β1 integrin-mediated signaling regulates MT1-MMP phosphorylation to promote tumor cell invasion
Bibliographic record
Abstract
ABSTRACT Malignant cancer cells can invade extracellular matrix (ECM) through the formation of F-actin-rich subcellular structures termed invadopodia. ECM degradation at invadopodia is mediated by matrix metalloproteinases (MMPs), and recent findings indicate that membrane-anchored membrane type 1-matrix metalloproteinase (MT1-MMP, also known as MMP14) has a primary role in this process. Maintenance of an invasive phenotype is dependent on internalization of MT1-MMP from the plasma membrane and its recycling to sites of ECM remodeling. Internalization of MT1-MMP is dependent on its phosphorylation, and here we examine the role of β1 integrin-mediated signaling in this process. Activation of β1 integrin using the antibody P4G11 induced phosphorylation and internalization of MT1-MMP and resulted in increased cellular invasiveness and invadopodium formation in vitro. We also observed phosphorylation of Src and epidermal growth factor receptor (EGFR) and an increase in their association in response to β1 integrin activation, and determined that Src and EGFR promote phosphorylation of MT1-MMP on Thr567. These results suggest that MT1-MMP phosphorylation is regulated by a β1 integrin-Src-EGFR signaling pathway that promotes recycling of MT1-MMP to sites of invadopodia formation during cancer cell invasion. This article has an associated First Person interview with the first author of the paper.
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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) | 0.002 | 0.001 |
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".