MMP8 increases tongue carcinoma cell–cell adhesion and diminishes migration via cleavage of anti-adhesive FXYD5
Bibliographic record
Abstract
Matrix metalloproteinases (MMPs) modify bioactive factors via selective processing or degradation resulting in tumour-promoting or tumour-suppressive effects, such as those by MMP8 in various cancers. We mapped the substrates of MMP8 to elucidate its previously shown tumour-protective role in oral tongue squamous cell carcinoma (OTSCC). MMP8 overexpressing (+) HSC-3 cells, previously demonstrated to have reduced migration and invasion, showed enhanced cell-cell adhesion. By analysing the secretomes of MMP8 + and control cells with terminal amine isotopic labelling of substrates (TAILS) coupled with liquid chromatography and tandem mass spectrometry (LC-MS/MS), we identified 36 potential substrates of MMP8, including FXYD domain-containing ion transport regulator 5 (FXYD5). An anti-adhesive glycoprotein FXYD5 has been previously shown to predict poor survival in OTSCC. Cleavage of FXYD5 by MMP8 was confirmed using recombinant proteins. Furthermore, we detected a loss of FXYD5 levels on cell membrane of MMP8 + cells, which was rescued by inhibition of the proteolytic activity of MMP8. Silencing (si) FXYD5 increased the cell-cell adhesion of control but not that of MMP8 + cells. siFXYD5 diminished the viability and motility of HSC-3 cells independent of MMP8 and similar effects were seen in another tongue cancer cell line, SCC-25. FXYD5 is a novel substrate of MMP8 and reducing FXYD5 levels either with siRNA or cleavage by MMP8 increases cell adhesion leading to reduced motility. FXYD5 being a known prognostic factor in OTSCC, our findings strengthen its potential as a therapeutic target.
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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 | 0.000 | 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) | 0.000 | 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".