Uveal melanomas express vascular endothelial growth factor and basic fibroblast growth factor and support endothelial cell growth
Bibliographic record
Abstract
BACKGROUND: Tumour microvascularity is a significant determinant of prognosis for a large number of different tumours, including uveal melanoma. The development of blood vessels within these and other tumours is partly controlled by soluble pro-angiogenic cytokines, of which basic fibroblast growth factor (bFGF) and vascular endothelial growth factor-A (VEGF) are the best described. METHODS: Because VEGF has been inconsistently found within uveal melanomas and bFGF is described as an autocrine growth factor in cutaneous melanoma, the authors looked at the expression of these cytokines in uveal melanomas using immunohistochemistry and reverse transcriptase polymerase chain reaction (RT-PCR). The cross talk between uveal melanoma cells and endothelial cells was then assessed in an in vitro co-culture model. RESULTS: While most tumour cells expressed bFGF at the protein level by immunohistochemistry (89%), relatively few (22%) expressed VEGF, and this was of limited extent. All 20 tumours tested by RT-PCR contained mRNA for both bFGF and VEGF. Co-culture experiments using an ATP based bioassay showed that uveal melanomas could support the growth of a rat brain endothelial cell line (GPNT) and human umbilical vein endothelial cells (HUVEC), and that this could be modulated by cytokines and anti-cytokine antibodies. CONCLUSION: These results suggest that angiogenesis within uveal melanoma may be the result of a complex interplay between endothelial and tumour cells, and that bFGF and VEGF could play a part.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".