Abstract 14112: Apabetalone (RVX-208) Reduces ACE2 Expression in Human Cell Culture Systems, Which Could Attenuate SARS-CoV-2 Viral Entry
Bibliographic record
Abstract
Introduction: Apabetalone is an orally available small molecule that affects gene transcription by inhibiting BET protein interactions with acetylated histones and transcription factors. Apabetalone is in late stage clinical development for the treatment of cardiovascular disease (CVD). Clinical trials show apabetalone is well tolerated and has a favorable safety profile. Recent evidence indicates this drug could be repurposed to treat COVID-19 by reducing expression of the angiotensin converting enzyme 2 (ACE2) receptor that is essential for SARS-CoV-2 viral entry and/or disrupting viral protein E interaction with BET proteins. The spike protein of SARS-CoV-2 engages with human ACE2 expressed in multiple organs such as lung, liver, kidney, heart and intestine to initiate infection in host cells. Ultimately, the infection leads to life threatening complications in COVID-19 patients. Hypothesis: Apabetalone downregulates ACE2 expression to protect human cells from SARS-CoV-2. Methods: Primary human kidney tubular epithelial cells (RPTEC) were stimulated with TNFα and co-treated with apabetalone overnight. Primary human hepatocytes (PHH) and the hepatoma cell line, HepG2, were treated up to 96 h with apabetalone or other BET inhibitors (BETi). Gene expression was analyzed by microarray or RT-PCR. Human aortic endothelial cells (HAEC) were pretreated with apabetalone for 1 h followed by TNFα stimulation for another 1h. Chromatin occupancy of the BET protein BRD4 was examined by ChIP-seq. Results: In RPTEC, 5μM apabetalone downregulated ACE2 mRNA by 50%. Apabetalone dose dependently reduced ACE2 gene expression in HepG2 or PHH from 3 independent donors by up to 90%. JQ1 is a pan BET inhibitor, whereas MZ1 promotes BET protein degradation. Both JQ1 and MZ1 treatments downregulated ACE2 in liver cells, indicating an on target BETi effect. In HAEC, apabetalone abolished BRD4 occupancy at an enhancer in proximity to the ACE2 gene. Conclusions: Apabetalone reduces ACE2 gene expression in multiple human cell types. ACE2 expression may be regulated by adjacent BRD4 enhancer occupancy. The impact of apabetalone on SARS-CoV-2 life cycle is under investigation. The results will provide mechanistic support for potential COVID-19 clinical trials.
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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) | 0.006 | 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".