Ranking candidate genes of esophageal squamous cell carcinomas based on differentially expressed genes and the topological properties of the co-expression network

BACKGROUND: The aim of this study was to identify the candidate genes of esophageal squamous cell carcinoma (ESCC). METHODS: Gene expression profiling of 17 ESCC samples and 17 adjacent normal samples, GSE20347, was downloaded from Gene Expression Omnibus database. The raw data were preprocessed, and the differentially expressed genes (DEGs) between ESCC and normal samples were identified by using SAM software (false discovery rate <0.001). Then, the co-expression network of DEGs was constructed based on Pearson’s correlation test (r-value ≥0.8). Furthermore, the topological properties of the co-expression network were analyzed through NetworkAnalyzer (default settings) of Cytoscape. The expression fold changes of DEGs and topological properties were utilized to identify the candidate genes of ESCC (Cri(n) score >4), which were further analyzed based on DAVID functional enrichment analysis (P-value <0.05). RESULTS: A total of 1,063 DEGs were identified, including 490 up-regulated and 573 down-regulated DEGs. Then, the co-expression network of DEGs was constructed, containing 999 nodes and 46,323 edges. Based on the expression fold changes of DEGs and the topological properties of the co-expression network, DEGs were ranked, and the top 24 genes were candidate genes of ESCC, such as CRISP3, EREG, CXCR2, and CRNN. Furthermore, the 24 genes were significantly enriched in bio-functions regarding cell differentiation, glucan biosynthetic process and immune response. CONCLUSION: The present study suggested that CRISP3, EREG, CXCR2, and CRNN might be causative genes of ESCC, and play vital roles in the development of ESCC. However, further experimental studies are needed to confirm our results. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40001-014-0052-x) contains supplementary material, which is available to authorized users.