Dataset Information

Integrated analysis of gene expression and DNA methylation profiles in ovarian cancer.

ABSTRACT: BACKGROUND:Ovarian cancer is an epithelial malignancy that intrigues people for its poor outcome and lack of efficient treatment, while methylation is an important mechanism that have been recognized in many malignancies. In this study, we attempt to assess abnormally methylated gene markers and pathways in ovarian cancer by integrating three microarray datasets. METHODS:Three datasets including expression (GSE26712 and GSE66957) and methylation (GSE81224) datasets were accessed. GEO2R platform was used to detect abnormally methylated-differentially expressed genes. Protein-protein interaction (PPI) networks were built and analysed for hypermethylated and hypermethylated differentially expressed genes using Cytoscape software and Mcode app. GEPIA and cBioPortal platforms were used to validate the expression of the hub genes and the correlation between their mRNA expressions and methylation levels. Kaplan Meier-plotter platform were used to assess the prognostic significance of the hub genes. RESULTS:Six hundred eighty-one hypomethylated-upregulated genes were detected and involved in Rap1 signaling pathway, biosynthesis of amino acids, endocrine resistance, apoptosis, pathways in cancer. The hub genes were TNF, UBC, SRC, ESR1, CDK1, PECAM1, CXCR4, MUC1, IKBKG. Additionally, 337 hypermethylated-downregulated genes were detected and involved in pathways in cancer, focal adhesion, sphingolipid signaling pathway, EGFR tyrosine kinase inhibitor resistance, cellular senescence. The hub genes were BDNF, CDC42, CD44, PPP2R5C, PTEN, UBB, BMP2, FOXO1, KLHL2. TNF, ESR1, MUC1, CD44, PPP2R5C, PTEN, UBB and FOXO1 showed significant negative correlation between their mRNA expressions and methylation levels. TNF, ESR1 and FOXO1 showed prognostic significance. CONCLUSIONS:Two novel gene networks were found for ovarian cancer. TNF, ESR1, MUC1 and FOXO1 are our candidate genes that might take part in ovarian cancer progression in an epigenetic approach, TNF, ESR1 and FOXO1 may serve as potential markers for ovarian cancer prognosis evaluation.

SUBMITTER: Gong G

PROVIDER: S-EPMC7082962 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Integrated analysis of gene expression and DNA methylation profiles in ovarian cancer.

Gong Guanghui G Lin Ting T Yuan Yishu Y

Journal of ovarian research 20200319 1

<h4>Background</h4>Ovarian cancer is an epithelial malignancy that intrigues people for its poor outcome and lack of efficient treatment, while methylation is an important mechanism that have been recognized in many malignancies. In this study, we attempt to assess abnormally methylated gene markers and pathways in ovarian cancer by integrating three microarray datasets.<h4>Methods</h4>Three datasets including expression (GSE26712 and GSE66957) and methylation (GSE81224) datasets were accessed. ...[more]

PMID: 32192517

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Project description:Cisplatin and carboplatin are the primary first-line therapies for the treatment of ovarian cancer. However, resistance to these platinum-based drugs occurs in the large majority of initially responsive tumors, resulting in fully chemoresistant, fatal disease. Although the precise mechanism(s) underlying the development of platinum resistance in late-stage ovarian cancer patients currently remains unknown, CpG-island (CGI) methylation, a phenomenon strongly associated with aberrant gene silencing and ovarian tumorigenesis, may contribute to this devastating condition.To model the onset of drug resistance, and investigate DNA methylation and gene expression alterations associated with platinum resistance, we treated clonally derived, drug-sensitive A2780 epithelial ovarian cancer cells with increasing concentrations of cisplatin. After several cycles of drug selection, the isogenic drug-sensitive and -resistant pairs were subjected to global CGI methylation and mRNA expression microarray analyses. To identify chemoresistance-associated, biological pathways likely impacted by DNA methylation, promoter CGI methylation and mRNA expression profiles were integrated and subjected to pathway enrichment analysis.Promoter CGI methylation revealed a positive association (Spearman correlation of 0.99) between the total number of hypermethylated CGIs and GI50 values (i.e., increased drug resistance) following successive cisplatin treatment cycles. In accord with that result, chemoresistance was reversible by DNA methylation inhibitors. Pathway enrichment analysis revealed hypermethylation-mediated repression of cell adhesion and tight junction pathways and hypomethylation-mediated activation of the cell growth-promoting pathways PI3K/Akt, TGF-beta, and cell cycle progression, which may contribute to the onset of chemoresistance in ovarian cancer cells.Selective epigenetic disruption of distinct biological pathways was observed during development of platinum resistance in ovarian cancer. Integrated analysis of DNA methylation and gene expression may allow for the identification of new therapeutic targets and/or biomarkers prognostic of disease response. Finally, our results suggest that epigenetic therapies may facilitate the prevention or reversal of transcriptional repression responsible for chemoresistance and the restoration of sensitivity to platinum-based chemotherapeutics.

Project description:BackgroundThe incidence of cholangiocarcinoma (CCA) has risen in recent years, and it has become a significant health burden worldwide. However, the mechanisms underlying tumorigenesis and progression of this disease remain largely unknown. An increasing number of studies have demonstrated crucial biological functions of epigenetic modifications, especially DNA methylation, in CCA. The present study aimed to identify and analyze methylation-regulated differentially expressed genes (MeDEGs) involved in CCA tumorigenesis and progression by bioinformatics analysis.MethodsThe gene expression profiling dataset (GSE119336) and gene methylation profiling dataset (GSE38860) were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were identified using the limma packages of R and GEO2R, respectively. The MeDEGs were obtained by overlapping the DEGs and DMGs. Functional enrichment analyses of these genes were then carried out. Protein-protein interaction (PPI) networks were constructed using STRING and visualized in Cytoscape to determine hub genes. Finally, the results were verified based on The Cancer Genome Atlas (TCGA) database.ResultsWe identified 98 hypermethylated, downregulated genes and 93 hypomethylated, upregulated genes after overlapping the DEGs and DMGs. These genes were mainly enriched in the biological processes of the cell cycle, nuclear division, xenobiotic metabolism, drug catabolism, and negative regulation of proteolysis. The top nine hub genes of the PPI network were F2, AHSG, RRM2, AURKB, CCNA2, TOP2A, BIRC5, PLK1, and ASPM. Moreover, the expression and methylation status of the hub genes were significantly altered in TCGA.ConclusionsOur study identified novel methylation-regulated differentially expressed genes (MeDEGs) and explored their related pathways and functions in CCA, which may provide novel insights into a further understanding of methylation-mediated regulatory mechanisms in CCA.

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Integrated analysis of gene expression and DNA methylation profiles in ovarian cancer.

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Integrated analysis of gene expression and DNA methylation profiles in ovarian cancer.

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