MEK Inhibition in a Newborn with RAF1-Associated Noonan Syndrome Ameliorates Hypertrophic Cardiomyopathy but Is Insufficient to Revert Pulmonary Vascular Disease
Bibliographic record
Abstract
The RAF1:p.Ser257Leu variant is associated with severe Noonan syndrome (NS), progressive hypertrophic cardiomyopathy (HCM), and pulmonary hypertension. Trametinib, a MEK-inhibitor approved for treatment of RAS/MAPK-mutated cancers, is an emerging treatment option for HCM in NS. We report a patient with NS and HCM, treated with Trametinib and documented by global RNA sequencing before and during treatment to define transcriptional effects of MEK-inhibition. A preterm infant with HCM carrying the RAF1:p.Ser257Leu variant, rapidly developed severe congestive heart failure (CHF) unresponsive to standard treatments. Trametinib was introduced (0.022 mg/kg/day) with prompt clinical improvement and subsequent amelioration of HCM at ultrasound. The appearance of pulmonary artery aneurysm and pulmonary hypertension contributed to a rapid worsening after ventriculoperitoneal shunt device placement for posthemorrhagic hydrocephalus: she deceased for untreatable CHF at 3 months of age. Autopsy showed severe obstructive HCM, pulmonary artery dilation, disarrayed pulmonary vascular anatomy consistent with pulmonary capillary hemangiomatosis. Transcriptome across treatment, highlighted robust transcriptional changes induced by MEK-inhibition. Our findings highlight a previously unappreciated connection between pulmonary vascular disease and the severe outcome already reported in patients with RAF1-associated NS. While MEK-inhibition appears a promising therapeutic option for HCM in RASopathies, it appears insufficient to revert pulmonary hypertension.
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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 | 0.001 |
| 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".