An Integrated Immunometabolic Signature Predicts Prognosis and Immunotherapy Response in ccRCC and Identifies UCN-Mediated Immune Evasion as a Therapeutic Vulnerability: Evidence from In Vitro and In Vivo Studies

Background/Objectives: Clear cell renal cell carcinoma (ccRCC) involves complex interactions between immune evasion and metabolic reprogramming. This study aimed to characterize ccRCC through integrated immunometabolic profiling, develop a prognostic signature, and investigate the functional role of the key driver gene UCN using in vitro and in vivo approaches. Methods: Integrated immunometabolic profiling was performed to identify molecular subtypes and establish a prognostic gene signature. Two distinct molecular subtypes were identified, and a 9-gene Immune Metabolic Index (IMI) was constructed. The functional role of the key driver gene UCN was investigated through in vitro functional assays and in vivo xenograft models in BALB/c mice, including combination with PD-1 blockade. Results: Two molecular subtypes with significant survival differences (p < 0.001) were identified. The established IMI demonstrated high prognostic accuracy, with Area Under the Curve (AUC) values of 0.813, 0.751, and 0.779 at 1-, 3-, and 5-year intervals, respectively. UCN was identified as the highest-risk gene in the signature. Functional assays showed that UCN silencing significantly inhibited cell proliferation and migration (p < 0.05). In BALB/c mouse xenograft models, UCN silencing remodeled the tumor microenvironment by increasing CD8+ T cell infiltration and reducing regulatory T cells (p < 0.01). Furthermore, UCN knockdown significantly suppressed tumor growth and synergized with PD-1 blockade to enhance antitumor efficacy (p < 0.001). Conclusions: The IMI is a robust tool for risk stratification in ccRCC. Targeting the UCN-driven immunometabolic axis represents a promising therapeutic strategy to overcome immune resistance in ccRCC.