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Characterizing DNA methylation patterns in pancreatic cancer genome.

ABSTRACT: We performed a global methylation profiling assay on 1505 CpG sites across 807 genes to characterize DNA methylation patterns in pancreatic cancer genome. We found 289 CpG sites that were differentially methylated in normal pancreas, pancreatic tumors and cancer cell lines. We identified 23 and 35 candidate genes that are regulated by hypermethylation and hypomethylation in pancreatic cancer, respectively. We also identified candidate methylation markers that alter the expression of genes critical to gemcitabine susceptibility in pancreatic cancer. These results indicate that aberrant DNA methylation is a frequent epigenetic event in pancreatic cancer; and by using global methylation profiling assay, it is possible to identify these markers for diagnostic and therapeutic purposes in this disease.

SUBMITTER: Tan AC

PROVIDER: S-EPMC5527529 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature

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Characterizing DNA methylation patterns in pancreatic cancer genome.

Tan Aik Choon AC Jimeno Antonio A Lin Steven H SH Wheelhouse Jenna J Chan Fonda F Solomon Anna A Rajeshkumar N V NV Rubio-Viqueira Belen B Hidalgo Manuel M

Molecular oncology 20090422 5-6

We performed a global methylation profiling assay on 1505 CpG sites across 807 genes to characterize DNA methylation patterns in pancreatic cancer genome. We found 289 CpG sites that were differentially methylated in normal pancreas, pancreatic tumors and cancer cell lines. We identified 23 and 35 candidate genes that are regulated by hypermethylation and hypomethylation in pancreatic cancer, respectively. We also identified candidate methylation markers that alter the expression of genes critic ...[more]

PMID: 19497796

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Project description:BACKGROUND: Circulating free fatty acids are often elevated in patients with type 2 diabetes (T2D) and obese individuals. Chronic exposure to high levels of saturated fatty acids has detrimental effects on islet function and insulin secretion. Altered gene expression and epigenetics may contribute to T2D and obesity. However, there is limited information on whether fatty acids alter the genome-wide transcriptome profile in conjunction with DNA methylation patterns in human pancreatic islets. To dissect the molecular mechanisms linking lipotoxicity to impaired insulin secretion, we investigated the effects of a 48 h palmitate treatment in vitro on genome-wide mRNA expression and DNA methylation patterns in human pancreatic islets. METHODS: Genome-wide mRNA expression was analyzed using Affymetrix GeneChip(®) Human Gene 1.0 ST whole transcript-based array (n = 13) and genome-wide DNA methylation was analyzed using Infinium HumanMethylation450K BeadChip (n = 13) in human pancreatic islets exposed to palmitate or control media for 48 h. A non-parametric paired Wilcoxon statistical test was used to analyze mRNA expression. Apoptosis was measured using Apo-ONE(®) Homogeneous Caspase-3/7 Assay (n = 4). RESULTS: While glucose-stimulated insulin secretion was decreased, there was no significant effect on apoptosis in human islets exposed to palmitate. We identified 1,860 differentially expressed genes in palmitate-treated human islets. These include candidate genes for T2D, such as TCF7L2, GLIS3, HNF1B and SLC30A8. Additionally, genes in glycolysis/gluconeogenesis, pyruvate metabolism, fatty acid metabolism, glutathione metabolism and one carbon pool by folate were differentially expressed in palmitate-treated human islets. Palmitate treatment altered the global DNA methylation level and DNA methylation levels of CpG island shelves and shores, 5'UTR, 3'UTR and gene body regions in human islets. Moreover, 290 genes with differential expression had a corresponding change in DNA methylation, for example, TCF7L2 and GLIS3. Importantly, out of the genes differentially expressed due to palmitate treatment in human islets, 67 were also associated with BMI and 37 were differentially expressed in islets from T2D patients. CONCLUSION: Our study demonstrates that palmitate treatment of human pancreatic islets gives rise to epigenetic modifications that together with altered gene expression may contribute to impaired insulin secretion and T2D.

