Disulfidptosis related immune genes drive prognostic model development and tumor microenvironment characterization in bladder urothelial carcinoma

The intricate nature and varied forms of bladder urothelial carcinoma (BLCA) highlight the need for new indicators to define tumor prognosis. Disulfidptosis, a novel form of cell death, is closely linked to BLCA progression, prognosis, and treatment outcomes. Our current goal is to develop a novel disulfidptosis-related immune prognostic model to enhance BLCA treatment strategies. Utilizing RNA-seq data from The Cancer Genome Atlas (TCGA) , which included 419 patients (19 normal, 400 tumor), we performed weighted gene co-expression network analysis (WGCNA) to identify disulfidptosis-associated immune genes. Through multivariate Cox regression, and the least absolute shrinkage and selection operator (LASSO) regularization, we established a disulfidptosis-related immune risk scoring system. A nomogram combining risk score and clinical features predicted prognosis. Model performance was validated through survival curve analysis and independent validation cohort. Immune checkpoints, cell infiltration, and tumor mutation load were assessed. Differential gene enrichment analysis was conducted. Prognostic genes were validated via in vitro experiments. Eight immune genes related to disulfidptosis were identified and verified in BLCA prognosis. A prognostic model outperformed previous ones in predicting overall survival (OS) for high- and low-risk groups. Patients with low-risk scores had higher OS rates and tumor mutation burden (TMB) compared to high-risk score patients. CD4 memory T cells, CD8 T cells, M1 macrophages, and resting NK cells were found to be higher in the low-risk group. Immune checkpoint inhibitor (ICI) treatment may be more effective for the low-risk score group. High-risk score group exhibited stronger correlation with cancer malignant pathways. Knocking out tumor necrosis factor receptor superfamily member 12 A (TNFRSF12A) inhibits BLCA cell proliferation and invasion while overexpressing it has the opposite effect. We constructed a novel risk score model that combines disulfidptosis and immune genes, demonstrating good prognostic prediction performance. We discovered and verified that the TNFRSF12A gene is an oncogene in BLCA, which may help provide personalized guidance for individualized treatment and immunotherapy selection for BLCA patients to a certain extent.