A comparative analysis of HIV drug resistance interpretation based on short reverse transcriptase sequences versus full sequences.

BACKGROUND: As second-line antiretroviral treatment (ART) becomes more accessible in resource-limited settings (RLS), the need for more affordable monitoring tools such as point-of-care viral load assays and simplified genotypic HIV drug resistance (HIVDR) tests increases substantially. The prohibitive expenses of genotypic HIVDR assays could partly be addressed by focusing on a smaller region of the HIV reverse transcriptase gene (RT) that encompasses the majority of HIVDR mutations for people on ART in RLS. In this study, an in silico analysis of 125,329 RT sequences was performed to investigate the effect of submitting short RT sequences (codon 41 to 238) to the commonly used virco®TYPE and Stanford genotype interpretation tools. RESULTS: Pair-wise comparisons between full-length and short RT sequences were performed. Additionally, a non-inferiority approach with a concordance limit of 95% and two-sided 95% confidence intervals was used to demonstrate concordance between HIVDR calls based on full-length and short RT sequences.The results of this analysis showed that HIVDR interpretations based on full-length versus short RT sequences, using the Stanford algorithms, had concordance significantly above 95%. When using the virco®TYPE algorithm, similar concordance was demonstrated (>95%), but some differences were observed for d4T, AZT and TDF, where predictions were affected in more than 5% of the sequences. Most differences in interpretation, however, were due to shifts from fully susceptible to reduced susceptibility (d4T) or from reduced response to minimal response (AZT, TDF) or vice versa, as compared to the predicted full RT sequence. The virco®TYPE prediction uses many more mutations outside the RT 41-238 amino acid domain, which significantly contribute to the HIVDR prediction for these 3 antiretroviral agents. CONCLUSIONS: This study illustrates the acceptability of using a shortened RT sequences (codon 41-238) to obtain reliable genotype interpretations by virco®TYPE and Stanford algorithms. Implementation of this simplified protocol could significantly reduce the cost of both resistance testing and ARV treatment monitoring in RLS.

Advantages of predicted phenotypes and statistical learning models in inferring virological response to antiretroviral therapy from HIV genotype.

BACKGROUND: Inferring response to antiretroviral therapy from the viral genotype alone is challenging. The utility of an intermediate step of predicting in vitro drug susceptibility is currently controversial. Here, we provide a retrospective comparison of approaches using either genotype or predicted phenotypes alone, or in combination. METHODS: Treatment change episodes were extracted from two large databases from the USA (Stanford-California) and Europe (EuResistDB) comprising data from 6,706 and 13,811 patients, respectively. Response to antiretroviral treatment was dichotomized according to two definitions. Using the viral sequence and the treatment regimen as input, three expert algorithms (ANRS, Rega and HIVdb) were used to generate genotype-based encodings and VircoTYPE() 4.0 (Virco BVBA, Mechelen, Belgium) was used to generate a predicted -phenotype-based encoding. Single drug classifications were combined into a treatment score via simple summation and statistical learning using random forests. Classification performance was studied on Stanford-California data using cross-validation and, in addition, on the independent EuResistDB data. RESULTS: In all experiments, predicted phenotype was among the most sensitive approaches. Combining single drug classifications by statistical learning was significantly superior to unweighted summation (P<2.2x10(-16)). Classification performance could be increased further by combining predicted phenotypes and expert encodings but not by combinations of expert encodings alone. These results were confirmed on an independent test set comprising data solely from EuResistDB. CONCLUSIONS: This study demonstrates consistent performance advantages in utilizing predicted phenotype in most scenarios over methods based on genotype alone in inferring virological response. Moreover, all approaches under study benefit significantly from statistical learning for merging single drug classifications into treatment scores.

Virological response to darunavir/ritonavir-based regimens in antiretroviral-experienced patients (PREDIZISTA study).

