Lack of impact of pre-existing T97A HIV-1 integrase mutation on integrase strand transfer inhibitor resistance and treatment outcome

Abram, Michael E.; Ram, Renee; Margot, Nicolas; Barnes, Tiffany; White, Kirsten; Callebaut, Christian; Miller, Michael D.

doi:10.1371/journal.pone.0172206

Cited by 25 publications

(25 citation statements)

References 103 publications

(167 reference statements)

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“…The Binding affinity is an indication of how strong the ligand is binding to the active site. NOPs associated with a reduction to EVG susceptibility have been previously reported to occur with a relatively high frequency within CRF02_AG IN, however those NOPs were not identified in our study [ 55 , 56 , 57 ].…”

Section: Discussioncontrasting

confidence: 64%

Structural Comparison of Diverse HIV-1 Subtypes using Molecular Modelling and Docking Analyses of Integrase Inhibitors

Isaacs

Mikasi

Obasa

et al. 2020

Viruses

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The process of viral integration into the host genome is an essential step of the HIV-1 life cycle. The viral integrase (IN) enzyme catalyzes integration. IN is an ideal therapeutic enzyme targeted by several drugs; raltegravir (RAL), elvitegravir (EVG), dolutegravir (DTG), and bictegravir (BIC) having been approved by the USA Food and Drug Administration (FDA). Due to high HIV-1 diversity, it is not well understood how specific naturally occurring polymorphisms (NOPs) in IN may affect the structure/function and binding affinity of integrase strand transfer inhibitors (INSTIs). We applied computational methods of molecular modelling and docking to analyze the effect of NOPs on the full-length IN structure and INSTI binding. We identified 13 NOPs within the Cameroonian-derived CRF02_AG IN sequences and further identified 17 NOPs within HIV-1C South African sequences. The NOPs in the IN structures did not show any differences in INSTI binding affinity. However, linear regression analysis revealed a positive correlation between the Ki and EC50 values for DTG and BIC as strong inhibitors of HIV-1 IN subtypes. All INSTIs are clinically effective against diverse HIV-1 strains from INSTI treatment-naïve populations. This study supports the use of second-generation INSTIs such as DTG and BIC as part of first-line combination antiretroviral therapy (cART) regimens, due to a stronger genetic barrier to the emergence of drug resistance.

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Section: Discussioncontrasting

confidence: 64%

Structural Comparison of Diverse HIV-1 Subtypes using Molecular Modelling and Docking Analyses of Integrase Inhibitors

Isaacs

Mikasi

Obasa

et al. 2020

Viruses

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“…However, a previous study shows that T97A does not significantly reduce susceptibility to INSTI with up to 94% and 97% viral suppression achievable in HIV-1 patients with preexisting and emerging T97A, respectively. 35 The prevalence of the M50I polymorphism observed in INSTI-naive patients is lower compared to the 10% found in patients infected with HIV-1 subtype B virus, which shows variation in the evolution of INSTI-associated mutations in different viral subtype populations. A relatively small number of patients were infected with viruses carrying the E157Q mutation, which has shown to increase susceptibility to DTG.…”

Section: Discussionmentioning

confidence: 88%

“…T97A has been shown to preexist in 5%-10% of INSTI-naive patients infected with subtype A virus. 35 In addition, T97A was previously coselected in the presence of primary INSTI DRMs by RAL in many clinical studies, 36,37 and by DTG in treatmentexperienced patients with preexisting RAL-associated resistance mutations. 32 As expected, the lack of INSTI resistance is attributable to the absence of INSTI treatment in Uganda and most of sub-Saharan Africa.…”

Section: Hiv-1 Susceptibility To Dolutegravirmentioning

confidence: 99%

Absence of HIV-1 Drug Resistance Mutations Supports the Use of Dolutegravir in Uganda

