The team drew on transcriptomic and clinical data from the TCGA database, using the independent E-MTAB-1980 cohort for external validation. After screening, they identified 45 lactylation-related genes that were differentially expressed in ccRCC. Using machine learning, they distilled these into a 15-gene prognostic model whose risk score proved to be an independent prognostic indicator with good predictive performance.

When patients were stratified by the model, the high-risk group was associated with advanced phenotypes, an immunosuppressive tumor immune microenvironment, and resistance to sorafenib, alongside higher sensitivity to sunitinib. The authors suggest this pattern could help inform targeted therapy choices for ccRCC patients.

The hub gene CCNA2 was markedly elevated in ccRCC tumors and correlated with poor prognosis. In cellular experiments, knocking down CCNA2 inhibited malignant phenotypes and reduced lactylation levels within the cells. Adding exogenous sodium lactate reversed these effects, indicating that lactate availability can restore the changes that CCNA2 knockdown produced.

These cellular findings position CCNA2 as a candidate molecule mediating lactylation-regulated ccRCC progression, but they are preclinical observations in cell models and do not by themselves establish a therapeutic benefit for patients. The authors conclude that the lactylation-based model can accurately predict ccRCC prognosis and treatment response, and that CCNA2 offers a new target for the precise diagnosis and treatment of this cancer. Because the published version is an early, citable release of the peer-reviewed accepted manuscript, further edits may appear in the final Version of Record.

Subject of Research: A lactylation-related prognostic gene signature and the role of CCNA2 in clear cell renal cell carcinoma progression

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

Article References: Lin, J., Liu, C., Zhang, M., Luo, J., Wu, Z., Luo, X., Liang, Y., & Chen, G. (2026). Identification of a lactylation-related prognostic signature and the critical role of CCNA2 in driving clear cell renal cell carcinoma progression. BMC Cancer. https://doi.org/10.1186/s12885-026-17141-5

Image Credits: AI Generated

DOI: 10.1186/s12885-026-17141-5

Keywords: clear cell renal cell carcinoma, lactylation, prognostic signature, CCNA2, machine learning, kidney cancer, TCGA, sunitinib, sorafenib, tumor immune microenvironment, Identification, lactylation-related