Prognostic value of immunogenic cell death genes in bladder cancer

Abstract

Abstract Background: The poor prognosis of bladder cancer (BLCA) highlights the need for the development of an effective and accurate prognostic model that can guide its diagnosis and treatment. Accumulating evidence suggest that immunogenic cell death (ICD) genes are involved in the BLCA tumorigenesisand which indicate their promise for the development of novel cell death-targeted treatments. Methods: We extracted 433 BLCA samples from The Cancer Genome Atlas and screened them with univariate Cox, multivariate, and lasso Cox regression analyses. We identified 19 ICD-related differentially expressed genes (DEGs) and used these to create a risk model. The effectiveness of the model was verified using two independent clinical datasets, GSE13507 and GSE32894, while its predictive ability was analyzed via Kaplan-Meier and receiver operating characteristic curve analyses of survival. Finally, we used decision curve analysis to evaluate the 1-, 3-, and 5-year clinical effectiveness of the prognostic model. Conclusions: We established a risk prognostic model based on ICD-related DEGs in BLCA. This model demonstrated high predictive accuracy for the overall survival of patients with BLCA, paving the way for an improved understanding of the disease.