Published online Dec 28, 2019. doi: 10.3748/wjg.v25.i48.6890
Peer-review started: September 29, 2019
First decision: November 27, 2019
Revised: December 3, 2019
Accepted: December 14, 2019
Article in press: December 14, 2019
Published online: December 28, 2019
Processing time: 90 Days and 6.7 Hours
Esophageal cancer is one of the most poorly diagnosed and fatal cancers in the world. Although a series of studies on esophageal cancer have been reported, the molecular pathogenesis of the disease remains elusive.
To investigate comprehensively the molecular process of esophageal cancer.
Differential expression analysis was performed to identify differentially expressed genes (DEGs) in different stages of esophageal cancer from The Cancer Genome Atlas data. Exacting gene interaction modules were generated, and hub genes in the module interaction network were found. Further, through survival analysis, methylation analysis, pivot analysis, and enrichment analysis, some important molecules and related functions/pathways were identified to elucidate potential mechanisms in esophageal cancer.
A total of 7457 DEGs and 14 gene interaction modules were identified. These module genes were significantly involved in the positive regulation of protein transport, gastric acid secretion, insulin-like growth factor receptor binding, and other biological processes as well as p53 signaling pathway, epidermal growth factor signaling pathway, and epidermal growth factor receptor signaling pathway. Transcription factors (including hypoxia inducible factor 1A) and non-coding RNAs (including colorectal differentially expressed and hsa-miR-330-3p) that significantly regulate dysfunction modules were identified. Survival analysis showed that G protein subunit gamma transducin 2 (GNGT2) was closely related to survival of esophageal cancer. DEGs with strong methylation regulation ability were identified, including SST and SH3GL2. Furthermore, the expression of GNGT2 was evaluated by quantitative real time polymerase chain reaction, and the results showed that GNGT2 expression was significantly upregulated in esophageal cancer patient samples and cell lines. Moreover, cell counting kit-8 assay revealed that GNGT2 could promote the proliferation of esophageal cancer cell lines.
This study not only revealed the potential regulatory factors involved in the development of esophageal cancer but also deepens our understanding of its underlying mechanism.
Core tip: Based on the esophageal cancer-associated RNA-seq in The Cancer Genome Atlas, we studied differentially expressed genes of esophageal cancer at various stages, constructed a protein-protein interaction network, obtained 14 dysfunctional modules, and screened Hub genes. We performed enrichment analysis to predict non-coding RNA and transcription factors as well as methylation analysis of the genes in the module. A series of regulatory factors was predicted to regulate to a certain degree the potential dysfunction mechanism of esophageal cancer, which provides new insight for future studies of esophageal cancer.