Isotretinoin promotes elimination of translation-competent HIV latent reservoirs in CD4T cells
Bibliographic record
Abstract
Development of novel therapeutic strategies that reactivate latent HIV and sensitize reactivated cells to apoptosis is crucial towards elimination of the latent viral reservoir. Among the clinically relevant latency reversing agents (LRA) under investigation, the γc-cytokine IL-15 and the superagonist N-803 have been shown to reactivate latent HIV ex vivo and in vivo. However, their clinical benefit can be hindered by IL-15 promoting survival of infected cells. We previously identified a small molecule, HODHBt, that sensitizes latently infected cells to death upon reactivation with γc-cytokines through a STAT-dependent pathway. In here, we aimed to identify and evaluate FDA-approved compounds that could also sensitize HIV-infected cells to apoptosis. Using the Connectivity Map (CMap), we identified the retinol derivative 13-cis-retinoic acid (Isotretinoin) causes similar transcriptional changes as HODHBt. Isotretinoin enhances IL-15-mediated latency reversal without inducing proliferation of memory CD4 T cells. Ex vivo analysis of PBMCs from ACTG A5325, where Isotretinoin was administered to ART-suppressed people with HIV, showed that Isotretinoin treatment enhances IL-15-mediated latency reversal. Furthermore, we showed that a combination of IL-15 with Isotretinoin promotes the reduction of translation-competent reservoirs ex vivo. Mechanistically, combination of IL-15 and Isotretinoin increases caspase-3 activation specifically in HIV-infected cells but not uninfected cells. Our results suggest that Isotretinoin can be a novel approach to target and eliminate translation-competent HIV reservoirs.
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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 | 0.000 |
| 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 | 0.001 |
| 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".