Screening and identification of key biomarkers in hepatocellular carcinoma: Evidence from bioinformatic analysis
- Lin Li
- Qingsong Lei
- Shujun Zhang
- Lingna Kong
- Bo Qin
Affiliations: Department of Infectious Diseases, The First Affiliated Hospital of Chongqing Medical University, Yuzhong, Chongqing 400016, P.R. China, The Nursing College of Chongqing Medical University, Yuzhong, Chongqing 400016, P.R. China
- Published online on: September 7, 2017 https://doi.org/10.3892/or.2017.5946
Copyright: © Li
et al. This is an open access article distributed under the
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Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. Intense efforts have been made to elucidate the pathogeny, but the molecular mechanisms of HCC are still not well understood. To identify the candidate genes in the carcinogenesis and progression of HCC, microarray datasets GSE19665, GSE33006 and GSE41804 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and function enrichment analyses were performed. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using STRING and Cytoscape. A total of 273 DEGs were identified, consisting of 189 downregulated genes and 84 upregulated genes. The enriched functions and pathways of the DEGs include protein activation cascade, complement activation, carbohydrate binding, complement and coagulation cascades, mitotic cell cycle and oocyte meiosis. Sixteen hub genes were identified and biological process analysis revealed that these genes were mainly enriched in cell division, cell cycle and nuclear division. Survival analysis showed that BUB1, CDC20, KIF20A, RACGAP1 and CEP55 may be involved in the carcinogenesis, invasion or recurrence of HCC. In conclusion, DEGs and hub genes identified in the present study help us understand the molecular mechanisms underlying the carcinogenesis and progression of HCC, and provide candidate targets for diagnosis and treatment of HCC.