Development of a prognostic model related to mitochondria and programmed cell death-related genes in bladder cancer.

Background: Various forms of programmed cell death (PCD) play a crucial role in regulating the development and spread of cancer, with mitochondria serving as key organelles involved in executing PCD. In this study, mitochondrial and PCD-related prognostic genes in bladder cancer (BLCA) were explored, and prognostic models were constructed. Methods: The GSE32894, GSE13507, and The Cancer Genome Atlas (TCGA)-BLCA datasets related to BLCA were retrieved. The intersection genes of differentially expressed genes (DEGs) between BLCA and control samples in TCGA-BLCA, mitochondrial-related genes (MRGs), and PCD-related genes (PCD-RGs) were obtained for univariate and multivariate Cox regression analysis. Prognostic genes were selected, and a prognostic model was developed. Then, the validity of the model was evaluated and subsequently validated in the GSE32894 dataset. To enhance the clinical precision of the model, a nomogram was developed and combined with clinical traits. Enrichment analysis, immune infiltration analysis, and drug sensitivity analysis were employed. Finally, the expressions of prognostic genes were verified in the GSE13507 and TCGA-BLCA datasets and by real-time quantitative polymerase chain reaction (RT-qPCR). Results: Based on the above analysis, five prognostic genes (POLB, FASN, CASP9, VDAC2, and RHOT2) were selected, and a prognostic model was constructed, which revealed a strong predictive capability for sample survival in both the TCGA-BLCA and GSE32894 datasets. Meanwhile, the risk scores of BLCA samples in TCGA-BLCA were calculated, and samples were divided into high- and low-risk categories based on the optimal threshold. Further analysis found that risk score, stage, and age were independent prognostic factors, and they were used to construct the nomogram. Thereafter, we observed that pathways (e.g., epithelial-mesenchymal transition (EMT) and inflammatory response) related to BLCA were markedly enriched in the high-risk patients, and the response to immunotherapy in high-risk patients was suboptimal. Importantly, the expression trends of FASN, VDAC2, and RHOT2 in the BLCA and control groups within the TCGA-BLCA and GSE13507 datasets, as well as in clinical samples, were consistent and significant. Conclusion: In this study, a novel prognostic model for bladder cancer was constructed based on POLB, FASN, CASP9, VDAC2, and RHOT2, which provided preliminary references for the prognostic evaluation of bladder cancer and subsequent studies related to its diagnosis and treatment.