37 DEGs were found to have a prognostic value. Eleven genetic markers including SLC2A12, CDO1, JDP2, MAFG, CAPG, RRM2, SLC2A3, SLC3A2, VDAC2, GCH1, and ANGPTL7 were identified through the LASSO regression analysis. The ROC curve analysis showed that the AUC was 0.702, 0.664, and 0.655 for the 1-year, 3-year, and 5-year survival outcomes, respectively. The prediction performance was verified in the TCGA-testing set and external set GSE13507. Multivariate Cox proportional hazards analysis showed that the risk score was an independent prognostic predictor. Moreover, we found differences in gene mutation, gene expression, and immune cell infiltration between the high and low-risk groups of BC patients. Finally, a nomogram was constructed by integrating clinical features and FRG signatures to predict the survival outcomes of BC patients. In addition, the differential expression of FRG mRNA and protein was verified through PCR and HPA online site. The characteristics of 11 FRG genes were examined and a prognostic nomogram for predicting the overall survival of BC was established.