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Utilizing data from the TCGA and CPTAC databases, we developed and validated a cuproptosis\u2010glycolysis\u2013related 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\u2010gene risk model with significant prognostic value that effectively stratifies ccRCC patients into distinct high\u2010 and low\u2010risk 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\u2010making in ccRCC.<\/jats:p>","DOI":"10.1155\/humu\/6111105","type":"journal-article","created":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T23:01:57Z","timestamp":1778367717000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Cuproptosis\u2013Glycolysis Signature Predicts Prognosis and Highlights AURKA as a Therapeutic Target in 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