DNA copy number profiling of 20 pancreatic cancer cell lines
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE41794 | GEO | 2012/11/01
SECONDARY ACCESSION(S): PRJNA178209
REPOSITORIES: GEO
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Project description:Genome wide copy number profiling of 20 PDAC cell lines to facilitate identification of novel tumor suppressor genes using an integrative genomics approach. Profiling of 20 commonly used PDAC cell lines
2012-11-01 | E-GEOD-41794 | biostudies-arrayexpress
Project description:Genome wide expression profiling of 20 PDAC cell lines and an immortalized non-malignant pancreatic duct cell line (HPDE) to facilitate identification of novel tumor suppressor genes using an integrative genomics approach Genome wide expression profiling of 20 PDAC cell lines and an immortalized non-malignant pancreatic duct cell line (HPDE) to facilitate identification of novel tumor suppressor genes using an integrative genomics approach RNA from the 21 samples was converted to Cy3 labeled cRNA and hybridized to the array; arrays were processed with GenePix software and median array normalization was performed
2012-11-01 | E-GEOD-40098 | biostudies-arrayexpress
Project description:Genome wide expression profiling of 20 PDAC cell lines and an immortalized non-malignant pancreatic duct cell line (HPDE) to facilitate identification of novel tumor suppressor genes using an integrative genomics approach Genome wide expression profiling of 20 PDAC cell lines and an immortalized non-malignant pancreatic duct cell line (HPDE) to facilitate identification of novel tumor suppressor genes using an integrative genomics approach
2012-11-01 | GSE40098 | GEO
Project description:Genome wide DNA methylation profiling of 20 PDAC cell lines and an immortalized non-malignant pancreatic duct cell line (HPDE) to facilitate identification of novel tumor suppressor genes using an integrative genomics approach Genome wide DNA methylation profiling of 20 PDAC cell lines and an immortalized non-malignant pancreatic duct cell line (HPDE) to identify novel tumor suppressor genes Bisulphite converted DNA from the 21 samples were hybridised to the Illumina Infinium 27k Human Methylation Beadchip
2012-11-01 | E-GEOD-40097 | biostudies-arrayexpress
Project description:Genome wide DNA methylation profiling of 20 PDAC cell lines and an immortalized non-malignant pancreatic duct cell line (HPDE) to facilitate identification of novel tumor suppressor genes using an integrative genomics approach Genome wide DNA methylation profiling of 20 PDAC cell lines and an immortalized non-malignant pancreatic duct cell line (HPDE) to identify novel tumor suppressor genes
2012-11-01 | GSE40097 | GEO
Project description:Background/Aims: Microarray-based comparative genomic hybridisation (CGH) has allowed high-resolution analysis of DNA copy number alterations across the entire cancer genome. Recent advances in bioinformatics tools enable us to perform a robust and highly sensitive analysis of array CGH data and facilitate the discovery of novel cancer-related genes. Methods: We analysed a total of 29 pancreatic ductal adenocarcinoma (PDAC) samples (six cell lines and 23 microdissected tissue specimens) using 1 Mb-spaced CGH arrays. The transcript levels of all genes within the identified regions of genetic alterations were then screened using our Pancreatic Expression Database. Results: In addition to 238 high-level amplifications and 35 homozygous deletions, we identified 315 minimal common regions of “non-random” genetic alterations (115 gains and 200 losses) which were consistently observed across our tumour samples. The small size of these aberrations (median size of 880 kb) contributed to the reduced number of candidate genes included (on average 12 Ensembl-annotated genes). The database has further specified the genes whose expression levels are consistent with their copy number status. Such genes were UQCRB, SQLE, DDEF1, SLA, ERICH1 and DLC1, indicating that these may be potential target candidates within regions of aberrations. Conclusion: This study has revealed multiple novel regions that may indicate the locations of oncogenes or tumour suppressor genes in PDAC. Using the database, we provide a list of novel target genes whose altered DNA copy numbers could lead to significant changes in transcript levels in PDAC. (Harada et al. Pancreatology) Keywords: pancreatic ductal adenocarcinima, tissue microdissection, array CGH, genetic alterations A panel of 23 microdissected PDAC tissues and 6 PDAC-derived cell lines were analysed using Sanger's CGH arrays with 1 Mb resolution. Clinical info of the samples used is provided as a supplementary file.
2008-12-16 | E-GEOD-9672 | biostudies-arrayexpress
Project description:Integrated profiling of somatic molecular alterations present in tumors is necessary to further our understanding of the tumorigenic process. We investigated the potential relationships between gene copy number alterations and DNA methylation profiles in a case series of pleural mesotheliomas (n=23). Gene copy number (CN) alterations profiled with 500K SNP arrays and DNA methylation measured at over 750 cancer-related genes with methylation bead-arrays were examined concomitantly. Considering each probed locus, there were no instances of significantly correlated CN alteration and methylation (no loci with Q < 0.05) and averaging loci over their associated genes revealed only two genes with significantly correlated CN and methylation alterations (Q < 0.04). In contrast to the lack of discrete correlations, the overall extent of tumor CN alteration was significantly associated with DNA methylation profile when comparing CN alteration extent among methylation profile classes (P < 0.02), and there was evidence that this association was partially attributable to prevalent allele loss observed at the maintenance DNA methyltransferase DNMT1. Taken together, this work indicates a strong association between global genetic and global epigenetic dysregulation in mesothelioma rather than a discrete, local coordination of gene inactivation, and further highlights the utility and necessity of integrative genomics approaches in cancer biology.
2010-07-01 | GSE21057 | GEO
Project description:We performed copy number analysis of high-grade osteosarcoma samples. in order to detect osteosarcoma drivers, we integrated these data with genome-wide gene expression data. We performed two different methods - a non-paired and a paired integrative analysis.
2012-03-28 | GSE33153 | GEO
Project description:Esophageal adenocarcinoma (EAC) is now the most common esophageal malignancy in the United States with >15,000 new cases per year. Prognosis for patients with EAC is poor due to both late diagnosis and early metastasis to lymph nodes. The goal of this study was to perform an integrated analysis of genome-wide DNA copy number changes, gene expression and patient clinical data in order to identify events and genes associated with clinical endpoints or that may play a key role in EAC development and therefore provide potential therapeutic targets. Specifically, we report on a series of 116 EAC specimens studied using Affymetrix SNP 6.0 and U133 Plus 2 GeneChip arrays plus additional cohorts of 73 and 114 EAC patients whose tumors were analyzed using Affymetrix StyI 250K arrays and fluorescence in-situ hybridization (FISH) respectively. Integration of this genomic data with clinical information and outcomes enabled identification of copy number changes and coordinate gene expression events that are associated with patient prognosis, that validate known or suspected oncogenes and tumor suppressor genes and that also facilitate identification of novel, putative driver genes in large regions of copy number gain and loss. These findings add to our understanding of the basic biology of EAC and provide a guide for development of novel prognostic tools and therapies.
2016-11-01 | GSE72660 | GEO
Project description:We performed copy number analysis of high-grade osteosarcoma samples. in order to detect osteosarcoma drivers, we integrated these data with genome-wide gene expression data. We performed two different methods - a non-paired and a paired integrative analysis. Copy number analysis was performed on 32 pre-treatment high-grade osteosarcoma diagnostic biopsies, of which 29 overlapped with the 84 samples used for gene expression analyses.
2012-03-27 | E-GEOD-33153 | biostudies-arrayexpress