BACKGROUND: We assessed the association of baseline HIV-1 mutations, phenotypic sensitivity and pharmacokinetics with virological failure (VF) at week 12 (W12) after onset of a darunavir/ritonavir (DRV/r)-based regimen in a cohort of 67 antiretroviral-experienced HIV-patients failing on highly active antiretroviral therapy (HAART). METHODS: VF was defined as HIV RNA >2.3 log10copies/ml at W12. HIV reverse transcriptase and protease sequencing was performed at WO; mutations with a P-value <0.25 in univariable analyses were used for a backward selection to find the best mutation set for VF prediction. Genotypic and phenotypic sensitivity scores were calculated and virtual phenotype predicted fold change (FC) assessed. DRV Cmin, Cmax, AUC(0-->12 h) and genotypic inhibitory quotient (GIQ) were determined. RESULTS: Patients had a median of 15 previous treatments for 10 years. Median W0 values included a T-cell count of 129 cells/microl, 4.7 log10 HIV RNA copies/ml, four major protease and six nucleoside reverse transcriptase inhibitor resistance mutations. At W12, median HIV RNA decrease was -2.1 log10 copies/ml with a gain of +67 CD4+ T-cells/microl; 40% of patients failed. We determined the genotypic score I13V+V32I+L33F/I/V+E35D+ M361/L/V+I47V+F53L+I62V. According to <4, 4-5 and >5 mutations, failure occurred in 11%, 48% and 100% of patients. Failure was associated with CDC stage, baseline CD4+ T-cell count, number of major protease inhibitor resistance mutations, FC and DRV/r score. Pharmacokinetics were not associated with failure, but GIQ was. CONCLUSION: At W12, 60% of heavily pretreated patients responded on DRV/r-based HAART. Genotypic and phenotypic information constituted the main virological response determinant in patients with optimal drug concentrations.

The influence of the M184V mutation in HIV-1 reverse transcriptase on the virological outcome of highly active antiretroviral therapy regimens with or without didanosine.

BACKGROUND: In vitro phenotypic resistance studies suggest that the presence of the M184V mutation leads to a reduction in HIV-1 susceptibility to didanosine (ddl). The relevance of this to clinical outcomes remains unclear. In this study, we compared the virological response of ddl- and non-ddl-containing regimens in the presence or absence of the M184V mutation. METHODS: Data from an observational cohort study of all HIV-1 patients who had phenotypic resistance testing following the emergence of virological failure to an existing highly active antiretroviral therapy (HAART) regimen were analysed. A total of 586 patients entered the study and were followed-up over 48 weeks; 281 (48%) were switched to ddl-containing HAART, of whom 105 had the M184V mutation at baseline. Virological efficacy of combination therapy was studied by reference to average area under the curve of viral load (VL) response and the proportion of patients attaining an undetectable VL (<400 copies/ml). Baseline characteristics and univariate analysis of changes in VL were compared using the Wilcoxon rank sum test. Multivariate analyses were performed using the Van Elteren test. Additional variables included the number of baseline nucleoside reverse transcriptase inhibitor mutations and the number of active antiretroviral drugs given to each group as compared by 'real phenotype' resistance test results. RESULTS: Amongst patients on ddl-containing HAART, median fold changes in phenotypic susceptibility to ddl were greater in patients with the M184V mutation (fold changes of 2.2 vs 1.2, P<0.001). Nonetheless, the median change in VL and percentage of patients attaining an undetectable VL were similar in those taking ddl, irrespective of whether the M184V mutation was present at baseline. In the group of patients with the M184V mutation at baseline, the virological outcome was significantly better in those treated with ddl-containing HAART than in those on HAART without ddl (P<0.05). CONCLUSIONS: While the M184V did increase the fold resistance of HIV to ddl, these changes appeared to be lower than the clinically relevant threshold for phenotypic resistance for this drug.

Ultra-deep sequencing of HIV-1 reverse transcriptase before start of an NNRTI-based regimen in treatment-naive patients.

