CpG islands Methylation Profiling by DMH in Epithelial Ovarian Cancer: Screening Set
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Wei Dai
PROVIDER: E-GEOD-23240 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:We have systematically profiled DNA methylation at promoter CpG islands (CGIs) in ovarian cancer. Epithelial ovarian tumours, excluding mucinous and clear cell cancers, prospectively collected through a cohort study, were analyzed by differential methylation hybridization (DMH) (Nouzova M et al, 2004) in duplicates. The loci targeted by the custom-designed microarray are the promoter CpG islands (Gardiner-Garden and Frommer, 1987) of the genes involved in the Wnt, p53, AKT/mTOR, BRCA1/2 and Redox pathways, DNA repair (HR, NHEJ and MMR), FA family and IgLON family.
2011-06-01 | GSE23240 | GEO
Project description:The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to identify genes critical to the development and progression of cancer. We provide a bioinformatic analysis of copy number variation and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We individually examined the copy number variation and DNA methylation for 44 primary ovarian cancer samples and 7 ovarian normal samples using our MOMA-ROMA technology and Affymetrix expression data as well as 379 tumor samples analyzed by The Cancer Genome Atlas. We have identified 346 genes with significant deletions or amplifications among the tumor samples. Utilizing associated gene expression data we predict 156 genes with significantly altered copy number and correlated changes in expression. We identify changes in DNA methylation and expression for all amplified and deleted genes. We predicted 615 potential oncogenes and tumor suppressors candidates by integrating these multiple genomic and epigenetic data types. We have developed a method to profile genome wide methylation. 7 ovarian normal samples and 44 tumor samples from other individuals were analyzed for CpG methylation. After inter array normalization, the tumor samples were taken together and the methylation compared to that of the normal samples to identify regions of the CpG islands that are significantly altered between the two datasets. Some of these regions were validated for their methylation as a proof of principle for the method. Kamalakaran S., et. al. Mol Oncol. 2011;5:77-92 (PMID: 21169070).
2011-10-16 | E-GEOD-27940 | biostudies-arrayexpress
Project description:Epithelial ovarian cancer is the leading cause of death from gynecological malignancies. Currently platinum-based chemotherapy, coupled with a taxane based drug is the primary treatment for ovarian cancer. Approximately 25% of patients either present with or rapidly develop resistance to platinum based chemotherapy and all recurrent tumors ultimately become resistant. Epigenetic modifications have been associated with tumor formation and progression and may contribute to therapy response. We performed a methylation screen on a set of tumors and have found a number of genes and family members differentially methylated between resistant patients and sensitive patients. Here we show that loss of expression of CHD3, a member of the Mi-2/NuRD complex, causes increased resistance to platinum chemotherapy drugs. Additionally, ovarian cell lines transcriptionally silenced for CHD3 are more invasive, have migratory ability, and display a transformed epithelial to mesenchymal (EMT) phenotype. Taken together, we provide the first evidence of a role for CHD3 as an important epigenetic regulator of chemoresistance in ovarian cancer and hypothesize EMT as one of the underlying mechanisms. Furthermore, CHD3 expression might represent a therapy response predictor and could be a future therapeutic target for ovarian cancer. We have developed a method to profile genome wide methylation. 71 ovarian tumor samples and 9 normal tissue samples from individuals were analyzed for CpG methylation. Some of these regions were validated for their methylation as a proof of principle for the method. Kamalakaran S., et. al. Mol Oncol. 2011;5:77-92 (PMID: 21169070).
2012-05-14 | E-GEOD-33011 | biostudies-arrayexpress
Project description:Methylation of CpG islands associated with genes can affect the expression of the proximal gene, and methylation of non associated CpG islands correlates to genomic instability. This epigenetic modification has been shown to be important in many pathologies, from development and disease to cancer. We report the development of a novel high-resolution microarray that detects the methylation status of over 25,000 CpG islands in the human genome. Experiments were performed to demonstrate low system noise in the methodology and that the array probes have a high signal to noise ratio. Methylation measurements between different cell lines were validated demonstrating the accuracy of measurement. We then identified alterations in CpG islands, both those associated with gene promoters, as well as non-promoter associated islands in a set of breast and ovarian tumors. We demonstrate that this methodology accurately identifies methylation profiles in cancer and in principle it can differentiate any CpG methylation alterations and can be adapted to analyze other species. We have developed a method to profile genome wide methylation. 7 ovarian normal samples and 11 tumor samples from other individuals were analyzed for CpG methylation. After inter array normalization, the tumor samples were taken together and the methylation compared to that of the normal samples to identify regions of the CpG islands that are significantly altered between the two datasets. Some of these regions were validated for their methylation as a proof of principle for the method.
