Identification of Model Based on Oxidative Stress-related Genes for Predicting Prognosis and Therapeutic Features in Bladder Cancer

Background : Bladder cancer is one of the most common malignant tumors, presenting as a heterogenous entity that requires a severe stratified strategy to enhance clinical decision-making and patient counseling. Multiple studies have investigated the relationship between oxidative stress and tumor progression, highlighting its potential role in cancer pathogenesis. Herein, our study aimed to establish a prognostic model based on the oxidative stress-related gene for risk stratification in bladder cancer. Methods : Differentially expressed oxidative stress genes (oxidative stress DEGs) were identified using microarray and clinical data from the GEO database. Functional enrichment and survival analyses were performed in screened oxidative stress DEGs. A risk score model was constructed, and its diagnostic value and relationship with the prognosis as well as its sensitivity to chemotherapy and immunotherapy were verified through Cox regression, receiver operating characteristic curve and drug sensitivity analysis. The TCGA-BLCA cohort was set as the training cohort, GSE13507 and GSE32894 were used for external validation. A nomogram was constructed to facilitate the clinical application. Results : The risk score model demonstrated a significant difference in overall survival between the high- and low-risk groups. The area under the curve and hazard ratio revealed the independent prognostic value of the model. There are differences in the sensitivity of chemotherapy and immunotherapy between the high- and low-risk groups. Conclusions : Our findings provide a new prognostic model that can serve as a reliable reference for the prognosis and personalized therapy of patients with bladder cancer.