Angiopoietin-1 deficiency increases tumor metastasis in mice
Bibliographic record
Abstract
BACKGROUND: Angipoietin-1 activation of the tyrosine kinase receptor Tek expressed mainly on endothelial cells leads to survival and stabilization of endothelial cells. Studies have shown that Angiopoietin-1 counteracts permeability induced by a number of stimuli. Here, we test the hypothesis that loss of Angiopoietin-1/Tek signaling in the vasculature would increase metastasis. METHODS: Angiopoietin-1 was deleted in mice just before birth using floxed Angiopoietin-1 and Tek mice crossed to doxycycline-inducible bitransgenic ROSA-rtTA/tetO-Cre mice. By crossing Angiopoietin-1 knockout mice to the MMTV-PyMT autochthonous mouse breast cancer model, we investigated primary tumor growth and metastasis to the lung. Furthermore, we utilized B16F10 melanoma cells subcutaneous and experimental lung metastasis models in Angiopoietin-1 and Tek knockout mice. RESULTS: We found that primary tumor growth in MMTV-PyMT mice was unaffected, while metastasis to the lung was significantly increased in Angiopoietin-1 knockout MMTV-PyMT mice. In addition, angiopoietin-1 deficient mice exhibited a significant increase in lung metastasis of B16F10 melanoma cells, compared to wild type mice 3 weeks after injection. Additional experiments showed that this was likely an early event due to increased attachment or extravasation of tumor cells, since seeding of tumor cells was significantly increased 4 and 24 h post tail vein injection. Finally, using inducible Tek knockout mice, we showed a significant increase in tumor cell seeding to the lung, suggesting that Angiopoietin-1/Tek signaling is important for vascular integrity to limit metastasis. CONCLUSIONS: This study show that loss of the Angiopoietin-1/Tek vascular growth factor system leads to increased metastasis without affecting primary tumor growth.
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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".