表观基因组
转录组
免疫系统
基因
生物
癌症研究
肾细胞癌
肿瘤微环境
癌症
肾透明细胞癌
细胞
计算生物学
DNA甲基化
免疫学
医学
基因表达
遗传学
肿瘤科
作者
Nikhil Gadewal,Abhiram Natu,Siddhartha Sen,Sukanya Rauniyar,Virupaksha Bastikar,Sanjay Gupta
标识
DOI:10.1016/j.bbagen.2024.130596
摘要
Clear 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. We 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. The 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. The 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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