Elucidating the role of the kinase activity of endothelial cell focal adhesion kinase in angiocrine signalling and tumour growth
Bibliographic record
Abstract
A common limitation of cancer treatments is chemotherapy resistance. We have previously identified that endothelial cell (EC)-specific deletion of focal adhesion kinase (FAK) sensitises tumour cells to DNA-damaging therapies, reducing tumour growth in mice. The present study addressed the kinase activity dependency of EC FAK sensitisation to the DNA-damaging chemotherapeutic drug, doxorubicin. FAK is recognised as a therapeutic target in tumour cells, leading to the development of a range of inhibitors, the majority being ATP competitive kinase inhibitors. We demonstrate that inactivation of EC FAK kinase domain (kinase dead; EC FAK-KD) in established subcutaneous B16F0 tumours improves melanoma cell sensitisation to doxorubicin. Doxorubicin treatment in EC FAK-KD mice reduced the percentage change in exponential B16F0 tumour growth further than in wild-type mice. There was no difference in tumour blood vessel numbers, vessel perfusion or doxorubicin delivery between genotypes, suggesting a possible angiocrine effect on the regulation of tumour growth. Doxorubicin reduced perivascular malignant cell proliferation, while enhancing perivascular tumour cell apoptosis and DNA damage in tumours grown in EC FAK-KD mice 48 h after doxorubicin injection. Human pulmonary microvascular ECs treated with the pharmacological FAK kinase inhibitors defactinib, PF-562,271 or PF-573,228 in combination with doxorubicin also reduced cytokine expression levels. Together, these data suggest that targeting EC FAK kinase activity may alter angiocrine signals that correlate with improved acute tumour cell chemosensitisation. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.
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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 | 0.001 | 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".