Integrated multi‑dataset analysis identifies ADH6, ALDOC, PHKA2, and PNMA2 as novel candidate biomarkers for clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common and lethal subtype of kidney cancer, yet reliable diagnostic and prognostic biomarkers remain lacking. This study aimed to identify robust cross-dataset differentially expressed genes (DEGs) and novel prognostic biomarkers through integrative analysis. We integrated 12 GEO datasets (349 controls, 485 ccRCC) and TCGA (72 controls, 527 ccRCC). Common DEGs across all datasets were identified using standard criteria.Functional enrichment, GSEA, and CIBERSORT immune infiltration were performed. The AUC was calculated to evaluate gene discriminatory ability. Novel core genes were validated in TCGA and the Human Protein Atlas (HPA) at both mRNA and protein levels, with additional qRT-PCR validation in ccRCC cell lines. 83 upregulated and 77 downregulated common DEGs were identified. GSEA revealed consistent positive enrichment of immune- and inflammation-related pathways across all 12 datasets, and immune infiltration analysis showed a distinct microenvironment remodeling in ccRCC. Four previously unreported genes—ADH6, ALDOC, PHKA2, and PNMA2—were identified as candidate biomarkers. Univariate Cox regression demonstrated that high expression of each gene was significantly associated with better overall survival (HRs: 0.595–0.728, all P < 0.05), and multivariate analysis confirmed their independent prognostic value (HRs: 0.631–0.896, all P < 0.05). This study establishes a cross-dataset conserved transcriptomic and immune signature of ccRCC. ADH6, ALDOC, PHKA2, and PNMA2 are novel candidate biomarkers for diagnostic evaluation, prognosis, and potential immunotherapy.