SWI/SNF complex alterations predict immunotherapy response in bladder cancer.

BACKGROUND: Immune checkpoint inhibitors have revolutionized the treatment of urothelial bladder cancer (UBC), yet response remains limited to a subset of patients. The SWItch/sucrose non-fermentable (SWI/SNF) chromatin remodeling complex is recurrently altered across cancers, but its prevalence, functional impact, and predictive value in UBC remain unclear. This study aimed to comprehensively delineate the mutational spectrum of SWI/SNF genes in UBC and assess their utility as predictive biomarkers for response to immune checkpoint blockade. METHODS: We analyzed tumor specimens from 49 patients in the Daping Cohort and integrated data from five independent public cohorts comprising 2,280 cases in total. Somatic alterations were identified using targeted or whole-exome sequencing, and transcriptomic profiles were obtained from RNA sequencing datasets. Survival outcomes were evaluated using Kaplan-Meier survival analysis and time-dependent ROC curves. Tumor immune landscape was characterized via xCell-based deconvolution and corroborated by multiplex immunofluorescence on institutional samples. Prognostic modeling was performed across 65 machine-learning configurations, encompassing survival SVM, CoxBoost, and stepwise Cox, with external validation in independent cohorts. RESULTS: SWI/SNF alterations were present in 42.8% of UBCs, with the highest frequencies in ARID1A, ARID1B, ARID2, SMARCA4, and PBRM1. Tumors harboring these alterations displayed higher tumor mutational burden, increased neoantigen load, an immune-inflamed microenvironment, and a significantly improved overall survival following immune checkpoint blockade (p < 0.05). Genotype-specific models achieved strong prognostic discrimination (C-index > 0.75), with AUCs up to 0.909 in SWI/SNF-mutant and 0.772 in wild-type tumors, substantially outperforming single-modality biomarkers. CONCLUSIONS: SWI/SNF alterations define an immunotherapy-responsive stratification of UBC. The accompanying genotype-specific prognostic models provide a ready-to-test framework for guiding precision immunotherapy.