TMPRSS2-ERG Fusion Prostate Cancer: An Early Molecular Event Associated With Invasion
Bibliographic record
Abstract
Prostate cancer (PCA) is one of the most prevalent cancers and a major leading cause of morbidity and mortality in the Western world. The TMPRSS2-ERG fusion was recently identified as a common recurrent chromosomal aberration in this malignancy. In our study, we interrogated a broad spectrum of benign, precursor, and malignant prostatic lesions to assess the TMPRSS2-ERG fusion status using a multicolor interphase fluorescence in situ hybridization assay. Samples from hospital-based cohorts consisted of 237 clinically localized PCA, 34 hormone naive metastases, 9 hormone refractory metastases, 26 high grade prostatic intraepithelial neoplasia lesions, 15 samples of benign prostatic hyperplasia, 38 of proliferative inflammatory atrophy, and 47 of benign prostatic tissue. The TMPRSS2-ERG fusion was present in 48.5% of clinically localized PCA, 30% of hormone naive metastases, 33% of hormone refractory metastases, and in 19% of high grade prostatic intraepithelial neoplasia lesions in intermingling to cancer foci. Almost all these fusion positive cases show a homogenous distribution of the fusion pattern. In contrast, none of the other samples harbored this genetic aberration. If we consider the high incidence of PCA and the high frequency of this gene fusion, TMPRSS2-ERG is the most common genetic aberration so far described in human malignancies. Furthermore, its clinical application as a biomarker and ancillary diagnostic test is promising given its high specificity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".