Phosphorylation of Membrane Type 1-Matrix Metalloproteinase (MT1-MMP) and Its Vesicle-associated Membrane Protein 7 (VAMP7)-dependent Trafficking Facilitate Cell Invasion and Migration
Bibliographic record
Abstract
In multicellular organisms, uncontrolled movement of cells can contribute to pathological conditions, such as multiple sclerosis and cancer. In highly aggressive tumors, the expression of matrix metalloproteinases (MMPs) is linked to the capacity of tumor cells to invade surrounding tissue and current research indicates that the membrane-anchored membrane type 1-matrix metalloproteinase (MT1-MMP) has a central role in this process. Endocytosis and trafficking of MT1-MMP are essential for its proper function, and here we examine the phosphorylation, internalization, and recycling of this enzyme, and the associated biochemical signaling in HeLa and HT-1080 fibrosarcoma cells. Activation of protein kinase C with phorbol 12-myristate 13-acetate resulted in phosphorylation of endogenous MT1-MMP at Thr(567) in vivo. Mutation of Thr(567) to alanine (to mimic non-phosphorylated MT1-MMP) reduced internalization of MT1-MMP, whereas mutation of Thr(567) to glutamic acid (to mimic phosphorylation) resulted in decreased levels of MT1-MMP on the cell surface. The endosomal trafficking and recycling of MT1-MMP was found to be dependent upon Rab7 and VAMP7, and blocking the function of these proteins reduced cell migration and invasion. Intracellular trafficking of MT1-MMP was observed to be coupled to the trafficking of integrin α5 and phosphorylation of ERK that coincided with this was dependent on phosphorylation of MT1-MMP. Together, these results reveal important roles for MT1-MMP phosphorylation and trafficking in both cell signaling and cell invasion.
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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".