Urine <i>TMPRSS2:ERG</i> Fusion Transcript Stratifies Prostate Cancer Risk in Men with Elevated Serum PSA
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Bibliographic record
Abstract
More than 1,000,000 men undergo prostate biopsy each year in the United States, most for "elevated" serum prostate-specific antigen (PSA). Given the lack of specificity and unclear mortality benefit of PSA testing, methods to individualize management of elevated PSA are needed. Greater than 50% of PSA-screened prostate cancers harbor fusions between the transmembrane protease, serine 2 (TMPRSS2) and v-ets erythroblastosis virus E26 oncogene homolog (avian) (ERG) genes. Here, we report a clinical-grade, transcription-mediated amplification assay to risk stratify and detect prostate cancer noninvasively in urine. The TMPRSS2:ERG fusion transcript was quantitatively measured in prospectively collected whole urine from 1312 men at multiple centers. Urine TMPRSS2:ERG was associated with indicators of clinically significant cancer at biopsy and prostatectomy, including tumor size, high Gleason score at prostatectomy, and upgrading of Gleason grade at prostatectomy. TMPRSS2:ERG, in combination with urine prostate cancer antigen 3 (PCA3), improved the performance of the multivariate Prostate Cancer Prevention Trial risk calculator in predicting cancer on biopsy. In the biopsy cohorts, men in the highest and lowest of three TMPRSS2:ERG+PCA3 score groups had markedly different rates of cancer, clinically significant cancer by Epstein criteria, and high-grade cancer on biopsy. Our results demonstrate that urine TMPRSS2:ERG, in combination with urine PCA3, enhances the utility of serum PSA for predicting prostate cancer risk and clinically relevant cancer on biopsy.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it