Identification of Tumor Suppressors and Oncogenes from Genomic and Epigenetic Features in Ovarian Cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Kazimierz Wrzeszczynski
PROVIDER: E-GEOD-28015 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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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: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:This SuperSeries is composed of the following subset Series: GSE16598: Tumor T1 Sectors GSE16599: Tumor T2 Sectors GSE16600: Tumor T3 Sectors GSE16601: Tumor T4 Sectors GSE16602: Tumor T5 Sectors GSE16603: Tumor T6 Sectors GSE16604: Tumor T7 Sectors GSE16605: Tumor T8 Sectors GSE16606: Tumor T9 Sectors GSE16607: Tumor T10 Sectors GSE16608: Tumor T11 Sectors GSE16609: Tumor T12 Sectors GSE16610: Tumor T13 Sectors GSE16611: Tumor T14 Sectors GSE16663: Tumor T15 Sectors GSE16664: Tumor T16 Sectors GSE16665: Tumor T17 Sectors GSE16667: Tumor T18 Sectors GSE16668: Tumor T19 Sectors GSE16669: Tumor T20 Sectors ROMA CGH experiments were conducted on four to six dissected sectors (S1-S6) from single primary ductal carcinomas (T1-T20). T1-T4 were analyzed by sectoring and analysis by ROMA. T5-T20 were analyzed using the Sector-Ploidy-Profiling (SPP) Approach. SPP involves macro-dissecting the tumor, flow-sorting nuclei by differences in total genomic DNA content and profiling the genome of the tumor subpopulations. The genomic DNA from each tumor was labeled with Cy5 and a reference fibroblast genome was labeled with Cy3 and cohybridized to a ROMA microarray (85K or 390K). Experiments were performed in color-reversal by dye-swapping samples and hybridizing the labeled DNA to a second microarray for T1-T15 experiments, but not for T16-T20 experiments.
2009-07-10 | E-GEOD-16672 | biostudies-arrayexpress
Project description:DNA copy number profiling for all primary tumor samples and HCC cell lines was performed by ROMA, a form of comparative genomic hybridization. The aim was to identify commonly amplifiied and deleted regions across human HCC. 88 primary HCC samples and 12 human HCC cell lines were analyzed.
2011-01-10 | E-GEOD-22916 | biostudies-arrayexpress
Project description:DNA copy number profiling for all primary tumor samples and cell lines was performed by ROMA, a form of comparative genomic hybridization. The aim was to identify commonly amplifiied and deleted regions. 538 primary tumor samples and 253 human cell lines were analyzed.
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Project description:Distinct molecular subtypes of breast carcinomas have been identified, but translation into clinical use has been limited. We have developed two platform independent algorithms to explore genomic architectural distortion using array comparative genomic hybridization (aCGH) data to measure 1) whole arm gains and losses (WAAI) and 2) complex rearrangements (CAAI). By applying CAAI and WAAI to data from 595 breast cancer patients we were able to separate the cases into eight subgroups with different distribution of genomic distortion. Within each subgroup data from expression analyses, sequencing and ploidy indicated that progression occurs along separate paths into more complex genotypes. Histological grade had prognostic impact only in the Luminal related groups while the complexity identified by CAAI had an overall independent prognostic power. This study emphasizes the relationship between structural genomic alterations, molecular subtype and clinical behavior, and provides a score of genomic complexity as a new tool for prognostication in breast cancer. Array CGH of 255 breast tumor samples vs a male skin fibroblast reference sample, in color reversal.
2009-12-15 | E-GEOD-19425 | biostudies-arrayexpress
Project description:The following CGH experiments were conducted on four sectors (S1-S4) from a single primary ductal carcinoma tumor (T16) using the Sector-Ploidy-Profiling (SPP) Approach. SPP involves macro-dissecting the tumor, flow-sorting nuclei by differences in total genomic DNA content and profiling the genome of the tumor subpopulations. The genomic DNA from each tumor subpopulation was labeled with Cy5 and hybridized to an 390K Rubble-Rep ROMA Microarray. A normal reference male fibroblast was labeled with Cy3 as a control. Samples were cohybridize to the same single microarray.
2010-05-16 | E-GEOD-16664 | biostudies-arrayexpress
Project description:The following CGH experiments were conducted on four sectors (S1-S4) from a single primary ductal carcinoma tumor (T20) using the Sector-Ploidy-Profiling (SPP) Approach. SPP involves macro-dissecting the tumor, flow-sorting nuclei by differences in total genomic DNA content and profiling the genome of the tumor subpopulations. The genomic DNA from each tumor subpopulation was labeled with Cy5 and hybridized to an 390K Rubble-Rep ROMA Microarray. A normal reference male fibroblast was labeled with Cy3 as a control. Samples were cohybridize to the same single microarray.
2010-05-16 | E-GEOD-16669 | biostudies-arrayexpress
Project description:The following CGH experiments were conducted on six sectors (S1-S6) from a single primary ductal carcinoma tumor (T19) using the Sector-Ploidy-Profiling (SPP) Approach. SPP involves macro-dissecting the tumor, flow-sorting nuclei by differences in total genomic DNA content and profiling the genome of the tumor subpopulations. The genomic DNA from each tumor subpopulation was labeled with Cy5 and hybridized to an 390K Rubble-Rep ROMA Microarray. A normal reference male fibroblast was labeled with Cy3 as a control. Samples were cohybridize to the same single microarray.
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