Project description:Epigenetic modifications, particularly DNA methylation have been increasingly implicated in cancer. Although some genes display aberrant methylation in pancreatic cancer, a comprehensive global analysis is yet to be performed. To define the genome-wide pattern of DNA methylation in pancreatic ductal adenocarcinomas (PDAC), the methylation profile of 156 PDAC and 23 non-malignant pancreas was captured using high-density arrays. More than 90,000 CpG sites were significantly differentially methylated (DM) in PDAC relative to non-malignant pancreas, with pronounced alterations in a sub-set of 13,517 CpG sites. This sub-set of differentially methylated CpG sites segregated PDAC from non-malignant pancreas, regardless of tumour cellularity. As expected, PDAC hyper-methylation was most prevalent in the 5’ region of genes (including the proximal promoter, 5’UTR and CpG islands). From 3981 genes aberrantly methylated, approximately 36% showed significant correlation between methylation and mRNA expression levels. Pathway analysis revealed an enrichment of aberrant methylation in genes involved in key molecular mechanisms important to PDAC: TGF-β, WNT, Integrin signaling, Cell adhesion, Stellate cell activation and Axon guidance. Bisulfite amplicon deep sequencing and qRT-PCR expression analyses of axon guidance pathway genes SLIT2, SLIT3, ROBO1, ROBO3, SRGAP1, and MET suggested epigenetic suppression of SLIT-ROBO signaling and up-regulation of MET expression. Hypo-methylation of MET and ITGA2 correlated with high gene expression, which correlated with poor survival of PDAC patients. These data suggest that aberrant methylation plays an important role in pancreatic carcinogenesis affecting known core signaling pathways with important implications for disease pathophysiology and therapy. This dataset includes gene expression data from 103 primary tumour samples. 86 samples from this dataset have already been deposited into GEO (GSE36924), and has been duplicated here since the data has been processed differently. This data is also available through the International Cancer Genome Consortium (ICGC) Data Portal (http://dcc/icgc.org), under the project code: Pancreatic Cancer (QCMG, AU). Access to the restricted clinical data must be made through the ICGC Data Access Compliance Office (http://www.icgc.org/daco). This dataset contains gene expression array data from 103 primary pancreatic ductal adenocarcinoma samples. All samples have 1 biological replicate. These data have corresponding methylation 450K array data (GSE49149).

Project description:This is the experiment set used for a paper written in collaboration with Hopkins. It compares genes that are differentially expressed between normal pancreas, pancreatic cell lines and pancreatic adenocarcinoma. Pancreatic cancer is the fifth leading cause of cancer death in the United States. We used cDNA microarrays to analyze global gene expression patterns in 14 pancreatic cancer cell lines, 17 resected infiltrating pancreatic cancer tissues, and 5 samples of normal pancreas to identify genes that are differentially expressed in pancreatic cancer. We found more than 400 cDNAs corresponding to genes that were differentially expressed in the pancreatic cancer tissues and cell lines as compared to normal pancreas. These genes that tended to be expressed at higher levels in pancreatic cancers were associated with a variety of processes, including cell-cell and cell-matrix interactions, cytoskeletal remodeling, proteolytic activity, and Ca(++) homeostasis. Two prominent clusters of genes were related to the high rates of cellular proliferation in pancreatic cancer cell lines and the host desmoplastic response in the resected pancreatic cancer tissues. Of 149 genes identified as more highly expressed in the pancreatic cancers compared with normal pancreas, 103 genes have not been previously reported in association with pancreatic cancer. The expression patterns of 14 of these highly expressed genes were validated by either immunohistochemistry or reverse transcriptase-polymerase chain reaction as being expressed in pancreatic cancer. The overexpression of one gene in particular, 14-3-3 sigma, was found to be associated with aberrant hypomethylation in the majority of pancreatic cancers analyzed. The genes and expressed sequence tags presented in this study provide clues to the pathobiology of pancreatic cancer and implicate a large number of potentially new molecular markers for the detection and treatment of pancreatic cancer. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Using regression correlation

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