TMPRSS2-ERG fusion is frequently observed in gleason pattern 3 prostate cancer in a Canadian cohort
Bibliographic record
Abstract
PURPOSE: TMPRSS2-ERG gene fusion was recently reported as the most common gene rearrangement in prostate cancer (PCA). RESULTS: In this cohort 41% of the patients showed positive gene fusion status in their PCA. The TMPRSS2-ERG gene fusion status was homogenous within the same cancer focus and 82% of fusion positive PCA were present in GS 6 or 7 vs. 14% in GS 8 (p = 0.004). Moreover, TMPRSS2-ERG fusion was present in 42% of Gleason pattern 3 vs. 27% of Gleason pattern 4 (p = 0.014). However, in this study, no significant association was noticed between TMPRSS2-ERG fusion status in relation to pathological stage, surgical margin or biochemical failure. EXPERIMENTAL DESIGN: Using break-apart FISH assay to indirectly assess the fusion of TMPRSS2-ERG. We sought to characterize the incidence, pathological features and clinical parameters of TMPRSS2-ERG gene fusion in a cohort of 196 Canadian men treated by radical prostatectomy for localized PCA, and to investigate its potential as a biomarker in PCA. CONCLUSION: The higher association of TMPRSS2-ERG with Gleason score 6 and 7 should be further investigated. If confirmed, this could have significant clinical impact in further stratifying patients with PCA should the TMPRSS2-ERG be confirmed as a prognostic biomarker.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".