Thrombomodulin is a determinant of metastasis through a mechanism linked to the thrombin binding domain but not the lectin-like domain
Bibliographic record
Abstract
Thrombomodulin (TM) is a predominantly endothelial transmembrane glycoprotein that modulates hemostatic function through a domain that controls thrombin-mediated proteolysis and an N-terminal lectin-like domain that controls inflammatory processes. To test the hypothesis that TM is a determinant of malignancy and dissect the importance of these functional domains in cancer biology, metastatic potential was evaluated in TM(Pro) mice expressing a mutant form of TM with reduced thrombin affinity and TM(LeD) mice lacking the N-terminal lectin-like domain. Studies of TM(Pro) mice revealed that TM is a powerful determinant of hematogenous metastasis. TM(Pro) mice exhibited a strongly prometastatic phenotype relative to control mice that was found to result from increased survival of tumor cells newly localized to the lung rather than any alteration in tumor growth. The impact of the TM(Pro) mutation on metastasis was dependent on both tumor cell-associated tissue factor and thrombin procoagulant function. In contrast, expression of a mutant form of TM lacking the lectin-like domain had no significant impact on metastasis. These studies directly demonstrate for the first time that TM-mediated regulation of tumor cell-driven procoagulant function strongly influences metastatic potential and suggest that endothelial cell-associated modulators of hemostasis may represent novel therapeutic targets in limiting tumor dissemination.
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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 | 0.000 | 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".