Tissue Factor-Expressing Tumor-Derived Extracellular Vesicles Activate Quiescent Endothelial Cells via Protease-Activated Receptor-1
Bibliographic record
Abstract
Tissue factor (TF)-expressing tumor-derived extracellular vesicles (EV) can promote metastasis and pre-metastatic niche formation, but the mechanisms by which this occurs remain largely unknown. We hypothesized that generation of activated factor X (FXa) by TF expressed on tumor-derived EV could activate protease-activated receptors (PAR) on non-activated endothelial cells to induce a pro-adhesive and pro-inflammatory phenotype. We obtained EV from TF-expressing breast (MDA-MB-231) and pancreatic (BxPC3 and Capan-1) tumor cell lines. We measured expression of E-selectin and secretion of interleukin-8 (IL-8) in human umbilical vein endothelial cells after exposure to EV and various immunologic and chemical inhibitors of TF, FXa, PAR-1 and PAR-2. After 6 hours of exposure to tumor-derived EV (pretreated with FVIIa and FX) in vitro, endothelial cells upregulated E-selectin expression and secreted IL-8. These changes were decreased with an anti-TF antibody, FXa inhibitors (FPRCK and EGRCK), and PAR-1 antagonist (E5555), demonstrating that FXa generated by TF-expressing tumor-derived EV was signaling through endothelial PAR-1. Due to weak constitutive PAR-2 expression, these endothelial responses were not induced by a PAR-2 agonist peptide (SLIGKV) and were not inhibited by a PAR-2 antagonist (FSLLRY) after exposure to tumor-derived EV. In conclusion, we found that TF-expressing cancer-derived EV activate quiescent endothelial cells, upregulating E-selectin and inducing IL-8 secretion through generation of FXa and cleavage of PAR-1. Conversion of resting endothelial cells to an activated phenotype by TF-expressing cancer-derived EV could promote cancer metastases.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".