<scp>BRD</scp>4 associates with p53 in <scp>DNMT</scp>3A‐mutated leukemia cells and is implicated in apoptosis by the bromodomain inhibitor <scp>JQ</scp>1
Bibliographic record
Abstract
The bromodomain and extra terminal (BET) family protein bromodomain containing protein 4 (BRD4) is an epigenetic regulator recently identified as a therapeutic target for several hematological cancers, notably mixed lineage leukemia-fusion acute myeloid leukemia (MLL-AML). Here, we show that the BRD4 bromodomain inhibitor JQ1 is highly active against the p53-wild-type Ontario Cancer Institute (OCI)-AML3 cell line which carries mutations in nucleophosmin (NPM1) and DNA methyltransferase 3 (DNMT3A) genes commonly associated with poor prognostic disease. We find that JQ1 causes caspase 3/7-mediated apoptosis and DNA damage response in these cells. In combination studies, we show that histone deacetylase (HDAC) inhibitors, the HDM2 inhibitor Nutlin-3, and the anthracycline daunorubicin all enhance the apoptotic response of JQ1. These compounds all induce activation of p53 suggesting that JQ1 might sensitize AML cells to p53-mediated cell death. In further experiments, we show that BRD4 associates with acetylated p53 but that this association is not inhibited by JQ1 indicating that the protein-protein interaction does not involve bromodomain binding of acetylated lysines. Instead, we propose that JQ1 acts to prevent BRD4-mediated recruitment of p53 to chromatin targets following its activation in OCI-AML3 cells resulting in cell cycle arrest and apoptosis in a c-MYC-independent manner. Our data suggest that BET bromodomain inhibition might enhance current chemotherapy strategies in AML, notably in poor-risk DNMT3A/NPM1-mutated disease.
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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) | 0.002 | 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".