Abstract 4382: Bioinformatics analysis for hub genes and pathways in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver cancer with a high recurrence rate and mortality. There is no effective treatment for HCC and the molecular mechanisms of HCC are still not fully understood. To identify the potential biomarkers in the carcinogenesis and progression of HCC, microarray datasets GSE101685, GSE121248, GSE38941, GSE62232 and GSE87630 were downloaded from Gene Expression Omnibus (GEO) database. Screening of differential expressed genes (DEGs), and functional enrichment analyses were performed. The protein-protein interaction network (PPI) were constructed and significant module genes and hub genes were identified using STRING and Cytoscape. 149 DEGs were screened, including 114 down-regulated genes and 35 up-regulated genes. Fifteen hub genes were identified and biological process analysis revealed that these genes were mainly enriched in cell cycle, oocyte meiosis and protein binding. Survival analysis and co-expression network analysis showed that TOP2A, TPX2, RACGAP1 and PTTG1 may be involved in the carcinogenesis, invasion or recurrence of HCC. In conclusion, the present study may help us understand the molecular mechanisms underlying the carcinogenesis and progression of HCC, and provide candidate targets for diagnosis and treatment of HCC. Key words: Hepatocellular carcinoma; Differentially expressed genes; Protein-protein interaction; Bioinformatics; Microarray Citation Format: Xianzhang Zeng, Lu Ao, Xinjian Lin, Xu Lin, Wannan Chen. Bioinformatics analysis for hub genes and pathways in hepatocellular carcinoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4382.