RARE-21. CANCER SPECTRUM IN GERMLINE SUFU MUTATION CARRIERS: A COLLABORATIVE PROJECT OF THE SIOPE HOST GENOME WORKING GROUP
Bibliographic record
Abstract
Abstract BACKGROUND Little is known about cancer risk associated with pathogenic germline SUFU variants. METHODS Data of all previously published and 25 still unpublished patients with a pathogenic germline SUFU mutation were compiled. RESULTS 124 patients in 67 families were identified, most of them ascertained after the occurrence of a medulloblastoma (MB) or as part of Gorlin syndrome cohorts. Overall, 30 patients were healthy carriers and 94 patients developed a total of 129 tumors (up to 4 tumors/patient): 68 MBs, always as first tumor (median age at diagnosis: 1.5yr [0.1–5]), 22 patients with at least 1 basal cell carcinoma (BCC) (median 10/patient) (median age at first BCC: 43yr, [17–52]), 15 meningiomas (median age 43yr, [13–72]), 7 ovarian stromal/fibrous tumors (median age 12yr [5–34]), and 17 other tumors including 5 sarcomas (median age: 50yr [7–79]). Median age at last follow-up was 30yr. Nineteen patients died, including 11 from MB. Second malignancies were diagnosed in 21 patients including 13 in MB survivors. Mutations were inherited in 58/66 (88%) of cases in which inheritance could be tested and de novo in 8. In 6/67 families (9%), >2 children were diagnosed with a MB. CONCLUSION In this large cohort of germline SUFU mutation carriers, MB in infants is the most frequent tumor but the spectrum also includes typical Gorlin syndrome tumors (BCC, meningiomas, and ovarian stromal/fibrous tumors) either as first tumors or as second malignancies. This broad tumor spectrum and the high risk of second malignancies justify the implementation of specific cancer surveillance programs.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".