Project description:Pancreatic cancer (PC) is the fourth leading cause of cancer death with an overall 5-year survival rate of < 5%, a statistic that has changed little in almost 50 years. A deeper understanding of the underlying molecular pathophysiology is expected to advance the urgent need to develop novel therapeutic and early detection strategies for this disease. Genomic characterisation of PC has previously relied on targeted PCR based exome sequencing of small cohorts of mixed primary and metastatic lesions propagated as xenografts or cell lines (Jones et al, Science 321:1801-1806), leaving the true mutational spectrum of the clinical disease largely unresolved. Here we use exome sequencing (https://www.ebi.ac.uk/ega/studies/EGAS00001000154) and copy number analysis (not submitted) to define genomic aberrations in a prospectively accrued clinical cohort (n = 142) of early (Stage I and II) pancreatic adenocarcinoma. Detailed analysis of 99 informative tumours identified 1982 non-silent mutations and 1628 significant CNV events, and defined 439 significantly mutated genes based on stringent Significant Mutated Gene or GISTIC analysis. Integration with functional data from in vitro shRNA and in vivo Sleeping Beauty-mediated somatic mutagenesis screens provided supportive evidence for 184 of these as candidate driver mutations. Pathway based analysis recapitulated clustering of mutations in core signalling pathways in PC, and identified multiple new components in each, particularly in DNA damage repair mechanisms (ATM, TOP2A, TLM, RPA1). We also identified frequent somatic aberrations in genes involved in novel mechanisms including chromatin modification (SWI/SNF complex members, SETD2, EPC1), and axon guidance (Semaphorin, Slit, Netrin and Ephrin signalling), extending the number of core perturbed pathways in PC. Aberrant expression of axon guidance genes co- segregated with poor patient survival, and in animal models was associated with disease development and progression, further implicating perturbation of the axon guidance pathway as a novel mechanism important in PC. This dataset includes gene expression data from 90 primary tumour samples, 88 of which were used in this manuscript for survival analysis. Much of 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 strictly restricted clinical data must be made through the ICGC Data Access Compliance Office (http://www.icgc.org/daco).

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:Pancreatic cancer (PC) is the fourth leading cause of cancer death with an overall 5-year survival rate of < 5%, a statistic that has changed little in almost 50 years. A deeper understanding of the underlying molecular pathophysiology is expected to advance the urgent need to develop novel therapeutic and early detection strategies for this disease. Genomic characterisation of PC has previously relied on targeted PCR based exome sequencing of small cohorts of mixed primary and metastatic lesions propagated as xenografts or cell lines (Jones et al, Science 321:1801-1806), leaving the true mutational spectrum of the clinical disease largely unresolved. Here we use exome sequencing (https://www.ebi.ac.uk/ega/studies/EGAS00001000154) and copy number analysis (not submitted) to define genomic aberrations in a prospectively accrued clinical cohort (n = 142) of early (Stage I and II) pancreatic adenocarcinoma. Detailed analysis of 99 informative tumours identified 1982 non-silent mutations and 1628 significant CNV events, and defined 439 significantly mutated genes based on stringent Significant Mutated Gene or GISTIC analysis. Integration with functional data from in vitro shRNA and in vivo Sleeping Beauty-mediated somatic mutagenesis screens provided supportive evidence for 184 of these as candidate driver mutations. Pathway based analysis recapitulated clustering of mutations in core signalling pathways in PC, and identified multiple new components in each, particularly in DNA damage repair mechanisms (ATM, TOP2A, TLM, RPA1). We also identified frequent somatic aberrations in genes involved in novel mechanisms including chromatin modification (SWI/SNF complex members, SETD2, EPC1), and axon guidance (Semaphorin, Slit, Netrin and Ephrin signalling), extending the number of core perturbed pathways in PC. Aberrant expression of axon guidance genes co- segregated with poor patient survival, and in animal models was associated with disease development and progression, further implicating perturbation of the axon guidance pathway as a novel mechanism important in PC. This dataset includes gene expression data from 90 primary tumour samples, 88 of which were used in this manuscript for survival analysis. Much of 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 strictly restricted clinical data must be made through the ICGC Data Access Compliance Office (http://www.icgc.org/daco). This dataset contains expression array data from 90 primary pancreatic ductal adenocarcinoma samples. One sample is present with two biological replicates, all others have 1 biological replicate.

Dataset Information

2014-4-04-14-15-28-Hawaii_20140320-hawaii_20140320-icgc-release-16-wgs-paired-dataset - samples

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