Proteins involved in regulating bone invasion in skull base meningiomas
Bibliographic record
Abstract
BACKGROUND: Bone invasive skull base meningiomas are a subset of meningiomas that present a unique clinical challenge due to brain and neural structure involvement and limitations in complete surgical resection, resulting in higher recurrence and need for repeat surgery. To date, the pathogenesis of meningioma bone invasion has not been investigated. We investigated immunoexpression of proteins implicated in bone invasion in other tumor types to establish their involvement in meningioma bone invasion. METHODS: Retrospective review of our database identified bone invasive meningiomas operated on at our institution over the past 20 years. Using high-throughput tissue microarray (TMA), we established the expression profile of osteopontin (OPN), matrix metalloproteinase-2 (MMP2), and integrin beta-1 (ITGB1). Differential expression in tumor cell and vasculature was evaluated and comparisons were made between meningioma anatomical locations. RESULTS: MMP2, OPN, and ITGB1 immunoreactivity was cytoplasmic in tumor and/or endothelial cells. Noninvasive transbasal meningiomas exhibited higher vascular endothelial cell MMP2 immunoexpression compared to invasive meningiomas. We found higher expression levels of OPN and ITGB1 in bone invasive transbasal compared to noninvasive meningiomas. Strong vascular ITGB1 expression extending from the endothelium through the media and into the adventitia was found in a subset of meningiomas. CONCLUSIONS: We have demonstrated that key proteins are differentially expressed in bone invasive meningiomas and that the anatomical location of bone invasion is a key determinant of expression pattern of MMP1, OPN, and ITGB1. This data provides initial insights into the pathophysiology of bone invasion in meningiomas and identifies factors that can be pursued as potential therapeutic 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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".