Early genetic evolution of driver mutations in uveal melanoma
Bibliographic record
Abstract
Uveal melanoma (UM) is an aggressive eye cancer that frequently results in metastatic death despite successful primary tumor treatment. Subclinical micrometastasis is thought to occur early, when tumors are small and difficult to distinguish from benign nevi. However, the early genetic evolution of UM is poorly understood, and biomarkers for malignant transformation are lacking. Here, we perform integrated genetic profiling of 1140 primary UMs, including 131 small tumors. A clinically available 15-gene expression profile (15-GEP) prospectively validated by our group is more accurate than driver mutations for predicting patient survival. Small tumors are significantly more likely to be in earlier stages of genetic evolution than larger tumors. Further, the 15-GEP support vector machine discriminant score predicts small tumors undergoing transformation from low-risk Class 1 to high-risk Class 2 profile. These results shed light on the early genetic evolution of UM and move us closer to a molecular definition of malignant transformation in this cancer type.
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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 | 0.001 |
| 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) | 0.001 | 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".