Genome-wide DNA methylation patterns in pancreatic ductal adenocarcinoma (PDAC)
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE49149 | GEO | 2014/07/08
SECONDARY ACCESSION(S): PRJNA213312
REPOSITORIES: GEO
Similar Datasets
Project description:Determine methylation pattern in PDAC a genome-wide analysis was performed in a cohort of 167 PDAC and 29 adjacent pancreatic tissues samples using the Infinium 450k methylation arrays (Illumina). 167 pancreatic tumors (PDAC) x 29 adjacent -non tumor samples.
2014-07-08 | E-GEOD-49149 | biostudies-arrayexpress
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).
2014-05-05 | E-GEOD-50827 | biostudies-arrayexpress
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:Pancreatic adenocarcinoma (PDAC) is one of the most lethal human malignancies and a major health problem. Patient-derived xenografts (PDX) are appearing as a prime approach for preclinical studies despite being insufficiently characterized as a model of the human disease and its diversity. We generated subcutaneous PDX from PDAC samples obtained either surgically or using diagnostic biopsies (endoscopic ultrasound guided fine needle aspirate). The extensive multiomics characterization of the xenografts demonstrated that PDX is a suitable model for preclinical studies, representing the diversity of the primary cancers. We generated subcutaneous PDX from PDAC samples obtained either surgically or using diagnostic biopsies (endoscopic ultrasound guided fine needle aspirate). The variable 'MultiOmicsClassification' indicates the resulting sample's group. 'CIMPclass' is the CpG island methylator phenotype as estimated from the methylation arrays analysis. In this dataset, Illumina Infinium HumanCode-24 BeadChips SNP arrays were used to analyze the DNA xenografts samples from pancreatic ductal adenocarcinoma.
2017-12-12 | E-MTAB-5006 | biostudies-arrayexpress
Project description:The aim of the study was to characterize a common molecular mechanism for paclitaxel resistance in Patu-T and Suit-2.028 PDAC cell lines. Despite the ATP-binding cassette (ABC) trasnsporters were already shown to be involved in various chemo-resistant forms of cancers but not in PDAC, the most likely impact of ABCB1 overexpression in PDAC cell models was taken into account in this dataset.
2024-01-26 | PXD040930 | Pride
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
2008-12-17 | GSE9672 | GEO
Project description:Pancreatic adenocarcinoma (PDAC) is one of the most lethal human malignancies and a major health problem. Patient-derived xenografts (PDX) are appearing as a prime approach for preclinical studies despite being insufficiently characterized as a model of the human disease and its diversity. We generated subcutaneous PDX from PDAC samples obtained either surgically or using diagnostic biopsies (endoscopic ultrasound guided fine needle aspirate). The extensive multiomics characterization of the xenografts demonstrated that PDX is a suitable model for preclinical studies, representing the diversity of the primary cancers. the variable MultiOmicsClassification indicates the resulting sample's group. Whole-genome DNA methylation was analyzed using the Illumina Infinium HumanMethylation450 Beadchips. Integragen SA (Evry, France) carried out microarray experiments and hybridized to the BeadChip arrays following the manufacturer’s instructions. Illumina GenomeStudio software was used to extract the beta value DNA methylation score for each locus. We removed data from probes that contained SNPs or overlapped with a repetitive element that was not uniquely aligned to the human genome or regions of insertions and deletions in the human genome. The CpG Island Methylator Phenotype (CIMP) index was determined using methylation Illumina Infinium HumanMethylation450 BeadChips based on previous low throughput work (Toyota, 1999). In brief, all island CpG found to be unmethylated (<20% Beta-value) in all 25 normal pancreatic samples from the ICGC consortium (Nones, 2014) were selected. The CIMP index was calculated independently for each sample as the proportion of methylated (>30% Beta-value) CpGs among the selected normally unmethylated island CpG.
2017-12-12 | E-MTAB-5008 | biostudies-arrayexpress
Project description:The presence of some malignancies, such as cancer, impacts on peripheral blood mononuclear cells (PBMCs) gene expression profiling, suggesting the potential suitability of these genes as diagnostic and prognostic markers. The objective of this study was to identify new markers in peripheral blood that differentiate between PDAC patients and healthy controls as a means of facilitating early detection of the disease. 18 patients with unresectable PDAC were recruited. The diagnosis of PDAC was based on a positive biopsy of the pancreatic mass during the surgery. 18 gender, age, and habits matched healthy controls were also included. Whole genome cDNA microarray hybridization of PBMC samples was performed to identify potential PDAC markers.
2013-08-12 | E-GEOD-49641 | biostudies-arrayexpress
Project description:PDAC tumor DNA hybridized against pooled normal genomic DNA DNA was extracted from tumor samples and hybridized against normal DNA in order to query copy number aberrations.
2011-01-11 | E-GEOD-19852 | biostudies-arrayexpress
Project description:PDAC tumor DNA hybridized against pooled normal genomic DNA
2011-01-11 | GSE19852 | GEO