Functional Evaluation of Plasmin Formation in Primary Breast Cancer
Bibliographic record
Abstract
PURPOSE: Plasmin generation is controlled by the plasminogen activators (PA)/plasmin system, which comprises proteases (urokinase-type PA [uPA] and tissue-type PA [tPA]) and antiproteases (PA inhibitors, PAI-1 and PAI-2). The tumoral content of uPA and PAI-1 has been shown to carry prognostic value in breast cancer; however, because most assays used so far have relied on immunometric determinations, we have explored the enzymatic activities governing plasmin formation in breast cancer specimens. PATIENTS AND METHODS: We applied semiquantitative histochemical zymography to 201 primary breast cancer tissue sections. Enzymatic activities were correlated with histopathologic parameters and clinical outcome. The median follow-up was 91 months. RESULTS: A wide range of PA-mediated catalytic activities was detected. The overall survival was significantly worse for patients with tumors showing tPA in the lowest quartile of activity (P =.003). The 5-year overall survival of patients with tPA activity in the lowest quartile was 58% compared with 81% for patients with tPA value in the other three quartiles. Tumor size, axillary lymph node metastasis, histologic grade, lymphovascular infiltration, TP53 mutation, and tPA activity were all major risk factors in univariate analysis. tPA activity was an independent prognostic factor in a multivariate Cox regression model, both in the whole population (relative risk = 0.5, 95% confidence interval, 0.3 to 0.9; P =.02) and in the node-negative subgroup (relative risk = 0.2, 95% confidence interval, 0.08 to 0.6; P =.004). CONCLUSION: By using a zymographic assay performed directly on primary tumor tissue sections, we demonstrate that reduced tPA-mediated plasmin production is an independent adverse prognostic factor in breast cancer.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".