Ontology highlight
ABSTRACT:
PROVIDER: PRJNA137991 | ENA |
REPOSITORIES: ENA
Similar Datasets
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. Expression data accompaniment to CSHL ROMA and MOMA3 human ovarian analysis. Correlation of expression to Methylation and Copy Number Variation in ovarian cancer.
2011-10-16 | E-GEOD-27943 | biostudies-arrayexpress
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. Expression data accompaniment to CSHL ROMA and MOMA3 human ovarian analysis.
2011-10-17 | GSE27943 | 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.
2011-10-17 | GSE27940 | 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. This ROMA experiment was performed on Ovarian Tumor samples using the same platform as previously reported by Navin, N. et. al. Genome Res. 2010 Jan;20(1):68-80 (PMID: 19903760). Analysis of the array data was performed as previously reported in Chen, S. et. al. Cancer Biol Ther. 2008 Nov;7(11):1793-802. (PMID: 18836286 ).
2011-10-17 | GSE28013 | 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: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. This ROMA experiment was performed on Ovarian Tumor samples using the same platform as previously reported by Navin, N. et. al. Genome Res. 2010 Jan;20(1):68-80 (PMID: 19903760). Analysis of the array data was performed as previously reported in Chen, S. et. al. Cancer Biol Ther. 2008 Nov;7(11):1793-802. (PMID: 18836286 ). The genomic DNA from each tumor was labeled with Cy5 and hybridized to an 85K Bgl2 ROMA Microarray. A normal reference male fibroblast was labeled with Cy3 as a control. The value data repesents a log ratio. (As previously reported Chen, S. et. al. Cancer Biol Ther. 2008 Nov;7(11):1793-802. PMID: 18836286 ).
2011-10-16 | E-GEOD-28013 | biostudies-arrayexpress
Project description:miRNAs are involved in cancer development and progression,acting as tumor suppressors or oncogenes. Half of the human miRNAs are located in cancer-associated genomic regions and can function as tumor suppressor genes or oncogenes depending on their targets miRNA profiling was performed on paired bladder cancer tissues and differentially expressed miRNAs were identified in BC and adjacent noncancerous tissues of any disease stage/grade.
2012-07-07 | GSE39093 | GEO
Project description:Tumor suppressors are mostly defined by inactivating somatic mutations in tumors, yet little is known about their epigenetic features in normal cells. Here, through integrative analysis of 1,134 genome-wide epigenetic profiles and mutations from >8,200 tumor-normal pairs, we discovered broad H3K4me3 (wider than 4 kb) as the first epigenetic signature for tumor suppressors in normal cells. Broad H3K4me3 is associated with increased transcription elongation and enhancer activity together leading to exceptionally high gene expression, and is distinct from other broad epigenetic features, such as super enhancers. Broad H3K4me3 conserved across normal cells represents core tumor suppressors, such as P53 and PTEN, whereas cell-type-specific broad H3K4me3 may indicate cell-identity genes and cell-type-specific tumor suppressors. Furthermore, widespread shortening of broad H3K4me3 in cancers is strongly associated with repression of tumor suppressors. Together, the broad H3K4me3 epigenetic signature we reported here may provide a new direction for the discovery and characterization of novel tumor suppressors. H3K4me3 ChIP-Seq was conducted in 1) liver tumor and matched tissue, 2) lung tumor and matched tissue, 3) cell line A549 grown under normal and flavopiridol treatment conditions.
2015-07-29 | E-GEOD-67471 | biostudies-arrayexpress
Project description:Tumor suppressors are mostly defined by inactivating somatic mutations in tumors, yet little is known about their epigenetic features in normal cells. Here, through integrative analysis of 1,134 genome-wide epigenetic profiles and mutations from >8,200 tumor-normal pairs, we discovered broad H3K4me3 (wider than 4 kb) as the first epigenetic signature for tumor suppressors in normal cells. Broad H3K4me3 is associated with increased transcription elongation and enhancer activity together leading to exceptionally high gene expression, and is distinct from other broad epigenetic features, such as super enhancers. Broad H3K4me3 conserved across normal cells represents core tumor suppressors, such as P53 and PTEN, whereas cell-type-specific broad H3K4me3 may indicate cell-identity genes and cell-type-specific tumor suppressors. Furthermore, widespread shortening of broad H3K4me3 in cancers is strongly associated with repression of tumor suppressors. Together, the broad H3K4me3 epigenetic signature we reported here may provide a new direction for the discovery and characterization of novel tumor suppressors.
2015-07-29 | GSE67471 | GEO
Project description:Epigenetic aberrations are a hallmark of cancer; however, we have limited information on chromatin aberrations present in cancer cells. Here we provide genome-wide maps for histone modification binding for 6 reference histone markers in 145 cancer cell lines belonging to 9 cancer types generating 680 chromatin maps. NMF clustering for H3K27ac-defined enhancers classified cancer cells into 5 distinct subtypes. These subtypes were either correlated with the developmental trajectory of original tissue or cell phenotype such as mesenchymal features. We identify a cluster consisting of different tumor types but with a unique enhancer profile and its dependency on key oncogenes. Detailed characterization of bivalent state switches between cancer cells and their normal counterparts identified epithelial-to-mesenchymal driver transcription factors to be activated via this mechanism in breast, GBM and melanomas. Finally, we identify cancer-specific lengthening of H3K4me3 domains on oncogenes and their shortening on specific tumor-suppressors, respectively. Overall, our study provides epigenome reference maps for widely-used cancer cell lines which will be useful for discovery of important principles about chromatin mediated cancer gene regulation.
2026-07-03 | GSE142751 | GEO