Basic Study
Copyright ©The Author(s) 2018. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jun 28, 2018; 24(24): 2605-2616
Published online Jun 28, 2018. doi: 10.3748/wjg.v24.i24.2605
Bioinformatics analysis of aberrantly methylated-differentially expressed genes and pathways in hepatocellular carcinoma
Liang Sang, Xue-Mei Wang, Dong-Yang Xu, Wen-Jing Zhao
Liang Sang, Xue-Mei Wang, Dong-Yang Xu, Wen-Jing Zhao, Department of Ultrasound, The First Hospital of China Medical University, Shenyang 110001, Liaoning Province, China
Author contributions: Sang L and Wang XM conceived and designed the experiments; Sang L and Xu DY performed the experiments; Sang L and Zhao WJ analyzed the data; Sang L wrote the paper; all authors agreed and approved the final version of the manuscript.
Supported by the Liaoning Natural Science Foundation Project, No. 20170541039.
Institutional review board statement: Our data are from microarrays downloaded from Gene Expression Omnibus (GEO,, which are not related to human tissues or animals. Therefore, “Institutional review board statement” is not needed.
Conflict-of-interest statement: The authors declare no conflict of interest.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See:
Correspondence to: Xue-Mei Wang, MD, Professor, Department of Ultrasound, The First Hospital of China Medical University, No. 155, Nanjing North Street, Shenyang 110001, Liaoning Province, China.
Telephone: +86-24-83282998 Fax: +86-24-83282998
Received: March 27, 2018
Peer-review started: March 27, 2018
First decision: April 27, 2018
Revised: May 2, 2018
Accepted: May 11, 2018
Article in press: May 11, 2018
Published online: June 28, 2018
Research background

Pathogenesis of hepatocellular carcinoma (HCC) is a complicated biological process involving epigenetic and genetic changes. Most prior studies, however, mainly focused on either gene expression or methylation data but not the association and did not perform a conjoint analysis. The detection of methylated-differentially expressed genes (MDEGs) and a better understanding of their characteristics may be useful for discovering the molecular mechanism and pathogenesis of HCC.

Research motivation

In view of the insights from previous studies that MDEGs can be detected concurrently by joining gene expression and methylation microarray data, we explored the interaction network of differentially expressed genes and differentially methylated genes along with interrelated signalling pathways to find novel insights into the biological characteristics and pathways of methylated-differentially expressed genes in HCC.

Research objectives

The objective was to discover MDEGs in HCC, and explore relevant hub genes and potential pathways to make notional viewpoints available for the development and progression of HCC.

Research methods

We analyzed differentially methylated genes and differentially expressed genes using a series of bioinformatics databases and tools including GEO Datasets, DAVID, STRING, and Cytoscape.

Research results

We categorized 266 hypermethylated, lowly expressed genes (Hyper-LGs) and 161 hypomethylated, highly expressed genes (Hypo-HGs) in GO, KEGG, and PPI analyses. Hyper-LGs mainly refer to endogenous and hormone stimulus, cell surface receptor linked signal transduction, and behavior, while Hypo-HGs refer to DNA replication, metabolic processes, cell cycle, and cell division. Pathway analysis showed that Hyper-LGs were enriched in cancer, Wnt, and chemokine signalling pathways, while Hypo-HGs were related to cell cycle and steroid hormone biosynthesis pathways. Based on PPI networks, PTGS2, PIK3CD, CXCL1, ESR1, and MMP2 were identified as hub genes for Hyper-LGs, and CDC45, DTL, AURKB, CDKN3, MCM2, and MCM10 were identified for Hypo-HGs by combining six ranked methods of cytoHubba.

Research conclusions

We found that interactions among MDEGs of different functions and signalling pathways are related to the pathogenesis of HCC by a series of bioinformatics databases and tools. Hub genes for Hyper-LGs of HCC included PTGS2, PIK3CD, CXCL1, ESR1, and MMP2; such genes for Hypo-HGs included CDC45, DTL, AURKB, CDKN3, MCM2, and MCM10. As special biomarkers based on aberrant methylation, these hub genes might be useful for accurate diagnosis and treatment of HCC. This study provides hypothetical and biological characteristic insight into the pathogenesis of HCC.

Research perspectives

The present findings indicate that the MDEGs in HCC can have a regulatory function in biological processes and molecular function and that they are reliable with functional enrichment analysis. As some genes and pathways identified in the present study have not been formally investigated as targets in the progression of HCC, further research is needed.