Ndashimye

Avino

Kyeyune

et al. 2018

AIDS Research and Human Retroviruses

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To screen for drug resistance and possible treatment with Dolutegravir (DTG) in treatment-naive patients and those experiencing virologic failure during first-, second-, and third-line combined antiretroviral therapy (cART) in Uganda. Samples from 417 patients in Uganda were analyzed for predicted drug resistance upon failing a first- (N = 158), second- (N = 121), or third-line [all 51 involving Raltegravir (RAL)] treatment regimen. HIV-1 pol gene was amplified and sequenced from plasma samples. Drug susceptibility was interpreted using the Stanford HIV database algorithm and SCUEAL was used for HIV-1 subtyping. Frequency of resistance to nucleoside reverse transcriptase inhibitors (NRTIs) (95%) and non-NRTI (NNRTI, 96%) was high in first-line treatment failures. Despite lack of NNRTI-based treatment for years, NNRTI resistance remained stable in 55% of patients failing second-line or third-line treatment, and was also at 10% in treatment-naive Ugandans. DTG resistance (n = 366) was not observed in treatment-naive individuals or individuals failing first- and second-line cART, and only found in two patients failing third-line cART, while 47% of the latter had RAL- and Elvitegravir-resistant HIV-1. Secondary mutations associated with DTG resistance were found in 2%-10% of patients failing third-line cART. Of 14 drugs currently available for cART in Uganda, resistance was readily observed to all antiretroviral drugs (except for DTG) in Ugandan patients failing first-, second-, or even third-line treatment regimens. The high NNRTI resistance in first-line treatment in Uganda even among treatment-naive patients calls for the use of DTG to reach the UNAIDS 90:90:90 goals.

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“…In our post-hoc analysis of phenotypic data in HIVDB, E157Q alone was not found to reduce RAL and EVG susceptibility, whereas T97A alone was found to reduce EVG susceptibility by about five fold ( Table 11 ). However, in a study published during the completion of this manuscript, the presence of T97A at baseline was reported to not interfere with virological response to therapy with a first-line EVG-containing regimen [ 60 ].…”

Section: Discussionmentioning

confidence: 99%

Collaborative update of a rule-based expert system for HIV-1 genotypic resistance test interpretation

et al. 2017

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IntroductionHIV-1 genotypic resistance test (GRT) interpretation systems (IS) require updates as new studies on HIV-1 drug resistance are published and as treatment guidelines evolve.MethodsAn expert panel was created to provide recommendations for the update of the Stanford HIV Drug Resistance Database (HIVDB) GRT-IS. The panel was polled on the ARVs to be included in a GRT report, and the drug-resistance interpretations associated with 160 drug-resistance mutation (DRM) pattern-ARV combinations. The DRM pattern-ARV combinations included 52 nucleoside RT inhibitor (NRTI) DRM pattern-ARV combinations (13 patterns x 4 NRTIs), 27 nonnucleoside RT inhibitor (NNRTI) DRM pattern-ARV combinations (9 patterns x 3 NNRTIs), 39 protease inhibitor (PI) DRM pattern-ARV combinations (13 patterns x 3 PIs) and 42 integrase strand transfer inhibitor (INSTI) DRM pattern-ARV combinations (14 patterns x 3 INSTIs).ResultsThere was universal agreement that a GRT report should include the NRTIs lamivudine, abacavir, zidovudine, emtricitabine, and tenofovir disoproxil fumarate; the NNRTIs efavirenz, etravirine, nevirapine, and rilpivirine; the PIs atazanavir/r, darunavir/r, and lopinavir/r (with “/r” indicating pharmacological boosting with ritonavir or cobicistat); and the INSTIs dolutegravir, elvitegravir, and raltegravir. There was a range of opinion as to whether the NRTIs stavudine and didanosine and the PIs nelfinavir, indinavir/r, saquinavir/r, fosamprenavir/r, and tipranavir/r should be included. The expert panel members provided highly concordant DRM pattern-ARV interpretations with only 6% of NRTI, 6% of NNRTI, 5% of PI, and 3% of INSTI individual expert interpretations differing from the expert panel median by more than one resistance level. The expert panel median differed from the HIVDB 7.0 GRT-IS for 20 (12.5%) of the 160 DRM pattern-ARV combinations including 12 NRTI, two NNRTI, and six INSTI pattern-ARV combinations. Eighteen of these differences were updated in HIVDB 8.1 GRT-IS to reflect the expert panel median. Additionally, HIVDB users are now provided with the option to exclude those ARVs not considered to be universally required.ConclusionsThe HIVDB GRT-IS was updated through a collaborative process to reflect changes in HIV drug resistance knowledge, treatment guidelines, and expert opinion. Such a process broadens consensus among experts and identifies areas requiring further study.

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Lack of impact of pre-existing T97A HIV-1 integrase mutation on integrase strand transfer inhibitor resistance and treatment outcome

Cited by 25 publications

References 103 publications

Structural Comparison of Diverse HIV-1 Subtypes using Molecular Modelling and Docking Analyses of Integrase Inhibitors

Structural Comparison of Diverse HIV-1 Subtypes using Molecular Modelling and Docking Analyses of Integrase Inhibitors

Absence of HIV-1 Drug Resistance Mutations Supports the Use of Dolutegravir in Uganda

Collaborative update of a rule-based expert system for HIV-1 genotypic resistance test interpretation

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