Inhibition of MT1-MMP proteolytic function and ERK1/2 signalling influences cell migration and invasion through changes in MMP-2 and MMP-9 levels
Bibliographic record
Abstract
Membrane type-1 matrix metalloproteinase (MT1-MMP, MMP-14) is a unique protease that cleaves extracellular proteins, activates proMMPs, and initiates intracellular signalling. MCF-7 cells are non-invasive and deficient in MT1-MMP, MMP-2, and MMP-9 expression. We created an MCF-7 cell line (C2) that stably produces active MT1-MMP and demonstrated increased ERK1/2 phosphorylation. MAPK inhibition in this cell line showed an inverse relationship in MMP-2 and MMP-9 transcripts where levels of these genes increased and decreased, respectively. Using invasive MDA-MB 231 cells that endogenously produce MT1-MMP and have naturally high pERK levels, we demonstrated the identical inverse relationship between MMP-2 and -9 transcript and protein levels, suggesting that this novel relationship is conserved amongst MT1-MMP positive breast cancer cells. To further analyze the relationship between MMP-2 and -9 levels, we chemically inhibited activation and catalytic activity of MT1-MMP using a furin and MMP inhibitor, respectively, to show that interference with the functions of MT1-MMP induced changes in MMP-2 and 9 transcript levels that were always inverse of each other, and likely mediated by differential transcriptional activity of the NF-κB transcription factor. Furthermore, we analyzed the functional consequences of these expression changes to show MMP, and in particular ERK, inhibition decreased migration and invasion using 2D culture, and inhibits the formation of an invasive phenotype in Matrigel 3D culture. This study demonstrated a novel inverse transcriptional relationship between MMP-2 and -9 levels and MT1-MMP activity that have functional consequences, and also showed that increases in the levels of MMPs does not necessarily correlate with an invasive phenotype.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".