There are conflicting data on the impact of low frequency HIV-1 drug-resistant mutants on the response of first-line highly active antiretroviral therapy (HAART), more specifically containing a NNRTI. As population sequencing does not detect resistant viruses representing less than 15-25% of the viral population, more sensitive techniques have been developed but still need clinical validation. We evaluated ultra-deep sequencing (UDPS), recently more available and affordable, as a tool for the detection of HIV-1 minority species carrying drug resistant mutation (DRM) in a clinical setting. A retrospective analysis of the reverse transcriptase (RT) gene of plasma HIV-1 from 70 patients starting a NNRTI based regimen was performed. Minority populations were defined as representing > 1% and < 20% of the total viral population. Using UDPS, we could not confirm an association between the presence of low minority variants harbouring RT mutations at the start of therapy and primary or secondary therapeutic failure.

A synthetic HIV-1 subtype C backbone generates comparable PR and RT resistance profiles to a subtype B backbone in a recombinant virus assay.

In order to determine phenotypic protease and reverse transcriptase inhibitor-associated resistance in HIV subtype C virus, we have synthetically constructed an HIV-1 subtype C (HIV-1-C) viral backbone for use in a recombinant virus assay. The in silico designed viral genome was divided into 4 fragments, which were chemically synthesized and joined together by conventional subcloning. Subsequently, gag-protease-reverse-transcriptase (GPRT) fragments from 8 HIV-1 subtype C-infected patient samples were RT-PCR-amplified and cloned into the HIV-1-C backbone (deleted for GPRT) using In-Fusion reagents. Recombinant viruses (1 to 5 per patient sample) were produced in MT4-eGFP cells where cyto-pathogenic effect (CPE), p24 and Viral Load (VL) were monitored. The resulting HIV-1-C recombinant virus stocks (RVS) were added to MT4-eGFP cells in the presence of serial dilutions of antiretroviral drugs (PI, NNRTI, NRTI) to determine the fold-change in IC50 compared to the IC50 of wild-type HIV-1 virus. Additionally, viral RNA was extracted from the HIV-1-C RVS and the amplified GPRT products were used to generate recombinant virus in a subtype B backbone. Phenotypic resistance profiles in a subtype B and subtype C backbone were compared. The following observations were made: i) functional, infectious HIV-1 subtype C viruses were generated, confirmed by VL and p24 measurements; ii) their rate of infection was slower than viruses generated in the subtype B backbone; iii) they did not produce clear CPE in MT4 cells; and iv) drug resistance profiles generated in both backbones were very similar, including re-sensitizing effects like M184V on AZT.

Clinical cut-offs for HIV-1 phenotypic resistance estimates: update based on recent pivotal clinical trial data and a revised approach to viral mixtures.

The clinical utility of HIV-1 resistance testing is dependent upon accurate interpretation and application of results. The development of clinical cut-offs (CCOs) for most HIV antiretroviral drugs assessed by the vircoTYPE HIV-1 resistance test has been described previously. Updated CCOs based on new methodology and new data from clinical cohorts and pivotal clinical studies are presented in this communication. Data for analysis included the original records for CCO derivation from eight clinical trials and two cohort studies plus new records from the clinical cohorts and from the TITAN, POWER, and DUET clinical studies. Drug-specific linear regression models were developed to describe the relationship between baseline characteristics (phenotypic resistance as estimated by virtualPhenotype-LM using methods revised recently for handling mixed viral sequences; viral load; and treatment history), new treatment regimen, and 8-week virologic outcome. The clinical cut-offs were defined as the estimated phenotypic resistance levels (fold change, FC) associated with a 20% and 80% loss of drug activity. The development dataset included 6550 records with an additional 2299 reserved for validation. The updated, v.4.2 CCOs were generally close to the v4.1 values, with a trend observed toward marginally higher cut-offs for the NRTIs. These results suggest that the updated CCOs provide a relevant tool for estimating the contribution to virological response of individual antiviral drugs in antiretroviral drug combinations as used currently in clinical practice.

CXCR4-using HIV type 1 variants are more commonly found in peripheral blood mononuclear cell DNA than in plasma RNA.

