Caveolin‐1 overexpression is associated with aggressive prostate cancer recurrence
Bibliographic record
Abstract
BACKGROUND: Caveolin-1 protein suppresses apoptotic cell death in prostate cancer. The objectives of this study were to investigate the association of Caveolin-1 expression with established features of prostate cancer as well as overall and aggressive disease recurrence in patients treated with radical prostatectomy (RP). METHODS: Caveolin-1 immunostaining was performed on a tissue microarray containing prostatectomy specimen cores from 232 consecutive patients treated with RP for clinically localized prostatic adenocarcinoma. Caveolin-1 over-expression was defined as more than 50% of cells staining positively for Caveolin-1. Patients were categorized as having features of aggressive disease recurrence if they had a positive metastatic work-up, post-recurrence PSA doubling time less than 10 months, and/or failure to respond to local salvage radiation therapy. RESULTS: Seventy patients (30.2%) exhibited over-expression of Caveolin-1. Caveolin-1 over-expression was associated with higher pathologic Gleason sum (P=0.038) and higher pre-operative PSA level (P=0.024). Patients with Caveolin-1 over-expression were at increased risk of PSA recurrence after surgery (P=0.023) in univariate but not in standard post-operative multivariate analysis. However, patients with Caveolin-1 over-expression were at increased risk of aggressive prostate cancer recurrence in both univariate and multivariate analysis (P<0.001 and P=0.001, respectively). CONCLUSIONS: Over-expression of Caveolin-1 was associated with established features of prostate cancer and aggressive PSA recurrence. Caveolin-1 might help identify patients at high risk of developing aggressive prostate cancer recurrence, thus allowing selection of patients who might benefit from early systemic therapeutic intervention.
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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 | 0.000 | 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) | 0.001 | 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".