Jonathan M. Schapiro

Antiretroviral Drug Resistance Testing in Adult HIV-1 Infection: 2008 Recommendations of an International AIDS Society-USA Panel

Resistance to antiretroviral drugs remains an important limitation to successful human immunodeficiency virus type 1 (HIV-1) therapy. Resistance testing can improve treatment outcomes for infected individuals. The availability of new drugs from various classes, standardization of resistance assays, and the development of viral tropism tests necessitate new guidelines for resistance testing. The International AIDS Society-USA convened a panel of physicians and scientists with expertise in drug-resistant HIV-1, drug management, and patient care to review recently published data and presentations at scientific conferences and to provide updated recommendations. Whenever possible, resistance testing is recommended at the time of HIV infection diagnosis as part of the initial comprehensive patient assessment, as well as in all cases of virologic failure. Tropism testing is recommended whenever the use of chemokine receptor 5 antagonists is contemplated. As the roll out of antiretroviral therapy continues in developing countries, drug resistance monitoring for both subtype B and non-subtype B strains of HIV will become increasingly important.

Drug Resistance Mutations for Surveillance of Transmitted HIV-1 Drug-Resistance: 2009 Update

Programs that monitor local, national, and regional levels of transmitted HIV-1 drug resistance inform treatment guidelines and provide feedback on the success of HIV-1 treatment and prevention programs. To accurately compare transmitted drug resistance rates across geographic regions and times, the World Health Organization has recommended the adoption of a consensus genotypic definition of transmitted HIV-1 drug resistance. In January 2007, we outlined criteria for developing a list of mutations for drug-resistance surveillance and compiled a list of 80 RT and protease mutations meeting these criteria (surveillance drug resistance mutations; SDRMs). Since January 2007, several new drugs have been approved and several new drug-resistance mutations have been identified. In this paper, we follow the same procedures described previously to develop an updated list of SDRMs that are likely to be useful for ongoing and future studies of transmitted drug resistance. The updated SDRM list has 93 mutations including 34 NRTI-resistance mutations at 15 RT positions, 19 NNRTI-resistance mutations at 10 RT positions, and 40 PI-resistance mutations at 18 protease positions.

Clinical utility of HIV-1 genotyping and expert advice: the Havana trial.

Objective To determine whether HIV-1 genotyping and expert advice add additional short-term virologic benefit in guiding antiretroviral changes in HIV+ drug-experienced patients. Design A two factorial (genotyping and expert advice), randomized, open label, multi-center trial. The patients were stratified according to the number of treatment failures. Patients and methods HIV-1 infected patients on stable antiretroviral therapy who presented virological failure were included into the study. Genotypic testing was performed by using TrueGene HIV Genotyping kit and the results were interpreted by a software package (RetroGram®, version 1.0). An expert advisory committee suggested the new therapeutic approach based on clinical information alone or on clinical information plus HIV-1 genotyping results. Plasma HIV-1 RNA load, CD4+ cell count and adverse events were recorded at baseline and every 12 weeks. Results A total of 326 patients were included. The baseline CD4+ cell count and plasma HIV-1 RNA were 387 (± 224) × 106 cells/l and 4 (± 1) log10 respectively. The proportion of patients with plasma HIV-1 RNA < 400 copies/ml at 24 weeks differed between genotyping and no genotyping arms (48.5 and 36.2%, P < 0.05). Factors associated with a higher probability of plasma HIV-1 RNA < 400 copies/ml were HIV-1 genotyping [odds ratio (OR), 1.7; 95% confidence interval (CI), 1.1–2.8;P = 0.016] and the expert advice in patients failing to a second-line antiretroviral therapy (OR, 3.2; 95% CI, 1.2–8.3;P = 0.016). Conclusions HIV-1 genotyping interpreted by a software package improves the virological outcome when it is added to the clinical information as a basis for decisions on changing antiretroviral therapy. The expert advice also showed virologic benefit in the second failure group.

