Inhibition of melanoma brain metastasis by targeting melanotransferrin at the cell surface
Bibliographic record
Abstract
Brain metastases are a common feature of malignant melanoma and are associated with poor prognosis. Melanotransferrin (MTf), one of several antigens associated with the surface of melanoma cells, has been demonstrated to promote cell invasion. In this study, we investigated the role of membrane-bound MTf in several of the steps leading to the development of melanoma brain metastasis. Our results indicated that MTf-positive cells were detected in the brains of nude mice injected intravenously with human melanoma SK-Mel 28 cells. Moreover, administration of a single dose of a monoclonal antibody (L235) directed against human MTf significantly reduced the development of human melanoma brain metastases in nude mice. The ability of melanoma cells to cross the blood-brain barrier (BBB) in vitro is correlated with their MTf expression levels at the cell surface. Overall, our results indicated that membrane-bound MTf is a key element in melanoma cell transmigration across the BBB and subsequent brain metastasis. Thus, these data suggest MTf as an attractive target and demonstrate the therapeutic potential of an anti-MTf mAb for preventing metastatic melanoma.
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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".