HIV-1 phenotypic reverse transcriptase inhibitor drug resistance test interpretation is not dependent on the subtype of the virus backbone.

To date, the majority of HIV-1 phenotypic resistance testing has been performed with subtype B virus backbones (e.g. HXB2). However, the relevance of using this backbone to determine resistance in non-subtype B HIV-1 viruses still needs to be assessed. From 114 HIV-1 subtype C clinical samples (36 ARV-naïve, 78 ARV-exposed), pol amplicons were produced and analyzed for phenotypic resistance using both a subtype B- and C-backbone in which the pol fragment was deleted. Phenotypic resistance was assessed in resulting recombinant virus stocks (RVS) for a series of antiretroviral drugs (ARV's) and expressed as fold change (FC), yielding 1660 FC comparisons. These Antivirogram® derived FC values were categorized as having resistant or sensitive susceptibility based on biological cut-off values (BCOs). The concordance between resistance calls obtained for the same clinical sample but derived from two different backbones (i.e. B and C) accounted for 86.1% (1429/1660) of the FC comparisons. However, when taking the assay variability into account, 95.8% (1590/1660) of the phenotypic data could be considered as being concordant with respect to their resistance call. No difference in the capacity to detect resistance associated with M184V, K103N and V106M mutations was noted between the two backbones. The following was concluded: (i) A high level of concordance was shown between the two backbone phenotypic resistance profiles; (ii) Assay variability is largely responsible for discordant results (i.e. for FC values close to BCO); (iii) Confidence intervals should be given around the BCO's, when assessing resistance in HIV-1 subtype C; (iv) No systematic resistance under- or overcalling of subtype C amplicons in the B-backbone was observed; (v) Virus backbone subtype sequence variability outside the pol region does not contribute to phenotypic FC values. In conclusion the HXB2 virus backbone remains an acceptable vector for phenotyping HIV-1 subtype C pol amplicons.

Broad phenotypic cross-resistance to elvitegravir in HIV-infected patients failing on raltegravir-containing regimens.

The failure of raltegravir (RAL) is generally associated with the selection of mutations at integrase position Y143, Q148, or N155. However, a relatively high proportion of failures occurs in the absence of these changes. Here, we report the phenotypic susceptibilities to RAL and elvitegravir (EVG) for a large group of HIV-infected patients failing on RAL-containing regimens. Plasma from HIV-infected individuals failing on RAL-containing regimens underwent genotypic and phenotypic resistance testing (Antivirogram v2.5.01; Virco). A control group of patients failing on other regimens was similarly tested. Sixty-one samples were analyzed, 40 of which belonged to patients failing on RAL-containing regimens. Full RAL susceptibility was found in 20/21 controls, while susceptibility to EVG was diminished in 8 subjects, with a median fold change (FC) of 2.5 (interquartile range [IQR], 2.1 to 3.1). Fourteen samples from patients with RAL failures showed diminished RAL susceptibility, with a median FC of 38.5 (IQR, 10.8 to 103.2). Primary integrase resistance mutations were found in 11 of these samples, displaying a median FC of 68.5 (IQR, 23.5 to 134.3). The remaining 3 samples showed a median FC of 2.5 (IQR, 2 to 2.7). EVG susceptibility was diminished in 19/40 samples from patients with RAL failures (median FC, 7.71 [IQR, 2.48 to 99.93]). Cross-resistance between RAL and EVG was high (R(2) = 0.8; P < 0.001), with drug susceptibility being more frequently reduced for EVG than for RAL (44.3% versus 24.6%; P = 0.035). Susceptibility to RAL and EVG is rarely affected in the absence of primary integrase resistance mutations. There is broad cross-resistance between RAL and EVG, which should preclude their sequential use. Resistance to EVG seems to be more frequent and might be more influenced by integrase variability.

Comparative analysis of drug resistance among B and the most prevalent non-B HIV type 1 subtypes (C, F, and CRF02_AG) in Italy.

In recent years, increasing numbers of patients infected with HIV-1 non-B subtypes have been treated with modern antiretroviral regimens. Therefore, a better knowledge of HIV drug resistance in non-B strains is crucial. Thus, we compared the mutational pathways involved in drug resistance among the most common non-B subtypes in Italy (F, C, and CRF02_AG) and the B subtype. In total, 2234 pol sequences from 1231 virologically failing patients from Central Italy were analyzed. The prevalence of resistance mutations in protease and reverse transcriptase between non-B and B subtypes has been evaluated. Among patients treated with nucleoside/nucleotide reverse transcriptase inhibitors (NRTI) and with thymidine analogues (TA) experience, TAMs1 M41L and L210W were less prevalent in CRF02_AG, while TAMs2 T215F and K219E were more prevalent in the F subtype. In NRTI-treated patients having experience with abacavir, didanosine, tenofovir, or stavudine the K65R mutation was mostly prevalent in the C subtype. In non-NRTI (NNRTI)-treated patients infected by the C subtype the prevalence of K103N was lower than in patients infected with other subtypes, while the prevalence of Y181C and Y188L was higher compared to subtype B. The prevalence of Y181C was higher also in subtype F as compared to subtype B. In patients treated with protease inhibitors, L89V was predominantly found in CRF02_AG, while the TPV resistance mutation T74P was predominantly found in the C subtype. Some differences in the genotypic drug resistance have been found among patients infected with B, C, F, and CRF02_AG subtypes in relationship to treatment. These results may be useful for the therapeutic management of individuals infected with HIV-1 non-B strains.

