Dual functions of <scp>ARP</scp>101 in targeting membrane type‐1 matrix metalloproteinase: Impact on U87 glioblastoma cell invasion and autophagy signaling
Bibliographic record
Abstract
Membrane type-1 matrix metalloproteinase (MT1-MMP) possesses both extracellular proteolytic and intracellular signal-transducing functions in tumorigenesis. An imbalance in MT1-MMP expression and/or function triggers a metastatic, invasive, and therapy resistance phenotype. MT1-MMP is involved in extracellular matrix (ECM) proteolysis, activation of latent MMPs, as well as in autophagy signaling in human hepatoma and glioblastoma cells. A low autophagy index in tumorigenesis has been inferred by recent studies where autophagic capacity was decreased during tumor progression. Here, we establish ARP101 as a dual-function small-molecule inhibitor against MT1-MMP ECM hydrolysis and autophagy signal-transducing functions in a model of grade IV glioblastoma cells. ARP101 inhibited concanavalin-A-mediated proMMP-2 activation into MMP-2, as well as MT1-MMP auto-proteolytic processing. When overexpressing recombinant Wt MT1-MMP, ARP101 inhibited proMMP-2 activation and triggered the formation of MT1-MMP oligomers that required trafficking to the plasma membrane. ARP101 further induced cell autophagy as reflected by increased formation of acidic vacuole organelles, LC3 puncta, and autophagy-related protein ATG9 transcription. These were all significantly reversed upon siRNA-mediated gene silencing of MT1-MMP. ARP101 can thus concomitantly inhibit MT1-MMP extracellular catalytic function and exploit its intracellular transducing signal function to trigger autophagy-mediated cell death in U87 glioblastoma cancer cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".