Integrated Analysis of Prognostic Gene Expression Profiles from Hepatitis B Virus-Positive Hepatocellular Carcinoma and Adjacent Liver Tissue

2011 ◽  
Vol 19 (S3) ◽  
pp. 328-338 ◽  
Author(s):  
Bu-Yeo Kim ◽  
Kyung-Suk Suh ◽  
Je-Geun Lee ◽  
Seon Rang Woo ◽  
In-Chul Park ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Hepatitis B Virus ◽  
Hepatitis B ◽  
Liver Tissue ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Integrated Analysis ◽  
Prognostic Gene ◽  
B Virus

scholarly journals Gene expression profiles of human liver cells mediated by hepatitis B virus X protein

2009 ◽  
Vol 30 (4) ◽  
pp. 424-434 ◽  
Author(s):  
Wei-ying Zhang ◽  
Fu-qing Xu ◽  
Chang-liang Shan ◽  
Rong Xiang ◽  
Li-hong Ye ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatitis B Virus ◽  
Hepatitis B ◽  
Human Liver ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Liver Cells ◽  
X Protein ◽  
Human Liver Cells ◽  
B Virus

scholarly journals Distinctive gene expression profiles associated with Hepatitis B virus x protein

Oncogene ◽  
2001 ◽  
Vol 20 (28) ◽  
pp. 3674-3682 ◽  
Author(s):  
Chuan-Ging Wu ◽  
David M Salvay ◽  
Marshonna Forgues ◽  
Kristoffer Valerie ◽  
Julie Farnsworth ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatitis B Virus ◽  
Hepatitis B ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
X Protein ◽  
B Virus

scholarly journals Screening and Functional Prediction of Key Candidate Genes in Hepatitis B Virus-Associated Hepatocellular Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Xia Chen ◽  
Ling Liao ◽  
Yuwei Li ◽  
Hengliu Huang ◽  
Qing Huang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Hepatitis B Virus ◽  
Hepatitis B ◽  
Pathway Analysis ◽  
Kegg Pathway ◽  
Metabolic Process ◽  
Hub Genes ◽  
Kegg Pathway Analysis ◽  
B Virus

Background. The molecular mechanism by which hepatitis B virus (HBV) induces hepatocellular carcinoma (HCC) is still unknown. The genomic expression profile and bioinformatics methods were used to investigate the potential pathogenesis and therapeutic targets for HBV-associated HCC (HBV-HCC). Methods. The microarray dataset GSE55092 was downloaded from the Gene Expression Omnibus (GEO) database. The data was analyzed by the bioinformatics software to find differentially expressed genes (DEGs). Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, ingenuity pathway analysis (IPA), and protein-protein interaction (PPI) network analysis were then performed on DEGs. The hub genes were identified using Centiscape2.2 and Molecular Complex Detection (MCODE) in the Cytoscape software (Cytoscape_v3.7.2). The survival data of these hub genes was downloaded from the Gene Expression Profiling Interactive Analysis (GEPIA). Results. A total of 2264 mRNA transcripts were differentially expressed, including 764 upregulated and 1500 downregulated in tumor tissues. GO analysis revealed that these DEGs were related to the small-molecule metabolic process, xenobiotic metabolic process, and cellular nitrogen compound metabolic process. KEGG pathway analysis revealed that metabolic pathways, complement and coagulation cascades, and chemical carcinogenesis were involved. Diseases and biofunctions showed that DEGs were mainly associated with the following diseases or biological function abnormalities: cancer, organismal injury and abnormalities, gastrointestinal disease, and hepatic system disease. The top 10 upstream regulators were predicted to be activated or inhibited by Z-score and identified 25 networks. The 10 genes with the highest degree of connectivity were defined as the hub genes. Cox regression revealed that all the 10 genes (CDC20, BUB1B, KIF11, TTK, EZH2, ZWINT, NDC80, TPX2, MELK, and KIF20A) were related to the overall survival. Conclusion. Our study provided a registry of genes that play important roles in regulating the development of HBV-HCC, assisting us in understanding the molecular mechanisms that underlie the carcinogenesis and progression of HCC.

scholarly journals Integrated Bioinformatic Analysis Identifies Networks and Promising Biomarkers for Hepatitis B Virus-Related Hepatocellular Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Yun Ji ◽  
Yue Yin ◽  
Weizhen Zhang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Hepatitis B Virus ◽  
Hepatitis B ◽  
Interaction Network ◽  
Cyclin B1 ◽  
Microtubule Assembly ◽  
Integrated Analysis ◽  
Hub Genes ◽  
Poor Overall Survival ◽  
B Virus

Chronic infection with hepatitis B virus (HBV) has long been recognized as a dominant hazard factor for hepatocellular carcinoma (HCC) and accounts for at least half of HCC instances globally. However, the underlying molecular mechanism of HBV-linked HCC has not been completely elucidated. Here, three microarray datasets, totally containing 170 tumoral samples and 181 adjacent normal tissues from the liver of patients suffering from HBV-related HCC assembled from the Gene Expression Omnibus (GEO) database, were subjected to integrated analysis of differentially expressed genes (DEGs). Subsequently, the analysis of function and pathway enrichment as well as the protein-protein interaction network (PPI) was performed. The ten hub genes screened out from the PPI network were further subjected to expression profile and survival analysis. Overall, 329 DEGs (67 upregulated and 262 downregulated) were identified. Ten DEGs with the highest degree of connectivity included cyclin-dependent kinase 1 (CDK1), cyclin B1 (CCNB1), cyclin B2 (CCNB2), PDZ-binding kinase (PBK), abnormal spindle microtubule assembly (ASPM), nuclear division cycle 80 (NDC80), aurora kinase A (AURKA), targeting protein for xenopus kinesin-like protein 2 (TPX2), kinesin family member 2C (KIF2C), and centromere protein F (CENPF). Kaplan-Meier analysis unveiled that overexpression levels of KIF2C and TPX2 were relevant to both the poor overall survival and relapse-free survival. In summary, the hub genes validated in the present study may provide promising targets for the diagnosis, prognosis, and therapy of HBV-associated HCC. Additionally, our work uncovers various crucial biological components (e.g., extracellular exosome) and signaling pathways that participate in the progression of HCC induced by HBV, serving comprehensive knowledge of the mechanisms regarding HBV-related HCC.

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