RAB1A is a novel vulnerability in uveal melanoma revealed by dual inhibition of MNK1/2 and mTOR
Bibliographic record
Abstract
ABSTRACT Uveal melanoma (UM) is an eye cancer that is fatal upon metastasis to the liver. Most treatments trialed in UM fail to provide therapeutic benefit, thus there is an urgent need for novel treatment strategies. The MAPK and PI3K signaling pathways, key molecular drivers found to be hyper-activated in UM, converge on the MNK1/2-eIF4E and mTORC1/2-4EBP axes. Here, we demonstrate that the pharmacologic inhibition of MNK1/2 in combination with an mTOR inhibitor impairs clonogenic outgrowth and UM cell invasion. Using proteomic analyses, we reveal that combined MNK1/2 and mTOR inhibition disrupts Golgi homeostasis and protein vesicle trafficking mainly due to downregulated RAB1A expression, a master regulator of intracellular protein transport. We uncover that the knockdown of RAB1A blocks liver metastasis, a result that is recapitulated by combined pharmacologic inhibition of MNK1/2 and mTOR. Finally, we show that RAB1A expression reshapes the surfaceome by increasing the abundance of plasma membrane proteins associated with poor overall survival in UM, highlighting its potential as a biomarker. This study identifies protein vesicle transport as an unrecognized vulnerability in UM and supports a mechanistic rationale for targeting MNK1/2 and mTOR in metastatic UM.
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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) | 0.002 | 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".