Blocking tumor-intrinsic MNK1 kinase restricts metabolic adaptation and diminishes liver metastasis
Bibliographic record
Abstract
Dysregulation of the mitogen-activated protein kinase interacting kinases 1/2 (MNK1/2)-eukaryotic initiation factor 4E (eIF4E) signaling axis promotes breast cancer progression. MNK1 is known to influence cancer stem cells (CSCs); self-renewing populations that support metastasis, recurrence, and chemotherapeutic resistance, making them a clinically relevant target. The precise function of MNK1 in regulating CSCs, however, remains unexplored. Here, we generated MNK1 knockout cancer cell lines, resulting in diminished CSC properties in vitro and slowed tumor growth in vivo. Using a multiomics approach, we functionally demonstrated that loss of MNK1 restricts tumor cell metabolic adaptation by reducing glycolysis and increasing dependence on oxidative phosphorylation. Furthermore, MNK1-null breast and pancreatic tumor cells demonstrated suppressed metastasis to the liver, but not the lung. Analysis of The Cancer Genome Atlas (TCGA) data from breast cancer patients validated the positive correlation between MNK1 and glycolytic enzyme protein expression. This study defines metabolic perturbations as a previously unknown consequence of targeting MNK1/2, which may be therapeutically exploited.
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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".