The Effect of High-Dose Saquinavir on Viral Load and CD4+ T-Cell Counts in HIV-Infected Patients

Human immunodeficiency virus (HIV) protease inhibitors are a new class of antiretroviral agents that target a different point in the HIV life cycle than do zidovudine and other dideoxy nucleoside or non-nucleoside reverse transcriptase inhibitors. The HIV genes gag and gag-pol are translated into large polyproteins that contain the individual structural and functional HIV proteins. The HIV protease is required to cleave these polyproteins to produce infectious virus. Studies showing that the inhibition of the HIV protease resulted in the production of immature and noninfectious virus [1-3] led to the development of HIV protease inhibitors. Saquinavir is a transitional state analogue peptidomimetic inhibitor of the HIV protease [4, 5]. In vitro studies have shown that it is a potent inhibitor of HIV replication [5, 6]; preliminary clinical trials [7] have shown that it elevates CD4+ T-cell counts and suppresses viral load as measured by plasma HIV RNA levels. Pharmacokinetics studies have shown that it has low bioavailability [8]. Reported side effects are of mild to moderate intensity and include abdominal discomfort, vomiting, diarrhea, headache, and dizziness. Abnormal laboratory results have included occasional elevations in serum aminotransferase and creatinine phosphokinase levels [7]. As have patients receiving other antiretroviral agents, patients receiving protease inhibitors have had mutations in the HIV genome, and in vitro studies have suggested that phenotypic resistance results from these changes [9-13]. Mutations at codons 48 (GV) and 90 (LM) of the HIV protease gene appear to develop in the presence of saquinavir and lead to phenotypic resistance to the drug [14-16]. Mutations at other codons, such as codon 54, have also occasionally been implicated in conferring resistance to saquinavir, and increased resistance has been found when more than one mutation is present [15-17]. Resistance mutations to other protease inhibitors currently being studied in clinical trials have also been well documented [18-20]. Cross-resistance between protease inhibitors has been shown to occur in vitro [9, 20, 21]. Although some evidence suggests this may be less of a problem with saquinavir than with other protease inhibitors [9, 22], other reports have shown that saquinavir is also involved in cross-resistance [20, 21]. The clinical relevance of these mutations is not yet completely understood. Saquinavir has been licensed for use in HIV-infected patients at a dose of 1800 mg/d. Studies of saquinavir at this dose showed that it produced a median reduction of 80% in plasma HIV RNA levels and a median elevation of 50 cells/mm3 in CD4+ T-cell count, although the duration of the effect was short and values had returned nearly to baseline by week 16 [7]. Preliminary results comparing combination therapy with zidovudine plus zalcitabine, zidovudine plus saquinavir, and all three drugs together showed that the triple combination produced a more favorable response without increased toxicity [23]. Because saquinavir at a dose of 1800 mg/d had been shown to favorably influence viral load and CD4+ T-cell counts without producing severe toxicity, and because the drug has low bioavailability, it was postulated that higher doses might produce a greater antiviral effect without significantly increasing toxicity. We studied saquinavir at twice and four times the currently licensed dose to determine the efficacy, safety, and pharmacokinetics of saquinavir and to identify the optimal dose of saquinavir for future study both as monotherapy and in combination with other antiretroviral agents. Methods Persons who were positive for HIV type 1, were 18 years of age or older, had CD4+ T-cell counts of 200 to 500 cells/mm3, and had no active opportunistic infections were eligible for the study. Saquinavir was dispensed to patients as 200-mg capsules twice weekly and then once monthly. Compliance was monitored by patient report and capsule count. Toxicity Patients were initially monitored three times a week, then twice a week, and then once a month for any reported symptoms or signs of drug toxicity. Frequent laboratory testing was also done; tests included measurement of complete blood and platelet counts; serum chemistry tests; liver function tests; tests for amylase, triglyceride, and creatinine phosphokinase levels; and urinalysis. In patients with grade 3 toxicity, drug therapy was briefly discontinued and then restarted. Virology Quantitative peripheral blood mononuclear cell cultures were done by incubating serial fivefold dilutions of patient peripheral blood mononuclear cells (starting with 1 106 cells) in duplicate with 1 106 phytohemagglutin-stimulated normal peripheral blood mononuclear cells for 14 days. This was done according to the AIDS (acquired immunodeficiency syndrome) Clinical Trials Group consensus protocol for quantitative microcultures [24]. Measurements of p24 antigen levels were made for each dilution by using a commercially available p24 antigen kit (Abbott Diagnostics, Chicago, Illinois), and the results were expressed as infectious units per million peripheral blood mononuclear cells. Plasma HIV RNA levels were measured by using a previously described reverse transcriptase polymerase chain reaction (PCR) technique [25] that has been validated in a multicenter study [26]. Duplicate plasma samples were subjected to ultracentrifugation, and the pellets were extracted by using phenolchloroform. The resulting RNA pellets were reverse transcribed along with a standard curve of known RNA copy number and then amplified by PCR with gag-specific primers. The amount of product in each reaction was measured using a nonisotopic enzyme hybridization assay and was expressed as optical density. The standard curve was generated by plotting the number of RNA copies against the optical density, and the Equation describing the curve was used to calculate the numbers of RNA copies in the patient samples. These numbers were expressed as log RNA copies/mL of plasma. Serum p24 antigen levels were measured by Immunodiagnostic Laboratories (Hayward, California) using an enzyme-linked immunoassay system with an immune-complex disassociation step. Peripheral blood mononuclear cell viral DNA levels were measured using a previously described quantitative PCR technique [27]. Aliquots of 1 10 (6) peripheral blood mononuclear cell pellets were lysed with proteinase K, and 250 000 cell equivalents were amplified in duplicate with a standard curve of known DNA copy number. The amount of product in each reaction was measured using a nonisotopic enzyme hybridization assay and expressed as optical density. The standard curve was generated by plotting the number of DNA copies against optical density, and the Equation describingthe curve was used to calculate the number of DNA copies in the patient samples. These numbers were corrected for percentages of cells that are CD4 cells and expressed as log DNA copies per million CD4 cells. Immunology CD4+ T-cell counts were measured by the AIDS Clinical Trials Group-qualified flow cytometry laboratory at Stanford University Hospital. A screening measurement and two baseline measurements (obtained 2 weeks apart) were done. The average of these three results was used as the baseline value. CD4+ T-cell counts were obtained monthly at the same time that blood was drawn for virologic tests. Mutations The presence of mutations at codon 48 (GV) and 90 (LM) in the plasma of patients was determined by using a selective PCR method similar to that used for the reverse transcriptase gene [28, 29]. Cryopreserved plasma was extracted as previously described [25] and was reverse transcribed using primer TGGAGTATTGTATGGATTTTCAG (Pro1). The complementary DNA was then amplified by using PCR under standard conditions with primer CAGAGCCAACAGCCCCACCA (Pro2). Five L of the 582-base pair first-round PCR product was then amplified with primers specific for the wild-type and mutant sequences at each codon. For codon 48, primers CTTCCTTTTCCATCTCTGTA (IR48) and TGGAAACCAAAAATGACAGG (48WT) were used to determine whether a wild-type sequence was present, and IR48 and TGGAAACCAAAAATGACAGT (48MU) were used to determine whether a mutant sequence was present. For codon 90, primers GAAGCTCTATTAGATACAGG (IR90) and GTGCAACCAATCTGAGCCAA (90WT) were used to determine whether a wild-type sequence was present, and IR90 and GTGCAACCAATCTGAGCCAT (90MU) were used to determine whether a mutant sequence was present. Twenty L of the PCR product from each of the second set of PCR reactions was analyzed for genotype on 3.0% agarose gel with ethidium bromide staining. The PCR products were determined to have a mutant or wild-type sequence according to the method described by Boucher and colleagues [30, 31] and Larder and associates [28]. A sample was considered to contain the codon 48 wild-type sequence if amplification with primers IR48 and 48WT resulted in a 309-base pair product. A sample was considered to contain the codon 90 wild-type sequence if amplification with primers IR90 and 90WT resulted in a 228-base pair product. A sample was considered to contain the codon 90 mutant sequence if amplification with primers IR90 and 90MU resulted in a 228-base pair product. Samples showing bands in both the wild-type and mutant reactions were re-evaluated using 5 L of a 1:20 and 1:400 dilution of the first-round PCR product in a second-round reaction. Samples showing only a wild-type or mutant product in the dilution reactions were scored as wild-type or mutant, respectively. Samples showing both the wild-type and mutant products in the dilution reactions were considered to be mixtures. Samples in which a mixture was detected were reported as mutant for the purposes of the analysis. Patients showing a mutation at either codon 48 or codon 90 at week 24 were assayed at earlier time points to determine the timing of the appearance of the mutation. The selectiv