A non-infectious cell-based phenotypic assay for the assessment of HIV-1 susceptibility to protease inhibitors.

OBJECTIVES: HIV-1 genotyping is widely accepted as a diagnostic tool to optimize therapy changes in patients whose antiretroviral regimen is failing. Phenotyping can substantially complement the information obtained from genotyping, especially in the presence of complex mutational patterns. However, drug susceptibility tests are laborious and require biosafety facilities. We describe the molecular mechanism of a non-infectious HIV-1 protease phenotypic assay in eukaryotic cells and validate its applicability as a tool for monitoring drug resistance. METHODS: A cloning vector containing the fusion protein green fluorescent protein-HIV-1 protease (GFP-PR) was modified to facilitate the insertion of HIV-1 protease from infected subjects. Real-time quantitative PCR and western blot analysis were used to establish the molecular mechanism of the new phenotypic assay. The method was validated by analysing HIV-1 protease from 46 clinical isolates. Statistical comparisons were made between values obtained using our assay and those reported from alternative standardized phenotypic assays. RESULTS: The capacity of HIV-1 protease to cleave cellular translation factors, such as the eukaryotic translation initiation factor 4 (eIF4GI) and the poly(A)-binding protein (PABP), led to cyclical accumulation of GFP that varied with the dose of protease inhibitors. Validation and comparison revealed a significant correlation with the Virco TYPE HIV-1 test (P < 0.0001, Spearman's ρ = 0.60), the Antivirogram test (P = 0.0001, Spearman's ρ = 0.60) and the Stanford HIVdb (P < 0.0001, Spearman's ρ = 0.69). CONCLUSIONS: This cell-based non-infectious phenotypic method with a well-understood molecular mechanism was highly reliable and comparable to other widely used assays. The method can be used for both phenotyping of HIV-1 viral isolates resistant to protease inhibitors and screening of new protease inhibitors.

Cross-validated stepwise regression for identification of novel non-nucleoside reverse transcriptase inhibitor resistance associated mutations.

BACKGROUND: Linear regression models are used to quantitatively predict drug resistance, the phenotype, from the HIV-1 viral genotype. As new antiretroviral drugs become available, new resistance pathways emerge and the number of resistance associated mutations continues to increase. To accurately identify which drug options are left, the main goal of the modeling has been to maximize predictivity and not interpretability. However, we originally selected linear regression as the preferred method for its transparency as opposed to other techniques such as neural networks. Here, we apply a method to lower the complexity of these phenotype prediction models using a 3-fold cross-validated selection of mutations. RESULTS: Compared to standard stepwise regression we were able to reduce the number of mutations in the reverse transcriptase (RT) inhibitor models as well as the number of interaction terms accounting for synergistic and antagonistic effects. This reduction in complexity was most significant for the non-nucleoside reverse transcriptase inhibitor (NNRTI) models, while maintaining prediction accuracy and retaining virtually all known resistance associated mutations as first order terms in the models. Furthermore, for etravirine (ETR) a better performance was seen on two years of unseen data. By analyzing the phenotype prediction models we identified a list of forty novel NNRTI mutations, putatively associated with resistance. The resistance association of novel variants at known NNRTI resistance positions: 100, 101, 181, 190, 221 and of mutations at positions not previously linked with NNRTI resistance: 102, 139, 219, 241, 376 and 382 was confirmed by phenotyping site-directed mutants. CONCLUSIONS: We successfully identified and validated novel NNRTI resistance associated mutations by developing parsimonious resistance prediction models in which repeated cross-validation within the stepwise regression was applied. Our model selection technique is computationally feasible for large data sets and provides an approach to the continued identification of resistance-causing mutations.

The HIV-1 integrase G118R mutation confers raltegravir resistance to the CRF02_AG HIV-1 subtype.

BACKGROUND: Most of the previous studies that explored the molecular basis of raltegravir resistance were conducted studying the HIV-1 B subtype. It has been shown that the CRF02_AG subtype in relation to its natural integrase (IN) sequence could develop different genetic pathways associated with raltegravir resistance. The aim of this study was to explore resistance pathways preferably used by CRF02_AG viruses compared with subtype B. METHODS: Twenty-five HIV-1 CRF02_AG-infected patients failing a raltegravir-containing regimen were studied. IN gene sequences were examined for the presence of previously described IN inhibitor (raltegravir, elvitegravir, dolutegravir and MK-2048) resistance mutations at 20 amino acid positions. RESULTS: Among the 25 studied patients, 7 showed viruses harbouring major raltegravir resistance mutations mainly associated with the 155 genetic pathways and 18 showed viruses harbouring none of them; however, for 1 patient, we found a 118R mutation, associated with MK-2048 in vitro resistance, in a 74M background. For this patient, the phenotypic analysis showed that addition of only the G118R mutation conferred a high level of resistance to raltegravir (fold change = 25.5) and elvitegravir (fold change = 9.2). CONCLUSIONS: This study confirmed that mutation pathways for raltegravir resistance could be different between the two subtypes CRF02_AG and B with a preferential use of the 155 mutation in non-B subtypes. A new genetic pathway associated with raltegravir resistance, including the 118R mutation, has also been identified. This new genetic pathway, never described in subtype B, should be further evaluated for phenotypic susceptibility to dolutegravir and MK-2048.

