Zhengbin Li, Zijian Ye, Tiantian Niu, Siqi Lin, Zhiyu Yin, Fangyu Zhao, Xin Zhang, Jianning Zhang, Yifan Zhang, Xin Zhu, Meijiao Wang, Biao Xie
Integrated single-cell RNA sequencing, bulk transcriptomic, and methylation data to identify macrophage subtypes and DNA methylation-associated prognostic subtypes in clear-cell renal cell carcinoma. Identified a three-gene signature (HLA-DRA, HCST, and RNASE2) with robust prognostic performance across external cohorts, validated by qRT-PCR. Discovered Dactolisib as a potential therapeutic agent through molecular docking.
Macrophages are the predominant immune cells in the tumor microenvironment of clear-cell renal cell carcinoma (ccRCC), but the role of DNA methylation in regulating macrophage heterogeneity remains unclear. Integrating single-cell RNA sequencing, bulk transcriptomic, and methylation data, we identified six macrophage subtypes and three DNA methylation-associated prognostic subtypes. A three-gene signature (HLA-DRA, HCST, and RNASE2) demonstrated robust prognostic performance across external cohorts and was validated by qRT-PCR. Molecular docking identified Dactolisib as a potential therapeutic agent. These findings provide novel biomarkers and potential therapeutic targets for prognosis and personalized treatment of ccRCC.