CEBPA repression by MECOM blocks differentiation to drive aggressive leukemias
Bibliographic record
Abstract
Acute myeloid leukemias (AMLs) have an overall poor prognosis with many high-risk cases co-opting stem cell gene regulatory programs, yet the mechanisms through which this occurs remain poorly understood. Increased expression of the stem cell transcription factor, MECOM, underlies one key driver mechanism in largely incurable AMLs. How MECOM results in such aggressive AML phenotypes remains unknown. To address existing experimental limitations, we engineered and applied targeted protein degradation with functional genomic readouts to demonstrate that MECOM promotes malignant stem cell-like states by directly repressing pro-differentiation gene regulatory programs. Remarkably and unexpectedly, a single node in this network, a MECOM-bound cis -regulatory element located 42 kb downstream of the myeloid differentiation regulator CEBPA , is both necessary and sufficient for maintaining MECOM-driven leukemias. Importantly, targeted activation of this regulatory element promotes differentiation of these aggressive AMLs and reduces leukemia burden in vivo , suggesting a broadly applicable differentiation-based approach for improving therapy.
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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) | 0.001 | 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".