Abstract / Summary
Clear cell renal cell carcinoma (ccRCC) is characterized by prominent vascularization and cellular heterogeneity, but reliable biomarkers for angiogenesis and response to targeted therapy remain limited. In this study, transcriptomic data from GEO cohorts (GSE53757, GSE66271, GSE73731) and two validation datasets (GSE36895, GSE66270) were analyzed using WGCNA and multiple machine learning models. ANGPTL4, together with GPC3, SCARB1, and ADM, was identified as a candidate gene set. ANGPTL4 showed good diagnostic performance (AUC = 0.857) and was positioned between angiogenesis- and lipid metabolism- related modules in the PPI network. Single-cell analysis indicated heterogeneous expression across epithelial and immune cells, and in silico knockout suggested enhanced T-cell–related signaling. ANGPTL4 was identified from a candidate set enriched for hypoxia-related genes and showed cell-type-specific expression in the single-cell dataset. In vitro, ANGPTL4 knockdown altered CCL5 secretion, NK-92-cell-associated phenotypes, and Matrigel network formation. These findings support an association of ANGPTL4 with hypoxia-related, immune, and vascular phenotypes in ccRCC; however, they do not establish direct mediation through the HIF–VEGF signaling axis.