Dataset Information

Comparative Correlation Structure of Colon Cancer Locus Specific Methylation: Characterisation of Patient Profiles and Potential Markers across 3 Array-Based Datasets.

ABSTRACT: Abnormal DNA-methylation is well known to play an important role in cancer onset and development, and colon cancer is no exception to this rule. Recent years have seen the increased use of large-scale technologies, (such as methylation microarray assays or specific sequencing of methylated DNA), to determine whole genome profiles of CpG island methylation in tissue samples. Comprehensive study of methylation array data from transcriptome high-throughput platforms permits determination of gene methylation markers, important for cancer profiling. Here, three large-scale methylation datasets for colon cancer have been compared to determine locus-specific methylation agreement. These data are from the GEO database, where colon cancer and apparently healthy adjacent tissues are represented by sample sizes 125 and 29 respectively in the first dataset, 24 of each in the second and 118 of each in the third. Several data analysis techniques have been employed, including Clustering, Discriminant Principal Component Analysis, Discriminant Analysis and ROC curves, in order (i) to obtain a better insight on the locus-specific concomitant methylation structures for these diverse data and (ii) to determine a robust potential marker set for indicative screening, drawn from all data taken together. The extent of the agreement between the analysed datasets is reported. Further, potential screening methylation markers, for which methylation profiles are consistent across tissue samples and several datasets, are highlighted and discussed.

SUBMITTER: Barat A

PROVIDER: S-EPMC4504116 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Comparative Correlation Structure of Colon Cancer Locus Specific Methylation: Characterisation of Patient Profiles and Potential Markers across 3 Array-Based Datasets.

Barat Ana A Ruskin Heather J HJ

Journal of Cancer 20150714 8

Abnormal DNA-methylation is well known to play an important role in cancer onset and development, and colon cancer is no exception to this rule. Recent years have seen the increased use of large-scale technologies, (such as methylation microarray assays or specific sequencing of methylated DNA), to determine whole genome profiles of CpG island methylation in tissue samples. Comprehensive study of methylation array data from transcriptome high-throughput platforms permits determination of gene me ...[more]

PMID: 26185542

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Project description:IntroductionAberrant DNA methylation has been found frequently in human breast cancers, associated with the loss of expression of a number of regulatory genes for growth and correlated to clinical outcomes. The present study was undertaken to determine whether methylation of a set of growth-suppressor genes would correlate to the expression of estrogen receptors (ERs) and progesterone receptors (PRs).MethodsWe used a pyrosequencing methylation analysis to study the methylation of 12 known growth-suppressor genes in 90 pairs of malignant/normal breast tissues. We also examined the expression of ERs and PRs in those specimens by immunohistochemistry. Mutations of p53 in tumor cells were detected by direct sequencing.ResultsTwelve tumor-suppressor genes: ARHI, RASSF1A, HIN-1, RARbeta2, hMLH1, 14-3-3 sigma, RIZ1, p16, E-cadherin, RIL, CDH13, and NKD2 were selected for this methylation study. Five of them (RIL, HIN-1, RASSF1A, CDH13, and RARbeta2) were frequently methylated in breast cancers (57%, 49%, 58%, 44%, and 17%, respectively) but not the normal breast (0-4%). Two panels of methylation profiles were defined. The methylation of the HIN-1/RASSFIA panel strongly correlated to the expression of ERs, PRs, and hormone receptors (HRs; which were defined as 'positive' if ERs and/or PRs were positive; p < 0.001). Conversely, the methylation of the RIL/CDH13 panel strongly correlated to negative ER, PR, and HR expression (p = 0.001, 0.025, and 0.001, respectively). The subset of triple-negative breast cancers (in other words, those with negative ER, PR, and HER-2/neu status) was positively associated with the methylation of the RIL/CDH13 panel and negatively associated with the HIN-1/RASSF1A panel. Mutations of p53 were found in nine breast tumors (11%), seven of which lacked methylation in both panels.ConclusionWe have defined two panels (HIN-1/RASSFIA, and RIL/CDH13) of methylation profiles, which correlated, either positively or negatively, to HR status.

Project description:BackgroundEpigenetic gene silencing is one of the major causes of carcinogenesis. Its widespread occurrence in cancer genome could inactivate many cellular pathways including DNA repair, cell cycle control, apoptosis, cell adherence, and detoxification. The abnormal promoter methylation might be a potential molecular marker for cancer management.MethodsFor rapid identification of potential targets for aberrant methylation in gynecological cancers, methylation status of the CpG islands of 34 genes was determined using pooled DNA approach and methylation-specific PCR. Pooled DNA mixture from each cancer type (50 cervical cancers, 50 endometrial cancers and 50 ovarian cancers) was made to form three test samples. The corresponding normal DNA from the patients of each cancer type was also pooled to form the other three control samples. Methylated alleles detected in tumors, but not in normal controls, were indicative of aberrant methylation in tumors. Having identified potential markers, frequencies of methylation were further analyzed in individual samples. Markers identified are used to correlate with clinico-pathological data of tumors using chi2 or Fisher's exact test.ResultsAPC and p16 were hypermethylated across the three cancers. MINT31 and PTEN were hypermethylated in cervical and ovarian cancers. Specific methylation was found in cervical cancer (including CDH1, DAPK, MGMT and MINT2), endometrial cancer (CASP8, CDH13, hMLH1 and p73), and ovarian cancer (BRCA1, p14, p15, RIZ1 and TMS1). The frequencies of occurrence of hypermethylation in 4 candidate genes in individual samples of each cancer type (DAPK, MGMT, p16 and PTEN in 127 cervical cancers; APC, CDH13, hMLH1 and p16 in 60 endometrial cancers; and BRCA1, p14, p16 and PTEN in 49 ovarian cancers) were examined for further confirmation. Incidence varied among different genes and in different cancer types ranging from the lowest 8.2% (PTEN in ovarian cancer) to the highest 56.7% (DAPK in cervical cancer). Aberrant methylation for some genes (BRCA1, DAPK, hMLH1, MGMT, p14, p16, and PTEN) was also associated with clinico-pathological data.ConclusionThus, differential methylation profiles occur in the three types of gynecologic cancer. Detection of methylation for critical loci is potentially useful as epigenetic markers in tumor classification. More studies using a much larger sample size are needed to define the potential role of DNA methylation as marker for cancer management.

Dataset Information

Comparative Correlation Structure of Colon Cancer Locus Specific Methylation: Characterisation of Patient Profiles and Potential Markers across 3 Array-Based Datasets.

Publications

Comparative Correlation Structure of Colon Cancer Locus Specific Methylation: Characterisation of Patient Profiles and Potential Markers across 3 Array-Based Datasets.

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