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Applications of next-generation sequencing analysis for the detection of hepatocellular carcinoma-associated hepatitis B virus mutations
BACKGROUND: Next-generation sequencing (NGS) is a powerful and high-throughput method for the detection of viral mutations. This article provides a brief overview about optimization of NGS analysis for hepatocellular carcinoma (HCC)-associated hepatitis B virus (HBV) mutations, and hepatocarcinogene...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5984823/ https://www.ncbi.nlm.nih.gov/pubmed/29859540 http://dx.doi.org/10.1186/s12929-018-0442-4 |
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author | Wu, I-Chin Liu, Wen-Chun Chang, Ting-Tsung |
author_facet | Wu, I-Chin Liu, Wen-Chun Chang, Ting-Tsung |
author_sort | Wu, I-Chin |
collection | PubMed |
description | BACKGROUND: Next-generation sequencing (NGS) is a powerful and high-throughput method for the detection of viral mutations. This article provides a brief overview about optimization of NGS analysis for hepatocellular carcinoma (HCC)-associated hepatitis B virus (HBV) mutations, and hepatocarcinogenesis of relevant mutations. MAIN BODY: For the application of NGS analysis in the genome of HBV, four noteworthy steps were discovered in testing. First, a sample-specific reference sequence was the most effective mapping reference for NGS. Second, elongating the end of reference sequence improved mapping performance at the end of the genome. Third, resetting the origin of mapping reference sequence could probed deletion mutations and variants at a certain location with common mutations. Fourth, using a platform-specific cut-off value to distinguish authentic minority variants from technical artifacts was found to be highly effective. One hundred and sixty-seven HBV single nucleotide variants (SNVs) were found to be studied previously through a systematic literature review, and 12 SNVs were determined to be associated with HCC by meta-analysis. From comprehensive research using a HBV genome-wide NGS analysis, 60 NGS-defined HCC-associated SNVs with their pathogenic frequencies were identified, with 19 reported previously. All the 12 HCC-associated SNVs proved by meta-analysis were confirmed by NGS analysis, except for C1766T and T1768A which were mainly expressed in genotypes A and D, but including the subgroup analysis of A1762T. In the 41 novel NGS-defined HCC-associated SNVs, 31.7% (13/41) had cut-off values of SNV frequency lower than 20%. This showed that NGS could be used to detect HCC-associated SNVs with low SNV frequency. Most SNV II (the minor strains in the majority of non-HCC patients) had either low (< 20%) or high (> 80%) SNV frequencies in HCC patients, a characteristic U-shaped distribution pattern. The cut-off values of SNV frequency for HCC-associated SNVs represent their pathogenic frequencies. The pathogenic frequencies of HCC-associated SNV II also showed a U-shaped distribution. Hepatocarcinogenesis induced by HBV mutated proteins through cellular pathways was reviewed. CONCLUSION: NGS analysis is useful to discover novel HCC-associated HBV SNVs, especially those with low SNV frequency. The hepatocarcinogenetic mechanisms of novel HCC-associated HBV SNVs defined by NGS analysis deserve further investigation. |
format | Online Article Text |
id | pubmed-5984823 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-59848232018-06-07 Applications of next-generation sequencing analysis for the detection of hepatocellular carcinoma-associated hepatitis B virus mutations Wu, I-Chin Liu, Wen-Chun Chang, Ting-Tsung J Biomed Sci Review BACKGROUND: Next-generation sequencing (NGS) is a powerful and high-throughput method for the detection of viral mutations. This article provides a brief overview about optimization of NGS analysis for hepatocellular carcinoma (HCC)-associated hepatitis B virus (HBV) mutations, and hepatocarcinogenesis of relevant mutations. MAIN BODY: For the application of NGS analysis in the genome of HBV, four noteworthy steps were discovered in testing. First, a sample-specific reference sequence was the most effective mapping reference for NGS. Second, elongating the end of reference sequence improved mapping performance at the end of the genome. Third, resetting the origin of mapping reference sequence could probed deletion mutations and variants at a certain location with common mutations. Fourth, using a platform-specific cut-off value to distinguish authentic minority variants from technical artifacts was found to be highly effective. One hundred and sixty-seven HBV single nucleotide variants (SNVs) were found to be studied previously through a systematic literature review, and 12 SNVs were determined to be associated with HCC by meta-analysis. From comprehensive research using a HBV genome-wide NGS analysis, 60 NGS-defined HCC-associated SNVs with their pathogenic frequencies were identified, with 19 reported previously. All the 12 HCC-associated SNVs proved by meta-analysis were confirmed by NGS analysis, except for C1766T and T1768A which were mainly expressed in genotypes A and D, but including the subgroup analysis of A1762T. In the 41 novel NGS-defined HCC-associated SNVs, 31.7% (13/41) had cut-off values of SNV frequency lower than 20%. This showed that NGS could be used to detect HCC-associated SNVs with low SNV frequency. Most SNV II (the minor strains in the majority of non-HCC patients) had either low (< 20%) or high (> 80%) SNV frequencies in HCC patients, a characteristic U-shaped distribution pattern. The cut-off values of SNV frequency for HCC-associated SNVs represent their pathogenic frequencies. The pathogenic frequencies of HCC-associated SNV II also showed a U-shaped distribution. Hepatocarcinogenesis induced by HBV mutated proteins through cellular pathways was reviewed. CONCLUSION: NGS analysis is useful to discover novel HCC-associated HBV SNVs, especially those with low SNV frequency. The hepatocarcinogenetic mechanisms of novel HCC-associated HBV SNVs defined by NGS analysis deserve further investigation. BioMed Central 2018-06-02 /pmc/articles/PMC5984823/ /pubmed/29859540 http://dx.doi.org/10.1186/s12929-018-0442-4 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Review Wu, I-Chin Liu, Wen-Chun Chang, Ting-Tsung Applications of next-generation sequencing analysis for the detection of hepatocellular carcinoma-associated hepatitis B virus mutations |
title | Applications of next-generation sequencing analysis for the detection of hepatocellular carcinoma-associated hepatitis B virus mutations |
title_full | Applications of next-generation sequencing analysis for the detection of hepatocellular carcinoma-associated hepatitis B virus mutations |
title_fullStr | Applications of next-generation sequencing analysis for the detection of hepatocellular carcinoma-associated hepatitis B virus mutations |
title_full_unstemmed | Applications of next-generation sequencing analysis for the detection of hepatocellular carcinoma-associated hepatitis B virus mutations |
title_short | Applications of next-generation sequencing analysis for the detection of hepatocellular carcinoma-associated hepatitis B virus mutations |
title_sort | applications of next-generation sequencing analysis for the detection of hepatocellular carcinoma-associated hepatitis b virus mutations |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5984823/ https://www.ncbi.nlm.nih.gov/pubmed/29859540 http://dx.doi.org/10.1186/s12929-018-0442-4 |
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