Inhibition of the MiR-185-PAK6-Mediated Survival and Metabolic Pathways Selectively Targets Drug-Resistant CML Stem/Progenitor Cells
Bibliographic record
Abstract
Overcoming drug resistance and targeting leukemic stem cells (LSCs) remain major challenges for curative treatment of human leukemia, including chronic myeloid leukemia (CML). Indeed, most patients with CML require life-long therapy with ABL1 tyrosine kinase inhibitors (TKIs), due to the persistence of residual LSCs that maintain the potential for relapse. Increasing evidence also indicates that LSCs are susceptible to cellular metabolic changes and seem to have a greater dependence on mitochondrial oxidative phosphorylation (OXPHOS) for survival. Previously, through global transcriptome profiling, we identified a key microRNA (miRNA), miR-185 as a predictive biomarker and it is also required for CML LSC survival. Its expression was significantly reduced in CD34+treatment-naïve CML cells and predictive of therapy response. Conversely, restored expression of miR-185 by lentiviral transduction in CD34+TKI-nonresponder cells significantly impaired survival of these cells, sensitizing them to TKIs in vitroand in pre-clinical xenotransplantation models, indicating that miR-185 acts as a tumor suppressor and is critical in regulating TKI response/resistance of CML stem/progenitor cells. PAK6, a serine/threonine-protein kinase, was identified as a target gene of miR-185; it is upregulated in CD34+TKI-nonresponder cells vs. TKI-responders, correlating with reduced miR-185 expression. To further investigate the molecular and biological roles of the miR-185-PAK6 axisin the regulation of survival of drug-resistant cells, including LSCs, we performed RNA-seq and gene set enrichment analysis (GSEA) in the same CD34+patient cells where miR-185 and PAK6 were identified as being differentially expressed. Interestingly, this analysis has now identified a significant gene set enrichment of OXPHOS, reactive oxygen species (ROS), and adipogenesis pathways in CD34+CML cells compared to healthy CD34+cells (Normalized Enrichment Scores (NES): 2.44, 1.65 and 1.8). Moreover, these changes were significantly higher in TKI-nonresponder cells than in TKI-responders (NES: 1.73, 0.49 and 0.34). We have thus hypothesized that the miR-185-PAK6 axis may contribute to the perturbation of specific metabolic pathways in TKI-nonresponder LSC/progenitor cells and confer therapy-resistance to these cells. Indeed, a pre-clinically validated pan-PAK inhibitor (PF-3758309) alone, or in combination with a TKI, greatly reduced mitochondrial activity in TKI-nonresponder cells, in MitoTracker analysis, an effect that was not seen in the same cells treated with a TKI. Notably, ROS production was also significantly reduced in these cells treated with PF-3758309 and further reduction was observed with a combination of PF-3758309 and TKIs. Notably, PF-3758309 significantly reduced the growth of IM-resistant cell lines (IC50 25-70 nM) and CD34+TKI-nonresponder cells, as assessed by viability and colony-forming cell assays, and increased their apoptosis; these effects were greatly enhanced by TKIs (2-fold, P<0.05). These results were further confirmed in TKI-resistant cells using a lentiviral CRISPR/Cas9 knockout system that specifically targets PAK6. In addition, specific molecular changes associated with PF-3758309 treatment were also investigated using the PharmacoDB database and PharmacoGx R-package. Several candidates were identified, including growth factor independent 1B transcriptional repressor (GFI1B), a myeloid-enriched transcription factor. Its expression was reduced by PF-3758309 treatment and significantly increased in CML compared to healthy controls (>2-fold). Interestingly, expression of GFI1B is further upregulated in CD34+TKI-nonresponders compared to responders. Taken together, these findings indicate that dual targeting of miR-185-PAK6-mediated survival and metabolic pathways, along with BCR-ABL, selectively eradicates therapy-resistant LSC/progenitors, providing a valuable therapeutic strategy for improved treatment and care. Disclosures No relevant conflicts of interest to declare.
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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".