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Prostate cancer (PRAD) progression varies significantly among patients, with metabolic reprogramming linked to oncogenesis and immune response. However, the prognostic and immune-related roles of metabolic reprogramming-related genes (MRGs) in PRAD remain unclear. PRAD transcriptomic, mutation, and clinical data from TCGA were analyzed. WGCNA identified PRAD-associated gene modules. NMF clustering stratified patients into two molecular subgroups. Prognostic MRGs were screened via univariate Cox and LASSO regression. A gene-based prognostic model was established and validated using ROC, PCA, and Kaplan-Meier analyses. A clinical-variable nomogram predicted survival, with external validation via GEO data set GSE70770. Immune traits of subtypes/risk groups were assessed via ESTIMATE, CIBERSORT, and ssGSEA. Drug sensitivity and gene expression (qRT-PCR) were evaluated. Two metabolic subtypes with distinct survival and immune patterns were identified. A four-gene signature (AKR1C2, PITPNM3, PLA2G5, UCK2) formed a prognostic model. Risk stratification revealed groups with divergent survival rates. High-risk patients exhibited poorer outcomes, reduced immune infiltration, and altered drug sensitivity. The MRG prognostic model stratifies PRAD patients by survival and immune landscape, aiding precision immunotherapy and drug discovery.