Yimin Li^1,2 , Yang Wang^1,2 , Lin Yuan³ , Nur Fazleen Binti Idris^1,2 , Guowang Huang^1,2 , Zeng Tu^1,2

Author    Correspondence author
International Journal of Molecular Medical Science, 2020, Vol. 10, No. 7   
Received: 25 Feb., 2020    Accepted: 06 May, 2020    Published: 18 May, 2020

This article was first published in Genomics and Applied Biology in Chinese, and here was authorized to translate and publish the paper in English under the terms of Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Our study is based on the GEO database, the hepatocellular carcinoma chip profile GSE121248 induced by chronic hepatitis B was selected as the study subject. The differential expressed genes were screened by using GEO2R tools. GO analysis and KEGG pathway analysis were performed for differential expressed genes by using DAVID. Then, PPI network was constructed to picked out hub genes. Finally, the expression of hub genes and the patient survival were verified by the GEPIA and Kaplan Meier Plotter analysis tools. Through the above method, a total of 309 DEGs were screened, consisting of 94 up-regulated genes and 215 down-regulated genes. Functional analysis of DEGs showed that up-regulated DEGs are mainly involved in the cell cycle and oocyte meiosis pathways, down-regulated DEGs are enriched in the complement and coagulation cascades, metabolic pathways, and caffeine metabolic pathways. Moreover, fifteen hub genes with high correlation were screened, including BUB1, BUB1B , BIRC5, CCNB1, CCNB2, CDC20, CDK1, KIF20A, MAD2L1, NCAPG, ZWINT, PBK, DTL , TTK and NUSAP1. They were found to be associated with the overall survival in patients with HCC and constructed a miRNA regulatory network. Bioinformatics can effectively analyze the DEGs associated with the occurrence and development of HCC. The identification of the 15 Hub genes can provide theoretical guidance for further research on the molecular mechanism and molecular marker screening of HCC.

Hepatocellular carcinoma; Differential expressed genes; Bioinformatics

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