The role of c-kit and imatinib mesylate in uveal melanoma.
Bibliographic record
Abstract
BACKGROUND: Uveal melanoma (UM) is the most common primary intraocular tumor in adults, leading to metastasis in 40% of the cases and ultimately to death in 10 years, despite local and/or systemic treatment. The c-kit protein (CD117) is a membrane-bound tyrosine kinase receptor and its overexpression has been observed in several neoplasms. Imatinib mesylate is a FDA approved compound that inhibits tyrosine quinase receptors, as well as c-kit. Imatinib mesylate controls tumor growth in up to 85% of advanced gastrointestinal stromal tumors, a neoplasia resistant to conventional therapy. METHODS: Fifty-five specimens of primary UM selected from the archives of the Ocular Pathology Laboratory, McGill University, Montreal, Canada, were immunostained for c-kit. All cells displaying distinct immunoreactivity were considered positive. Four human UM cell lines and 1 human uveal transformed melanocyte cell line were tested for in vitro proliferation Assays (TOX-6) and invasion assay with imatinib mesylate (concentration of 10 microM). RESULTS: The c-kit expression was positive in 78.2% of the UM. There was a statistical significant decrease in the proliferation and invasion rates of all 5 cell lines. CONCLUSION: The majority of UM expressed c-kit, and imatinib mesylate does decrease the proliferation and invasion rates of human UM cell lines. These results justify the need for a clinical trial to investigate in vivo the response of UM to imatinib mesylate.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".