Malignant melanoma in patients with multiple endocrine neoplasia type 1 and involvement of theMEN1 gene in sporadic melanoma
Bibliographic record
Abstract
Multiple endocrine neoplasia type 1 (MEN 1) is a familial cancer syndrome associated primarily with endocrine tumors of the parathyroids, enteropancreas and anterior pituitary. However, tumors of mesenchymal origin such as angiofibroma and collagenoma of the skin have also been associated with the syndrome. This highlights the possibility of an association between MEN 1 and some other types of tumors. Here we report 7 cases of primary malignant melanoma occurring in 7 MEN 1 families, all patients exhibiting classic features of MEN 1. Based on these findings and the previous implication of multiple melanoma tumor suppressor(s) in 11q, including the MEN1 region, we have investigated the involvement of the MEN1 gene in melanoma tumorigenesis. Mutation analysis was performed on a panel of 39 sporadic metastatic melanomas, 13 melanoma cell lines and 20 melanoma families without CDKN2A or CDK4 germline mutations. In addition, 19 sporadic metastatic tumors were screened for loss of heterozygosity (LOH) in 11q13. LOH was detected in 6 tumors (32%), and in 4 of the tumors the pattern of LOH suggested that the deletion included the MEN1 gene locus. A novel somatic nonsense mutation in exon 7 (Q349X) was identified in 1 sporadic tumor which also showed loss of the wild-type allele. We conclude that the MEN1 gene plays a role in the tumorigenesis of a small subgroup of melanoma.
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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 | 0.001 | 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".