HIV-1 protease and reverse transcriptase mutations for drug resistance surveillance

Objectives:Monitoring regional levels of transmitted HIV-1 resistance informs treatment guidelines and provides feedback on the success of HIV-1 prevention efforts. Surveillance programs for estimating the frequency of transmitted resistance are being developed in both industrialized and resource-poor countries. However, such programs will not produce comparable estimates unless a standardized list of drug-resistance mutations is used to define transmitted resistance. Methods:In this paper, we outline considerations for developing a list of drug-resistance mutations for epidemiologic estimates of transmitted resistance. First, the mutations should cause or contribute to drug resistance and should develop in persons receiving antiretroviral therapy. Second, the mutations should not occur as polymorphisms in the absence of therapy. Third, the mutation list should be applicable to all group M subtypes. Fourth, the mutation list should be simple, unambiguous, and parsimonious. Results:Applying these considerations, we developed a list of 31 protease inhibitor-resistance mutations at 14 protease positions, 31 nucleoside reverse transcriptase inhibitor-resistance mutations at 15 reverse transcriptase positions, and 18 non-nucleoside reverse transcriptase inhibitor-resistance mutations at 10 reverse transcriptase positions. Conclusions:This list, which should be updated regularly using the same or similar criteria, can be used for genotypic surveillance of transmitted HIV-1 drug resistance.

