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Regulation of gene expression in HBV- and HCV-related hepatocellular carcinoma: integrated GWRS and GWGS analyses.

ABSTRACT: OBJECTIVES:To explore the molecular mechanism of hepatitis B virus-related and hepatitis C virus-related hepatocellular carcinoma, samples from hepatitis B virus and hepatitis C virus infected patients and the normal were compared, respectively. METHODS:In both experiments, genes with high value were selected based on a genome-wide relative significance and genome-wide global significance model. Co-expression network of the selected genes was constructed, and transcription factors in the network were identified. Molecular complex detection algorithm was used to obtain sub-networks. RESULTS:Based on the new model, the top 300 genes were selected. Co-expression network was constructed and transcription factors were identified. We obtained two common genes FCN2 and CXCL14, and two common transcription factors RFX5 and EZH2. In hepatitis B virus experiment, cluster 1 and 3 had the higher value. In cluster 1, ten of the 17 genes and one transcription factor were all reported associated with hepatocellular carcinoma. In cluster 3, transcription factor ESR1 was reported related with hepatocellular carcinoma. In hepatitis C virus experiment, the value of cluster 3 and 4 was higher. In cluster 3, nine genes were reported to play a key role in hepatocellular carcinoma. In cluster 4, there were 5 genes in the 34 genes. To compare the relevance of a node in holding together communicating nodes, centralities based analysis was performed and we obtained some genes with high stress value. CONCLUSION:The analysis above helped us to understand the pathogenesis of hepatitis B virus and hepatitis C virus associated hepatocellular carcinoma.

SUBMITTER: Zhou X

PROVIDER: S-EPMC4276171 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Regulation of gene expression in HBV- and HCV-related hepatocellular carcinoma: integrated GWRS and GWGS analyses.

Zhou Xu X Zhu Hua-Qiang HQ Lu Jun J

International journal of clinical and experimental medicine 20141115 11

<h4>Objectives</h4>To explore the molecular mechanism of hepatitis B virus-related and hepatitis C virus-related hepatocellular carcinoma, samples from hepatitis B virus and hepatitis C virus infected patients and the normal were compared, respectively.<h4>Methods</h4>In both experiments, genes with high value were selected based on a genome-wide relative significance and genome-wide global significance model. Co-expression network of the selected genes was constructed, and transcription factors ...[more]

PMID: 25550913

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Project description:The expression of cancer stemness is believed to reduce the efficacy of current therapies against hepatocellular carcinoma (HCC). Understanding of the stemness-regulating signaling pathways incurred by a specific etiology can facilitate the development of novel targets for individualized therapy against HCC. Niche environments, such as virus-induced inflammation, may play a crucial role. However, the mechanisms linking inflammation and stemness expression in HCC remain unclear. Here we demonstrated the distinct role of inflammatory mediators in expressions of stemness-related properties involving the pluripotent octamer-binding transcription factor 4 (OCT4) in cell migration and drug resistance of hepatitis B virus-related HCC (HBV-HCC). We observed positive immunorecognition for macrophage chemoattractant protein 1 (MCP-1)/CD68 and OCT4/NANOG in HBV-HCC tissues. The inflammation-conditioned medium (inflamed-CM) generated by lipopolysaccharide-stimulated U937 human leukemia cells significantly increased the mRNA and protein levels of OCT4/NANOG preferentially in HBV-active (HBV+HBsAg+) HCC cells. The inflamed-CM also increased the side population (SP) cell percentage, green fluorescent protein (GFP)-positive cell population, and luciferase activity of OCT4 promoter-GFP/luciferase in HBV-active HCC cells. Furthermore, the inflamed-CM upregulated the expressions of insulin-like growth factor-I (IGF-I)/IGF-I receptor (IGF-IR) and activated IGF-IR/Akt signaling in HBV-HCC. The IGF-IR phosphorylation inhibitor picropodophyllin (PPP) suppressed inflamed-CM-induced OCT4 and NANOG levels in HBV+HBsAg+ Hep3B cells. Forced expression of OCT4 significantly increased the secondary sphere formation and cell migration, and reduced susceptibility of HBV-HCC cells to cisplatin, bleomycin, and doxorubicin. Taking together, our results show that niche inflammatory mediators play critical roles in inducing the expression of stemness-related properties involving IGF-IR activation, and the upregulation of OCT4 contributes to cancer migration and drug resistance of HBV-HCC cells. Findings in this paper would provide potential targets for a therapeutic strategy targeting on inflammatory environment for HBV-HCC.

Project description:Background: Hepatocellular carcinoma (HCC) is a main cause of malignancy-related death all over the world with a poor prognosis. The current research is focused on developing novel prognostic and diagnostic models of Hepatocellular carcinoma from the perspective of hepatitis B virus (HBV)-related genes, and predicting its prognostic characteristics and potential reliable biomarkers for Hepatocellular carcinoma diagnosis. Methods: As per the information related to Hepatocellular carcinoma expression profile and the clinical data in multiple public databases, we utilized limma for assessing the differentially expressed genes (DEGs) in HBV vs non- hepatitis B virus groups, and the gene set was enriched, analyzed and annotated by WebGestaltR package. Then, STRING was employed to investigate the protein interactions. A risk model for evaluating Hepatocellular carcinoma prognosis was built with Lasso Cox regression analysis. The effect patients receiving immunotherapy was predicted using Tumor Immune Dysfunction and Exclusion (TIDE). Additionally, pRRophetic was used to investigate the drug sensitivity. Lastly, the Support Vector Machine (SVM) approach was utilized for building the diagnostic model. Results: The Hepatocellular Carcinoma Molecular Atlas 18 (HCCDB18) data set was utilized for the identification of 1344 HBV-related differentially expressed genes, mainly associated with cell division activities. Five functional modules were established and then we built a prognostic model in accordance with the protein-protein interaction (PPI) network. Five HBV-related genes affecting prognosis were identified for constructing a prognostic model. Then, the samples were assigned into RS-high and -low groups as per their relevant prognostic risk score (RS). High-risk group showed worse prognosis, higher mutation rate of TP53, lower sensitivity to immunotherapy but higher response to chemotherapeutic drugs than low-risk group. Finally, the hepatitis B virus diagnostic model of Hepatocellular carcinoma was established. Conclusion: In conclusion, the prognostic and diagnostic models of hepatitis B virus gene-related Hepatocellular carcinoma were constructed. ABCB6, IPO7, TIMM9, FZD7, and ACAT1, the five HBV-related genes that affect the prognosis, can work as reliable biomarkers for the diagnosis of Hepatocellular carcinoma, giving a new insight for improving the prognosis, diagnosis, and treatment outcomes of HBV-type Hepatocellular carcinoma.

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Regulation of gene expression in HBV- and HCV-related hepatocellular carcinoma: integrated GWRS and GWGS analyses.

Publications

Regulation of gene expression in HBV- and HCV-related hepatocellular carcinoma: integrated GWRS and GWGS analyses.

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