COX-2-mediated stimulation of the lymphangiogenic factor VEGF-C in human breast cancer
Bibliographic record
Abstract
Increased expression of COX-2 or VEGF-C has been correlated with progressive disease in certain cancers. Present study utilized several human breast cancer cell lines (MCF-7, T-47D, Hs578T and MDA-MB-231, varying in COX-2 expression) as well as 10 human breast cancer specimens to examine the roles of COX-2 and prostaglandin E (EP) receptors in VEGF-C expression or secretion, and the relationship of COX-2 or VEGF-C expression to lymphangiogenesis. We found a strong correlation between COX-2 mRNA expression and VEGF-C expression or secretion levels in breast cancer cell lines and VEGF-C expression in breast cancer tissues. Expression of LYVE-1, a selective marker for lymphatic endothelium, was also positively correlated with COX-2 or VEGF-C expression in breast cancer tissues. Inhibition of VEGF-C expression and secretion in the presence of COX-1/2 or COX-2 inhibitors or following downregulation of COX-2 with COX-2 siRNA established a stimulatory role COX-2 in VEGF-C synthesis by breast cancer cells. EP1 as well as EP4 receptor antagonists inhibited VEGF-C production indicating the roles of EP1 and EP4 in VEGF-C upregulation by endogenous PGE2. Finally, VEGF-C secretion by MDA-MB-231 cells was inhibited in the presence of kinase inhibitors for Her-2/neu, Src and p38 MAPK, indicating a requirement of these kinases for VEGF-C synthesis. These results, for the first time, demonstrate a regulatory role of COX-2 in VEGF-C synthesis (and thereby lymphangiogenesis) in human breast cancer, which is mediated at least in part by EP1/EP4 receptors.
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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) | 0.002 | 0.001 |
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".