MEK inhibition reduced vascular tumor growth and coagulopathy in a mouse model with hyperactive GNAQ
Bibliographic record
Abstract
Activating non-inherited mutations in the guanine nucleotide-binding protein G(q) subunit alpha (GNAQ) gene family have been identified in childhood vascular tumors. Patients experience extensive disfigurement, chronic pain and severe complications including a potentially lethal coagulopathy termed Kasabach-Merritt phenomenon. Animal models for this class of vascular tumors do not exist. This has severely hindered the discovery of the molecular consequences of GNAQ mutations in the vasculature and, in turn, the preclinical development of effective targeted therapies. Here we report a mouse model expressing hyperactive mutant GNAQ in endothelial cells. Mutant mice develop vascular and coagulopathy phenotypes similar to those seen in patients. Mechanistically, by transcriptomic analysis we demonstrate increased mitogen activated protein kinase signaling in the mutant endothelial cells. Targeting of this pathway with Trametinib suppresses the tumor growth by reducing vascular cell proliferation and permeability. Trametinib also prevents the development of coagulopathy and improves mouse survival.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".