2010-05-19 | E-GEOD-15747 | biostudies-arrayexpress
Project description:We report a new method for genome-wide methylation profiling that is able to probe methylation status in both single-copy DNA and interspersed repeats. This method, MethylMAPS, uses methylation-sensitive and -dependent enzymes to fractionate the genome according to methylation state. Methylated and unmethylated fragments are then sequenced with Next-Gen sequencing to map methylated and unmethylated CpG sites in the genome. We have used this method to determine the methylation status of >275 million CpG sites in human and mouse DNA from breast and brain tissues. We conclude that methylation is the default state of most CpG dinucleotides and that a combination of local dinucleotide frequencies, the interaction of repeated sequences, and the presence or absence of histone variants or modifications shields a population of CpG sites (most of which are in and around promoters) from DNA methyltransferases that lack intrinsic sequence specificity. Genome-wide methylation mapping in two normal human breast tissues, human brain tissue and mouse brain tissue.
2010-04-16 | E-GEOD-21242 | biostudies-arrayexpress
Project description:Methylation of CpG islands associated with genes can affect the expression of the proximal gene, and methylation of non associated CpG islands correlates to genomic instability. This epigenetic modification has been shown to be important in many pathologies, from development and disease to cancer. We report the development of a novel high-resolution microarray that detects the methylation status of over 25,000 CpG islands in the human genome. Experiments were performed to demonstrate low system noise in the methodology and that the array probes have a high signal to noise ratio. Methylation measurements between different cell lines were validated demonstrating the accuracy of measurement. We then identified alterations in CpG islands, both those associated with gene promoters, as well as non-promoter associated islands in a set of breast and ovarian tumors. We demonstrate that this methodology accurately identifies methylation profiles in cancer and in principle it can differentiate any CpG methylation alterations and can be adapted to analyze other species. We have developed a method to profile genome wide methylation. 12 breast normal samples and matching tumors from these individuals and an additional 28 tumor samples from other individuals were analyzed for CpG methylation. After inter array normalization, the tumor samples were taken together and the methylation compared to that of the normal samples to identify regions of the CpG islands that are significantly altered between the two datasets. Some of these regions were validated for their methylation as a proof of principle for the method.
2009-04-28 | E-GEOD-15746 | biostudies-arrayexpress
Project description:CpG islands Methylation Profiling by DMH in Epithelial Ovarian Cancer: Screening Set
| PRJNA131437 | ENA
Project description:This SuperSeries is composed of the following subset Series: GSE27940: Methylation detection Oligonucleotide Microarray Analysis: high resolution method for CpG island methylation detection 3. GSE27943: Gene Expression Array of Human Ovarian Cancer. GSE28013: Representational Oligonucleotide Microarray Analysis (ROMA) array for Copy Number Variation Detection. Refer to individual Series
2011-10-16 | E-GEOD-28015 | biostudies-arrayexpress
Project description:The complexity of the maize (Zea mays) genome makes it an ideal system for the study of both genetics and epigenetics. Here, we generated the integrated maps of transcriptomes and epigenomes of shoots and roots of two maize inbred lines and their reciprocal hybrids, and globally surveyed the epigenetic variations and their relationships with transcriptional divergence between different tissues and different genotypes. We observed that whereas histone modifications vary both between tissues and between genotypes, DNA methylation patterns are more distinguishable between genotypes than between tissues. Histone modifications were associated with transcriptomic divergence between tissues and between hybrids and parents. Further, we show that genes up-regulated in both shoots and roots of hybrids were significantly enriched in the nucleosome assembly pathway. Interestingly, 22- and 24-nt siRNAs were shown to be derived from distinct transposable elements (TEs), and for different TEs in both shoots and roots, the differences in siRNA activity between hybrids and patents were primarily driven by different siRNA species. Together, our results suggest that despite of the variations in specific genes or genomic loci, similar mechanisms may account for the genome-wide epigenetic regulation of gene activity and transposon stability in different tissues of maize hybrids. Genome-wide integrated maps of mRNA and small RNA (sRNA) transcriptomes, DNA methylomes and genome-wide distribution of three representative histone modifications (H3K4me3, H3K9ac and H3K36me3) in the shoots and roots of 14 day old seedlings of two maize inbred lines (B73 and Mo17) and their reciprocal hybrids (B73 x Mo17 and Mo17 x B73).
2013-03-19 | E-GEOD-43142 | biostudies-arrayexpress
Project description:Methylation of CpG islands associated with genes can affect the expression of the proximal gene, and methylation of non associated CpG islands correlates to genomic instability. This epigenetic modification has been shown to be important in many pathologies, from development and disease to cancer. We report the development of a novel high-resolution microarray that detects the methylation status of over 25,000 CpG islands in the human genome. Experiments were performed to demonstrate low system noise in the methodology and that the array probes have a high signal to noise ratio. Methylation measurements between different cell lines were validated demonstrating the accuracy of measurement. We then identified alterations in CpG islands, both those associated with gene promoters, as well as non-promoter associated islands in a set of breast and ovarian tumors. We demonstrate that this methodology accurately identifies methylation profiles in cancer and in principle it can differentiate any CpG methylation alterations and can be adapted to analyze other species.
2009-04-28 | GSE15747 | GEO