Bioinformatic Analysis to Identify and Understand Aberrant DNA Methylation Pattern Associated with Pancreatic Cancer

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Date

2021

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North Dakota State University

Abstract

In this study, we searched for significant hypo and hyper methylation CpG (5'-C-phosphate-G-3') probes from The Cancer Genome Atlas (TCGA) datasets. First, the relationship between hypo and hypermethylation pattern in significantly expressed genes associated in pancreatic ductal adenocarcinoma (PDAC) was analyzed using computational methodologies in R package. This was done by combining DNA methylation (DM) and gene expression (GE) information, and their corresponding metadata (i.e., clinical data and molecular subtypes) and saved as R files. Next, examination of differentially methylated CpG sites (DMCs) between two groups (normal vs tumor) was identified gene sets. From this analysis, we found nine (09) overexpressed hypomethylated and six (06) under expressed hypermethylated genes near significant CpG probes. Results from this work will shed light on the relationship between CpG methylation and gene expression associated with PDAC.

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Keywords

cancer, computational biology, pancreatic cancer

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