Added Value of Deep Sequencing Relative to Population Sequencing in Heavily Pre-Treated HIV-1-Infected Subjects

Abstract

ObjectiveTo explore the potential of deep HIV-1 sequencing for adding clinically relevant information relative to viral population sequencing in heavily pre-treated HIV-1-infected subjects.MethodsIn a proof-of-concept study, deep sequencing was compared to population sequencing in HIV-1-infected individuals with previous triple-class virological failure who also developed virologic failure to deep salvage therapy including, at least, darunavir, tipranavir, etravirine or raltegravir. Viral susceptibility was inferred before salvage therapy initiation and at virological failure using deep and population sequencing genotypes interpreted with the HIVdb, Rega and ANRS algorithms. The threshold level for mutant detection with deep sequencing was 1%.Results7 subjects with previous exposure to a median of 15 antiretrovirals during a median of 13 years were included. Deep salvage therapy included darunavir, tipranavir, etravirine or raltegravir in 4, 2, 2 and 5 subjects, respectively. Self-reported treatment adherence was adequate in 4 and partial in 2; one individual underwent treatment interruption during follow-up. Deep sequencing detected all mutations found by population sequencing and identified additional resistance mutations in all but one individual, predominantly after virological failure to deep salvage therapy. Additional genotypic information led to consistent decreases in predicted susceptibility to etravirine, efavirenz, nucleoside reverse transcriptase inhibitors and indinavir in 2, 1, 2 and 1 subject, respectively. Deep sequencing data did not consistently modify the susceptibility predictions achieved with population sequencing for darunavir, tipranavir or raltegravir.ConclusionsIn this subset of heavily pre-treated individuals, deep sequencing improved the assessment of genotypic resistance to etravirine, but did not consistently provide additional information on darunavir, tipranavir or raltegravir susceptibility. These data may inform the design of future studies addressing the clinical value of minority drug-resistant variants in treatment-experienced subjects.

Low-Frequency Drug Resistance in HIV-Infected Ugandans on Antiretroviral Treatment Is Associated with Regimen Failure

“…The impact of low-frequency drug-resistant HIV-1 variants on treatment outcomes in patients is a matter of great debate (32,34,(38)(39)(40)(41)72). Several studies suggest that preexisting minority drugresistant variants in treatment-naive patients have minimal to no effect on the treatment outcome even if the treatment involves drugs associated with the drug resistance pattern (e.g., treatment with NVP when a patient has 3% NVP-resistant variants) (32,49).…”

“…For this reason, a series of ultrasensitive HIV-1-genotyping assays, based on deep sequencing (next-generation sequencing [NGS]), have been developed to detect drug-resistant HIV-1 variants at levels below 20% of the viral population in an infected individual (24,(28)(29)(30)(31). Several studies have associated early detection of these minority HIV-1 drug-resistant variants with subsequent treatment failure (32)(33)(34)(35)(36)(37); however, with the advent of single-pill once-a-day (QD) cART regimens, treatment failures in HICs are rare, and the relevance of minority members of the viral population to the ART outcome is still under debate (32,(38)(39)(40)(41).…”

Sensitive Deep-Sequencing-Based HIV-1 Genotyping Assay To Simultaneously Determine Susceptibility to Protease, Reverse Transcriptase, Integrase, and Maturation Inhibitors, as Well as HIV-1 Coreceptor Tropism

“…As described above, DeepGen HIV detected additional (minority) HIV-1 drug resistance mutations and non-R5 variants compared to population sequencing; however, the clinical relevance of these minority members of the viral population is still under debate (33,51,55,57,(127)(128)(129). It is reasonable to assume that under appropriate selection (i.e., drug pressure), minority variants carrying drug resistance mutations will eventually outcompete other members of the viral population, and the earlier these mutations are detected, the sooner the proper strategy can be defined to control the growth of these viruses.…”

Insights from Genomics into Bacterial Pathogen Populations

“…In addition, several studies demonstrated that drug-resistance mutations detected by 454 had a significant impact on virological failure [103][104][105][106][107] while others did not find a strong association of low-frequency mutations with clinical responses [108,109]. Deep sequencing using the 454 platform has been also applied to investigate drug-resistance mutations against the more recently approved integrase inhibitors and CCR5 antagonists.…”