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, https://www.ncbi.nlm.nih.gov/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: http://creativecommons.org/licenses/by-nc/4.0/
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. wangxuemei@cmu1h.com
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
Abstract
AIM

To discover methylated-differentially expressed genes (MDEGs) in hepatocellular carcinoma (HCC) and to explore relevant hub genes and potential pathways.

METHODS

The data of expression profiling GSE25097 and methylation profiling GSE57956 were gained from GEO Datasets. We analyzed the differentially methylated genes and differentially expressed genes online using GEO2R. Functional and enrichment analyses of MDEGs were conducted using the DAVID database. A protein-protein interaction (PPI) network was performed by STRING and then visualized in Cytoscape. Hub genes were ranked by cytoHubba, and a module analysis of the PPI network was conducted by MCODE in Cytoscape software.

RESULTS

In total, we categorized 266 genes as hypermethylated, lowly expressed genes (Hyper-LGs) referring to endogenous and hormone stimulus, cell surface receptor linked signal transduction and behavior. In addition, 161 genes were labelled as hypomethylated, highly expressed genes (Hypo-HGs) referring to DNA replication and metabolic process, cell cycle and division. Pathway analysis illustrated 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 hub genes for Hypo-HGs by combining six ranked methods of cytoHubba.

CONCLUSION

In the study, we disclose numerous novel genetic and epigenetic regulations and offer a vital molecular groundwork to understand the pathogenesis of HCC. Hub genes, including PTGS2, PIK3CD, CXCL1, ESR1, MMP2, CDC45, DTL, AURKB, CDKN3, MCM2, and MCM10, can be used as biomarkers based on aberrant methylation for the accurate diagnosis and treatment of HCC.

Keywords: Hepatocellular carcinoma, Methylation, Gene expression, Bioinformatics analysis

Core tip: We explored methylated-differentially expressed genes in hepatocellular carcinoma (HCC) using a series of bioinformatics databases and tools. In total, we categorized 266 genes as hypermethylated, lowly expressed genes (Hyper-LGs) referring to endogenous and hormone stimulus, as well as 161 hypomethylated, highly expressed genes (Hypo-HGs) referring to DNA replication and metabolic process. Pathway analysis showed Hyper- LGs were mainly enriched in cancer, while Hypo-HGs were essentially related to cell cycle. Finally, we identified hub genes that might be utilized as biomarkers based on aberrant methylation, which might be useful for the accurate diagnosis and treatment of HCC.