期刊
FRONTIERS IN PHARMACOLOGY
卷 11, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fphar.2020.00881
关键词
bioinformatics analysis; Barrett's esophagus; hub gene signature; esophageal adenocarcinoma; weighted gene co-expression network analysis; protein-protein interaction
资金
- Ministry of Science and Technology of China [2016YFA0501703]
- National Natural Science Foundation of China [61832019, 61503244]
- Science and Technology Commission of Shanghai Municipality [19430750600]
- Henan Natural Science [162300410060]
- SJTU JiRLMDS Joint Research Funds for Medical and Engineering and Scientific Research at Shanghai Jiao Tong University [YG2017ZD14]
- Shanghai Jiao Tong University
- China Postdoctoral Science Foundation [2018M632766]
- Henan Province Postdoctoral Science Foundation [001802029, 001803035]
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.
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