European guidelines on the clinical management of HIV-1 tropism testing

Viral tropism is the ability of viruses to enter and infect specific host cells and is based on the ability of viruses to bind to receptors on those cells. Testing for HIV tropism is recommended before prescribing a chemokine receptor blocker. In most European countries, HIV tropism is identified with tropism phenotype testing. New data support genotype analysis of the HIV third hypervariable loop (V3) for the identification of tropism. The European Consensus Group on clinical management of tropism testing was established to make recommendations to clinicians and clinical virologists. The panel recommends HIV-tropism testing for the following groups: drug-naive patients in whom toxic effects are anticipated or for whom few treatment options are available; patients who have poor tolerability to or toxic effects from current treatment or who have CNS pathology; and patients for whom therapy has failed and a change in treatment is considered. In general, an enhanced sensitivity Trofile assay and V3 population genotyping are the recommended methods. Genotypic methods are anticipated to be used more frequently in the clinical setting because of their greater accessibility, lower cost, and faster turnaround time than other methods. For the interpretation of V3 loop genotyping, clinically validated systems should be used when possible. Laboratories doing HIV tropism tests should have adequate quality assurance measures. Similarly, close collaboration between HIV clinicians and virologists is needed to ensure adequate diagnostic and treatment decisions.

Therapeutic drug monitoring: an aid to optimising response to antiretroviral drugs?

Therapeutic drug monitoring (TDM) has been proposed as a means to optimise response to highly active antiretroviral therapy (HAART) in HIV infection. Protease inhibitors (PIs) and the non-nucleoside reverse transcriptase inhibitors (NNRTIs) efavirenz and nevirapine satisfy many criteria for TDM. Nucleoside reverse transcriptase inhibitors (NRTIs) are not suitable candidates for TDM, since no clear plasma concentration-effect relationships have been established for these drugs.Several important limitations to the application of TDM for antiretroviral drugs should be recognised, including uncertainty about the best pharmacokinetic predictor of response and insufficient validation of target concentrations for individual PIs and NNRTIs. Data from two clinical trials support the use of TDM in treatment-naive HIV-infected patients who start with an indinavir- or nelfinavir-based regimen. TDM either prevented virological failures (presumably by preventing the development of resistance) or treatment discontinuations due to concentration-related toxicity. Application of routine TDM in other patient groups (treatment-experienced patients) or for drugs other than indinavir or nelfinavir (NNRTIs, other PIs, combination of PIs) is speculative at this moment. However, TDM can be used in selected patient groups (children, pregnant women, patients with renal or hepatic dysfunction) to confirm adequate drug concentrations, and for management of drug-drug interactions.TDM in treatment-experienced patients may be optimally used in conjunction with resistance testing. The integration of pharmacological and virological measures in the inhibitory quotient (IQ) needs to be standardised and elaborated further. TDM should be accompanied by careful assessment of adherence and can itself help identify non-adherence, although a drug concentration only reflects the last few drug doses taken by a patient. Additional clinical trials are needed before routine TDM can be adopted as standard of care in the treatment of HIV infection.

Genotypic changes in human immunodeficiency virus type 1 protease associated with reduced susceptibility and virologic response to the protease inhibitor tipranavir.

ABSTRACT Tipranavir is a novel, nonpeptidic protease inhibitor of human immunodeficiency virus type 1 (HIV-1) with activity against clinical HIV-1 isolates from treatment-experienced patients. HIV-1 genotypic and phenotypic data from phase II and III clinical trials of tipranavir with protease inhibitor-experienced patients were analyzed to determine the association of protease mutations with reduced susceptibility and virologic response to tipranavir. Specific protease mutations were identified based on stepwise multiple-regression analyses of phase II study data sets. Validation included analyses of phase III study data sets to determine if the same mutations would be selected and to assess how these mutations contribute to multiple-regression models of tipranavir-related phenotype and of virologic response. A tipranavir mutation score was developed from these analyses, which consisted of a unique string of 16 protease positions and 21 mutations (10V, 13V, 20M/R/V, 33F, 35G, 36I, 43T, 46L, 47V, 54A/M/V, 58E, 69K, 74P, 82L/T, 83D, and 84V). HIV-1 isolates displaying an increasing number of these tipranavir resistance-associated mutations had a reduced phenotypic susceptibility and virologic response to tipranavir. Regression models for predicting virologic response in phase III trials revealed that each point in the tipranavir score was associated with a 0.16-log10 copies/ml-lower virologic response to tipranavir at week 24 of treatment. A lower number of points in the tipranavir score and a greater number of active drugs in the background regimen were predictive of virologic success. These analyses demonstrate that the tipranavir mutation score is a potentially valuable tool for predicting the virologic response to tipranavir in protease inhibitor-experienced patients.

