Antithrombin-binding heparan sulfate is ubiquitously expressed in epithelial cells and suppresses pancreatic tumorigenesis
Bibliographic record
Abstract
3-O-sulfation of heparan sulfate (HS) is the key determinant for binding and activation of antithrombin III (AT). This interaction is the basis of heparin treatment to prevent thrombotic events and excess coagulation. Antithrombin-binding HS (HSAT) is expressed in human tissues but is thought to be expressed in the subendothelial space, mast cells, and follicular fluid. Here, we show that HSAT is ubiquitously expressed in the basement membranes of epithelial cells in multiple tissues. In the pancreas, HSAT is expressed by healthy ductal cells, and its expression is increased in premalignant pancreatic intraepithelial neoplasia lesions but not in pancreatic ductal adenocarcinoma (PDAC). Inactivation of HS3ST1, a key enzyme in HSAT synthesis, in PDAC cells eliminated HSAT expression, induced an inflammatory phenotype, suppressed markers of apoptosis, and increased metastasis in an experimental mouse PDAC model. HSAT-positive PDAC cells bind AT, which inhibits the generation of active thrombin by tissue factor and factor VIIa. Furthermore, plasma from patients with PDAC showed accumulation of HSAT, suggesting its potential as a marker of tumor formation. These findings suggest that HSAT exerts a tumor-suppressing function through recruitment of AT and that the decrease in HSAT during progression of pancreatic tumorigenesis increases inflammation and metastatic potential.
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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".