RSK1 dependency in FLT3-ITD acute myeloid leukemia
Bibliographic record
Abstract
Internal tandem duplications (ITD) in fms-like tyrosine kinase 3 (FLT3) represent the most common genetic alteration in de novo acute myeloid leukemia (AML). Here, we identify ribosomal protein s6 kinase a1 (RSK1) as a core dependency in FLT3-ITD AML and unveil the existence of crucial bi-directional regulation. RSK1 perturbation resulted in marked apoptosis and abrogated phosphorylation of FLT3 and associated downstream signaling cascades in FLT3-ITD AML cell lines. Using cycloheximide, MG-132, and ubiquitination assays, we further demonstrate mechanistically that RSK1 regulates FLT3-ITD activity, and protein stability through deubiqutinase USP1, which we identify as a second dependency. Importantly, multivariate analysis revealed heightened expression of RPS6KA1 and USP1 to be associated with poor patient prognosis, and these effectors may serve as biomarkers predictive of patient survival and therapeutic response to FLT3-ITD inhibitors. Lastly, RSK1 inhibition utilizing a first-in-class RSK inhibitor, PMD-026, that is currently undergoing Phase 2 development for breast cancer, diminished leukemic disease burden in MV4-11 xenograft and syngeneic Flt3 ITD Tet2 KO leukemia models. These findings illustrate an unconventional and promising therapeutic strategy targeting FLT3-ITD leukemia.
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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".