Abstract 19: Selective BET Inhibitors Are Useful for Normalizing Inflammation Leading to Reduced Cardiovascular Disease (CVD) in Humans
Bibliographic record
Abstract
Apabetalone (RVX-208) a bromodomain extra-terminal (BET) inhibitor selectively binds the 2nd ligand domain within a BET protein thus displacing it from acetylated lysine marks on histone tails. In clinical trials of ~1000 patients, many (n=499) of whom with CVD when given 200 mg/d RVX-208 had a 55% relative risk reduction in major adverse cardiac events (MACE) vs placebo. This benefit of RVX-208 may stem from ability of BET inhibition (BETi) to calm inflammation, metabolism, coagulation and complement pathways with well-known roles in CVD risks. These potential benefits of RVX-208 underlie BETonMACE a phase 3 CVD events trial. Of major interest is the anti-inflammatory (AI) effects seen in clinical data showing BETi lowers CRP by 28% in RVX-208 treated patients (n=331). RVX-208 lowered IL-6 and MCP-1 U937 cells exposed to LPS in a dose and time dependent manner by 90 and 85%, respectively within 24 hrs. RVX-208 displaced BET proteins BRD2-4 from chromatin. These AI effects underpin studies of RVX-297 a more potent cousin of RVX-208 that lowered IL-6 and MCP-1 in LPS stimulated U937 cells by 95 and 80% respectively within 24 hrs. In ChIP assays, RVX-297 also displaced BET protein BRD4 and pol II from promoters of cytokine genes IL-6 and IL-1β that mediate inflammation. Together, data from studying RVX-208 and -297 show both BET inhibitors displace transcription factors from promoter DNA that control expression of inflammatory genes (IGs) with key roles in CVD. Importance of BETi displacement of BRD4 and pol II from DNA becomes clear when added to the fact that cellular response to inflammation requires immediate and robust expression of defined set of IGs. For this rapid transcriptional response, the cell places chromatin structures upstream of IGs called super-enhancers (SE) or latent enhancers (LE) that act as molecular sinks for attracting BET proteins such as BRD4. The placement of a SE or LE adjacent to a promoter that controls a IG recruits this gene to the response against an inflammatory insult. Thus targeting BET proteins including BRD4 with a selective BETi may have broad effects on many genes or pathways by crippling SE or LE mediated cellular response to the inflammatory component of CVD. This mechanism may have potential implications to other inflammatory diseases.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".