Matrix metalloproteinase 2 attenuates brain tumour growth, while promoting macrophage recruitment and vascular repair
Bibliographic record
Abstract
Matrix metalloproteinase 2 (MMP2) is an extracellular protein-degrading enzyme widely believed to be involved in the invasion of brain tumour cells. However, this assumption is mainly based on in vitro studies. By characterizing the transcriptome and in vivo properties of 20 astrocytoma cell lines, we found that the levels of MMP2 were higher in GFAP(-) astrocytoma cells and correlated with their ability to induce vascular changes, a common complication of malignant tumours. To study the relationship between MMP2 expression and vascular alteration, we intracerebrally implanted immunodeficient mice with human astrocytoma cells stably transduced with lentiviral vectors expressing either MMP2 or a short hairpin RNA against MMP2. We found that the tumours depleted of MMP2 were larger, contained more proliferating cells and fewer macrophages, and had a vasculature that was more destabilized and regressed with fewer capillary sprouts. In contrast, the tumours overexpressing MMP2 were smaller and showed no histological difference compared to the controls. We therefore suggest that MMP2 is not the cause of vascular atypia in malignant brain tumours, but is involved in a tissue repair response that tends to limit the growth of these tumours. This study argues against MMP2 inhibition as a therapeutic approach for brain cancer and provides a comprehensive characterization of popular astrocytoma cell lines that should help to identify alternative targets.
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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) | 0.001 | 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".