.. Acknowledgments This work was supported by Grants-in-Aids from the Gemcitabine FDA Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT); the Ministry of Health, Labour and Welfare of Japan; and the ��Private University Strategic Research Based Support Project: Epigenetics research project aimed at general cancer cure using epigenetic targets’ from MEXT. Footnotes This work is published under the standard license to publish agreement. After 12 months the work will become freely available and the license terms will switch to a Creative Commons Attribution-NonCommercial-Share Alike 3.0 Unported License.
Hepatitis B virus (HBV) can cause chronic infection, which can lead to cirrhosis, end-stage liver disease, and hepatocellular carcinoma (1), and it is estimated that more than 240 million persons are chronically infected worldwide (2).
HBV genomes show a high rate of mutations because the virus replicates via reverse transcription of an RNA intermediate, and this process lacks proofreading mechanisms (3). The S open reading frame (ORF), which codes for the hepatitis B surface protein (HBsAg), is overlapped by the polymerase (P) gene. Therefore, mutations in the polymerase gene associated with drug resistance can result in changes in the HBV surface protein (4�C7). These, and mutations introduced in the S ORF by other mechanisms, can influence virion secretion (3). They can also reduce binding of HBsAg to anti-HbS antibodies (8), particularly when they occur in the so-called ��a�� determinant in the major hydrophilic loop (MHL) region of the HBsAg, which is the major antibody neutralization determinant of HBsAg (9).
Because the interaction between HBsAg and anti-HbS antibodies is also the basis for routine HBV diagnosis and therapy monitoring by quantitative and qualitative detection of HBsAg (1, 10), changes in HBsAg influencing the interaction with antibodies or secretion of virions might have an impact on the results obtained by these diagnostic assays. This is especially relevant since HBsAg quantitative measurements are now discussed as a predictor to guide treatment decisions (11, 12). Based on viral genome sequence variability, eight HBV genotypes have been defined by specific mutations and a divergence of >8% in the whole genome, and they have been labeled A to H (13).
The clinical impact of the virus genotype in regard to treatment response, to viral mutation patterns associated with drug resistance, and to MHL mutations is not entirely clear (10). For the rapid online genetic interpretation of HBV sequence data, three internet tools are available free of cost: HIV-grade HBV drug resistance interpretation (DRI), (14), Geno2pheno[HBV] (G2P) (15), and Stanford Brefeldin_A HBVseq (STAN) (16). All three of these programs have thus far been developed for research use only and to predict patient virus genotype and known drug resistance-associated mutations from P.
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