Dataset Information

Gene methylation profiles as prognostic markers in ovarian clear cell and endometrioid adenocarcinomas.

ABSTRACT: Ovarian cancer is a cancer of high mortality. Aberrant gene methylation of tumor suppressor genes has been shown to be related to the development of malignancy. This study aimed to investigate the methylation of various genes in ovarian clear cell adenocarcinoma (OCCA) and ovarian endometrioid adenocarcinoma (OEA) and evaluate methylation biomarkers in terms of patient chemo-response and outcome. Eight candidate genes from 66 OCCA and 51 OEA patients were evaluated by methylation-specific polymerase chain reaction and capillary electrophoresis. Clinico-pathological parameters and patient outcomes were analyzed. The frequencies of gene methylation in RASSF1A (79% vs. 59%, p=0.025), E-cadherin (30% vs. 10%, p=0.011), and DLEC1 (71% vs. 43%, p=0.003) were higher in the patients with OCCA than in those with OEA. The chemo-resistant group had a significantly higher percentage of E-cadherin methylation (36.7% vs. 16.1%, p=0.036) than the chemo-sensitive group. In multivariate analysis (log-rank test), advanced stage (4.79 [2.10-10.94], p<0.001) was the only risk factor for mortality. Those with methylation of more than two out of three genes (E-cadherin, DLEC1, and SFRP5) had a shorter disease-free survival (1.89 [1.07-3.32], p=0.028) and overall survival (3.29 [1.57-6.87], p=0.002) than those with methylation of one or no gene. In advanced-stage malignancies, those with more than two out of the three gene methylations also had a shorter overall survival (3.86 [1.63-9.09], p=0.002) than those with methylation of only one or no gene. Patients with OCCA have different patterns of gene methylation than those with OEA. Methylation of the E-cadherin, DLEC1 and SFRP5 genes can be a prognostic biomarker for OCCA and OEA.

SUBMITTER: Chen CA

PROVIDER: S-EPMC4346531 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Gene methylation profiles as prognostic markers in ovarian clear cell and endometrioid adenocarcinomas.

Chen Chi-An CA Chiang Ying-Cheng YC Chang Ming-Cheng MC Hu Yu-Hao YH You San-Lin SL Cheng Yeu-Yao Kevin YY Chou Cheng-Yang CY Cheng Wen-Fang WF

American journal of translational research 20150115 1

Ovarian cancer is a cancer of high mortality. Aberrant gene methylation of tumor suppressor genes has been shown to be related to the development of malignancy. This study aimed to investigate the methylation of various genes in ovarian clear cell adenocarcinoma (OCCA) and ovarian endometrioid adenocarcinoma (OEA) and evaluate methylation biomarkers in terms of patient chemo-response and outcome. Eight candidate genes from 66 OCCA and 51 OEA patients were evaluated by methylation-specific polyme ...[more]

PMID: 25755836

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Project description:Ovarian cancer, the second most common gynecological malignancy, accounts for 3% of all cancers among women in the United States, and has a high mortality rate, largely because existing therapies for widespread disease are rarely curative. Ovarian endometrioid adenocarcinoma (OEA) accounts for about 20% of the overall incidence of all ovarian cancer. We have used proteomics profiling to characterize low stage (FIGO stage 1 or 2) versus high stage (FIGO stage 3 or 4) human OEAs. In general, the low stage tumors lacked p53 mutations and had frequent CTNNB1, PTEN, and/or PIK3CA mutations. The high stage tumors had mutant p53, were usually high grade, and lacked mutations predicted to deregulate Wnt/?-catenin and PI3K/Pten/Akt signaling. We utilized 2-D liquid-based separation/mass mapping techniques to elucidate molecular weight and pI measurements of the differentially expressed intact proteins. We generated 2-D protein mass maps to facilitate the analysis of protein expression between both the low stage and high stage tumors. These mass maps (over a pI range of 5.6-4.6) revealed that the low stage OEAs demonstrated protein over-expression at the lower pI ranges (pI 4.8-4.6) in comparison to the high stage tumors, which demonstrated protein over-expression in the higher pI ranges (pI 5.4-5.2). These data suggest that both low and high stage OEAs have characteristic pI signatures of abundant protein expression probably reflecting, at least in part, the different signaling pathway defects that characterize each group. In this study, the low stage OEAs were distinguishable from high stage tumors based upon the proteomic profiles. Interestingly, when only high-grade (grade 2 or 3) OEAs were included in the analysis, the tumors still tended to cluster according to stage, suggesting that the altered protein expression was not solely dependent upon tumor cell differentiation. Further, these protein profiles clearly distinguish OEA from other types of ovarian cancer at the protein level.

