Derivation and external validation of dendritic cell-related gene signatures for predicting prognosis and immunotherapy efficacy in bladder urothelial carcinoma

Abstract

Background: In the regulation of tumor-related immunity, dendritic cells (DCs) are crucial sentinel cells; they are powerful to present antigens and initiate immune responses. Therefore, we concentrated on investigating the DC-related gene profile, prognosis, and gene mutations in bladder urothelial carcinoma (BLCA) patients to identify sensitivity to immunotherapy of patients. Methods: According to DC infiltration, BLCA patients were divided into two subgroups, and differentially expressed genes (DEGs) were obtained. Patients were classified by unsupervised clustering into new subgroups. The least absolute shrinkage and selection operator (LASSO) regression analysis and Cox regression were used to develop a DC-related risk model. CIBERSORT, xCell, and GSEA were used to infer immune cells’ relative abundance separately and enriched immune pathways. Results: A total of 29 prognosis-related DEGs were identified from the unsupervised cluster. Among them, 22 genes were selected for constructing the DC-related risk model. The dendritic cell-related risk score (DCRS) can accurately distinguish patients with different sensitive responses to immunotherapy and overall survival outcomes. Furthermore, patients with ryanodine receptor 2 (RYR2) mutation had a better prognosis. Conclusions: The DCRS played an essential part in immunity pathway and formation of TME diversity. Our study indicated that RYR2 mutation combined with DCRS is useful for predicting the prognosis and discovering appropriate patients for immunotherapy.