Study on Differential Expression Genes in HCC Based on GEO Database

Abstract

Background: Primary hepatocellular carcinoma (HCC) is is a complex malignant tumor with high mortality. To explore the pathogenesis of HCC, Based on the GEO database, bioinformatics analysis was carried out based on the GEO database in this study. Methods: The gene expression datasets: GSE121248 were downloaded from the GEO database for bioinformatics analysis. Geo 2R was used to identify differentially expressed genes (DEGs) with the predefined criterion (P < 0.05 and | log FC| ≥ 1). STRING construct protein-protein interaction network, and identify hubgenes by Cyto-Hubba plug-in in Cytoscape, MCODE algorithm was employed to detect the PPI network. Then Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used for DEGs using DAVID and metascape. Results: From the GSE121248 database, the research obtained 1324 DEGs (423 were up-regulated and 901 were down-regulated). Through Cyto_Hubba plug-in in Cytoscape software, we identified 7 hub genes: CCNA2, CCNB1, CDK1, MAD2L1, TOP2A, RRM2, NDC80, of which TOP2A is at the core. Enrichment analysis showed that the main functions of DEGs are concentrated in negative regulation of apoptosis process, mitotic spindle, mitotic spindle, chromatin binding, and progesterone-mediated oocyte maturation. In the analysis of the KEGG pathway, they are mainly rich cell cycle, p53 signal pathway and Oocyte meiosis. Conclusion: The occurrence of hepatocellular carcinoma is the result of the joint action of many genes based on geo-informatics data mining through GEO database.