Affiliation:
1. Department of Hepatopancreatobiliary Surgery, The Affiliated Calmette Hospital of Kunming Medical University,
Kunming, 650224, Yunnan, China
Abstract
Background:
Liver cancer is a major medical problem because of its high morbidity
and mortality. Hepatocellular carcinoma (HCC) is the most common type of liver cancer. Currently,
the mechanism of HCC is unclear, and the prognosis is poor with limited treatment.
Objective:
The purpose of this study is to identify hub genes and potential therapeutic drugs for
HCC.
Methods:
We used the GEO2R algorithm to analyze the differential expression of each gene in 4
gene expression profiles (GSE101685, GSE62232, GSE46408, and GSE45627) between HCC
and normal hepatic tissues. Next, we screened out the differentially expressed genes (DEGs) by
corresponding calculation data according to adjusted P-value < 0.05 and | log fold change (FC) | >
1.0. Subsequently, we used the DAVID software to analyze the DEGs by GO and KEGG enrichment
analysis. Then, we carried out the protein-protein interaction (PPI) network analysis of
DEGs using the STRING tool, and the PPI network was constructed by Cytoscape software.
MCODE plugin was used for module analysis, and the hub genes were screened out by the Cyto-
Hubba plugin. Meanwhile, we used The Kaplan-Meier plotter, GEPIA2 and HPA databases to
exert survival analysis and verify the expression alternation of hub genes. Furthermore, we used
ENCORI, TargetScan, miRDB and miRWalk database to predict the upstream regulated miRNA
of hub genes and construct a miRNA-hub genes network by Cytoscape software. Finally, we selected
potential therapeutic drugs for HCC through DGIdb databases.
Results:
A total of 415 DEGs were screened in HCC, including 196 up-regulated DEGs and 219
down-regulated DEGs. The results of KEGG pathway analysis suggested that the up-regulated
DEGs can regulate the cell cycle, and DNA replication signal pathway, while the down-regulated
DEGs were associated with metabolic pathways. In this study, we identified 11 hub genes
(AURKA, BUB1B, TOP2A, MAD2L1, CCNA2, CCNB1, BUB1, KIF11, CDK1, CCNB2 and
TPX2), which were independent risk factors of HCCand all up-regulated DEGs. We verified the
expression difference of hub genes through the GEPIA2 and HPA database, which was consistent
with the results of GEO data. We found that those hub genes were mutations in HCC according to
the cBioPortal database. Finally, we used the DGIdb database to select 32 potential therapeutic
targeting drugs for hub genes.
Conclusions:
In summary, our study provided a new perspective for researching the molecular
mechanism of HCC. Hub genes, miRNAs, and candidate drugs provide a new direction for the
early diagnosis and treatment of HCC.
Publisher
Bentham Science Publishers Ltd.
Subject
Pharmaceutical Science,Biotechnology