Inhibition of the MNK1/2–eIF4E Axis Augments Palbociclib-Mediated Antitumor Activity in Melanoma and Breast Cancer
Bibliographic record
Abstract
Aberrant cell-cycle progression is characteristic of melanoma, and CDK4/6 inhibitors, such as palbociclib, are currently being tested for efficacy in this disease. Despite the promising nature of CDK4/6 inhibitors, their use as single agents in melanoma has shown limited clinical benefit. Herein, we discovered that treatment of tumor cells with palbociclib induces the phosphorylation of the mRNA translation initiation factor eIF4E. When phosphorylated, eIF4E specifically engenders the translation of mRNAs that code for proteins involved in cell survival. We hypothesized that cancer cells treated with palbociclib use upregulated phosphorylated eIF4E (phospho-eIF4E) to escape the antitumor benefits of this drug. Indeed, we found that pharmacologic or genetic disruption of MNK1/2 activity, the only known kinases for eIF4E, enhanced the ability of palbociclib to decrease clonogenic outgrowth. Moreover, a quantitative proteomics analysis of melanoma cells treated with combined MNK1/2 and CDK4/6 inhibitors showed downregulation of proteins with critical roles in cell-cycle progression and mitosis, including AURKB, TPX2, and survivin. We also observed that palbociclib-resistant breast cancer cells have higher basal levels of phospho-eIF4E, and that treatment with MNK1/2 inhibitors sensitized these palbociclib-resistant cells to CDK4/6 inhibition. In vivo we demonstrate that the combination of MNK1/2 and CDK4/6 inhibition significantly increases the overall survival of mice compared with either monotherapy. Overall, our data support MNK1/2 inhibitors as promising drugs to potentiate the antineoplastic effects of palbociclib and overcome therapy-resistant disease.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".