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 set 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 are successfully replicated 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 facilitate follow-up functional studies on the pathogenic mechanism of HCC.

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

10.21203/rs.2.14627/v4 ◽

2020 ◽

Author(s):

Deke Jiang(Former Corresponding Author) ◽

Jiaen Deng ◽

Changzheng Dong ◽

Xiaopin Ma ◽

Qianyi Xiao ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Hepatitis B Virus ◽

Hepatitis B ◽

Candidate Genes ◽

Association Analysis ◽

Susceptibility Loci ◽

Gene Set ◽

Knowledge Based ◽

Gene Sets ◽

B Virus

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 set 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 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.

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Knowledge-based genetic association study of hepatitis B virus related hepatocellular carcinoma

10.21203/rs.2.14627/v2 ◽

2019 ◽

Author(s):

Deke Jiang ◽

Jiaen Deng ◽

Changzheng Dong ◽

Xiaopin Ma ◽

Qianyi Xiao ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Hepatitis B Virus ◽

Hepatitis B ◽

Association Analysis ◽

Susceptibility Loci ◽

Association Tests ◽

Gene Set ◽

Knowledge Based ◽

Gene Sets ◽

B Virus

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 set 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 are successfully replicated in the independent sample. Conclusions: This comprehensive knowledge-based association mining study suggested several promising genes and gene-sets associated with HBV-related HCC risk. More experiments or larger samples are needed to validate their contribution to the pathogenic mechanism of HCC.

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Knowledge-based genetic association study of hepatitis B virus related hepatocellular carcinoma

10.21203/rs.2.14627/v1 ◽

2019 ◽

Author(s):

Deke Jiang ◽

Jiaen Deng ◽

Changzheng Dong ◽

Xiaopin Ma ◽

Qianyi Xiao ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Hepatitis B Virus ◽

Hepatitis B ◽

Association Analysis ◽

Small Sample ◽

Susceptibility Loci ◽

Association Analyses ◽

Gene Set ◽

Knowledge Based ◽

B Virus

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 gene- and gene-set-based association tests.Methods: We performed a meta-analysis of two existing GWASs of HBV-related HCC, based on which a series of association analyses at genes and multiple gene sets curated according to current knowledge were carried out for prioritizing potential risk genes. A series of prioritized SNPs were selected to replicate genetic associations in an independent sample of 965 cases and 923 controls.Results: The gene-based association analysis suggested that five genes are significantly associated with HBV-related HCC risk: RNY4, GOLGA8M, LINC01207, WHAMMP2 and SLC39A8. Through gene-set-based association analysis, we found that the genes in systemic lupus erythematosus pathway may be relevant to development of HBV-related HCC. Three previously reported genes, NAT2, GSTA1 and GSTA2, were also highlighted to be susceptibility genes of HBV-related HCC when genes were stratified in a liver-specific expression set. However, probably due to small sample size, none of the genes prioritized by knowledge-based association analyses are successfully replicated in an independent sample.Conclusions: This comprehensive knowledge-based association mining study suggested several promising genes significantly associated with HBV-related HCC risk. More experiments or larger samples are needed to validate their contribution to the pathogenic mechanism of HCC.

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

BMC Cancer ◽

10.1186/s12885-020-06842-0 ◽

2020 ◽

Vol 20 (1) ◽

Cited By ~ 1

Author(s):

Deke Jiang ◽

Jiaen Deng ◽

Changzheng Dong ◽

Xiaopin Ma ◽

Qianyi Xiao ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Hepatitis B Virus ◽

Hepatitis B ◽

Candidate Genes ◽

Knowledge Based ◽

B Virus

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Dynamic edge-based biomarker non-invasively predicts hepatocellular carcinoma with hepatitis B virus infection for individual patients based on blood testing

Journal of Molecular Cell Biology ◽

10.1093/jmcb/mjz025 ◽

2019 ◽

Vol 11 (8) ◽

pp. 665-677 ◽

Cited By ~ 4

Author(s):

Yiyu Lu ◽

Zhaoyuan Fang ◽

Meiyi Li ◽

Qian Chen ◽

Tao Zeng ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Hepatitis B Virus ◽

Hepatitis B ◽

Candidate Genes ◽

Mononuclear Cells ◽

Prediction Models ◽

Non Invasive ◽

Diagnosis And Prognosis ◽

B Virus ◽

Edge Based

Abstract Hepatitis B virus (HBV)-induced hepatocellular carcinoma (HCC) is a major cause of cancer-related deaths in Asia and Africa. Developing effective and non-invasive biomarkers of HCC for individual patients remains an urgent task for early diagnosis and convenient monitoring. Analyzing the transcriptomic profiles of peripheral blood mononuclear cells from both healthy donors and patients with chronic HBV infection in different states (i.e. HBV carrier, chronic hepatitis B, cirrhosis, and HCC), we identified a set of 19 candidate genes according to our algorithm of dynamic network biomarkers. These genes can both characterize different stages during HCC progression and identify cirrhosis as the critical transition stage before carcinogenesis. The interaction effects (i.e. co-expressions) of candidate genes were used to build an accurate prediction model: the so-called edge-based biomarker. Considering the convenience and robustness of biomarkers in clinical applications, we performed functional analysis, validated candidate genes in other independent samples of our collected cohort, and finally selected COL5A1, HLA-DQB1, MMP2, and CDK4 to build edge panel as prediction models. We demonstrated that the edge panel had great performance in both diagnosis and prognosis in terms of precision and specificity for HCC, especially for patients with alpha-fetoprotein-negative HCC. Our study not only provides a novel edge-based biomarker for non-invasive and effective diagnosis of HBV-associated HCC to each individual patient but also introduces a new way to integrate the interaction terms of individual molecules for clinical diagnosis and prognosis from the network and dynamics perspectives.

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