Project description:BackgroundCholangiocarcinoma (CCA) is a rare disease, but it is amongst the most lethal cancers with a median survival under 1 year. Variations in DNA methylation and gene expression have been extensively studied in other cancers for their role in pathogenesis and disease prognosis, but these studies are very limited in CCA. This study focusses on the identification of DNA methylation and gene expression prognostic biomarkers using multi-omics data of CCA tumors from The Cancer Genome Atlas (TCGA).MethodWe have conducted a genome-wide analysis of differential DNA methylation and gene/miRNA expression using data from 36 CCA tumor and 9 normal samples from TCGA. The impact of DNA methylation in promoters and long-range distal enhancers on the regulation and expression of CCA-associated genes was examined using linear regression. Next, we conducted network analyses on genes which are regulated by DNA methylation as well as by miRNA. Finally, we performed Kaplan-Meier and Cox proportional hazards regression analyses in order to identify the role of selected methylation sites and specific genes and miRNAs in patient survival. We also performed real-time quantitative PCR (qPCR) to confirm the change in gene expression in CCA patients' tumor and adjacent normal samples.ResultsAltered DNA methylation was observed on 12,259 CpGs across all chromosomes, of which 78% were hypermethylated. We observed a strong negative relationship between promoter hypermethylation and corresponding gene expression in 92% of the CpGs. Differential expression analyses revealed altered expression patterns in 3,305 genes and 101 miRNAs. Finally, we identified 17 differentially methylated promoter CpGs, 72 differentially expressed genes, and two miRNAs that are likely associated with patient survival. Pathway analysis suggested that cell division, bile secretion, amino acid metabolism, PPAR signaling, hippo signaling were highly affected by gene expression and DNA methylation alterations. The qPCR analysis further confirmed that MDK, HNF1B, PACS1, and GLUD1 are differentially expressed in CCA.ConclusionBased on the survival analysis, we conclude that DEPDC1, FUT4, MDK, PACS1, PIWIL4 genes, miR-22, miR-551b microRNAs, and cg27362525 and cg26597242 CpGs can strongly support their use as prognostic markers of CCA.

Project description:BackgroundCurrent risk models for renal cell carcinoma (RCC) based on clinicopathological factors are sub-optimal in accurately identifying high-risk patients. Here, we perform a head-to-head comparison of previously published DNA methylation markers and propose a potential prognostic model for clear cell RCC (ccRCC).Patients and methodsPromoter methylation of PCDH8, BNC1, SCUBE3, GREM1, LAD1, NEFH, RASSF1A, GATA5, SFRP1, CDO1, and NEURL was determined by nested methylation-specific PCR. To identify clinically relevant methylated regions, The Cancer Genome Atlas (TCGA) was used to guide primer design. Formalin-fixed paraffin-embedded (FFPE) tissue samples from 336 non-metastatic ccRCC patients from the prospective Netherlands Cohort Study (NLCS) were used to develop a Cox proportional hazards model using stepwise backward elimination and bootstrapping to correct for optimism. For validation purposes, FFPE ccRCC tissue of 64 patients from the University Hospitals Leuven and a series of 232 cases from The Cancer Genome Atlas (TCGA) were used.ResultsMethylation of GREM1, GATA5, LAD1, NEFH, NEURL, and SFRP1 was associated with poor ccRCC-specific survival, independent of age, sex, tumor size, TNM stage or tumor grade. Moreover, the association between GREM1, NEFH, and NEURL methylation and outcome was shown to be dependent on the genomic region. A prognostic biomarker model containing GREM1, GATA5, LAD1, NEFH and NEURL methylation in combination with clinicopathological characteristics, performed better compared to the model with clinicopathological characteristics only (clinical model), in both the NLCS and the validation population with a c-statistic of 0.71 versus 0.65 and a c-statistic of 0.95 versus 0.86 consecutively. However, the biomarker model had limited added prognostic value in the TCGA series with a c-statistic of 0.76 versus 0.75 for the clinical model.ConclusionIn this study we performed a head-to-head comparison of potential prognostic methylation markers for ccRCC using a novel approach to guide primers design which utilizes the optimal location for measuring DNA methylation. Using this approach, we identified five methylation markers that potentially show prognostic value in addition to currently known clinicopathological factors.

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Gene methylation profiles as prognostic markers in ovarian clear cell and endometrioid adenocarcinomas.

Publications

Gene methylation profiles as prognostic markers in ovarian clear cell and endometrioid adenocarcinomas.

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