Mice expressing KrasG12D in hematopoietic multipotent progenitor cells develop neonatal myeloid leukemia
Bibliographic record
Abstract
Juvenile myelomonocytic leukemia (JMML) is a pediatric myeloproliferative neoplasm that bears distinct characteristics associated with abnormal fetal development. JMML has been extensively modeled in mice expressing the oncogenic KrasG12D mutation. However, these models have struggled to recapitulate the defining features of JMML due to in utero lethality, nonhematopoietic expression, and the pervasive emergence of T cell acute lymphoblastic leukemia. Here, we have developed a model of JMML using mice that express KrasG12D in multipotent progenitor cells (Flt3Cre+ KrasG12D mice). These mice express KrasG12D in utero, are born at normal Mendelian ratios, develop hepatosplenomegaly, anemia, and thrombocytopenia, and succumb to a rapidly progressing and fully penetrant neonatal myeloid disease. Mutant mice have altered hematopoietic stem and progenitor cell populations in the BM and spleen that are hypersensitive to granulocyte macrophage-CSF due to hyperactive RAS/ERK signaling. Biased differentiation in these progenitors results in an expansion of neutrophils and DCs and a concomitant decrease in T lymphocytes. Flt3Cre+ KrasG12D fetal liver hematopoietic progenitors give rise to a myeloid disease upon transplantation. In summary, we describe a KrasG12D mouse model that reproducibly develops JMML-like disease. This model will prove useful for preclinical drug studies and for elucidating the developmental origins of pediatric neoplasms.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".