Identification of a lactylation-related prognostic signature and the critical role of CCNA2 in driving clear cell renal cell carcinoma progression

This study was designed to construct a prognostic signature for clear cell renal cell carcinoma (ccRCC) using lactylation‑related genes (LRGs) with aberrant expression, assess its capacity in predicting clinical outcomes, tumor immune microenvironment characteristics, and drug responsiveness, and explore the biological function of the hub gene CCNA2 in driving malignant progression of ccRCC. Transcriptomic and clinical information of ccRCC were retrieved from the TCGA database, with E-MTAB-1980 as the external validation cohort. Differentially expressed LRGs were screened, and a prognostic score was constructed and validated via machine learning. Tumor immune microenvironment and drug sensitivity were analyzed, and the function of CCNA2 and its effect on lactylation were verified by cellular experiments. 45 LRGs with significant differential expression were identified, and a 15-gene prognostic model was established. The model was an independent prognostic indicator for ccRCC with good predictive performance. The high-risk group was associated with advanced phenotypes, immunosuppression, sorafenib resistance, and higher sensitivity to sunitinib. CCNA2 exhibited markedly elevated expression in ccRCC and correlated with poor prognosis; its knockdown inhibited malignant phenotypes and lactylation levels, which could be reversed by exogenous sodium lactate. The LRG-based prognostic model can accurately predict ccRCC prognosis and treatment response. CCNA2 is a key molecule mediating lactylation-regulated ccRCC progression, providing new targets and strategies for precise diagnosis and treatment of ccRCC.