A role for matrix remodelling proteins in invasive and malignant meningiomas
Bibliographic record
Abstract
AIMS: Meningiomas are one of the most common brain tumours in adults. Invasive and malignant meningiomas present a significant therapeutic challenge due to high recurrence rates and invasion into surrounding bone, brain, neural and soft tissues. Understanding the molecular mechanism of invasion could help in designing novel therapeutic approaches in order to prevent the need for repeat surgery, decrease morbidity and improve patient survival. The aim of this study was to identify the key factors and underlying mechanisms which govern invasive properties of meningiomas. METHODS: Formalin-fixed paraffin-embedded (FFPE) as well as frozen tumour tissues from bone-invasive, non-invasive and malignant meningiomas were used for RNA microarray, quantitative real-time PCR or Western blot analyses. Malignant meningioma cell lines (F5) were subject to MMP16 downregulation or overexpression and used for in vitro and in vivo functional assays. Subdural xenograft meningioma tumours were generated to study the invasion of tumour cells into brain parenchyma using cell lines with altered MMP16 expression. RESULTS: We establish that the expression level of MMP16 was significantly elevated in both bone-invasive and brain invasive meningiomas. Gain- and loss-of-function experiments indicated a role for MMP16 in meningioma cell movement, invasion and tumour cell growth. Furthermore, MMP16 was shown to positively regulate MMP2, suggesting this mechanism may modulate meningioma invasion in invasive meningiomas. CONCLUSIONS: Overall, the results support a role for MMP16 in promoting invasive properties of the meningioma tumours. Further studies to explore the potential value for clinical use of matrix metalloproteinases inhibitors are warranted.
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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".