PAEDIATRIC TUMOURS IN GORLIN SYNDROME: EXPANDING THE GENETIC INSIGHTS
Bibliographic record
Abstract
Introduction : Gorlin syndrome (GS) is a known cancer predisposing syndrome, mainly associated with basal cell carcinomas (BCCs), fibromas, meningiomas and medulloblastoma (MB). However, a number of different tumours have been increasingly associated with GS, and a thorough understanding of the spectrum of associated cancers is key to counselling families and designing appropriate surveillance protocols. Methods : This is a retrospective case series of paediatric patients with GS identified at the Royal Marsden Hospital and South West Thames Regional Genetic Service between 2000 and 2021. Clinical information, including data on genotype, were retrospectively collected. Patients with a cancer diagnosis were described in detail, and results from somatic NGS were reported, when available. Results : Fifty-five patients across 34 families were identified. Nine (16%) patients developed one or more benign or malignant tumours, other than BCCs, before the age of 18, including SHH-activated MB (n=4); Sertoli-Leydig tumour, myelodysplasia, Wilms tumour, low grade myofibroblastic spindle cell proliferation, ganglioneuroma, macroprolactinoma and breast fibroadenoma (n=1 each). Somatic analysis showed PTCH1 /SUFU loss of heterozygosity (LOH) in 4 out of 6 cases analysed. Conclusion : This case series expands the spectrum of tumours described in patients with GS, raising the possibility of novel links with Sertoli-Leydig tumour, myofibroblastic tumours and ganglioneuroma. Somatic analyses provided further evidence for PTCH1/SUFU LOH as a potential driver in the pathogenesis of GS–associated tumours.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".