MT1-MMP Down-regulates the Glucose 6-Phosphate Transporter Expression in Marrow Stromal Cells
Bibliographic record
Abstract
Bone marrow-derived stromal cells (BMSC) are avidly recruited by experimental vascularizing tumors, which implies that they must respond to tumor-derived growth factor cues. In fact, BMSC chemotaxis and cell survival are regulated, in part, by the membrane type-1 matrix metalloproteinase (MT1-MMP), an MMP also involved in pro-MMP-2 activation and in degradation of the extracellular matrix (ECM). Given that impaired chemotaxis was recently observed in bone marrow cells isolated from a glucose 6-phosphate transporter-deficient (G6PT-/-) mouse model, we sought to investigate the potential MT1-MMP/G6PT signaling axis in BMSC. We show that MT1-MMP-mediated activation of pro-MMP-2 by concanavalin A (ConA) correlated with an increase in the sub-G1 cell cycle phase as well as with cell necrosis, indicative of a decrease in BMSC survival. BMSC isolated from Egr-1-/- mouse or MT1-MMP gene silencing in BMSC with small interfering RNA (siMT1-MMP) antagonized both the ConA-mediated activation of pro-MMP-2 and the induction of cell necrosis. Overexpression of recombinant full-length MT1-MMP triggered necrosis and this was signaled through the cytoplasmic domain of MT1-MMP. ConA inhibited both the gene and protein expression of G6PT, while overexpression of recombinant G6PT inhibited MT1-MMP-mediated pro-MMP-2 activation but could not rescue BMSC from ConA-induced cell necrosis. Cell chemotaxis in response to the tumorigenic growth factor sphingosine 1-phosphate was significantly abrogated in siMT1-MMP BMSC and in chlorogenic acid-treated BMSC. Altogether, we provide evidence for an MT1-MMP/G6PT signaling axis that regulates BMSC survival, ECM degradation, and mobilization. This may lead to optimized clinical applications that use BMSC as a platform for the systemic delivery of therapeutic or anti-cancer recombinant proteins in vivo.
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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 | 0.001 |
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".