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Cuproptosis, a recently identified form of cell death, is closely linked to glycolysis; however, the mechanistic interplay between these processes in clear cell renal cell carcinoma (ccRCC) remains to be fully elucidated. Utilizing data from the TCGA and CPTAC databases, we developed and validated a cuproptosis-glycolysis-related gene (CuG) scoring model to investigate its associations with clinical outcomes, tumor immune infiltration, immunotherapy response, and drug sensitivity. Our analysis established a robust 10-gene risk model with significant prognostic value that effectively stratifies ccRCC patients into distinct high- and low-risk groups exhibiting marked differences in clinical profiles and therapeutic responses. Through integrated bioinformatic analyses alongside in vitro and in vivo experimental validation, we identified AURKA as a key functional regulator within this signature. Beyond promoting tumor cell proliferation, migration, and invasion, AURKA may have a significant role in modulating antitumor immunity. Collectively, by establishing a clinically applicable prognostic scoring system and nominating AURKA as a potential therapeutic target, our study offers translational implications for treatment decision-making in ccRCC.