Inhibition of SRC Corrects GM-CSF Hypersensitivity That Underlies Juvenile Myelomonocytic Leukemia
Bibliographic record
Abstract
Juvenile myelomonocytic leukemia (JMML) is an aggressive myeloproliferative neoplasm in children characterized by the overproduction of monocytic cells that infiltrate the spleen, lung, and liver. JMML remains a disease for which few curative therapies are available other than myeloablative hematopoietic stem cell transplant (HSCT); however, relapse remains a major cause of treatment failure and the long-term morbidities of HSCT for survivors are substantial. A hallmark feature of JMML is acquired hypersensitivity by clonal myeloid progenitor cells to granulocyte macrophage-colony stimulating factor (GM-CSF) via a largely unknown mechanism. Here, we identify c-Cbl (henceforth referred to as Cbl) as a GM-CSF receptor (GMR) adaptor protein that targets Src for ubiquitin-mediated destruction upon GM-CSF stimulation and show that a loss of negative regulation of Src is pivotal in the hyperactivation of GMR signaling in Cbl-mutated JMML cells. Notably, dasatinib, an U.S. Food and Drug Administration-approved multikinase inhibitor that also targets Src family, dramatically attenuated the spontaneous and GM-CSF-induced hypersensitive growth phenotype of mononuclear cells from peripheral blood and bone marrow collected from JMML patients harboring Cbl or other known JMML-associated mutations. These findings reveal Src kinase as a critical oncogenic driver underlying JMML.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
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".