Comparison of drug resistance scores for tipranavir in protease inhibitor-naive patients infected with HIV-1 B and non-B subtypes.

Genotypes of samples from protease inhibitor-naïve patients in Frankfurt's HIV Cohort were analyzed with five tipranavir resistance prediction algorithms. Mean scores were higher in non-B than in B subtypes. The proportion of non-B subtypes increased with increasing scores, except in weighted algorithms. Virtual and in vitro phenotype analyses of samples with increased scores showed no reduced tipranavir susceptibility. Current algorithms appear suboptimal for interpretation of resistance to tipranavir in non-B subtypes; increased scores might reflect algorithm bias rather than "natural resistance."

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.

A comparison of HIV-1 drug susceptibility as provided by conventional phenotyping and by a phenotype prediction tool based on viral genotype.

Concordance between the conventional HIV-1 phenotypic drug resistance assay, PhenoSense (PS), and vircoTYPE HIV-1 (vT), a drug resistance assay based on prediction of the phenotype, was investigated in a data set from the Stanford HIV Resistance database (hivdb). Depending on the drug, between 287 and 902 genotype-phenotype data pairs were available for comparisons. Test results (fold-change values) in the two assays were highly correlated, with an overall mean correlation coefficient of 0.90 using single PS measurements. This coefficient rose to 0.94 when the vT results were compared to the mean of repeat PS measurements. These results are comparable with the corresponding correlation coefficients of 0.87 and 0.95, calculated using single measurements, and the mean of repeat measurements, respectively, as obtained in the Antivirogram assay, the conventional HIV-1 phenotypic drug resistance test on which vT is based. The proportion of resistance calls resulting in a "major" discordance (fully susceptible or maximal response by one assay but fully resistant or minimal response by the other) ranged from 0% to 8.1% for drugs for which two clinical test cut-offs were available in both assays (didanosine, abacavir, tenofovir, saquinavir/r, fosamprenavir/r, and lopinavir/r), from 2.4% to 8.1% for the drugs for which two clinical test cut-offs were available in the vT assay and one clinical test cut-off in the PS assay (lamivudine, stavudine, indinavir/r, and atazanavir/r) and from 3.1% to 10.3% for drugs for which biological test cut-offs were used (zidovudine, nevirapine, delavirdine, efavirenz, indinavir, ritonavir, nelfinavir, saquinavir, and fosamprenavir). Our analyses suggest that these assays provide comparable resistance information, which will be of value to physicians who may be presented with either or both types of test report in their practice.

Natural polymorphism in protease and reverse transcriptase genes and in vitro antiretroviral drug susceptibilities of non-B HIV-1 strains from treatment-naive patients.

BACKGROUND: Most studies on antiretroviral (ARV) resistance of human immunodeficiency virus (HIV) have been done on subtype B which only represent a limited proportion of infections worldwide. OBJECTIVE: Understand baseline susceptibilities to ARVs in non-B strains. METHODS: To explore in greater detail possible intrinsic resistance to antiretroviral drugs in non-B subtypes, phenotypic resistance was tested in 35 non-B (A, D, F, G, J; CRF02, 06, 09, 11, 13) HIV-1 isolates obtained from ARV treatment naive patients. The panel includes strains with an increasing number of minor mutations in the protease gene and/or with atypical mutations at positions associated with resistance in protease and RT. RESULTS: We detected phenotypic resistance (fold-change values equal or superior to biological test cut-offs (BCO) in 14 of the 35 strains, 4 strains had decreased in vitro susceptibility to more than one drug. However, it is important to note that in most cases the increased fold-changes were close to the BCOs. Phenotypic resistance was observed against each of the three ARV drug classes: ritonavir (n=3), nelfinavir (n=2), saquinavir (n=2), zidovudine (n=2), stavudine (n=1), didanosine (n=1); delavirdine (n=6), efavirenz (n=1) and nevirapine (n=1). Some mutations could be associated with decreased in vitro susceptibility: 1 of 3 strains only with mutations M46I/L in protease, 1/2 A98S, K101N, V108I, V179I, and P236L in reverse transcriptase. Interestingly, the presence of an increasing number of minor mutations in the protease gene was not associated with decreased in vitro susceptibility to protease inhibitors. CONCLUSION: It is necessary to continue phenotypic studies on non-subtype B strains to identify the role of all polymorphisms present in protease and RT genes and to optimize interpretation algorithms. Data obtained from large, diverse populations of HIV-1 infected individuals is critical for defining and standardizing the quantification of resistance (phenotypic and genotypic testing).