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Abstract P1-07-32: Activated thrombin activatable fibrinolysis inhibitor is a novel anti-metastatic factor in breast cancer

2015· article· en· W1937278795 on OpenAlexaff
Zainab Bazzi, Deborah Rudy, Lisa A. Porter, Dora Cavallo‐Medved, Michael B. Boffa

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtease and Inhibitor Mechanisms
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPlasminZymogenThrombomodulinThrombinCancer researchCancer cellFibrinolysisPlasminogen activatorChemistryCarboxypeptidaseCell migrationTissue factorCancerCell biologyCellBiochemistryBiologyImmunologyMedicineEndocrinologyInternal medicineCoagulationEnzymePlatelet

Abstract

fetched live from OpenAlex

Abstract Thrombin activatable fibrinolysis inhibitor (TAFI) is a plasma zymogen initially known for its role in attenuating fibrinolysis. Activated TAFI (TAFIa) is formed through proteolytic cleavage by thrombin, plasmin or, its most effective activator, thrombin in complex with the endothelial cofactor thrombomodulin (TM). TAFIa is a carboxypeptidase, which acts by cleaving 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 vital role in accelerating plasminogen activation to plasmin on the cell surface. Plasmin has many critical functions including cleaving components of the extracellular matrix (ECM), which enhances invasion and migration of cancer cells. In addition, plasmin can activate matrix metalloproteinases (MMPs), which also play a role in degrading the ECM. Furthermore, the expression of TM in tumours is inversely correlated to metastasis. Studies have shown that the anti-metastatic effects of TM result from its ability to bind thrombin. Given that the thrombin/TM complex is responsible for the activation of TAFI, the anti-metastatic effects of TM may be modulated by TAFIa. We therefore hypothesize that the activation of TAFI on the cell surface inhibits plasminogen activation and decreases breast cancer cell invasion and migration. Expression of TAFI and TM were assessed in breast cancer cells with varying degrees of metastatic potential. Although TAFI mRNA levels did not correlate with malignancy, TM mRNA levels were found to be inversely correlated with breast cancer cell malignancy. Moreover, cell invasion and migration of MDA-MB-231 and SUM149 cells were assessed upon treatment with potato tuber carboxypeptidase inhibitor (PTCI), which is a specific inhibitor of TAFIa. Inhibition of TAFIa resulted in a significant increase in cell invasion and migration of both cell lines. Cell invasion and migration of MDA-MB-231 and SUM149 cells were also assessed upon treatment with TM. Treatment with TM significantly decreased cell invasion and migration of both MDA-MB-231 and SUM149 cells. Additionally, experiments using a fluorogenic collagen substrate showed an increase in extracellular collagen cleavage after PTCI treatment, using both MDA-MB-231 and SUM149 cells. Furthermore, the ability of TAFIa to inhibit pericellular plasminogen activation was evaluated. Plasminogen activation was significantly decreased on the surface of MDA-MB-231 and SUM149 cells following treatment with various concentrations of TAFIa. Taken together, these results indicate a vital role for TAFIa in regulating pericellular plasminogen activation and ultimately ECM proteolysis. Enhancement of TAFI activation in the breast cancer tumour microenvironment may be a therapeutic strategy to inhibit invasion and prevent metastasis of breast cancer cells. Citation Format: Zainab A Bazzi, Deborah Rudy, Lisa A Porter, Dora Cavallo-Medved, Michael B Boffa. Activated thrombin activatable fibrinolysis inhibitor is a novel anti-metastatic factor in breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P1-07-32.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.089
GPT teacher head0.379
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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