Bioinformatics analysis of differentially expressed genes in esophageal cancer

Abstract:

Objective：To identify differentially expressed genes in esophageal cancer as targets for further treatment of esophageal cancer. Methods：Gene data sets GSE20347，GSE92396 and GSE1420 were downloaded from the GEO database，and differentially expressed genes in esophageal cancer tissues and normal esophageal tissues were selected on the basis of GEO2R analysis tools. GO analysis and KEGG pathway analysis were performed using the DAVID online database. the protein-protein interaction analysis was carried out via the STRING online database. Cytoscape software was used to screen the core network genes in the protein-protein in－teraction network，and the differential expression was verified in the TCGA database. Results：A total of 274 differentially expressed genes were revealed. 269 genes had the same expression trend，of which 96 were up-regulated and 173 were down-regulated（P<0.05 after adjustment，|log2FC|>1）. GO enrichment analysis（P<0.05） showed they were mainly involved in biological processes such as epidermal development，peptide bond cross-linking，keratinocyte differentiation，and extracellular matrix tissue formation. Molecular functions include extracellular matrix structural components and molecular activities，the function of calcium ion and platelet-derived growth factor binding，and cell composition analysis suggested that these differential genes are mainly concentrated in the ex－tracellular matrix. The KEGG enrichment pathway analysis（P<0.05） showed that the main signaling pathways include those of amebiasis，the extracellular matrix，glycolysis and gluconeogen－esis. MCODE analysis revealed that TIMP metallopeptidase inhibitor 1（TIMP1），matrix metallopeptidase 3（MMP3），secreted phos－phoprotein 1（SPP1），serpin family E member 1（SERPINE1），periostin（POSTN），insulin like growth factor binding protein 3（IGFBP3），collagen type Ⅲ alpha 1 chain（COL3A1） and desmoglein 2（DSG2） may be the key genes for the development of esophageal carci－noma（P<0.05）. These eight genes were verified by TCGA database，and COL3A1，IGFBP3，MMP3，SPP1 and TIMP1 were further screened as key genes，all of which were highly expressed in esophageal squamous cell carcinoma and adenocarcinoma（P<0.05）. Conclusion：Bioinformatics method can effectively screen the differentially expressed genes between esophageal cancer and normal esophageal tissue. In this study，five genes including COL3A1，IGFBP3，MMP3，SPP1 and TIMP1 were screened，indicating that they may be new biomarkers for the pathogenesis of esophageal cancer.