UM171 cooperates with PIM1 inhibitors to restrict HSC expansion markers and suppress leukemia progression
Bibliographic record
Abstract
Abstract The pyrimido-indole derivative UM171 promotes human Hematopoietic Stem Cells Expansion (HSCE), but its impact on leukemia is not known. Herein, we show in a mouse model of erythroleukemia that UM171 strongly suppresses leukemia progression. UM171 inhibits cell cycle progression and apoptosis of leukemic cells in culture. The effect of UM171 on leukemia differentiation was accompanied by increased expression of HSCE markers. RNAseq analysis combined with Q-RT-PCR and western blotting revealed that the PIM1 protein kinase is highly elevated in response to UM171 treatment. Moreover, docking analysis combined with immunoprecipitation assays revealed high binding affinity of UM171 to PIM1. Interestingly, pan-PIM kinase inhibitors counteracted the effect of UM171 on HSCE marker expression and PIM1 transcription, but not its suppression of leukemic cell growth. Moreover, combination treatment with UM171 and a pan-PIM inhibitor further suppressed leukemic cell proliferation compared to each drug alone. To uncover the mechanism of growth inhibition, we showed strong upregulation of the cyclin-dependent kinase inhibitor P21CIP1 and the transcription factor KLF2 by UM171. In accordance, KLF2 knockdown attenuated growth inhibition by UM171. KLF2 upregulation by UM171 is also responsible for the activation of P21CIP1 in leukemic cells leading to a G1/S arrest and suppression of leukemogenesis. Thus, suppression of leukemic growth by UM171 through KLF2 and P21CIP1 is thwarted by PIM-mediated expansion of leukemic stemness, uncovering a novel therapeutic modality involving combined UM171 plus PIM 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 | 0.000 |
| 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".