Bioinformatics analysis on multiple Gene Expression Omnibus datasets of the hepatitis B virus infection and its response to the interferon-alpha therapy

对多个基因表达综合数据库(GEO)数据集进行生物信息学分析,研究乙型肝炎病毒感染及其对干扰素-α疗法的反应。

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Abstract

BACKGROUND: Hepatitis B virus (HBV) infection is a global health problem and interferon-alpha (IFN-α) is one of the effective therapies. However, little is known about the genetic background of the HBV infection or the genetic determinants of the IFN-α treatment response. Thus, we aim to explore the possible molecular mechanisms of HBV infection and its response to the IFN-α therapy with a comprehensive bioinformatics analysis. METHODS: The Gene Expression Omnibus datasets (GSE83148, GSE84044 and GSE66698) were collected and the differentially expressed genes (DEGs), key biological processes and intersecting pathways were analyzed. The expression of the co-expressed DEGs in the clinical samples was verified by quantitative real time polymerase chain reaction (qRT-PCR). RESULTS: Analysis of all the 3 datasets revealed that there were eight up-regulated and one down-regulated co-expressed DEGs following the HBV infection and after IFN-α treatment. In clinical samples, the mRNA level of HKDC1, EPCAM, GSN, ZWINT and PLD3 were significantly increased, while, the mRNA level of PLEKHA2 was significantly decreased in HBV infected liver tissues compared to normal liver tissues. PI3K-Akt signaling pathway, focal adhesion, HTLV-I infection, cytokine-cytokine receptor interaction, metabolic pathways, NF-κB signaling pathway were important pathways associated with the HBV infection and the response of IFN-α treatment. CONCLUSIONS: The co-expressed genes, common biological processes and intersecting pathways identified in the study might play an important role in HBV infection and response of IFN-α treatment. The dysregulated genes may act as novel biomarkers and therapeutic targets for HBV.

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