Therapeutic Potential of Spleen Tyrosine Kinase Inhibition for Treating High-Risk Precursor B Cell Acute Lymphoblastic Leukemia
Bibliographic record
Abstract
Intensified and central nervous system (CNS)-directed chemotherapy has improved outcomes for pediatric B cell acute lymphoblastic leukemia (B-ALL) but confers treatment-related morbidities. Moreover, many patients suffer relapses, underscoring the need to develop new molecular targeted B-ALL therapies. Using a mouse model, we show that leukemic B cells require pre-B cell receptor (pre-BCR)-independent spleen tyrosine kinase (SYK) signaling in vivo for survival and proliferation. In diagnostic samples from human pediatric and adult B-ALL patients, SYK and downstream targets were phosphorylated regardless of pre-BCR expression or genetic subtype. Two small-molecule SYK inhibitors, fostamatinib and BAY61-3606, attenuated the growth of 69 B-ALL samples in vitro, including high-risk (HR) subtypes. Orally administered fostamatinib reduced heavy disease burden after xenotransplantation of HR B-ALL samples into immunodeficient mice and decreased leukemia dissemination into spleen, liver, kidneys, and the CNS of recipient mice. Thus, SYK activation sustains the growth of multiple HR B-ALL subtypes, suggesting that SYK inhibitors may improve outcomes for HR and relapsed B-ALL.
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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 | 0.000 |
| 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".