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Knowledge-based analyses reveal new candidate genes associated with risk of hepatitis B virus related hepatocellular carcinoma.

ABSTRACT: BACKGROUND:Recent genome-wide association studies (GWASs) have suggested several susceptibility loci of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) by statistical analysis at individual single-nucleotide polymorphisms (SNPs). However, these loci only explain a small fraction of HBV-related HCC heritability. In the present study, we aimed to identify additional susceptibility loci of HBV-related HCC using advanced knowledge-based analysis. METHODS:We performed knowledge-based analysis (including gene- and gene-set-based association tests) on variant-level association p-values from two existing GWASs of HBV-related HCC. Five different types of gene-sets were collected for the association analysis. A number of SNPs within the gene prioritized by the knowledge-based association tests were selected to replicate genetic associations in an independent sample of 965 cases and 923 controls. RESULTS:The gene-based association analysis detected four genes significantly or suggestively associated with HBV-related HCC risk: SLC39A8, GOLGA8M, SMIM31, and WHAMMP2. The gene-set-based association analysis prioritized two promising gene sets for HCC, cell cycle G1/S transition and NOTCH1 intracellular domain regulates transcription. Within the gene sets, three promising candidate genes (CDC45, NCOR1 and KAT2A) were further prioritized for HCC. Among genes of liver-specific expression, multiple genes previously implicated in HCC were also highlighted. However, probably due to small sample size, none of the genes prioritized by the knowledge-based association analyses were successfully replicated by variant-level association test in the independent sample. CONCLUSIONS:This comprehensive knowledge-based association mining study suggested several promising genes and gene-sets associated with HBV-related HCC risks, which would facilitate follow-up functional studies on the pathogenic mechanism of HCC.

SUBMITTER: Jiang D

PROVIDER: S-EPMC7216662 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Knowledge-based analyses reveal new candidate genes associated with risk of hepatitis B virus related hepatocellular carcinoma.

Jiang Deke D Deng Jiaen J Dong Changzheng C Ma Xiaopin X Xiao Qianyi Q Zhou Bin B Yang Chou C Wei Lin L Conran Carly C Zheng S Lilly SL Ng Irene Oi-Lin IO Yu Long L Xu Jianfeng J Sham Pak C PC Qi Xiaolong X Hou Jinlin J Ji Yuan Y Cao Guangwen G Li Miaoxin M

BMC cancer 20200511 1

<h4>Background</h4>Recent genome-wide association studies (GWASs) have suggested several susceptibility loci of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) by statistical analysis at individual single-nucleotide polymorphisms (SNPs). However, these loci only explain a small fraction of HBV-related HCC heritability. In the present study, we aimed to identify additional susceptibility loci of HBV-related HCC using advanced knowledge-based analysis.<h4>Methods</h4>We performed kn ...[more]

PMID: 32393195

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Project description: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.

Project description:'Huaxin' is a new high-yielding timber cultivar of Camellia oleifera of high economic value, and has been widely cultivated in the red soil hilly region of Hunan Province of the People´s Republic of China in recent years. However, its quality and production are severely affected by low temperatures during flowering. To find genes related to cold tolerance and further explore new candidategenes for chilling-tolerance, Illumina NGS (Next Generation Sequencing) technology was used to perform transcriptomic analyses of C. oleifera'Huaxin' leaves under long-term cold stress. Nine cDNA libraries were sequenced, and 58.31 Gb high-quality clean reads were obtained with an average of 5.92 Gb reads for each sample. A total of 191,150 transcripts were obtained after assembly. Among them, 100,703 unigenes were generated, and 44,610 unigenes were annotated. In total, 1564 differentially expressed genes (DEGs) were identified both in the A_B and A_C gene sets. In the current study, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, andrevealed a group of cold-responsive genes related to hormone regulation, photosynthesis, membrane systems, and osmoregulation; these genes encoded many key proteins in plant biological processes, such as serine/threonine-protein kinase (STPK), transcription factors (TFs), fatty acid desaturase (FAD), lipid-transfer proteins (LTPs), soluble sugars synthetases, and flavonoid biosynthetic enzymes. Some physiological indicators of C. oleifera 'Huaxin' were determined under three temperature conditions, and the results were consistent with the molecular sequencing. In addition, the expression levels of 12 DEGs were verified using quantitative real-time polymerase chain reaction (qRT-PCR). In summary, the results of DEGs analysis together with qRT-PCR tests contribute to the understanding of cold tolerance and further exploring new candidate genes for chilling-tolerance in molecular breeding programs of C. oleifera 'Huaxin'.

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Knowledge-based analyses reveal new candidate genes associated with risk of hepatitis B virus related hepatocellular carcinoma.

Publications

Knowledge-based analyses reveal new candidate genes associated with risk of hepatitis B virus related hepatocellular carcinoma.

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