Activated thrombin-activatable fibrinolysis inhibitor (TAFIa) attenuates breast cancer cell metastatic behaviors through inhibition of plasminogen activation and extracellular proteolysis
Bibliographic record
Abstract
BACKGROUND: Thrombin activatable fibrinolysis inhibitor (TAFI) is a plasma zymogen, which can be converted to activated TAFI (TAFIa) through proteolytic cleavage by thrombin, plasmin, and most effectively thrombin in complex with the endothelial cofactor thrombomodulin (TM). TAFIa is a carboxypeptidase that cleaves carboxyl terminal lysine and arginine residues from protein and peptide substrates, including plasminogen-binding sites on cell surface receptors. Carboxyl terminal lysine residues play a pivotal role in enhancing cell surface plasminogen activation to plasmin. Plasmin has many critical functions including cleaving components of the extracellular matrix (ECM), which enhances invasion and migration of cancer cells. We therefore hypothesized that TAFIa could act to attenuate metastasis. METHODS: To assess the role of TAFIa in breast cancer metastasis, in vitro migration and invasion assays, live cell proteolysis and cell proliferation using MDA-MB-231 and SUM149 cells were carried out in the presence of a TAFIa inhibitor, recombinant TAFI variants, or soluble TM. RESULTS: Inhibition of TAFIa with potato tuber carboxypeptidase inhibitor increased cell invasion, migration and proteolysis of both cell lines, whereas addition of TM resulted in a decrease in all these parameters. A stable variant of TAFIa, TAFIa-CIIYQ, showed enhanced inhibitory effects on cell invasion, migration and proteolysis. Furthermore, pericellular plasminogen activation was significantly decreased on the surface of MDA-MB-231 and SUM149 cells following treatment with various concentrations of TAFIa. CONCLUSIONS: Taken together, these results indicate a vital role for TAFIa in regulating pericellular plasminogen activation and ultimately ECM proteolysis in the breast cancer microenvironment. Enhancement of TAFI activation in this microenvironment may be a therapeutic strategy to inhibit invasion and prevent metastasis of breast cancer cells.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".