Entinostat Prevents Leukemia Maintenance in a Collaborating Oncogene-Dependent Model of Cytogenetically Normal Acute Myeloid Leukemia
Bibliographic record
Abstract
The incidence of refractory acute myeloid leukemia (AML) is on the increase due in part to an aging population that fails to respond to traditional therapies. High throughput genomic analysis promises better diagnosis, prognosis, and therapeutic intervention based on improved patient stratification. Relevant preclinical models are urgently required to advance drug development in this area. The collaborating oncogenes, HOXA9 and MEIS1, are frequently co-overexpressed in cytogenetically normal AML (CN-AML), and a conditional transplantation mouse model was developed that demonstrated oncogene dependency and expression levels comparable to CN-AML patients. Integration of gene signatures obtained from the mouse model and a cohort of CN-AML patients using statistically significant connectivity map analysis identified Entinostat as a drug with the potential to alter the leukemic condition toward the normal state. Ex vivo treatment of leukemic cells, but not age-matched normal bone marrow controls, with Entinostat validated the gene signature and resulted in reduced viability in liquid culture, impaired colony formation, and loss of the leukemia initiating cell. Furthermore, in vivo treatment with Entinostat resulted in prolonged survival of leukemic mice. This study demonstrates that the HDAC inhibitor Entinostat inhibits disease maintenance and prolongs survival in a clinically relevant murine model of cytogenetically normal AML.
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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 | 0.000 | 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) | 0.000 | 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".