The FLT3 Internal Tandem Duplication Mutation Prevents Apoptosis in Interleukin-3-Deprived BaF3 Cells Due to Protein Kinase A and Ribosomal S6 Kinase 1–Mediated BAD Phosphorylation at Serine 112
Bibliographic record
Abstract
Internal tandem duplication (ITD) mutations in the FLT3 tyrosine kinase have been detected in approximately 20% of acute myeloid leukemia (AML) patients. Patients harboring FLT3/ITD mutations have a relatively poor prognosis. FLT3/ITD results in constitutive autophosphorylation of the receptor and factor-independent survival. Previous studies have shown that FLT3/ITD activates the signal transducers and activators of transcription 5 (STAT5), p42/p44 mitogen-activated protein kinase [MAPK; extracellular signal-regulated kinase (ERK) 1/2], and phosphatidylinositol 3-kinase/Akt pathways. We herein provide biochemical and biological evidence that ribosomal S6 kinase 1 (RSK1) and protein kinase A (PKA) are the two principal kinases that mediate the antiapoptotic function of FLT3/ITD via phosphorylation of BAD at Ser112. Inhibiting both MAPK kinase (MEK)/ERK and PKA pathways by a combination of U0126 (10 micromol/L) and H-89 (5 micromol/L) reduced most of BAD phosphorylation at Ser112 and induced apoptosis to a level comparable with that induced by FLT3 inhibitor AG1296 (5 micromol/L) in BaF3/FLT3/ITD cells. RNA interference of RSK1 or PKA catalytic subunit reduced BAD phosphorylation and induced apoptosis. The MEK inhibitor U0126 and/or the PKA inhibitor H-89 greatly enhanced the efficacy of the FLT3 inhibitor AG1296, suggesting that combining FLT3/ITD downstream pathway inhibition with FLT3 inhibitors may be a viable therapeutic strategy for AML caused by a FLT3/ITD mutation.
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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".