INTRODUCTION: The identification of novel reverse-transcriptase (RT) drug-resistance mutations is critical in predicting the probability of success to anti-HBV treatment. Furthermore, due to HBV-RT/HBsAg gene-overlap, they can have an impact on HBsAg-detection and quantification. METHODS: 356 full-length HBV-RT sequences from 197 drug-naive patients and 159 patients experiencing virological-breakthrough to nucleoside/nucleotide-analogs (NUCs) were analyzed. Mutants and wild-type HBs-antigens were expressed in HuH7-hepatocytes and quantified in cell-supernatants and cell-lysates by Architect HBsAg-assay. RESULTS: Ten novel RT-mutations (rtN53T-rtS78T-rtS85F-rtS135T-rtA181I-rtA200V-rtK212Q-rtL229V/F-rtM309K) correlated with specific NUC-treatments and classical drug-resistance mutations on divergent evolutionary pathways. Some of them reduced RT-binding affinity for anti-HBV drugs and altered S-antigen structure. Indeed, rtS78T (prevalence: 1.1% in drug-naïve and 12.2% in adefovir-failing patients) decreased the RT-affinity for adefovir more than the classical adefovir-resistance mutations rtA181 T/V (WT:-9.63 kcal/mol, rtA181T:-9.30 kcal/mol, rtA181V:-7.96 kcal/mol, rtS78T:-7.37 kcal/mol). Moreover, rtS78T introduced a stop-codon at HBsAg-position 69, and completely abrogated HBsAg-quantification in both supernatants and cell-lysates, indicating an impaired HBsAg-secretion/production. Furthermore, the HBsAg-mutation sP217L, silent in RT, significantly correlated with M204V/I-related virological-breakthrough and increased HBsAg-quantification in cell-lysate. CONCLUSIONS: Mutations beyond those classically known can affect drug-binding affinity of mutated HBV-RT, and may have potential effects on HBsAg. Their cumulative effect on resistance and HBV-pathogenicity indicates the importance of preventing therapeutic failures.
INTRODUCTION: The identification of novel reverse-transcriptase (RT) drug-resistance mutations is critical in predicting the probability of success to anti-HBV treatment. Furthermore, due to HBV-RT/HBsAg gene-overlap, they can have an impact on HBsAg-detection and quantification. METHODS: 356 full-length HBV-RT sequences from 197 drug-naive patients and 159 patients experiencing virological-breakthrough to nucleoside/nucleotide-analogs (NUCs) were analyzed. Mutants and wild-type HBs-antigens were expressed in HuH7-hepatocytes and quantified in cell-supernatants and cell-lysates by Architect HBsAg-assay. RESULTS: Ten novel RT-mutations (rtN53T-rtS78T-rtS85F-rtS135T-rtA181I-rtA200V-rtK212Q-rtL229V/F-rtM309K) correlated with specific NUC-treatments and classical drug-resistance mutations on divergent evolutionary pathways. Some of them reduced RT-binding affinity for anti-HBV drugs and altered S-antigen structure. Indeed, rtS78T (prevalence: 1.1% in drug-naïve and 12.2% in adefovir-failing patients) decreased the RT-affinity for adefovir more than the classical adefovir-resistance mutations rtA181 T/V (WT:-9.63 kcal/mol, rtA181T:-9.30 kcal/mol, rtA181V:-7.96 kcal/mol, rtS78T:-7.37 kcal/mol). Moreover, rtS78T introduced a stop-codon at HBsAg-position 69, and completely abrogated HBsAg-quantification in both supernatants and cell-lysates, indicating an impaired HBsAg-secretion/production. Furthermore, the HBsAg-mutation sP217L, silent in RT, significantly correlated with M204V/I-related virological-breakthrough and increased HBsAg-quantification in cell-lysate. CONCLUSIONS: Mutations beyond those classically known can affect drug-binding affinity of mutated HBV-RT, and may have potential effects on HBsAg. Their cumulative effect on resistance and HBV-pathogenicity indicates the importance of preventing therapeutic failures.
Authors: Elham Shirvani-Dastgerdi; Benjamin Y Winer; Toni Celià-Terrassa; Yibin Kang; David Tabernero; Eray Yagmur; Francisco Rodríguez-Frías; Josep Gregori; Tom Luedde; Christian Trautwein; Alexander Ploss; Frank Tacke Journal: J Hepatol Date: 2017-04-07 Impact factor: 25.083
Authors: Carmen L Loureiro; Julio C Aguilar; Jorge Aguiar; Verena Muzio; Eduardo Pentón; Daymir Garcia; Gerardo Guillen; Flor H Pujol Journal: PLoS One Date: 2015-03-05 Impact factor: 3.240