Perlecan Proteolysis Induces an α2β1 Integrin- and Src Family Kinase-dependent Anti-apoptotic Pathway in Fibroblasts in the Absence of Focal Adhesion Kinase Activation
Bibliographic record
Abstract
Dysregulation of apoptosis in endothelial cells (EC) and fibroblasts contributes to fibrosis. We have shown previously that apoptosis of EC triggers the proteolysis of extracellular matrix components and the release of a C-terminal fragment of perlecan, which in turn inhibits apoptosis of fibroblasts. Here we have defined the receptors and pathways implicated in this anti-apoptotic response in fibroblasts. Neutralizing alpha2beta1 integrin activity in fibroblasts exposed to either medium conditioned by apoptotic EC (SSC) or a recombinant perlecan C-terminal fragment (LG3) prevented resistance to apoptosis and is associated with decreased levels of Akt phosphorylation. Co-incubation of fibroblasts for 24 h with SSC or LG3 in the presence of PP2 (AG1879), a biochemical inhibitor of Src family kinases (SFKs) and focal adhesion kinase, showed a significantly decreased anti-apoptotic response. However, focal adhesion kinase gene silencing with RNA interference did not inhibit the anti-apoptotic response in fibroblasts. Src phosphorylation was increased in fibroblasts exposed to SSC, and transfection of fibroblasts with constitutively active Src mutants induced an anti-apoptotic response that was not further increased by SSC. Also, Src(-/-)Fyn(-/-) fibroblasts failed to mount an anti-apoptotic response in presence of SSC for 24 h but developed a complete anti-apoptotic response when exposed to SSC for 7 days. These results suggest that extracellular matrix fragments produced by apoptotic EC initiate a state of resistance to apoptosis in fibroblasts via an alpha2beta1 integrin/SFK (Src and Fyn)/phosphatidylinositol 3-kinase (PI3K)-dependent pathway. In the long term, additional SFK members are recruited for sustaining the anti-apoptotic response, which could play crucial roles in abnormal fibrogenic healing.
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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".