Regulation of breast cancer extravasation by Angiopoietin‐1
Bibliographic record
Abstract
The objective of this study was to investigate the roles of Angiopoietin‐1 (Ang‐1), a selective endothelial cell (EC) agonist, during breast cancer extravasation. We report for the first time that Ang‐1 modulates extravasation of metastatic breast cancer. We quantified breast cancer extravasation using a trans EC migration assay, where MDA‐MB‐231 cells were plated on a HUVEC monolayer which was pretreated with VEGF, TNF(or solvent. To determine the influence of Ang‐1 on breast cancer extravasation, either cell type was infected with Ang‐1 adenoviruses. Over expression of Ang‐1 in MDA‐MB‐231 cells potently inhibited their extravasation, both in the absence and presence of VEGF or TNF((p(0.05 vs Ad‐Fc‐infected control), an effect possibly mediated through the posttranslational phosphorylation of the MAPK pathway in ECs. Overexpression of Ang‐1 in HUVECs resulted in a significant reduction of MDA‐MB‐231 extravasation in the presence of TNF(or solvent. Interestingly, in contrast to MDA‐MB‐231 cells‐overexpressing Ang‐1, HUVEC‐derived Ang‐1 potentiated VEGF‐induced extravasation (p(0.05). We conclude that Ang‐1, mainly acting in a paracrine manner, is a potent inhibitor of breast cancer extravasation and counteracts the metastatic effects of VEGF and TNF(. Overexpressing Ang‐1 in breast cancer, rather than in endothelial, cells could hence be therapeutically beneficial for breast cancer patients.
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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".