ERG Protein Expression Is of Limited Prognostic Value in Men with Localized Prostate Cancer
Bibliographic record
Abstract
Background. The prognostic significance of ERG expression in prostate cancer (PCA) has generated mixed results. We sought to investigate the prognostic significance of ERG expression in a localized cohort of men with PCA. Material and Methods. We investigated ERG protein expression in a cohort of 198 men with localized PCA. ERG expression was correlated with patients' clinical outcome and several pathological parameters, including Gleason score (GS), pathological stage, surgical margin, and extra-capsular extension. Results. ERG expression was detected in 86/198 (43.4%) patients exclusively in neoplastic epithelium. Overall, ERG mean expression intensity was 1.01 ± 1.27 versus 0.37 ± 0.83 in acinar PCA compared to foamy type PCA (P < 0.001). In HGPIN, ERG intensity levels were comparable to those in foamy type PCA (0.13 ± 0.56) but significantly lower than those in acinar PCA (P < 0.001). ERG expression was significantly associated with extra-prostatic extension and higher pathological stage and showed a trend toward seminal vesicle invasion. Herein, ERG expression was documented in 50/131 (38.1%) patients with pT2 versus 30/55 (54.5%) patients with pT3 (P = 0.04). ERG association with higher pathological stage was more pronounced in patients with GS > 7. Grouping patients into those with GS ≤ 7 versus >7, there was no significant association between ERG expression and GS. Similarly, no association was present in relation to either surgical margins or postsurgical serum PSA levels. Conclusion. We report significant association between ERG protein levels and extra-prostatic extension and higher pathological stage. ERG expression is not associated with adverse clinical outcome and is of limited prognostic value in localized PCA.
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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".