Background Pancreatic ductal adenocarcinoma (PDAC) is one of the leading cancers worldwide and has a poor survival, with a 5-year survival rate of only 8.5%. In this study we investigated altered DNA methylation associated with PDAC severity and prognosis. Methods Methylome data, generated using 450 K bead array, was compared between paired PDAC and normal samples in the TCGA cohort (n = 9) and our Indian cohort (n = 7). The total Indian Cohort (n = 75) was split into cohort 1 (n = 7), cohort 2 (n = 22), cohort 3 (n = 26) and cohort 4 (n = 20).Validation of differential methylation (6 selected CpG loci) and associated gene expression for differentially methylated genes (10 selected gDMs) were carried out in separate validation cohorts, using MSP, RT-PCR and IHC correlations between methylation and gene expression were observed in TCGA, GTEx cohorts and in validation cohorts. Kaplan–Meier survival analysis was done to study differential prognosis, during 2–5 years of follow-up. Results We identified 156 DMPs, mapped to 91 genes (gDMs), in PDAC; 68 (43.5%) DMPs were found to be differentially methylated both in TCGA cohort and our cohort, with significant concordance at hypo- and hyper-methylated loci. Enrichments of “regulation of ion transport”, “Interferon alpha/beta signalling”, “morphogenesis and development” and “transcriptional dysregulation” pathways were observed among 91 gDMs. Hyper-methylation of NPY and FAIM2 genes with down-regulated expression in PDAC, were significantly associated with poor prognosis in the Indian patient cohort. Conclusions Ethnic variations among populations may determine the altered epigenetic landscape in the PDAC patients of the Indian cohort. Our study identified novel differentially methylated genes (mainly NPY and FAIM2) and also validated the previously identified differentially methylated CpG sites associated with PDAC cancer patient’s survival. Comparative analysis of our data with TCGA and CPTAC cohorts showed that both NPY and FAIM2 hyper-methylation and down-regulations can be novel epigenetically regulated genes in the Indian patient population, statistically significantly associated with poor survival and advanced tumour stages.

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the leading cancers worldwide and has a poor survival, with a relative five-year survival rate of only 8.5%. In this study we investigated epigenetic marks associated with PDAC severity and prognosis, through studying alterations in DNA methylation patterns. Methods: DNA methylome for tumor and adjacent normal tissue samples from PDAC patients (n=7) were generated using Illumina 450K bead chips. Differentially methylated positions (DMPs) were identified with |delta beta| > 0.2 and p-value<0.01 by comparing tumors with the adjacent normal tissues. Validation of differential methylation and associated gene expression at selected genes was carried out in an independent cohort PDAC patient. Results: We identified 76 DMPs in PDAC patients that mapped to 43 genes. Among them, 44.7% (n=34) were hypo-methylated and 55.3% (n=42) were hyper-methylated DMPs in cancer samples. The trends of change in methylation at these 76 DMPs from well to moderate were like that from moderate to poorly differentiated cancer samples. The gradual trend in differential methylation was observed both in our cohort and the TCGA-PAAD cohort, suggesting methylation marks can serve as early indicators of disease pathology. Altered promoter methylation, which may affect gene expression, was observed for transcription regulators (BHLHE23, GSC2, FOXE1 and TWIST1), gated ion channels (KCNA6, and CACNB2), tumor suppressors (RASSF1, SPRED2, and NPY) and genes functioning in interferon signalling (SIGIRR, MX2, and OAS2). We also have compared the TCGA-PAAD dataset with normal pancreatic tissue data from GTEx V8 dataset leading to a confluent observation. Conclusions: We reported the first study on methylome in PDAC tumors from patients in India. We identified altered DNA methylation associated with increasing severity in PDAC among some genes like SIGIRR, MX2 along with other previously reported loci. We also concluded a confluence in our observation when comparing the TCGA-PAAD dataset with GTEx V8 dataset.