Characterization of <i>TMPRSS2-ERG</i> Fusion High-Grade Prostatic Intraepithelial Neoplasia and Potential Clinical Implications
Bibliographic record
Abstract
PURPOSE: More than 1,300,000 prostate needle biopsies are done annually in the United States with up to 16% incidence of isolated high-grade prostatic intraepithelial neoplasia (HGPIN). HGPIN has low predictive value for identifying prostate cancer on subsequent needle biopsies in prostate-specific antigen-screened populations. In contemporary series, prostate cancer is detected in approximately 20% of repeat biopsies following a diagnosis of HGPIN. Further, discrete histologic subtypes of HGPIN with clinical implication in management have not been characterized. The TMPRSS2-ERG gene fusion that has recently been described in prostate cancer has also been shown to occur in a subset of HGPIN. This may have significant clinical implications given that TMPRSS2-ERG fusion prostate cancer is associated with a more aggressive clinical course. EXPERIMENTAL DESIGN: In this study, we assessed a series of HGPIN lesions and paired prostate cancer for the presence of TMPRSS2-ERG gene fusion. RESULTS: Fusion-positive HGPIN was observed in 16% of the 143 number of lesions, and in all instances, the matching cancer shared the same fusion pattern. Sixty percent of TMPRSS2-ERG fusion prostate cancer had fusion-negative HGPIN. CONCLUSIONS: Given the more aggressive nature of TMPRSS2-ERG prostate cancer, the findings of this study raise the possibility that gene fusion-positive HGPIN lesions are harbingers of more aggressive disease. To date, pathologic, molecular, and clinical variables do not help stratify which men with HGPIN are at increased risk for a cancer diagnosis. Our results suggest that the detection of isolated TMPRSS2-ERG fusion HGPIN would improve the positive predictive value of finding TMPRSS2-ERG fusion prostate cancer in subsequent biopsies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".