Background Clear cell renal cell carcinoma (ccRCC) is highly heterogeneous, and robust biomarkers for risk stratification and therapeutic guidance remain limited. Methods We integrated single-cell RNA sequencing (scRNA-seq) of tumor and adjacent tissues with multi-cohort transcriptomic validation. High-dimensional weighted gene co-expression network analysis (hdWGCNA) was applied to identify pathogenic immune subsets and candidate genes. Prognostic modeling was performed using CoxBoost, and UBE2S function was validated by in vitro knockdown assays. Results scRNA-seq revealed extensive remodeling of the tumor microenvironment, highlighting NK cell subpopulations with strong intercellular signaling. hdWGCNA identified 12 core genes enriched in protein processing and MAPK pathways, with UBE2S emerging as the top driver. A CoxBoost-based 12-gene signature demonstrated robust predictive accuracy across independent datasets. Functionally, UBE2S knockdown suppressed ccRCC cell proliferation and migration, while immune correlation analyses linked UBE2S to altered tumor immunogenicity and genomic stability. Conclusions Our study identifies NK cell subsets and UBE2S as key contributors to ccRCC progression and establishes a clinically relevant 12-gene prognostic model, offering potential targets for precision therapy.
Leng et al. (Thu,) studied this question.