Discordance between etravirine phenotype and genotype-based predicted phenotype for subtype C HIV-1 from first-line antiretroviral therapy failures in South Africa

Etravirine (ETR) is a nonnucleoside reverse transcriptase inhibitor (NNRTI) used in treatment-experienced individuals. Genotypic resistance test-interpretation systems can predict ETR resistance; however, genotype-based algorithms are derived primarily from HIV-1 subtype B and may not accurately predict resistance in non-B subtypes. The frequency of ETR resistance among recombinant subtype C HIV-1 and the accuracy of genotypic interpretation systems were investigated. HIV-1LAI containing full-length RT from HIV-1 subtype C-positive individuals experiencing virologic failure (>10,000 copies/ml and >1 NNRTI resistance-associated mutation) were phenotyped for ETR susceptibility. Fold change (FC) was calculated against a composite 50% effective concentration (EC50) from treatment-naive individuals and three classifications were assigned: (i) <2.9-FC, susceptible; (ii) <2.9- to 10-FC, partially resistant; and (iii) <10-FC, fully resistant. The Stanford HIVdb-v8.4 was used for genotype predictions merging the susceptible/potential low-level and low-level/intermediate groups for 3×3 comparison. Fifty-four of a hundred samples had reduced ETR susceptibility (≥2.9-FC). The FC correlated with HIVdb-v8.4 (Spearman's rho=0.62; P < 0.0001); however, 44% of samples were partially (1 resistance classification difference) and 4% completely discordant (2 resistance classification differences). Of the 34 samples with an FC of>10, 26 were HIVdb-v8.4 classified as low-intermediate resistant. Mutations L100I, Y181C, or M230L were present in 27/34 (79%) of samples with an FC of >10 but only in 2/46 (4%) of samples with an FC of <2.9. No other mutations were associated with ETR resistance. Viruses containing the mutation K65R were associated with reduced ETR susceptibility, but 65R reversions did not increase ETR susceptibility. Therefore, genotypic interpretation systems were found to misclassify ETR susceptibility in HIV-1 subtype C samples. Modifications to genotypic algorithms are needed to improve the prediction of ETR resistance for the HIV-1 subtype C.