Combined inhibition of receptor tyrosine and p21-activated kinases as a therapeutic strategy in childhood ALL
Bibliographic record
Abstract
Abstract Receptor tyrosine kinase (RTK)-dependent signaling has been implicated in the pathogenesis of acute lymphoblastic leukemia (ALL) of childhood. However, the RTK-dependent signaling state and its interpretation with regard to biological behavior are often elusive. To decipher signaling circuits that link RTK activity with biological output in vivo, we established patient-derived xenograft ALL (PDX-ALL) models with dependencies on fms-like tyrosine kinase 3 (FLT3) and platelet-derived growth factor receptor β (PDGFRB), which were interrogated by phosphoproteomics using iTRAQ mass spectrometry. Signaling circuits were determined by receptor type and cellular context with few generic features, among which we identified group I p21-activated kinases (PAKs) as potential therapeutic targets. Growth factor stimulation markedly increased catalytic activities of PAK1 and PAK2. RNA interference (RNAi)-mediated or pharmacological inhibition of PAKs using allosteric or adenosine triphosphate (ATP)-competitive compounds attenuated cell growth and increased apoptosis in vitro. Notably, PAK1- or PAK2-directed RNAi enhanced the antiproliferative effects of the type III RTK and protein kinase C inhibitor midostaurin. Treatment of FLT3- or PDGFRB-dependent ALLs with ATP-competitive PAK inhibitors markedly decreased catalytic activities of both PAK isoforms. In FLT3-driven ALL, this effect was augmented by coadministration of midostaurin resulting in synergistic effects on growth inhibition and apoptosis. Finally, combined treatment of FLT3D835H PDX-ALL with the ATP-competitive group I PAK inhibitor FRAX486 and midostaurin in vivo significantly prolonged leukemia progression-free survival compared with midostaurin monotherapy or control. Our study establishes PAKs as potential downstream targets in RTK-dependent ALL of childhood, the inhibition of which might help prevent the selection or acquisition of resistance mutations toward tyrosine kinase inhibitors.
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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 | 0.001 |
| 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".