Investigation of NS3 protease resistance-associated variants and phenotypes for the prediction of treatment response to HCV triple therapy

Triple therapy of chronic hepatitis C virus (HCV) infection with boceprevir (BOC) or telaprevir (TVR) leads to virologic failure in many patients which is often associated with the selection of resistance-associated vari
Triple therapy of chronic hepatitis C virus (HCV) infection with boceprevir (BOC) or telaprevir (TVR) leads to virologic failure in many patients which is often associated with the selection of resistance-associated variants (RAVs). These resistance profiles are of importance for the selection of potential rescue treatment options. In this study, we sequenced baseline NS3 RAVs population-based and investigated the sensitivity of NS3 phenotypes in an HCV replicon assay together with clinical factors for a prediction of treatment response in a cohort of 165 German and Swiss patients treated with a BOC or TVR-based triple therapy. Overall, the prevalence of baseline RAVs was low, although the frequency of RAVs was higher in patients with virologic failure compared to those who achieved a sustained virologic response (SVR) (7% versus 1%, P = 0.06). The occurrence of RAVs was associated with a resistant NS3 quasispecies phenotype (P<0.001), but the sensitivity of phenotypes was not associated with treatment outcome (P = 0.2). The majority of single viral and host predictors of SVR was only weakly associated with treatment response. In multivariate analyses, low AST levels, female sex and an IFNL4 CC genotype were independently associated with SVR. However, a combined analysis of negative predictors revealed a significantly lower overall number of negative predictors in patients with SVR in comparison to individuals with virologic failure (P<0.0001) and the presence of 2 or less negative predictors was indicative for SVR. These results demonstrate that most single baseline viral and host parameters have a weak influence on the response to triple therapy, whereas the overall number of negative predictors has a high predictive value for SVR.
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Metadaten
Author:Julia Dietz, Daniel Rupp, Simone Susser, Johannes Vermehren, Kai-Henrik Peiffer, Natalie Filmann, Dimitra Bon, Thomas Kuntzen, Stefan Mauß, Georgios Grammatikos, Dany Perner, Caterina Berkowski, Eva Herrmann, Stefan Zeuzem, Ralf Bartenschlager, Christoph Sarrazin
URN:urn:nbn:de:hebis:30:3-414668
DOI:http://dx.doi.org/10.1371/journal.pone.0156731
ISSN:1932-6203
Pubmed Id:http://www.ncbi.nlm.nih.gov/pubmed?term=27281344
Parent Title (English):PLoS One
Publisher:PLoS
Place of publication:Lawrence, Kan.
Document Type:Article
Language:English
Date of Publication (online):2016/06/09
Date of first Publication:2016/06/09
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2016/09/15
Volume:11
Issue:(6): e0156731
Pagenumber:17
First Page:1
Last Page:17
Note:
Copyright: © 2016 Dietz et al. This is an open access article distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
HeBIS PPN:400651343
Institutes:Medizin
Dewey Decimal Classification:610 Medizin und Gesundheit
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - Namensnennung 4.0

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