Integrated Transcriptomic Analysis Identifies a Six-Gene Prognostic Signature, RNA Editing Derived Neoantigens, and miRNA Regulatory Networks in Renal Cell Carcinoma.

Background: are frequent, their integrated effects on tumor biology, RNA editing, and non-coding RNA regulation remain unclear. This study aims to integrate genetic, epigenetic, and immune features to provide mechanistic insights into RCC progression and support precision immuno-oncology and vaccine development. Methods: Transcriptomic data from TCGA-KIRC and four Gene Expression Omnibus (GEO) cohorts were normalized, batch-corrected, and integrated. Differentially expressed genes were analyzed using LASSO-Cox regression, Kaplan-Meier survival, ROC curves, and nomogram modeling. RNA editing events from REDIportal were annotated for nonsynonymous substitutions and assessed for human leukocyte antigen (HLA) class I binding. Parallel miRNA-mRNA analyses identified regulatory interactions. Functional enrichment and immune LASSO deconvolution were used to explore pathways and tumor microenvironment features. Results: mutations with reduced NK/Treg infiltration and identified chromatin genes associated with endothelial and immune activity. Conclusion: This integrative study identifies a six-gene signature, recurrent RNA editing-derived neoantigens, and miRNA networks in RCC. By connecting genomic, epigenetic, and immune features, it provides mechanistic insights into RCC progression and supports precision immuno-oncology and vaccine development.