Mutations in <i>GNA11</i> in Uveal Melanoma
Bibliographic record
Abstract
BACKGROUND: Uveal melanoma is the most common intraocular cancer. There are no effective therapies for metastatic disease. Mutations in GNAQ, the gene encoding an alpha subunit of heterotrimeric G proteins, are found in 40% of uveal melanomas. METHODS: We sequenced exon 5 of GNAQ and GNA11, a paralogue of GNAQ, in 713 melanocytic neoplasms of different types (186 uveal melanomas, 139 blue nevi, 106 other nevi, and 282 other melanomas). We sequenced exon 4 of GNAQ and GNA11 in 453 of these samples and in all coding exons of GNAQ and GNA11 in 97 uveal melanomas and 45 blue nevi. RESULTS: We found somatic mutations in exon 5 (affecting Q209) and in exon 4 (affecting R183) in both GNA11 and GNAQ, in a mutually exclusive pattern. Mutations affecting Q209 in GNA11 were present in 7% of blue nevi, 32% of primary uveal melanomas, and 57% of uveal melanoma metastases. In contrast, we observed Q209 mutations in GNAQ in 55% of blue nevi, 45% of uveal melanomas, and 22% of uveal melanoma metastases. Mutations affecting R183 in either GNAQ or GNA11 were less prevalent (2% of blue nevi and 6% of uveal melanomas) than the Q209 mutations. Mutations in GNA11 induced spontaneously metastasizing tumors in a mouse model and activated the mitogen-activated protein kinase pathway. CONCLUSIONS: Of the uveal melanomas we analyzed, 83% had somatic mutations in GNAQ or GNA11. Constitutive activation of the pathway involving these two genes appears to be a major contributor to the development of uveal melanoma. (Funded by the National Institutes of Health and others.).
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".