AUTHOR=Nangraj Asma Sindhoo , Selvaraj Gurudeeban , Kaliamurthi Satyavani , Kaushik Aman Chandra , Cho William C. , Wei Dong Qing 

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

JOURNAL=Frontiers in Pharmacology

VOLUME=Volume 11 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2020.00881

DOI=10.3389/fphar.2020.00881

ISSN=1663-9812

ABSTRACT=Esophageal adenocarcinoma (EAC) is one of the highest death-causing cancer types, especially in economically advanced countries, while Barrett’s esophagus (BE) is reported to be a precursor that immensely increases the risk of EAC. Due to the complexity of these diseases, their molecular mechanisms are not revealed clearly. This study aims to explore the shared gene signatures between BE and EAC based on integrated network analysis. We obtained EAC- and BE-associated microarray datasets GSE26886, GSE1420, GSE37200, and GSE37203 using systematic meta-analysis from Gene expression omnibus (GEO) and Array express. These data are accompanied by clinical data and RNAseq data from 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, and to discover the key relationships hidden under the co-expression modules. Differentially expressed genes-based protein–protein interaction (PIP) complex was used to deeply extract hub genes through Cytoscape plugins. The results demonstrated that 403 DEGs were excavated, including 236 upregulated and 167 downregulated genes, which are enriched in the cell cycle and replication pathways. There are 40 key genes identified using modules of MCODE, CytoHubba, and CytoNCA with different algorithms. A dark gray module with 207 genes was identified through high correlation with phenotype (gender) from the weighted gene co-expression network analysis (WGCNA). Finally, 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 network complex and WGCNA co-expression network highlight the importance of phenotypic variants on BE and EAC biomarkers for prognosis and treatment.