Integrative epigenome-transcriptome analysis unravels cancer-specific over-expressed genes potentially regulating immune microenvironment in clear cell renal cell carcinoma

被引:1
作者
Gadewal, Nikhil [1 ,4 ]
Natu, Abhiram [2 ,3 ]
Sen, Siddhartha [1 ]
Rauniyar, Sukanya [2 ,3 ]
Bastikar, Virupaksha [4 ]
Gupta, Sanjay [2 ,3 ,5 ]
机构
[1] Tata Mem Hosp, Adv Ctr Treatment Res & Educ Canc, Bioinformat & Computat Biol Facil, Navi Mumbai 410210, MH, India
[2] Tata Mem Hosp, Canc Res Inst, Gupta Lab, Adv Ctr Treatment Res & Educ Canc,Epigenet & Chrom, Navi Mumbai 410210, MH, India
[3] Homi Bhabha Natl Inst, Training Sch Complex, Mumbai 400094, MH, India
[4] Amity Univ, Amity Inst Biotechnol, Ctr Computat Biol & Translat Res, Mumbai Pune Expressway, Mumbai 410206, MH, India
[5] Tata Mem Hosp, Adv Ctr Treatment Res & Educ Canc, Canc Res Inst, Kharghar 410210, MH, India
来源
BIOCHIMICA ET BIOPHYSICA ACTA-GENERAL SUBJECTS | 2024年 / 1868卷 / 05期
关键词
ccRCC; Epigenome; DNA methylation; Histone modification; Immune system; GROWTH-FACTOR-ALPHA; PROMOTES;
D O I
10.1016/j.bbagen.2024.130596
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Background: 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. Method: 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. Results: 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. Conclusions: 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 epidrugs for more precise immunotherapy in ccRCC.
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页数:9
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