Analysis of the thrombotic and fibrinolytic activities of tumor cell–derived extracellular vesicles
Bibliographic record
Abstract
Exosomes and microvesicles (MVs) are small extracellular vesicles secreted by tumor cells and are suggested to contribute to the thrombotic events that commonly occur in patients with advanced malignancies. Paradoxically, these vesicles have been reported to also possess fibrinolytic activity. To determine whether thrombotic or fibrinolytic activity is a predominant characteristic of these extracellular vesicles, we prepared exosomes and MVs from 2 breast cancer cell lines (MDA-MB-231 and MCF7), a lung cancer cell line (A549), and a leukemia cell line (NB4) and assayed their thrombotic and fibrinolytic activities. We observed that thrombotic activity was a common feature of MVs but not exosomes. Exosomes and/or MVs from several cell lines, with the exception of the A549 cell line, displayed fibrinolytic activity toward a pure fibrin clot, but only exosomes from MDA-MB-231 cells could degrade a fibrin clot formed in plasma. Increasing the malignant potential of MCF7 cells decreased the thrombotic activity of their MVs but did not alter their fibrinolytic activity. Decreasing the malignant potential of NB4 cells did not alter the thrombotic or fibrinolytic activity of their MVs or exosomes. Finally, the incubation of MDA-MB-231 cell-derived exosomes with A549 cells increased plasmin generation by these cells. Our data indicate that MVs generally have thrombotic activity, whereas thrombotic activity is not commonly observed for exosomes. Furthermore, exosomes and MVs generally do not display fibrinolytic activity under physiological conditions.
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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 | 0.001 |
| 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) | 0.000 | 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 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".