Project description:Pancreatic cancer (PC) is the fourth leading cause of cancer deaths in the United States with a five-year patient survival rate of only 6%. Early detection and treatment of this disease is hampered due to lack of reliable diagnostic and prognostic markers. Recent studies have shown that dynamic changes in the global DNA methylation and gene expression patterns play key roles in the PC development; hence, provide valuable insights for better understanding the initiation and progression of PC. In the current study, we used DNA methylation, gene expression, copy number, mutational and clinical data from pancreatic patients. We independently investigated the DNA methylation and differential gene expression profiles between normal and tumor samples and correlated methylation levels with gene expression patterns. We observed a total of ~23-thousand differentially methylated CpG sites (???0.1) between normal and tumor samples, where majority of the CpG sites are hypermethylated in PC, and this phenomenon is more prominent in the 5'UTRs and promoter regions compared to the gene bodies. Differential methylation is observed in genes associated with the homeobox domain, cell division and differentiation, cytoskeleton, epigenetic regulation and development, pancreatic development and pancreatic signaling and pancreatic cancer core signaling pathways. Correlation analysis suggests that methylation in the promoter region and 5'UTR has mostly negative correlations with gene expression while gene body and 3'UTR associated methylation has positive correlations. Regulatory element analysis suggests that HOX cluster and histone core proteins are upstream regulators of hypomethylation, while SMAD4, STAT4, STAT5B and zinc finger proteins (ZNF) are upstream regulators of hypermethylation. Non-negative matrix factorization (NMF) clustering of differentially methylated sites generated three clusters in PCs suggesting the existence of distinct molecular subtypes. Cluster 1 and cluster 2 showed samples enriched with clinical phenotypes like neoplasm histological grade and pathologic T-stage T3, respectively, while cluster 3 showed the enrichment of samples with neoplasm histological grade G1. To the best of our knowledge, this is the first genome-scale methylome analysis of PC data from TCGA. Our clustering analysis provides a strong basis for future work on the molecular subtyping of epigenetic regulation in pancreatic cancer.

Project description:BackgroundDNA methylation is a form of epigenetic modification that has been shown to play a significant role in gene regulation. In cancer, DNA methylation plays an important role by regulating the expression of oncogenes. The role of DNA methylation in the onset and progression of various cancer types is now being elucidated as more large-scale data become available. The Cancer Genome Atlas (TCGA) provides a wealth of information for the analysis of various molecular aspects of cancer genetics. Gene expression data and DNA methylation data from TCGA have been used for a variety of studies. A traditional understanding of the effects of DNA methylation on gene expression has linked methylation of CpG sites in the gene promoter region with the decrease in gene expression. Recent studies have begun to expand this traditional role of DNA methylation.ResultsHere we present a pan-cancer analysis of correlation patterns between CpG methylation and gene expression. Using matching patient data from TCGA, 33 cancer-specific correlations were calculated for each CpG site and the expression level of its corresponding gene. These correlations were used to identify patterns on a per-site basis as well as patterns of methylation across the gene body. Using these identified patterns, we found genes that contain conflicting methylation signals beyond the commonly accepted association between the promoter region methylation and silencing of gene expression. Beyond gene body methylation in whole, we examined individual CpG sites and show that, even in the same gene body, some sites can have a contradictory effect on gene expression in cancers.ConclusionsWe observed that within promoter regions there was a substantial amount of positive correlation between methylation and gene expression, which contradicts the commonly accepted association. We observed that the correlation between CpG methylation and gene expression does not exhibit in a tissue-specific manner, suggesting that the effects of methylation on gene expression are largely tissue independent. The analysis of correlation associated with the location of the CpG site in the gene body has led to the identification of several different methylation patterns that affect gene expression, and several examples of methylation activating gene expression were observed. Distinctly opposing or conflicting effects were seen in close proximity on the gene body, where negative and positive correlations were seen at the neighboring CpG sites.

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Characterizing DNA methylation patterns in pancreatic cancer genome.

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Characterizing DNA methylation patterns in pancreatic cancer genome.

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