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Comprehensive methylome analysis of ovarian tumors reveals hedgehog signaling pathway regulators as prognostic DNA methylation biomarkers.

ABSTRACT: Women with advanced stage ovarian cancer (OC) have a five-year survival rate of less than 25%. OC progression is associated with accumulation of epigenetic alterations and aberrant DNA methylation in gene promoters acts as an inactivating "hit" during OC initiation and progression. Abnormal DNA methylation in OC has been used to predict disease outcome and therapy response. To globally examine DNA methylation in OC, we used next-generation sequencing technology, MethylCap-sequencing, to screen 75 malignant and 26 normal or benign ovarian tissues. Differential DNA methylation regions (DMRs) were identified, and the Kaplan-Meier method and Cox proportional hazard model were used to correlate methylation with clinical endpoints. Functional role of specific genes identified by MethylCap-sequencing was examined in in vitro assays. We identified 577 DMRs that distinguished (p < 0.001) malignant from non-malignant ovarian tissues; of these, 63 DMRs correlated (p < 0.001) with poor progression free survival (PFS). Concordant hypermethylation and corresponding gene silencing of sonic hedgehog pathway members ZIC1 and ZIC4 in OC tumors was confirmed in a panel of OC cell lines, and ZIC1 and ZIC4 repression correlated with increased proliferation, migration and invasion. ZIC1 promoter hypermethylation correlated (p < 0.01) with poor PFS. In summary, we identified functional DNA methylation biomarkers significantly associated with clinical outcome in OC and suggest our comprehensive methylome analysis has significant translational potential for guiding the design of future clinical investigations targeting the OC epigenome. Methylation of ZIC1, a putative tumor suppressor, may be a novel determinant of OC outcome.

SUBMITTER: Huang RL

PROVIDER: S-EPMC3857342 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature

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Comprehensive methylome analysis of ovarian tumors reveals hedgehog signaling pathway regulators as prognostic DNA methylation biomarkers.

Huang Rui-Lan RL Gu Fei F Kirma Nameer B NB Ruan Jianhua J Chen Chun-Liang CL Wang Hui-Chen HC Liao Yu-Ping YP Chang Cheng-Chang CC Yu Mu-Hsien MH Pilrose Jay M JM Thompson Ian M IM Huang Hsuan-Cheng HC Huang Tim Hui-Ming TH Lai Hung-Cheng HC Nephew Kenneth P KP

Epigenetics 20130510 6

Women with advanced stage ovarian cancer (OC) have a five-year survival rate of less than 25%. OC progression is associated with accumulation of epigenetic alterations and aberrant DNA methylation in gene promoters acts as an inactivating "hit" during OC initiation and progression. Abnormal DNA methylation in OC has been used to predict disease outcome and therapy response. To globally examine DNA methylation in OC, we used next-generation sequencing technology, MethylCap-sequencing, to screen 7 ...[more]

PMID: 23774800

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Project description:BackgroundProstate cancer is a clinically heterogeneous disease with a subset of patients rapidly progressing to lethal-metastatic prostate cancer. Current clinicopathological measures are imperfect predictors of disease progression. Epigenetic changes are amongst the earliest molecular changes in tumourigenesis. To find new prognostic biomarkers to enable earlier intervention and improved outcomes, we performed methylome sequencing of DNA from patients with localised prostate cancer and long-term clinical follow-up.MethodsWe used whole-genome bisulphite sequencing (WGBS) to comprehensively map and compare DNA methylation of radical prostatectomy tissue between patients with lethal disease (n = 7) and non-lethal (n = 8) disease (median follow-up 19.5 years). Validation of differentially methylated regions (DMRs) was performed in an independent cohort (n = 185, median follow-up 15 years) using targeted multiplex bisulphite sequencing of candidate regions. Survival was assessed via univariable and multivariable analyses including clinicopathological measures (log-rank and Cox regression models).ResultsWGBS data analysis identified cancer-specific methylation patterns including CpG island hypermethylation, and hypomethylation of repetitive elements, with increasing disease risk. We identified 1420 DMRs associated with prostate cancer-specific mortality (PCSM), which showed enrichment for gene sets downregulated in prostate cancer and de novo methylated in cancer. Through comparison with public prostate cancer datasets, we refined the DMRs to develop an 18-gene prognostic panel. Applying this panel to an independent cohort, we found significant associations between PCSM and hypermethylation at EPHB3, PARP6, TBX1, MARCH6 and a regulatory element within CACNA2D4. Strikingly in a multivariable model, inclusion of CACNA2D4 methylation was a better predictor of PCSM versus grade alone (Harrell's C-index: 0.779 vs. 0.684).ConclusionsOur study provides detailed methylome maps of non-lethal and lethal prostate cancer and identifies novel genic regions that distinguish these patient groups. Inclusion of our DNA methylation biomarkers with existing clinicopathological measures improves prognostic models of prostate cancer mortality, and holds promise for clinical application.

Project description:Ovarian cancer (OC) is a major health threat to females, as it has high morbidity and mortality. Evidence has increasingly demonstrated that long non-coding RNAs (lncRNAs) regulate OC progression and they may have value as early diagnostic biomarkers, prognostic biomarkers and/or therapeutic targets. In the present study, the regulatory mechanisms and prognosis associated with cancer-specific lncRNAs and their related competing endogenous (ce)RNA network in OC were investigated. The differential expression profiles and prognostic significance of lncRNAs and mRNAs were systematically explored based on data from 359 OC cases from The Cancer Genome Atlas and 180 healthy individuals from the Genotype-Tissue Expression database. Functional enrichment analyses, RNA-RNA interactome prediction, ceRNA network analysis, correlation analysis and survival analysis were utilized to identify hub lncRNAs and biomarkers associated with OC diagnosis or prognosis. A total of 1,049 differentially expressed lncRNAs and 6,516 differentially expressed mRNAs between OC and healthy tissues were detected. An lncRNA-micro (mi)RNA-mRNA regulatory network in OC was further established, containing 91 lncRNAs, 23 miRNAs and 179 mRNAs. After survival analysis based on the expression of the RNAs in the ceRNA network, 8 lncRNAs, 4 miRNAs and 11 mRNAs that were significantly associated with OC patient survival (P<0.05) were obtained. Using least absolute shrinkage and selection operator-penalized Cox regression, an eight-lncRNA risk score model was generated, which was able to readily discriminate between OC and healthy individuals and predict the survival of patients with OC. In addition, the differential expression of several key lncRNAs and mRNAs was verified by reverse transcription-quantitative PCR and western blot analysis. The current study presents a novel lncRNA-miRNA-mRNA network, which provides insight into the potential pathogenesis of OC and allows the identification of prognostic biomarkers and treatment strategies for OC.

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Comprehensive methylome analysis of ovarian tumors reveals hedgehog signaling pathway regulators as prognostic DNA methylation biomarkers.

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Comprehensive methylome analysis of ovarian tumors reveals hedgehog signaling pathway regulators as prognostic DNA methylation biomarkers.

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