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

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.

Integrative analysis identifies key mRNA biomarkers for diagnosis, prognosis, and therapeutic targets of HCV-associated hepatocellular carcinoma

“…In a previous study, we reported 17 hub genes with diagnostic and prognostic values in HBV-HCC [ 16 ]. Interestingly, three of them (CCNB1, TOP2A, NEK2) were also identified as crucial genes in HCV-HCC, which might to some extent reflect the common transcriptome regulatory mechanisms in liver cancer induced by viral hepatitis.…”

“…In previous studies, all of the four risk signature genes had been reported to play oncogenic roles in HCC and their elevated expression levels were closely related to the reduced overall survival of HCC patients [ 18 – 27 ], which is in agreement with this study. For example, CCNB1 and AURKA were proved to be significantly associated with the prognosis of HCC and HBV-HCC and proposed as hub genes in these cancers [ 16 , 19 , 25 – 28 ]. Weng, L. et al demonstrated that the elevated expression of CCNB1 was an independent prognostic indicator for the recurrence in HBV-HCC patients [ 27 ].…”

“…Other hub genes were also reported to be predictors for HCC prognosis. It is notable that TOP2A was a widely accepted hub gene in both HCC and HBV-HCC [ 16 , 19 , 28 , 29 ], and it was also used to establish an mRNA-based signature for prognosis prediction in HBV-HCC previously [ 16 ]. Moreover, CENPF was correlated with higher cumulative recurrence rates and shorter overall survival of HCC [ 30 , 31 ].…”

Unique Features of Hepatitis B Virus-Related Hepatocellular Carcinoma in Pathogenesis and Clinical Significance

“…Individual combination of these novel biomarkers with AFP improved the diagnostic sensitivity of HCC achieved to approximately 90% [138][139][140], depending upon stages. Besides, the integrated bioinformatics analysis based on the HBV-related HCC transcriptome databases suggested the key hub genes with a dysregulated expression profile as potential diagnosis and/or prognosis signatures [141]. However, more prospective lines of evidence from large cohorts and experimental results with solid molecular explanations are needed to support the clinical application of these novel serum biomarkers or genetic tools.…”

Study of the G Protein Nucleolar 2 Value in Liver Hepatocellular Carcinoma Treatment and Prognosis

“…As far as the most common inducers of carcinoma-associated mortality in the world, primary liver carcinoma ranks second, thus becoming a great public health challenge [3][4][5]. Primary liver carcinoma consists of liver hepatocellular carcinoma (LIHC), intrahepatic cholangiocarcinoma (iCCA), and other rarely seen neoplasms [6,7]. Mostly, LIHC occurs in patients with chronic liver disease, and it is generally caused by a vicious cycle of liver damage, inflammation, and regeneration that usually span several decades [8][9][10][11].…”