Occurrence of <i>BAP1</i> germline mutations in cutaneous melanocytic tumors with loss of BAP1‐expression: A pilot study
Bibliographic record
Abstract
Melanocytic BAP1-associated intradermal tumors (MBAITs) can either be sporadic or associated with a cancer-predisposition syndrome. In this study we explored the clinical status of 136 patients in which at least one MBAIT was found. 49/136 (36%) of them gave their signed consent for an oncogenetic BAP1 blood test. 28/136 patients (20%) diagnosed with an MBAIT had other MBAITs and/or a personal or familial history of BAP1-related cancers that could clinically designate them as potential carriers of a BAP1 germline mutation. 17 of these 28 patients underwent oncogenetic testing. A deleterious mutation of BAP1 was confirmed in 12/17 cases. 4/17 cases were wild-type; all had a single MBAIT and a history of skin melanoma. A variant of unknown significance was found in one case with multiple MBAITs. Among the 12 mutated cases, multiple MBAITs were present in 10/12 cases and were the only clinical sign in 4/12 cases. The remaining 32/49 blood-tested cases with an isolated MBAIT were wild type for BAP1 in 25/32 cases or showed a variant of unknown significance in 7/32 cases. We recommend, following the diagnosis of a MBAIT, performing a BAP1 immunohistochemistry in all other cutaneous melanocytic tumors removed previously or simultaneously and all skin melanomas. This screening could help clinicians prioritize which patients would most benefit from oncogenetic testing.
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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 | 0.001 | 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 | 0.000 |
| 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".