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

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 fr...

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Published inBiochimica et biophysica acta. General subjects Vol. 1868; no. 5; p. 130596
Main Authors Gadewal, Nikhil, Natu, Abhiram, Sen, Siddhartha, Rauniyar, Sukanya, Bastikar, Virupaksha, Gupta, Sanjay
Format Journal Article
LanguageEnglish
Published Netherlands Elsevier B.V 01.05.2024
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Abstract 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. [Display omitted] •Integrative analysis predicts six overexpressed genes in ccRCC.•The overexpressed genes associate with nodal and metastatic status of patients.•Network analysis showed association of genes with immunosuppressive environment.•Genes may be a potential marker in stratification for immunotherapy in ccRCC.
AbstractList 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.
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.
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. [Display omitted] •Integrative analysis predicts six overexpressed genes in ccRCC.•The overexpressed genes associate with nodal and metastatic status of patients.•Network analysis showed association of genes with immunosuppressive environment.•Genes may be a potential marker in stratification for immunotherapy in ccRCC.
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.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.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.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.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.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.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.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.
ArticleNumber 130596
Author Rauniyar, Sukanya
Sen, Siddhartha
Natu, Abhiram
Bastikar, Virupaksha
Gupta, Sanjay
Gadewal, Nikhil
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Keywords TREML1
ccRCC
VWF
DNA methylation
Histone modification
TGFA
Epigenome
MSC
ADA
Immune system
RUNX1
Language English
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Snippet Clear cell Renal Cell Carcinoma (ccRCC) is the frequently diagnosed histological life-threatening tumor subtype in the urinary system. Integrating multi-omics...
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SubjectTerms Carcinoma, Renal Cell - genetics
Carcinoma, Renal Cell - pathology
ccRCC
chromatin immunoprecipitation
data collection
DNA
DNA methylation
Epigenome
Gene Expression Profiling
gene ontology
histology
histone code
Histone modification
histones
Humans
Immune system
immunosuppression
immunotherapy
Kidney Neoplasms - genetics
Kidney Neoplasms - pathology
metastasis
multiomics
neoplasm progression
patients
prognosis
Receptors, Immunologic - genetics
renal cell carcinoma
transcriptome
Transcriptome - genetics
Tumor Microenvironment - genetics
Title Integrative epigenome-transcriptome analysis unravels cancer-specific over-expressed genes potentially regulating immune microenvironment in clear cell renal cell carcinoma
URI https://dx.doi.org/10.1016/j.bbagen.2024.130596
https://www.ncbi.nlm.nih.gov/pubmed/38471632
https://www.proquest.com/docview/2956684984
https://www.proquest.com/docview/3153575195
Volume 1868
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