Matrix stiffness regulates vascular integrity through focal adhesion kinase activity
Bibliographic record
Abstract
Tumor vasculature is known to be more permeable than the vasculature found in healthy tissue, which in turn can lead to a more aggressive tumor phenotype and impair drug delivery into tumors. While the stiffening of the stroma surrounding solid tumors has been reported to increase vascular permeability, the mechanism of this process remains unclear. Here, we utilize an in vitro model of tumor stiffening, ex ovo culture, and a mouse model to investigate the molecular mechanism by which matrix stiffening alters endothelial barrier function. Our data indicate that the increased endothelial permeability caused by heightened matrix stiffness can be prevented by pharmaceutical inhibition of focal adhesion kinase (FAK) both in vitro and ex ovo. Matrix stiffness-mediated FAK activation determines Src localization to cell-cell junctions, which then induces increased vascular endothelial cadherin phosphorylation both in vitro and in vivo. Endothelial cells in stiff tumors have more activated Src and higher levels of phosphorylated vascular endothelial cadherin at adherens junctions compared to endothelial cells in more compliant tumors. Altogether, our data indicate that matrix stiffness regulates endothelial barrier integrity through FAK activity, providing one mechanism by which extracellular matrix stiffness regulates endothelial barrier function. Additionally, our work also provides further evidence that FAK is a promising potential target for cancer therapy because FAK plays a critical role in the regulation of endothelial barrier integrity.-Wang, W., Lollis, E. M., Bordeleau, F., Reinhart-King, C. A. Matrix stiffness regulates vascular integrity through focal adhesion kinase activity.
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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".