Prostaglandin E synthase is upregulated by Gas6 during cancer-induced venous thrombosis
Bibliographic record
Abstract
Venous thromboembolism is a common complication of cancer. Based on recent evidence that (1) growth arrest-specific 6 (Gas6) regulates the expression of tissue factor during venous thrombosis, and (2) cancer promotes a procoagulant milieu, we hypothesize that Gas6 may be involved in cancer-induced coagulopathy. Venous thrombi were induced in both wild-type (WT) and Gas6-deficient ((-/-)) mice with cancer. WT mice with cancer developed larger thrombi than their healthy counterparts; these larger thrombi induced by cancer were not seen in Gas6(-/-) mice. Whole genome microarray analysis of differential gene expression in WT and Gas6(-/-) endothelial cells exposed to M27 murine lung carcinoma cells reveal that Gas6 increases prostaglandin E synthase (Ptges) expression in endothelial cells. This was confirmed using real-time polymerase chain reaction and immunofluorescence staining. Culture of WT endothelial cells with M27 increases the secretion of prostaglandin E2 (PGE2), the enzymatic product of Ptges, in WT but not in Gas6(-/-) endothelial cells. In WT endothelial cells, Ptges expression was regulated through extracellular signal-regulated kinase 1/2 phosphorylation (ERK1/2). In vitro, PGE2 activates platelets after binding to its receptor, EP3. In vivo, EP3 receptor antagonism reversed the effect of cancer-induced thrombosis in WT mice. These results show that Gas6, through upregulation of PGE2, contributes to cancer-induced venous thrombosis.
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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".