title: Parameters Influencing Baseline HIV-1 Genotypic Tropism Testing Related to Clinical Outcome in Patients on Maraviroc.
abstract: OBJECTIVE
  We analysed the impact of different parameters on genotypic tropism testing related to clinical outcome prediction in 108 patients on maraviroc (MVC) treatment.
  
  
  METHODS
  87 RNA and 60 DNA samples were used. The viral tropism was predicted using the geno2pheno[coreceptor] and T-CUP tools with FPR cut-offs ranging from 1%-20%. Additionally, 27 RNA and 28 DNA samples were analysed in triplicate, 43 samples with the ESTA assay and 45 with next-generation sequencing. The influence of the genotypic susceptibility score (GSS) and 16 MVC-resistance mutations on clinical outcome was also studied.
  
  
  RESULTS
  Concordance between single-amplification testing compared to ESTA and to NGS was in the order of 80%. Concordance with NGS was higher at lower FPR cut-offs. Detection of baseline R5 viruses in RNA and DNA samples by all methods significantly correlated with treatment success, even with FPR cut-offs of 3.75%-7.5%. Triple amplification did not improve the prediction value but reduced the number of patients eligible for MVC. No influence of the GSS or MVC-resistance mutations but adherence to treatment, on the clinical outcome was detected.
  
  
  CONCLUSIONS
  Proviral DNA is valid to select candidates for MVC treatment. FPR cut-offs of 5%-7.5% and single amplification from RNA or DNA would assure a safe administration of MVC without excluding many patients who could benefit from this drug. In addition, the new prediction system T-CUP produced reliable results.
authors.affiliation: Institute of Virology, University of Cologne, Cologne, Germany.
authors.forename: Saleta
authors.initials: S
authors.lastname: Sierra
authors.affiliation: Department for Bioinformatics, University of Duisburg-Essen, Essen, Germany.
authors.forename: J Nikolai
authors.initials: JN
authors.lastname: Dybowski
authors.affiliation: Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbrücken, Germany.
authors.forename: Alejandro
authors.initials: A
authors.lastname: Pironti
authors.affiliation: Department for Bioinformatics, University of Duisburg-Essen, Essen, Germany.
authors.forename: Dominik
authors.initials: D
authors.lastname: Heider
authors.affiliation: Institute of Virology, University of Cologne, Cologne, Germany.
authors.forename: Lisa
authors.initials: L
authors.lastname: Güney
authors.affiliation: Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbrücken, Germany.
authors.forename: Alex
authors.initials: A
authors.lastname: Thielen
authors.affiliation: Department of Gastroenterology, Hepatology and Infectiology, University Hospital of Düsseldorf, Düsseldorf, Germany.
authors.forename: Stefan
authors.initials: S
authors.lastname: Reuter
authors.affiliation: Department of Dermatology, University of Duisburg-Essen, Essen, Germany.
authors.forename: Stefan
authors.initials: S
authors.lastname: Esser
authors.affiliation: First Department of Internal Medicine, University of Cologne, Cologne, Germany.
authors.forename: Gerd
authors.initials: G
authors.lastname: Fätkenheuer
authors.affiliation: Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbrücken, Germany.
authors.forename: Thomas
authors.initials: T
authors.lastname: Lengauer
authors.affiliation: Department for Bioinformatics, University of Duisburg-Essen, Essen, Germany.
authors.forename: Daniel
authors.initials: D
authors.lastname: Hoffmann
authors.affiliation: Institute of Virology, University of Cologne, Cologne, Germany.
authors.forename: Herbert
authors.initials: H
authors.lastname: Pfister
authors.affiliation: Department of Gastroenterology, Hepatology and Infectiology, University Hospital of Düsseldorf, Düsseldorf, Germany.
authors.forename: Björn
authors.initials: B
authors.lastname: Jensen
authors.affiliation: Institute of Virology, University of Cologne, Cologne, Germany.
authors.forename: Rolf
authors.initials: R
authors.lastname: Kaiser
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003510:Cyclohexanes / Q000627:therapeutic use*; D005260:Female; D005814:Genes, Viral; D056726:Genetic Association Studies; D005838:Genotype; D023581:HIV Fusion Inhibitors / Q000627:therapeutic use*; D015658:HIV Infections / Q000188:drug therapy* / Q000821:virology; D015497:HIV-1 / Q000187:drug effects / Q000235:genetics*; D006801:Humans; D008297:Male; D000077592:Maraviroc; D008875:Middle Aged; D016896:Treatment Outcome; D014230:Triazoles / Q000627:therapeutic use*; D056189:Viral Tropism / Q000235:genetics*; D055815:Young Adult
chemical_list: D003510:Cyclohexanes; D023581:HIV Fusion Inhibitors; D014230:Triazoles; D000077592:Maraviroc