Integrated PPI- and WGCNA-Retrieval of Hub Gene Signatures Shared Between Barrett's Esophagus and Esophageal Adenocarcinoma

Asma Sindhoo Nangraj; Gurudeeban Selvaraj; Satyavani Kaliamurthi; Aman Chandra Kaushik; William C Cho; Dong Qing Wei

doi:10.3389/fphar.2020.00881

Integrated PPI- and WGCNA-Retrieval of Hub Gene Signatures Shared Between Barrett's Esophagus and Esophageal Adenocarcinoma

Front Pharmacol. 2020 Jul 31:11:881. doi: 10.3389/fphar.2020.00881. eCollection 2020.

Authors

Asma Sindhoo Nangraj¹, Gurudeeban Selvaraj², Satyavani Kaliamurthi², Aman Chandra Kaushik^{1

3}, William C Cho⁴, Dong Qing Wei^{1

2

5}

Affiliations

¹ The State Key Laboratory of Microbial Metabolism, Department of Bioinformatics and Biostatistics, School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
² Center of Interdisciplinary Sciences-Computational Life Sciences, Henan University of Technology, Zhengzhou, China.
³ Wuxi School of Medicine, Jiangnan University, Wuxi, China.
⁴ Department of Clinical Oncology, Queen Elizabeth Hospital, Hong Kong, China.
⁵ Peng Cheng Laboratory, Shenzhen, China.

Abstract

Esophageal adenocarcinoma (EAC) is a deadly cancer with high mortality rate, especially in economically advanced countries, while Barrett's esophagus (BE) is reported to be a precursor that strongly increases the risk of EAC. Due to the complexity of these diseases, their molecular mechanisms have not been revealed clearly. This study aims to explore the gene signatures shared between BE and EAC based on integrated network analysis. We obtained EAC- and BE-associated microarray datasets GSE26886, GSE1420, GSE37200, and GSE37203 from the Gene Expression Omnibus and ArrayExpress using systematic meta-analysis. These data were accompanied by clinical data and RNAseq data from The Cancer Genome Atlas (TCGA). Weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis were conducted to explore the relationship between gene sets and clinical traits as well as to discover the key relationships behind the co-expression modules. A differentially expressed gene-based protein-protein interaction (PPI) complex was used to extract hub genes through Cytoscape plugins. As a result, 403 DEGs were excavated, comprising 236 upregulated and 167 downregulated genes, which are involved in the cell cycle and replication pathways. Forty key genes were identified using modules of MCODE, CytoHubba, and CytoNCA with different algorithms. A dark-gray module with 207 genes was identified which having a high correlation with phenotype (gender) in the WGCNA. Furthermore, five shared hub gene signatures (SHGS), namely, pre-mRNA processing factor 4 (PRPF4), serine and arginine-rich splicing factor 1 (SRSF1), heterogeneous nuclear ribonucleoprotein M (HNRNPM), DExH-Box Helicase 9 (DHX9), and origin recognition complex subunit 2 (ORC2), were identified between BE and EAC. SHGS enrichment denotes that RNA metabolism and splicosomes play a key role in esophageal cancer development and progress. We conclude that the PPI complex and WGCNA co-expression network highlight the importance of phenotypic identifying hub gene signatures for BE and EAC.

Keywords: Barrett's esophagus; bioinformatics analysis; esophageal adenocarcinoma; hub gene signature; protein–protein interaction; weighted gene co-expression network analysis.