AXL Inhibition Extinguishes Primitive JAK2 Mutated Myeloproliferative Neoplasm Progenitor Cells
Bibliographic record
Abstract
Myeloproliferative neoplasms (MPN) are clonal stem cell associated disorders inclusive of chronic myeloid leukemia (CML), Polycythaemia vera (PV), myelofibrosis (MF), and essential thrombocythemia (ET). They are characterized by increased production of myeloid cells with minimal effects on terminal differentiation but can undergo transformation to acute leukemias. PV is the most common chronic myeloproliferative neoplasm and in the majority of cases is characterized by a V617F point mutation in JAK2. This JAK2 activating mutation is also found in about half the patients with MF and ET. Such aberrant proteins offer great potential for the treatment of these diseases however inhibitors to JAK2 have had limited success in the clinic in terms of curing the disease. We have previously used advanced proteomic techniques to identify drug targets and thus develop novel treatment strategies to distinguish the leukemic clone in both CML and PV. Here, we build on our proteomic data sets to characterize a new target, the receptor tyrosine kinase AXL. AXL is overexpressed in acute myeloid leukemia and importantly small molecule inhibitors have been developed which are currently in clinical trial hence offer the opportunity to repurpose this drug for the treatment of MPNs. We demonstrate that AXL is upregulated and activated in JAK2 associated MPNs. Further we show that inhibition of AXL preferentially kills early hemopoietic stem cells from PV patients and as such represents a promising therapeutic approach for JAK2 driven MPNs.
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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".