Breast, colon, glioblastoma, lung, melanoma, ovarian, pancreas, prostate tumors and cell lines.
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE31586 | GEO | 2011/08/24
SECONDARY ACCESSION(S): PRJNA145601
REPOSITORIES: GEO
Similar Datasets
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.
2011-08-23 | E-GEOD-31586 | 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.
2011-01-10 | GSE22916 | GEO
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: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. 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. 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: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:Copy number profiling of 36 ovarian tumors on Affymetrix 100K SNP arrays Thirty-six ovarian tumors were profiled for copy-number alterations with the Affymetrix 100K Mapping Array. Copy number profiling of 36 ovarian tumors on Affymetrix 500K SNP arrays Sixteen ovary tumors were profiled for copy-number alterations with the high-resolution Affymetrix 500K Mapping Array.
2010-12-16 | GSE26075 | 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:Highly rearranged and mutated cancer genomes present major challenges in the identification of pathogenetic events driving the cancer process. Here, we engineered lymphoma-prone mice with chromosomal instability to assess the utility of mouse models in cancer gene discovery and the extent of cross-species overlap in cancer-associated copy number aberrations. Integrating with targeted re-sequencing, our comparative oncogenomic studies efficiently identified FBXW7 and PTEN as commonly deleted or mutated tumor suppressors in human T-cell acute lymphoblastic leukemia/lymphoma (T-ALL). More generally, the murine cancers acquire widespread recurrent clonal amplifications and deletions targeting loci syntenic to alterations present in not only human T-ALL but also diverse tumors of hematopoietic, mesenchymal and epithelial types. These results thus support the view that murine and human tumors experience common biological processes driven by orthologous genetic events as they evolve towards a malignant phenotype. The highly concordant nature of genomic events encourages the use of genome unstable murine cancer models in the discovery of biologically relevant driver events in human cancer. Keywords: comparative genomic hybridization
2007-06-05 | GSE7599 | GEO