Mosaic RAS/MAPK variants cause sporadic vascular malformations which respond to targeted therapy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Sporadic vascular malformations (VMs) are complex congenital anomalies of blood vessels that lead to stroke, life-threatening bleeds, disfigurement, overgrowth, and/or pain. Therapeutic options are severely limited, and multidisciplinary management remains challenging, particularly for high-flow arteriovenous malformations (AVM). METHODS: To investigate the pathogenesis of sporadic intracranial and extracranial VMs in 160 children in which known genetic causes had been excluded, we sequenced DNA from affected tissue and optimized analysis for detection of low mutant allele frequency. RESULTS: We discovered multiple mosaic-activating variants in 4 genes of the RAS/MAPK pathway, KRAS, NRAS, BRAF, and MAP2K1, a pathway commonly activated in cancer and responsible for the germline RAS-opathies. These variants were more frequent in high-flow than low-flow VMs. In vitro characterization and 2 transgenic zebrafish AVM models that recapitulated the human phenotype validated the pathogenesis of the mutant alleles. Importantly, treatment of AVM-BRAF mutant zebrafish with the BRAF inhibitor vemurafinib restored blood flow in AVM. CONCLUSION: Our findings uncover a major cause of sporadic VMs of different clinical types and thereby offer the potential of personalized medical treatment by repurposing existing licensed cancer therapies. FUNDING: This work was funded or supported by grants from the AVM Butterfly Charity, the Wellcome Trust (UK), the Medical Research Council (UK), the UK National Institute for Health Research, the L'Oreal-Melanoma Research Alliance, the European Research Council, and the National Human Genome Research Institute (US).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it