Geno2pheno(HCV) - a web-based interpretation system to support Hepatitis C treatment decisions in the era of direct-acting antiviral agents

• Verfasst von: Kalaghatgi, Prabhav [VerfasserIn]
• Verfasst von: Sikorski, Anna Maria [VerfasserIn]
• Verfasst von: Knops, Elena [VerfasserIn]
• Verfasst von: Rupp, Daniel [VerfasserIn]
• Verfasst von: Sierra, Saleta [VerfasserIn]
• Verfasst von: Heger, Eva [VerfasserIn]
• Verfasst von: Neumann-Fraune, Maria [VerfasserIn]
• Verfasst von: Beggel, Bastian [VerfasserIn]
• Verfasst von: Walker, Andreas [VerfasserIn]
• Verfasst von: Timm, Jörg [VerfasserIn]
• Verfasst von: Walter, Hauke [VerfasserIn]
• Verfasst von: Obermeier, Martin [VerfasserIn]
• Verfasst von: Kaiser, Rolf [VerfasserIn]
• Verfasst von: Bartenschlager, Ralf [VerfasserIn]
• Verfasst von: Lengauer, Thomas [VerfasserIn]
• Titel: Geno2pheno(HCV) - a web-based interpretation system to support Hepatitis C treatment decisions in the era of direct-acting antiviral agents
• Verf.angabe: Prabhav Kalaghatgi, Anna Maria Sikorski, Elena Knops, Daniel Rupp, Saleta Sierra, Eva Heger, Maria Neumann-Fraune, Bastian Beggel, Andreas Walker, Jörg Timm, Hauke Walter, Martin Obermeier, Rolf Kaiser, Ralf Bartenschlager, Thomas Lengauer
• E-Jahr: 2016
• Jahr: May 19, 2016
• Umfang: 16 S.
• Illustrationen: Illustrationen
• Fussnoten: (HCV) ist im Titel tiefgestellt ; Gesehen am 07.05.2020
• Titel Quelle: Enthalten in: PLOS ONE
• Ort Quelle: San Francisco, California, US : PLOS, 2006
• Jahr Quelle: 2016
• Band/Heft Quelle: 11(2016,5) Artikel-Nummer e0155869, 16 Seiten
• ISSN Quelle: 1932-6203
• DOI: doi:10.1371/journal.pone.0155869
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Amino acid sequence analysis
• Sach-SW: Antimicrobial resistance
• Sach-SW: Drug licensing
• Sach-SW: Hepatitis C virus
• Sach-SW: Multiple alignment calculation
• Sach-SW: Sequence alignment
• Sach-SW: Sequence analysis
• Sach-SW: Substitution mutation
• K10plus-PPN: 1697637566

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.