AHI-1 interacts with BCR-ABL and modulates BCR-ABL transforming activity and imatinib response of CML stem/progenitor cells
Bibliographic record
Abstract
Chronic myeloid leukemia (CML) represents the first human malignancy successfully treated with a tyrosine kinase inhibitor (TKI; imatinib). However, early relapses and the emergence of imatinib-resistant disease are problematic. Evidence suggests that imatinib and other inhibitors may not effectively eradicate leukemic stem/progenitor cells, and that combination therapy directed to complimentary targets may improve treatment. Abelson helper integration site 1 (Ahi-1)/AHI-1 is a novel oncogene that is highly deregulated in CML stem/progenitor cells where levels of BCR-ABL transcripts are also elevated. Here, we demonstrate that overexpression of Ahi-1/AHI-1 in murine and human hematopoietic cells confer growth advantages in vitro and induce leukemia in vivo, enhancing effects of BCR-ABL. Conversely, RNAi-mediated suppression of AHI-1 in BCR-ABL-transduced lin(-)CD34(+) human cord blood cells and primary CML stem/progenitor cells reduces their growth autonomy in vitro. Interestingly, coexpression of Ahi-1 in BCR-ABL-inducible cells reverses growth deficiencies exhibited by BCR-ABL down-regulation and is associated with sustained phosphorylation of BCR-ABL and enhanced activation of JAK2-STAT5. Moreover, we identified an AHI-1-BCR-ABL-JAK2 interaction complex and found that modulation of AHI-1 expression regulates phosphorylation of BCR-ABL and JAK2-STAT5 in CML cells. Importantly, this complex mediates TKI response/resistance of CML stem/progenitor cells. These studies implicate AHI-1 as a potential therapeutic target downstream of BCR-ABL in CML.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".