OBJECTIVE: To compare the distribution of R5-like and X4-like HIV-1 envelope sequences in plasma and peripheral blood mononuclear cell (PBMC). METHODS: Clonal sequencing of the HIV-1 glycoprotein 120 region was performed on PBMC DNA and plasma RNA of 11 HIV-1 subtype B-infected patients with high probability of carrying X4 virus. Coreceptor use was predicted using the position-specific scoring matrix (PSSM). RESULTS: A total of 330 and 427 clonal envelope sequences were obtained from PBMC and plasma, respectively. PSSM interpretation revealed the presence of a mixture of predicted X4 and R5 sequences in 10 patients and pure R5 sequences in 1. The X4 sequences were significantly more represented in PBMC (with an average of 52.2% of the clonal proviral sequences scored X4) compared with plasma (19.7% X4 sequences) (P < 0.0001). At the single patient level, the higher representation of X4 sequences in PBMC reached statistical significance (P < 0.002) in 6 individuals. CONCLUSIONS: Mixtures of X4 and R5 sequences with highly divergent PSSM scores are present in both plasma and PBMC, but a shift toward a more abundant representation of X4-like PSSM scores in PBMC-derived DNA was apparent. Additional studies are needed to evaluate the clinical importance of these findings with regard to tropism prediction and the use of CCR5 antagonists.

A combined genotypic and phenotypic human immunodeficiency virus type 1 recombinant virus assay for the reverse transcriptase and integrase genes.

With the approval of the first HIV-1 integrase inhibitor raltegravir and a second one in phase III clinical development (elvitegravir), genotypic and phenotypic resistance assays are required to guide antiretroviral therapy and to investigate treatment failure. In this study, a genotypic and phenotypic recombinant virus assay was validated for determining resistance against integrase inhibitors. The assays are based on the amplification of a region encompassing not only HIV-1 integrase, but also reverse transcriptase and RNAseH. The overall amplification success was 85% (433/513) and increased to 93% (120/129) for samples with a viral load above 3 log(10) copies/ml. Both B and non-B HIV-1 subtypes could be genotyped successfully (93%; 52/56 and 100%; 49/49, respectively) and reproducibly. The phenotypic assay showed a high success rate (96.5%; 139/144) for subtype B (100%; 19/19) and non-B subtypes (92%; 45/49), and was found to be accurate and reproducible as assessed using well-characterized integrase mutants. Using both assays, baseline resistance to raltegravir and elvitegravir in subtype B and non-B HIV-1 strains selected at random was not observed, although integrase polymorphisms were present at varying prevalence. Biological cutoff values were found to be 2.1 and 2.0 for raltegravir and elvitegravir, respectively. In summary, a genotypic and phenotypic integrase resistance assay was validated successfully for accuracy, reproducibility, analytical and clinical sensitivity, and dynamic range.

Determination of clinically relevant cutoffs for HIV-1 phenotypic resistance estimates through a combined analysis of clinical trial and cohort data.

BACKGROUND: Clinically relevant cutoffs are needed for the interpretation of HIV-1 phenotypic resistance estimates as predicted by "virtual" phenotype HIV resistance analysis. METHODS: Using a clinical data set containing 2596 treatment change episodes in 2217 patients in 8 clinical trials and 2 population-based cohorts, drug-specific linear regression models were developed to describe the relation between baseline characteristics (resistance, viral load, and treatment history), new treatment regimen selected, and 8-week virologic outcome. RESULTS: These models were used to derive clinical cutoffs (CCOs) for 6 nucleoside/nucleotide reverse transcriptase inhibitors (zidovudine, lamivudine, stavudine, didanosine, abacavir, and tenofovir), 3 unboosted protease inhibitors (PIs; indinavir, amprenavir, and nelfinavir), and 4 ritonavir-boosted PIs (indinavir/ritonavir, amprenavir/ritonavir, saquinavir/ritonavir, lopinavir/ritonavir). The CCOs were defined as the phenotypic resistance levels (fold change [FC]) associated with a 20% and 80% loss of predicted wild-type drug effect and depended on the drug-specific dynamic range of the assay. CONCLUSIONS: The proposed CCOs were better correlated with virologic response than were biological cutoffs and provide a relevant tool for estimating the resistance to antiretroviral drug combinations used in clinical practice. They can be applied to diverse patient populations and are based on a consistent methodologic approach to interpreting phenotypic drug resistance.