Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA167189 | ENA |
REPOSITORIES: ENA
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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).
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Project description:Here, we report an enrichment-based ultra-low input cfDNA methylation profiling method using methyl-CpG binding proteins capture, termed cfMBD-seq. We optimized the conditions of cfMBD capture by adjusting the amount of MethylCap protein along with using methylated filler DNA. Our data showed that cfMBD-seq performs equally to the standard MBD-seq (>1000 ng input) even when using 1 ng DNA as the input. cfMBD-seq demonstrated equivalent sequencing data quality as well as similar methylation profile when compared to cfMeDIP-seq. We showed that cfMBD-seq outperforms cfMeDIP-seq in the enrichment of CpG islands. This new bisulfite-free ultra-low input methylation profiling technology has a great potential in non-invasive and cost-effective cancer detection and classification.
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