Mutation D30N Is Not Preferentially Selected by Human Immunodeficiency Virus Type 1 Subtype C in the Development of Resistance to Nelfinavir

ABSTRACT Differences in baseline polymorphisms between subtypes may result in development of diverse mutational pathways during antiretroviral treatment. We compared drug resistance in patients with human immunodeficiency virus subtype C (referred to herein as “subtype-C-infected patients”) versus subtype-B-infected patients following protease inhibitor (PI) therapy. Genotype, phenotype, and replication capacity (Phenosense; Virologic) were determined. We evaluated 159 subtype-C- and 65 subtype-B-infected patients failing first PI treatment. Following nelfinavir treatment, the unique nelfinavir mutation D30N was substantially less frequent in C (7%) than in B (23%; P = 0.03) while L90M was similar (P < 0.5). Significant differences were found in the rates of M36I (98 and 36%), L63P (35 and 59%), A71V (3 and 32%), V77I (0 and 36%), and I93L (91 and 32%) (0.0001 < P < 0.05) in C and B, respectively. Other mutations were L10I/V, K20R, M46I, V82A/I, I84V, N88D, and N88S. Subtype C samples with mutation D30N showed a 50% inhibitory concentration (IC50) change in susceptibility to nelfinavir only. Other mutations increased IC50 correlates to all PIs. Following accumulation of mutations, replication capacity of the C virus was reduced from 43% ± 22% to 22% ± 15% (P = 0.04). We confirmed the selective nature of the D30N mutation in C, and the broader cross-resistance of other common protease inhibitor mutations. The rates at which these mutational pathways develop differ in C and subtype-B-infected patients failing therapy, possibly due to the differential impact of baseline polymorphisms. Because mutation D30N is not preferentially selected in nelfinavir-treated subtype-C-infected patients, as it is in those infected with subtype B, the consideration of using this drug initially to preserve future protease inhibitor options is less relevant for subtype-C-infected patients.

Genetic variation at NNRTI resistance-associated positions in patients infected with HIV-1 subtype C.

Objective: Genetic differences between subtypes of HIV-1, even when not associated with key resistance mutations, are known to affect baseline susceptibility to specific antiretroviral drugs and resistance-development pathways. We studied the prevalence and patterns of non-nucleoside reverse transcriptase inhibitor (NNRTI)-associated mutations in HIV-1 subtype C-infected patients. Method: We analysed the genetic variation at sites associated with NNRTI and nucleoside reverse transcriptase inhibitor resistance in subtype C- versus B-infected patients, both drug-naive and -experienced. We extended the comparison to subtype B records from the Stanford database. Results: A total of 150 subtype B and 341 subtype C-infected patients were studied. No significant differences were found in treatment and clinical parameters between the groups. In NNRTI-naive patients, changes in NNRTI positions were present in 9.3% of subtype B- versus 33.1% of subtype C-infected patients (P < 0.001). Differences were seen in both drug-naive (subtype B, 10.0% versus subtype C, 50.1%; P < 0.021) and drug-experienced NNRTI-naive patients (subtype B, 9.0% versus subtype C, 23.8%; P < 0.001). In NNRTI experienced patients, the number of A98G/S changes was significantly higher in subtype C patients treated with either efavirenz or nevirapine (P < 0.0001), and V106M was higher in efavirenz-treated subtype C-infected patients (P < 0.0001). The average mutation rates were 1.26 and 1.67 per patient for subtypes B and C, respectively (P = 0.036). The frequency of nucleoside associated mutations, but not M184V, in treated patients was significantly higher in subgroup B-infected patients (P = 0.028). Conclusion: Collectively, these data indicate that genetic variation at NNRTI resistance-associated positions such as V106M and A98S is substantially greater in subtype C-infected patients than in subtype B-infected patients. The natural structure of each subtype probably affects the frequency and pattern of drug resistance mutations selected under treatment.