Expression of the Metastasis Suppressor KAI1 in Uveal Melanoma
Bibliographic record
Abstract
Introduction. Uveal melanoma (UM) is an intraocular tumor that leads to metastatic disease in approximately 50% of afflicted patients. There is no efficacious treatment for metastatic disease in this cancer. Identification of markers that can offer prognostic and therapeutic value is a major focus in this field at present. KAI1 is a metastasis suppressor gene that has been reported to play a role in various human malignancies, although it has not previously been evaluated in UM. Purpose. To investigate the expression of KAI1 in UM and its potential value as a prognostic marker. Materials and Methods. 18 cases of human primary UM were collected and immunostained for KAI1 expression. A pathologist evaluated staining intensity and distribution semiquantitatively. Each case was categorized as group 1 (low staining) or group 2 (high staining). Results. In group 2, two of the 12 cases presented with metastasis. Conversely, in group 1, five out of 6 cases had metastasis. The mean follow-up of patients who did not develop metastasis was 81.81 months (median: 75 months) versus 42.14 months (median: 44 months) for patients with metastasis. Conclusions. KAI1 is a promising candidate marker that may offer prognostic value in UM; it may also represent a therapeutic target in metastatic disease.
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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 | 0.001 | 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".