Novel findings and expansion of phenotype in a mosaic <scp>RASopathy</scp> caused by somatic <scp><i>KRAS</i></scp> variants
Bibliographic record
Abstract
Mosaic KRAS variants and other RASopathy genes cause oculoectodermal, encephalo-cranio-cutaneous lipomatosis, and Schimmelpenning-Feuerstein-Mims syndromes, and a spectrum of vascular malformations, overgrowth and other associated anomalies, the latter of which are only recently being characterized. We describe eight individuals in total (six unreported cases and two previously reported cases) with somatic KRAS variants and variably associated features. Given the findings of somatic overgrowth (in seven individuals) and vascular or lymphatic malformations (in eight individuals), we suggest mosaic RASopathies (mosaic KRAS variants) be considered in the differential diagnosis for individuals presenting with asymmetric overgrowth and lymphatic or vascular anomalies. We expand the association with embryonal tumors, including the third report of embryonal rhabdomyosarcoma, as well as novel findings of Wilms tumor and nephroblastomatosis in two individuals. Rare or novel findings in our series include the presence of epilepsy, polycystic kidneys, and T-cell deficiency in one individual, and multifocal lytic bone lesions in two individuals. Finally, we describe the first use of targeted therapy with a MEK inhibitor for an individual with a mosaic KRAS variant. The purposes of this report are to expand the phenotypic spectrum of mosaic KRAS-related disorders, and to propose possible mechanisms of pathogenesis, and surveillance of its associated findings.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".