Abstract

Pancreatic cancer remains one of the chief contributors to cancer related deaths on a global scale, with its diagnosis often associated with poor prognosis and high mortality. Accumulating literature continues to highlight the role of aberrant DNA methylation in relation to pancreatic cancer progression. Integrated bioinformatics approaches in the characterization of methylated-differentially expressed genes (MeDEGs) in pancreatic cancer were employed to enhance our understanding of the potential underlying molecular mechanisms of this cancer. We initially identified differentially expressed genes (DEGs) between 178 pancreatic cancer samples and 4 normal samples and differentially methylated genes (DMGs) based on 185 pancreatic cancer samples as well as 10 normal samples by analyzing RNA sequencing data in the TCGA database. Eventually, 31 MeDEGs including 5 hypomethylated/upregulated genes and 26 hypermethylated/downregulated genes were identified. Univariate Cox model and Kaplan–Meier method revealed that, among 31 MeDEGs, 5 hypermethylated/downregulated genes (ZNF804A, ZFP82, TRIM58, SOX17, and C12orf42) were correlated with poor survival of patients with pancreatic cancer. KEGG pathway enrichment analysis by GSEA 3.0 and the protein–protein interaction (PPI) network revealed that these 5 MeDEGs were enriched in numerous cancer-related pathways in addition to interacting with each other, highlighting a significant role in the development of pancreatic cancer. Taken together, the key findings of the current study demonstrate that ZNF804A, ZFP82, TRIM58, SOX17, and C12orf42 are hypermethylated/downregulated genes in pancreatic cancer and may be associated, through their modulation of specific pathways, with unfavorable pancreatic cancer prognosis.

Highlights

  • Pancreatic cancer remains one of the deadliest solid malignancies known to man, with a mortality rate comparable to its incidence

  • The current study aimed to identify the potential methylationregulated differentially expressed genes (MeDEGs) associated with pancreatic cancer development and prognosis by bioinformatics analysis, in a bid to enhance the understanding of the molecular mechanisms that underpin the pathogenesis of pancreatic cancer

  • 2566 differentially expressed genes (DEGs), including 848 upregulated genes and 1718 downregulated ones, between 178 pancreatic cancer samples and 4 normal samples were identified following our analysis of the RNA-seq data deposited in The Cancer Genome Atlas (TCGA) database

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Summary

Introduction

Pancreatic cancer remains one of the deadliest solid malignancies known to man, with a mortality rate comparable to its incidence. Alterations of DNA methylation in cancer cells have been documented to play a notable role in the changes observed in the expression of genes that regulate tumor phenotypes (Cock-Rada and Weitzman, 2013). Research into gene expression and DNA methylation has provided some valuable insight for the identification of molecular markers for pancreatic cancer (Goggins, 2005). This being said, there remains insufficient study into methylation in gene expression regulation. Identification of methylationregulated differentially expressed genes (MeDEGs) based on high-throughput data has been speculated to be of notable significance due to its potential aid in elucidating the effect of methylation in addition to identifying future research candidates (Liang et al, 2019)

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