High-risk Melanoma Susceptibility Genes and Pancreatic Cancer, Neural System Tumors, and Uveal Melanoma across GenoMEL
Why this work is in the frame
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Bibliographic record
Abstract
GenoMEL, comprising major familial melanoma research groups from North America, Europe, Asia, and Australia has created the largest familial melanoma sample yet available to characterize mutations in the high-risk melanoma susceptibility genes CDKN2A/alternate reading frames (ARF), which encodes p16 and p14ARF, and CDK4 and to evaluate their relationship with pancreatic cancer (PC), neural system tumors (NST), and uveal melanoma (UM). This study included 466 families (2,137 patients) with at least three melanoma patients from 17 GenoMEL centers. Overall, 41% (n = 190) of families had mutations; most involved p16 (n = 178). Mutations in CDK4 (n = 5) and ARF (n = 7) occurred at similar frequencies (2-3%). There were striking differences in mutations across geographic locales. The proportion of families with the most frequent founder mutation(s) of each locale differed significantly across the seven regions (P = 0.0009). Single founder CDKN2A mutations were predominant in Sweden (p.R112_L113insR, 92% of family's mutations) and the Netherlands (c.225_243del19, 90% of family's mutations). France, Spain, and Italy had the same most frequent mutation (p.G101W). Similarly, Australia and United Kingdom had the same most common mutations (p.M53I, c.IVS2-105A>G, p.R24P, and p.L32P). As reported previously, there was a strong association between PC and CDKN2A mutations (P < 0.0001). This relationship differed by mutation. In contrast, there was little evidence for an association between CDKN2A mutations and NST (P = 0.52) or UM (P = 0.25). There was a marginally significant association between NST and ARF (P = 0.05). However, this particular evaluation had low power and requires confirmation. This GenoMEL study provides the most extensive characterization of mutations in high-risk melanoma susceptibility genes in families with three or more melanoma patients yet available.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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 it