Identification of a PAK6-Mediated MDM2/p21 Axis That Modulates Survival and Cell Cycle Control of Drug-Resistant Stem/Progenitor Cells in Chronic Myeloid Leukemia
Bibliographic record
Abstract
Chronic myeloid leukemia (CML) is a leading example of a malignancy where a molecular targeted therapy revolutionized treatment but has rarely led to cures. Overcoming tyrosine kinase inhibitor (TKI) drug resistance remains a challenge in the treatment of CML. We have recently identified miR-185 as a predictive biomarker where reduced expression in CD34+ treatment-naïve CML cells was associated with TKI resistance. We have also identified PAK6 as a target gene of miR-185 that was upregulated in CD34+ TKI-nonresponder cells. However, its role in regulating TKI resistance remains largely unknown. In this study, we specifically targeted PAK6 in imatinib (IM)-resistant cells and CD34+ stem/progenitor cells from IM-nonresponders using a lentiviral-mediated PAK6 knockdown strategy. Interestingly, the genetic and pharmacological suppression of PAK6 significantly reduced proliferation and increased apoptosis in TKI-resistant cells. Cell survivability was further diminished when IM was combined with PAK6 knockdown. Importantly, PAK6 inhibition in TKI-resistant cells induced cell cycle arrest in the G2-M phase and cellular senescence, accompanied by increased levels of DNA damage-associated senescence markers. Mechanically, we identified a PAK6-mediated MDM2-p21 axis that regulates cell cycle arrest and senescence. Thus, PAK6 plays a critical role in determining alternative cell fates in leukemic cells, and targeting PAK6 may offer a therapeutic strategy to selectively eradicate TKI-resistant cells.
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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".