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PLoS One. 2016 May 19;11(5):e0155869. doi: 10.1371/journal.pone.0155869. eCollection 2016.

Geno2pheno[HCV] - A Web-based Interpretation System to Support Hepatitis C Treatment Decisions in the Era of Direct-Acting Antiviral Agents.

Author information

1
German Center for Infection Research (DZIF)-Saarbrücken Partner Site, Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, 66123, Saarbrücken, Germany.
2
German Center for Infection Research (DZIF)-Cologne-Bonn Partner Site, Institute of Virology, University of Cologne, 50935, Cologne, Germany.
3
German Center for Infection Research (DZIF)-Heidelberg Partner Site, Department of Infectious Diseases, Molecular Virology, Heidelberg University, 69120, Heidelberg, Germany.
4
Institute for Virology, University Hospital Düsseldorf, Heinrich Heine University, 40225, Düsseldorf, Germany.
5
MVZ Medizinisches Infektiologiezentrum Berlin (MIB), 13353, Berlin, Germany.

Abstract

The face of hepatitis C virus (HCV) therapy is changing dramatically. Direct-acting antiviral agents (DAAs) specifically targeting HCV proteins have been developed and entered clinical practice in 2011. However, despite high sustained viral response (SVR) rates of more than 90%, a fraction of patients do not eliminate the virus and in these cases treatment failure has been associated with the selection of drug resistance mutations (RAMs). RAMs may be prevalent prior to the start of treatment, or can be selected under therapy, and furthermore they can persist after cessation of treatment. Additionally, certain DAAs have been approved only for distinct HCV genotypes and may even have subtype specificity. Thus, sequence analysis before start of therapy is instrumental for managing DAA-based treatment strategies. We have created the interpretation system geno2pheno[HCV] (g2p[HCV]) to analyse HCV sequence data with respect to viral subtype and to predict drug resistance. Extensive reviewing and weighting of literature related to HCV drug resistance was performed to create a comprehensive list of drug resistance rules for inhibitors of the HCV protease in non-structural protein 3 (NS3-protease: Boceprevir, Paritaprevir, Simeprevir, Asunaprevir, Grazoprevir and Telaprevir), the NS5A replicase factor (Daclatasvir, Ledipasvir, Elbasvir and Ombitasvir), and the NS5B RNA-dependent RNA polymerase (Dasabuvir and Sofosbuvir). Upon submission of up to eight sequences, g2p[HCV] aligns the input sequences, identifies the genomic region(s), predicts the HCV geno- and subtypes, and generates for each DAA a drug resistance prediction report. g2p[HCV] offers easy-to-use and fast subtype and resistance analysis of HCV sequences, is continuously updated and freely accessible under http://hcv.geno2pheno.org/index.php. The system was partially validated with respect to the NS3-protease inhibitors Boceprevir, Telaprevir and Simeprevir by using data generated with recombinant, phenotypic cell culture assays obtained from patients' virus variants.

PMID:
27196673
PMCID:
PMC4873220
DOI:
10.1371/journal.pone.0155869
[Indexed for MEDLINE]
Free PMC Article

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