Cancer Cells Induced to Express Mesenchymal Phenotype Release Exosome-like Extracellular Vesicles Carrying Tissue Factor
Bibliographic record
Abstract
Aggressive epithelial cancer cells frequently adopt mesenchymal characteristics and exhibit aberrant interactions with their surroundings, including the vasculature. Whether the release/uptake of extracellular vesicles (EVs) plays a role during these processes has not been studied. EVs are heterogeneous membrane structures that originate either at the surface (microparticles), or within (exosomes) activated or transformed cells, and are involved in intercellular trafficking of bioactive molecules. Here, we show that epithelial cancer cells (A431, DLD-1) adopt mesenchymal features (epithelial-to-mesenchymal transition-like state) upon activation of epidermal growth factor receptor (EGFR) coupled with blockade of E-cadherin. This treatment leads to a coordinated loss of EGFR and tissue factor (TF) from the plasma membrane and coincides with a surge in emission of small, exosome-like EVs containing both receptors. TF (but not EGFR) is selectively up-regulated in EVs produced by mesenchymal-like cancer cells and can be transferred to cultured endothelial cells rendering them highly procoagulant. We postulate that epithelial-to-mesenchymal transition-like changes may alter cancer cell interactions with the vascular systems through altered vesiculation and TF shedding.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".