High-level resistance to bictegravir and cabotegravir in subtype A- and D-infected HIV-1 patients failing raltegravir with multiple resistance mutations
Bibliographic record
Abstract
OBJECTIVES: The second-generation integrase strand transfer inhibitor (INSTI) bictegravir is becoming accessible in low- and middle-income countries (LMICs), and another INSTI, cabotegravir, has recently been approved as a long-acting injectable. Data on bictegravir and cabotegravir susceptibility in raltegravir-experienced HIV-1 subtype A- and D-infected patients carrying drug resistance mutations (DRMs) remain very scarce in LMICs. PATIENTS AND METHODS: HIV-1 integrase (IN)-recombinant viruses from eight patients failing raltegravir-based third-line therapy in Uganda were genotypically and phenotypically tested for susceptibility to bictegravir and cabotegravir. Ability of these viruses to integrate into human genomes was assessed in MT-4 cells. RESULTS: HIV-1 IN-recombinant viruses harbouring single primary mutations (N155H or Y143R/S) or in combination with secondary INSTI mutations (T97A, M50I, L74IM, E157Q, G163R or V151I) were susceptible to both bictegravir and cabotegravir. However, combinations of primary INSTI-resistance mutations such as E138A/G140A/G163R/Q148R or E138K/G140A/S147G/Q148K led to decreased susceptibility to both cabotegravir (fold change in EC50 values from 429 to 1000×) and bictegravir (60 to 100×), exhibiting a high degree of cross-resistance. However, these same IN-recombinant viruses showed impaired integration capacity (14% to 48%) relative to the WT HIV-1 NL4-3 strain in the absence of drug. CONCLUSIONS: Though not currently widely accessible in most LMICs, bictegravir and cabotegravir offer a valid alternative to HIV-infected individuals harbouring subtype A and D HIV-1 variants with reduced susceptibility to first-generation INSTIs but previous exposure to raltegravir may reduce efficacy, more so with cabotegravir.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".