Activation of a nongenetic AHR-ELMSAN1 axis optimizes BET-targeting therapy and suppresses leukemia stem cells in preclinical models
Bibliographic record
Abstract
Developing strategies to enhance the response to bromodomain and extraterminal domain (BET) inhibitors and effectively eradicate cancer stem cells would represent a major cancer treatment advance against leukemia. Through a functional CRISPR screen, we identified the aryl hydrocarbon receptor (AHR), a ligand-activated transcription factor, as a critical regulator of MYC expression and BET inhibitor sensitivity in human acute myeloid leukemia (AML). Constitutive or pharmacological activation of AHR repressed MYC and synergized with BET inhibitors to inhibit MYC transcription and suppress leukemia growth across diverse AML models. Mechanistically, AHR directly up-regulated a noncanonical target, ELMSAN1, a component of the MiDAC histone deacetylase complex, which promotes histone deacetylation at MYC regulatory elements. ELMSAN1 depletion led to up-regulation of MYC and impaired AHR signaling-induced BET inhibitor sensitization. In vivo, AHR agonists enhanced BET inhibitor efficacy in patient-derived xenografts and murine leukemia models, enabling the use of lower BET inhibitor doses while preserving therapeutic benefit and reducing toxicity. This combination suppressed leukemia stem cell (LSC) gene signatures and reduced LSC frequency, with minimal impact on normal hematopoietic stem and progenitor cells in both human cord blood xenografts and immunocompetent mouse models. Together, these findings uncover a MYC-repressive, nongenetic AHR-ELMSAN1 axis that enhances BET-targeting therapies and selectively impairs LSCs, providing a compelling rationale for clinical translation in AML and potentially other MYC-driven cancers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".