Bioinformatics-based study on hepatocellular carcinoma related genes and functions

doi:10.3877/cma.j.issn.2095-3232.2020.05.021

Abstract

Abstract:

Objective

To explore the genes and functions related to hepatocellular carcinoma (HCC) based on bioinformatics study.

Methods

Gene chips of HCC tissues and para-carcinoma tissues were screened and downloaded from the GEO public gene database, and differentially expressed genes (DEGs) were identified with GEO2R online tool and Venn diagram. The selected DEGs were subjected to GO function analysis and KEGG pathway enrichment analysis on DAVID website, and then the core DEGs were analyzed and selected through the protein-protein interaction network analysis with STRING website and Cytscape software. Finally, survival analysis of the core DEGs was performed on Kaplan-Meier Plotter website to screen the DEGs related to clinical prognosis. The DEGs related to clinical prognosis and highly expressed in HCC tissues were subjected to GO function and KEGG pathway enrichment analysis on metascape website to explore the genes and their functions which were associated with the development of HCC.

Results

A total of 124 DEGs were screened from 3 gene chips including GSE60502, GSE14520 and GSE45267. 22 core DEGs were screened by GO function, KEGG pathway enrichment analysis, STRING website and Cytscape software. Among them, 11 genes were related to the clinical prognosis of HCC, among which 9 genes were highly expressed in HCC tissues, including GINS1, AURKA, NUSAP1, TOP2A, ASPM, RRM2, PRC1, RACGAP1 and GMNN. Metascape website and KEGG pathway enrichment analysis showed that highly-expressed genes were involved in the nuclear division, mitosis in cell cycle, spindle assembly and DNA conformational changes.

Conclusions

Bioinformatics-based analysis demonstrates that 9 genes are important genes for the development of HCC, which participate in the process of nuclear division, mitosis in cell cycle, spindle assembly and DNA conformational change.

Key words: Carcinoma, hepatocellular, Bioinformatics, Genes

Guojun Zhou, Wei Ying, Wenbo Li, Yanchao Feng, Nisha Wu, Lizheng Huang, Lei Lei, Lin Shi, Zhengwei Leng. Bioinformatics-based study on hepatocellular carcinoma related genes and functions[J]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2020, 09(05): 488-492.

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