A Synthetic Lethal Approach to Eradicate AML Via Synergistic Activation of Pro-Apoptotic p53 By MDM2 and BET Inhibitors
Bibliographic record
Abstract
Acute Myeloid Leukemia (AML) is a typically-lethal molecularly heterogeneous disease, with few broad-spectrum therapeutic targets. Unusually compared to many other cancers, over 90% of AML patients retain wild type TP53, encoding pro-apoptotic tumor suppressor p53. However, wild-type p53 functions are frequently suppressed by MDM2, an E3 ubiquitin ligase that targets p53 for proteasomal degradation. MDM2 inhibitors (MDM2i), which activate wild-type p53, show encouraging pre-clinical activity, but limited clinical activity. In an effort to find targets that synergize with p53 activation via MDM2i and minimize toxicity, we performed a cell-based synthetic lethal drug screen and a CRISPR viability screen. These screens identified BRD4 inhibition as a candidate synthetic lethal partner of MDM2i. BRD4 is a member of the Bromodomains and Extraterminal (BET) family of proteins, a transcriptional co-activator and already a candidate AML therapeutic target. Surprisingly, we found inhibition of BRD4 alone induces expression of some of p53 target genes. We unexpectedly reveal that BRD4 binds to p53 target genes and acts as a transcriptional repressor of these genes. Synergistic cell killing by the drug combination (MDM2i + BET inhibitor (BETi)) depends on synergistic activation of p53 target genes, such as PUMA and NOXA, due to simultaneous stabilization of p53 by MDM2i and relief of BRD4-mediated repression by BETi. Our combined therapy of MDM2i and BETi is synergistically lethal to human AML cell lines harboring wild type TP53in vitro, against two mouse models of AML in vivo, and against primary human patient blasts in vitro. Furthermore, we used BET PROTACs to selectively and completely induce degradation of BRD4 in cells. Consistent with results from BETi, BET degraders and MDM2i synergize to suppress cell viability with superior potency. Taken together, our data show BRD4 represses p53-mediated transcription activation and apoptosis in AML. Therefore, co-targeting wild-type TP53 and a transcriptional repressor function of BRD4 represent a novel synthetic lethal vulnerability in AML. Disclosures Latif: AbbVie: Consultancy, Honoraria; Takeda UK: Speakers Bureau; Novartis: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Kite: Consultancy, Honoraria, Speakers Bureau; Jazz: Consultancy, Honoraria; Daiichi Sankyo: Consultancy, Honoraria. Higgins:Roche: Current Employment, Current equity holder in publicly-traded company, Other: Support of parent study and funding of editorial support. Copland:Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Cyclacel Ltd: Research Funding; Roche: Research Funding; Epizyme: Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Pfizer: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Daiichi-Sankyo: Membership on an entity's Board of Directors or advisory committees; Astellas: Speakers Bureau; Gilead: Speakers Bureau.
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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) | 0.001 | 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 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".