Abstract

BackgroundClear cell Renal Cell Carcinoma (ccRCC) is the frequently diagnosed histological life-threatening tumor subtype in the urinary system. Integrating multi-omics data is emerging as a tool to provide a comprehensive view of biology and disease for better therapeutic interventions. MethodWe have integrated freely available ccRCC data sets of genome-wide DNA methylome, transcriptome, and active histone modification marks, H3K27ac, H3K4me1, and H3K4me3 specific ChIP-seq data to screen genes with higher expression. Further, these genes were filtered based on their effect on survival upon alteration in expression. ResultsThe six multi-omics-based identified genes, RUNX1, MSC, ADA, TREML1, TGFA, and VWF, showed higher expression with enrichment of active histone marks and hypomethylated CpG in ccRCC. In continuation, the identified genes were validated by an independent dataset and showed a correlation with nodal and metastatic status. Furthermore, gene ontology and pathway analysis revealed that immune-related pathways are activated in ccRCC patients. ConclusionsThe network analysis of six overexpressed genes suggests their potential role in an immunosuppressive environment, leading to tumor progression and poor prognosis. Our study shows that the multi-omics approach helps unravel complex biology for patient subtyping and proposes combination strategies with epi-drugs for more precise immunotherapy in ccRCC.

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