Dasatinib interferes with HIV-1 proviral integration and the inflammatory potential of monocyte-derived macrophages from people with HIV
Bibliographic record
Abstract
HIV-1 infection is efficiently controlled by the antiretroviral treatment (ART) but viral persistence in long-lived reservoirs formed by CD4 + T cells and macrophages impedes viral eradication and creates a chronic inflammatory environment. Dasatinib is a tyrosine kinase inhibitor clinically used against chronic myeloid leukemia (CML) that has also showed an anti-inflammatory potential. We previously reported that dasatinib is very efficient at interfering with HIV-1 infection of CD4 + T cells by preserving the antiviral activity of SAMHD1, an innate immune factor that blocks T-cell activation and proliferation and that is inactivated by phosphorylation at T592 (pSAMHD1). We observed that short-term treatment in vitro with dasatinib significantly reduced pSAMHD1 in monocyte-derived macrophages (MDMs) isolated from people with HIV (PWH) and healthy donors, interfering with HIV-1 infection. This inhibition was based on low levels of 2-LTR circles and proviral integration, while viral reverse transcription was not affected. MDMs isolated from people with CML on long-term treatment with dasatinib also showed low levels of pSAMHD1 and were resistant to HIV-1 infection. In addition, dasatinib decreased the inflammatory potential of MDMs by reducing the release of M1-related cytokines like TNFα, IL-1β, IL-6, CXCL8, and CXCL9, but preserving the antiviral activity through normal levels of IL-12 and IFNγ. Due to the production of M2-related anti-inflammatory cytokines like IL-1RA and IL-10 was also impaired, dasatinib appeared to interfere with MDMs differentiation. The use of dasatinib along with ART could be used against HIV-1 reservoir in CD4 and macrophages and to alleviate the chronic inflammation characteristic of PWH.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".