c‐Met inhibition in a <i>HOXA9/Meis1</i> model of CN‐AML
Bibliographic record
Abstract
BACKGROUND: Hematopoiesis is a paradigm for developmental processes, hierarchically organized, with stem cells at its origin. Hematopoietic stem cells (HSCs) replenish progenitor and precursor cells of multiple lineages, which normally differentiate into short-lived mature circulating cells. Hematopoiesis has provided insight into the molecular basis of tissue homeostasis and malignancy. Malignant hematopoiesis, in particular acute myeloid leukemia (AML), results from impaired development or differentiation of HSCs and progenitors. Co-overexpression of HOX and TALE genes, particularly the HOXA cluster and MEIS1, is associated with AML. Clinically relevant models of AML are required to advance drug development for an aging patient cohort. RESULTS: Molecular analysis identified altered gene, microRNA, and protein expression in HOXA9/Meis1 leukemic bone marrow compared to normal controls. A candidate drug screen identified the c-Met inhibitor SU11274 for further analysis. Altered cell cycle status, apoptosis, differentiation, and impaired colony formation were shown for SU11274 in AML cell lines and primary leukemic bone marrow. CONCLUSIONS: The clonal HOXA9/Meis1 AML model is amenable to drug screening analysis. The data presented indicate that human AML cells respond in a similar manner to the HOXA9/Meis1 cells, indicating pre-clinical relevance of the mouse model.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".