Heparin Impairs Angiogenesis through Inhibition of MicroRNA-10b
Bibliographic record
Abstract
Heparin, which has been used as an anticoagulant drug for decades, inhibits angiogenesis, whereas thrombin promotes tumor-associated angiogenesis. However, the mechanisms underlying the regulation of angiogenesis by heparin and thrombin are not well understood. Here, we show that microRNA-10b (miR-10b) is down-regulated by heparin and up-regulated by thrombin in human microvascular endothelial cells (HMEC-1). Overexpression of miR-10b induces HMEC-1 cell migration, tube formation, and angiogenesis, and down-regulates homeobox D10 (HoxD10) expression via direct binding of miR-10b to the putative 3' UTR of HoxD10. In addition, HMEC-1 cell migration and tube formation are induced by HoxD10 knockdown, whereas angiogenesis is arrested when HoxD10 expression is increased after anti-miR-10b or heparin treatments. Furthermore, expression of miR-10b and its transcription factor Twist are up-regulated by thrombin, whereas HoxD10 expression is impaired by thrombin. Using quartz crystal microbalance analysis, we show that heparin binds to thrombin, thereby inhibiting thrombin-induced expression of Twist and miR-10b. However, the expression of miR-10b is not attenuated by heparin any more after thrombin expression is silenced by its siRNA. Interestingly, we find that heparin attenuates miR-10b expression and induces HoxD10 expression in vivo to inhibit angiogenesis and impair the growth of MDA-MB-231 tumor xenografts. These results provide insight into the molecular mechanism by which heparin and thrombin regulate angiogenesis.
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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) | 0.000 | 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) | 0.000 | 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".