Prostate cancer: MMP2, MMP9, MMP14, TIMP2 and disease-free survival
Bibliographic record
Abstract
1154 Introduction : We have recently shown that the matrix metalloproteinase 2 (MMP2, gelatinase A) overexpression by cancer cells was associated with a poor prognosis in prostate cancer (Pca) (Cancer Res, 2003). MMP14 activates MMP2 using pro-MMP2 specific inhibitor TIMP2 as a receptor. Activated MMP2 degrades extracellular matrix components such as collagen and gelatin, and activates other MMPs including MMP9 (gelatinase B). We therefore tested the influence of MMP9, MMP14 and TIMP2 expression on Pca disease-free survival and the association between MMP2, MMP9, MMP14 and TIMP2. Material and Methods: By immunohistochemistry, we analyzed the 200 T3NxM0 Pca cases used for our MMP2 prior study. We evaluated marker expression separately in cancer, stromal and benign epithelial (BE) cells according to a percentage scale (0, 10%) TIMP2 expression in stromal cells (HR = 0.573, p = 0.0233) and an increased risk of Pca recurrence with MMP2 expression by > 50% of BE cells (HR = 3.006, p = 0.0387). Increase risk of Pca recurrence was also observed with the following combinations: low TIMP2 in stromal cells and high MMP2 in BE cells (HR = 4.121, p
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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 | 0.001 |
| 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) | 0.004 | 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".