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Screening and Functional Prediction of Key Candidate Genes in Hepatitis B Virus-Associated Hepatocellular Carcinoma
المؤلفون المشاركون
Chen, Xia
Liao, Ling
Li, Yuwei
Huang, Hengliu
Huang, Qing
Deng, Shaoli
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-10-09
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
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.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Chen, Xia& Liao, Ling& Li, Yuwei& Huang, Hengliu& Huang, Qing& Deng, Shaoli. 2020. Screening and Functional Prediction of Key Candidate Genes in Hepatitis B Virus-Associated Hepatocellular Carcinoma. BioMed Research International،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1137122
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Chen, Xia…[et al.]. Screening and Functional Prediction of Key Candidate Genes in Hepatitis B Virus-Associated Hepatocellular Carcinoma. BioMed Research International No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1137122
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Chen, Xia& Liao, Ling& Li, Yuwei& Huang, Hengliu& Huang, Qing& Deng, Shaoli. Screening and Functional Prediction of Key Candidate Genes in Hepatitis B Virus-Associated Hepatocellular Carcinoma. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1137122
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1137122
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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