Disulfide bond-related gene signature development for bladder cancer prognosis prediction and immune microenvironment characterization.

Bladder cancer is the fourth most common malignant tumor in men, with limited therapeutic biomarkers and heterogeneous responses to immunotherapy. Disulfide bond-driven cell death has emerged as a critical regulator of tumor progression and immune microenvironment remodeling. By integrating data from TCGA and GEO cohorts, we developed a Disulfide-Related Prognostic Signature (DRPS) using ten machine learning algorithms. Single-cell RNA sequencing (scRNA-seq) elucidated the cell subtype-specific expression patterns of disulfide bond regulatory genes, while immune microenvironment and drug sensitivity analyses validated its clinical translational potential. qRT-PCR experiments confirmed differential expression patterns of core genes in bladder cancer cell lines. The DRPS model, optimized by the StepCox[backward] algorithm, demonstrated robust prognostic accuracy across four validation cohorts (mean C-index = 0.658). High-risk patients exhibited an enhanced immunosuppressive microenvironment characterized by infiltrated activated cancer-associated fibroblasts, upregulated APC co-inhibition pathways, and elevated immune checkpoint expression. Notably, high DRPS scores were associated with primary resistance to immunotherapy but showed increased sensitivity to anti-tumor agents such as Elephantine and Leflunomide. This study establishes a novel DRPS that serves as a predictive indicator for bladder cancer prognosis and pan-cancer immunotherapy efficacy.