Identification of Multiple Hub Genes and Pathways in Hepatocellular Carcinoma: A Bioinformatics Analysis

Junwei Liu; Fang Han; Jianyi Ding; Xiaodong Liang; Jie Liu; Dongsheng Huang; Chengwu Zhang

doi:10.1155/2021/8849415

Identification of Multiple Hub Genes and Pathways in Hepatocellular Carcinoma: A Bioinformatics Analysis

Biomed Res Int. 2021 Jul 12:2021:8849415. doi: 10.1155/2021/8849415. eCollection 2021.

Authors

Junwei Liu^{1

2}, Fang Han^{2

3}, Jianyi Ding², Xiaodong Liang⁴, Jie Liu², Dongsheng Huang^{1

2}, Chengwu Zhang²

Affiliations

¹ Medical College of Soochow University, Suzhou 215006, China.
² General Surgery, Department of Hepatobiliary and Pancreatic Surgery and Minimal Invasive Surgery, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang 310014, China.
³ Hepatobiliary and Pancreatic Surgery Department, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, China.
⁴ Radiotherapy Department, Zhejiang Provincial People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang 310014, China.

Abstract

Hepatocellular carcinoma (HCC) is a common malignant tumor of the digestive system, and its early asymptomatic characteristic increases the difficulty of diagnosis and treatment. This study is aimed at obtaining some novel biomarkers with diagnostic and prognostic meaning and may find out potential therapeutic targets for HCC. We screen differentially expressed genes (DEGs) from the HCC gene expression profile GSE14520 using GEO2R. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted by using the clusterProfiler software while a protein-protein interaction (PPI) network was performed based on the STRING database. Then, prognosis analysis of hub genes was conducted using The Cancer Genome Atlas (TCGA) database. Quantitative real-time polymerase chain reaction (qRT-PCR) was utilized to further verify the expression of hub genes and explore the correlation between gene expression and clinicopathological parameters. A total of 1053 DEGs were captured, containing 497 upregulated genes and 556 downregulated genes. GO and KEGG analysis indicated that the downregulated DEGs were mainly enriched in the fatty acid catabolic process while upregulated DEGs were primarily enriched in the cell cycle. Simultaneously, ten hub genes (CYP3A4, UGT1A6, AOX1, UGT1A4, UGT2B15, CDK1, CCNB1, MAD2L1, CCNB2, and CDC20) were identified by the PPI network. Five prognosis-related hub genes (CYP3A4, CDK1, CCNB1, MAD2L1, and CDC20) were uncovered by the survival analysis based on TCGA database. The ten hub genes were further validated by qRT-PCR using samples obtained from our hospital. The prognosis-related hub genes such as CYP3A4, CDK1, CCNB1, MAD2L1, and CDC20 could be considered potential diagnosis biomarkers and prognosis targets for HCC. We also use Oncomine for further verification, and we found CCNB1, CCNB2, CDK1, and CYP3A4 which were highly expressed in HCC. Meanwhile, CCNB1, CCNB2, and CDK1 are highly expressed in almost all cancer types, which may play an important role in cancer. Still, further functional study should be conducted to explore the underlying mechanism and biological effect in the near future.

MeSH terms

Adult
Aged
Carcinoma, Hepatocellular / genetics*
Computational Biology*
Down-Regulation / genetics
Female
Gene Expression Regulation, Neoplastic
Gene Ontology
Gene Regulatory Networks*
Humans
Liver Neoplasms / genetics*
Male
Middle Aged
Prognosis
Reproducibility of Results
Signal Transduction / genetics*
Survival Analysis
Transcriptome
Up-Regulation / genetics