The ingenol-based protein kinase C agonist GSK445A is a potent inducer of HIV and SIV RNA transcription
Bibliographic record
Abstract
Activation of the NF-κB signaling pathway by Protein Kinase C (PKC) agonists is a potent mechanism for human immunodeficiency virus (HIV) latency disruption in vitro. However, significant toxicity risks and the lack of evidence supporting their activity in vivo have limited further evaluation of PKC agonists as HIV latency-reversing agents (LRA) in cure strategies. Here we evaluated whether GSK445A, a stabilized ingenol-B derivative, can induce HIV/simian immunodeficiency virus (SIV) transcription and virus production in vitro and demonstrate pharmacological activity in nonhuman primates (NHP). CD4+ T cells from people living with HIV and from SIV+ rhesus macaques (RM) on antiretroviral therapy (ART) exposed in vitro to 25 nM of GSK445A produced cell-associated viral transcripts as well as viral particles at levels similar to those induced by PMA/Ionomycin, indicating that GSK445A can potently reverse HIV/SIV latency. Importantly, these concentrations of GSK445A did not impair the proliferation or survival of HIV-specific CD8+ T cells, but instead, increased their numbers and enhanced IFN-γ production in response to HIV peptides. In vivo, GSK445A tolerability was established in SIV-naïve RM at 15 μg/kg although tolerability was reduced in SIV-infected RM on ART. Increases in plasma viremia following GSK445A administration were suggestive of increased SIV transcription in vivo. Collectively, these results indicate that GSK445A is a potent HIV/SIV LRA in vitro and has a tolerable safety profile amenable for further evaluation in vivo in NHP models of HIV cure/remission.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".