Identification of key genes in esophageal adenocarcinoma and its clinical significance / 中国肿瘤生物治疗杂志

ABSTRACT

@#[Abstract] Objective: To screen the key genes associated with esophageal adenocarcinoma by using TCGA and GEO databases, and to analyze their biological functions, relevant signaling pathways and clinical significance. Methods: The esophageal adenocarcinoma data downloaded from TCGA database and GSE92396 microarray data from GEO database were integrated. The analysis of differentially expressed genes (DEGs) were performed by using DEseq2 and Limma packages of R software to obtain the co-differentially expressed genes, which were then chosen for the GO function enrichment analysis and KEGG pathway analysis with clusterProfiler package of R software. The key node genes that regulate the protein expressions in esophageal adenocarcinoma were screened out by protein-protein interaction (PPI) network analysis using the string website and Cytoscape 3.7.2 software. The correlation between key node genes and the survival of patients was further analyzed by combining with TCGA database. Results: By analyzing the chip data of 90 cases of adenocarcinoma tissues and 18 cases of normal esophageal tissues from databases, a total of 521 co-differentially expressed genes were obtained, including 356 upregulated genes and 165 downregulated genes. These genes were closely related to the metabolic-associated functions mainly involving epidermis development, epidermal cell differentiation and signaling pathways involving cytokine-cytokine receptor interaction, etc. The PPI network analysis revealed 15 key node genes. The survival time for patients with low CXCL8 and CCL20 expression was significantly longer compared with the patients with high expression level (median survival 32.4 vs 19.7 months, P<0.05; 32.4 vs 13.9 months, P<0.05). Conclusion: These results show that CXCL8 and CCL20 may play an important role in the occurrence, development and prognosis of esophageal adenocarcinoma, and may be used as potential indicators to judge the prognosis of patients.