“Dynamic Range” of Inferred Phenotypic HIV Drug Resistance Values in Clinical Practice

Abstract

Background‘Virtual’ or inferred phenotypes (vPhenotypes) are commonly used to assess resistance to antiretroviral agents in patients failing therapy. In this study, we provide a clinical context for understanding vPhenotype values.MethodsAll HIV-infected persons enrolled in the British Columbia Drug Treatment Program with a baseline plasma viral load (pVL) and follow-up genotypic resistance and pVL results were included up to October 29, 2008 (N = 5,277). Change from baseline pVL was determined as a function of Virco vPhenotype, and the “dynamic range” (defined here by the 10th and 90th percentiles for fold-change in IC50 amongst all patients) was estimated from the distribution of vPhenotye fold-changes across the cohort.ResultsThe distribution of vPhenotypes from a large cohort of HIV patients who have failed therapy are presented for all available antiretroviral agents. A maximum change in IC50 of at least 13-fold was observed for all drugs. The dideoxy drugs, tenofovir and most PIs exhibited small “dynamic ranges” with values of <4-fold change observed in >99% of samples. In contrast, zidovudine, lamivudine, emtricitabine and the non-nucleoside reverse transcriptase inihibitors (excluding etravirine) had large dynamic ranges.ConclusionWe describe the populational distribution of vPhenotypes such that vPhenotype results can be interpreted relative to other patients in a drug-specific manner.

Use of Four Next-Generation Sequencing Platforms to Determine HIV-1 Coreceptor Tropism

“…The use of CCR5 antagonists to block HIV-1 replication has accelerated the development of HIV-1 coreceptor tropism assays [7] , [8] , [9] and stressed the need for novel, sensitive, and more affordable tests to increase treatment with this drug class. Although Trofile is the most commonly used phenotypic assay for HIV-1 coreceptor tropism, less sensitive genotypic tests based on HIV-1 population (Sanger) sequencing are frequently used in Europe, leading to the rapid adoption of deep sequencing technologies in genotypic HIV-1 coreceptor tropism protocols [22] , [23] , [24] , [25] , [27] , [28] , [34] , [35] , [36] , [47] . Based on the need for these NGS-based genotypic assays, we have compared the ability of four NGS platforms (454™, Illumina®, PacBio®, and Ion Torrent™) to detect minority variants, and to infer the presence of non-R5 viruses within the HIV-1 population.…”

HIV drug resistance detected during low-level viraemia is associated with subsequent virologic failure

“…For each patient, at the time of first LLV, a score was generated based on the number of active drugs in their antiretroviral regimen. We estimated the scores, called genotypic susceptibility scores (GSS) using the Stanford HIV Drug Resistance Database [30] and separately, we estimated virtual phenotypic susceptibility scores (vPSS) using the Virco/Janssen VirtualPhenotype [31–33]. The GSS and vPSS were used to stratify patients into 4 categories based on the residual antiviral activity of the ARV regimen at the time of LLV.…”

Characterization of the Drug Resistance Profiles of Patients Infected with CRF07_BC Using Phenotypic Assay and Ultra-Deep Pyrosequencing

“…In addition, the fold increase interpretation used BCOs when CCOs were lacking. However, BCOs are not derived from data of clinical responses to ARV drugs and may lack clinical relevance [31–34]. …”