Identification of Potential Hub Genes Related to Diagnosis and Prognosis of Hepatitis B Virus-Related Hepatocellular Carcinoma via Integrated Bioinformatics Analysis.

Yuqin Tang,Xun Hu,Yongqiang Zhang,Nagarajan Raju

doi:10.1155/2020/4251761

Abstract

Hepatocellular carcinoma (HCC) is a common malignant cancer with poor survival outcomes, and hepatitis B virus (HBV) infection is most likely to contribute to HCC. But the molecular mechanism remains obscure. Our study intended to identify the candidate potential hub genes associated with the carcinogenesis of HBV-related HCC (HBV-HCC), which may be helpful in developing novel tumor biomarkers for potential targeted therapies. Four transcriptome datasets (GSE84402, GSE25097, GSE94660, and GSE121248) were used to screen the 309 overlapping differentially expressed genes (DEGs), including 100 upregulated genes and 209 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were used to explore the biological function of DEGs. A PPI network based on the STRING database was constructed and visualized by the Cytoscape software, consisting of 209 nodes and 1676 edges. Then, we recognized 17 hub genes by CytoHubba plugin, which were further validated on additional three datasets (GSE14520, TCGA-LIHC, and ICGC-LIRI-JP). The diagnostic effectiveness of hub genes was assessed with receiver operating characteristic (ROC) analysis, and all hub genes displayed good performance in discriminating TNM stage I patient samples and normal tissue ones. For prognostic analysis, two prognostic key genes (TOP2A and KIF11) out of the 17 hub genes were screened and used to develop a prognostic signature, which showed good potential for overall survival (OS) stratification of HBV-HCC patients. Gene Set Enrichment Analysis (GSEA) was performed in order to better understand the function of this prognostic gene signature. Finally, the miRNA–mRNA regulatory relationships of all hub genes in human liver were predicted using miRNet. In conclusion, the current study gives further insight on the pathogenesis and carcinogenesis of HBV-HCC, and the identified DEGs provide a promising direction for improving the diagnostic, prognostic, and therapeutic outcomes of HBV-HCC.

Highlights

Liver cancer, with about 841,000 new cases diagnosed and 782,000 deaths in 2018, still represents a common lethal solid tumor and ranks fourth leading cause of cancer-related deaths worldwide [1]
With the filtering criteria mentioned above, differentially expressed genes (DEGs) in hepatitis B virus (HBV)-Hepatocellular carcinoma (HCC) carcinogenesis were achieved using a total of 315 clinical samples from four Gene Expression Omnibus (GEO) datasets
For overlapping analysis of the Venn diagram, 121 upregulated genes or 302 downregulated genes were firstly shared by Affymetrix biosystems (Figure 1(e)); 309 common DEGs were obtained by Affymetrix and Illumina platforms, consisting of 100 upregulated genes and 209 downregulated genes (Figures 1(f) and 1(g))

Summary

Introduction

With about 841,000 new cases diagnosed and 782,000 deaths in 2018, still represents a common lethal solid tumor and ranks fourth leading cause of cancer-related deaths worldwide [1]. In China, liver cancer was one of the first five life killers in 2017 [2]. Hepatocellular carcinoma (HCC), comprising 75%-85% of all primary liver cancer cases worldwide [1], is the primary histological subtype. The major causative etiological factors of HCC are considered as infection of endemic hepatitis B virus (HBV) or hepatitis C virus (HCV), followed by exposition to aflatoxin B1, alcohol abuse, and obesity [1, 3]. HBV infection is considered the dominant cause of HCC, accounting for more than 80% of all HCC incidences in China and other developing countries [4]. Despite significant advances in early diagnosis, prevention and the standard therapeutic interventions such as surgery, radiation, chemotherapy, or personalized target

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Conclusion