Use of Single-Cell Data and scPagwas Analysis to Identify T Cell Subsets and Construct a Prognostic Model for Clear Cell Renal Cell Carcinoma

    January 2026 in “ Human Mutation ”
    Xincheng Yi, Zongming Jia, Jixiang Wu, Siyu Wang, Yiqi Yu, Ying Kong, Xuefeng He, Yuhua Huang
    TLDR T cell subsets are crucial in kidney cancer, and a new model predicts patient outcomes using key genes.
    This study focused on clear cell renal cell carcinoma (KIRC) and aimed to construct new prognostic models to improve treatment decisions and explore therapeutic targets. By integrating various omics data and using the scPagwas algorithm, researchers identified T cell subsets as key in KIRC. They combined key genes from single-cell RNA seq data with differentially expressed genes, resulting in 86 intersecting genes enriched in immune-related pathways. A clinical prognostic model with seven risk genes was developed, showing substantial survival advantages for low-risk patients and excellent predictive value. DOCK8 was identified as a potential biomarker, with five drugs predicted to target it. The study provides insights into the immune microenvironment and potential targets for KIRC therapy.
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