Membrane Type 1 Matrix Metalloproteinase-associated Degradation of Tissue Inhibitor of Metalloproteinase 2 in Human Tumor Cell Lines
Bibliographic record
Abstract
Tissue inhibitor of metalloproteinase 2 (TIMP-2) is required for the membrane type 1 matrix metalloproteinase (MT1-MMP)-dependent activation of pro-MMP-2 on the cell surface. MT1-MMP-bound TIMP-2 has been shown to function as a receptor for secreted pro-MMP-2, resulting in the formation of a trimolecular complex. In the presence of uncomplexed active MT1-MMP, the prodomain of cell surface-associated MMP-2 is cleaved, and activated MMP-2 is released. However, the behavior of MT1-MMP-bound TIMP-2 during MMP-2 activation is currently unknown. In this study, (125)I-labeled recombinant TIMP-2 ((125)I-rTIMP-2) was used to investigate the fate of TIMP-2 during pro-MMP-2 activation by HT1080 and transfected A2058 cells. HT1080 and A2058 cells transfected with MT1-MMP cDNA (but not vector-transfected A2058 cells) were able to bind (125)I-rTIMP-2, to activate pro-MMP-2, and to process MT1-MMP into an inactive 43-kDa form. Under these conditions, (125)I-rTIMP-2 bound to the cell surface was rapidly internalized and degraded in intracellular organelles through a bafilomycin A(1)-sensitive mechanism, and (125)I-bearing low molecular mass fragment(s) were released in the culture medium. These different processes were inhibited by hydroxamic acid-based synthetic MMP inhibitors and rTIMP-2, but not by rTIMP-1 or cysteine, serine, or aspartic proteinase inhibitors. These results support the concept that the MT1-MMP-dependent internalization and degradation of TIMP-2 by some tumor cells might be involved in the regulation of pericellular proteolysis.
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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) | 0.004 | 0.002 |
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".