Histologically benign PI‐RADS 4 and 5 lesions contain cancer‐associated epigenetic alterations
Bibliographic record
Abstract
BACKGROUND: The detection rate of clinically significant prostate cancer has improved with the use of multiparametric magnetic resonance imaging (mpMRI). Yet, even with MRI-guided biopsy 15%-35% of high-risk lesions (Prostate Imaging-Reporting and Data System [PI-RADS] 4 and 5) are histologically benign. It is unclear if these false positives are due to diagnostic/sampling errors or pathophysiological alterations. To better understand this, we tested histologically benign PI-RAD 4 and 5 lesions for common malignant epigenetic alterations. MATERIALS AND METHODS: MRI-guided in-bore biopsy samples were collected from 45 patients with PI-RADS 4 (n = 31) or 5 (n = 14) lesions. Patients had a median clinical follow-up of 3.8 years. High-risk mpMRI patients were grouped based on their histology into biopsy positive for tumor (BPT; n = 28) or biopsy negative for tumor (BNT; n = 17). From these biopsy samples, DNA methylation of well-known tumor suppressor genes (APC, GSTP1, and RARβ2) was quantified. RESULTS: Similar to previous work we observed high rates of promoter methylation at GSTP1 (92.7%), RARβ2 (57.3%), and APC (37.8%) in malignant BPT samples but no methylation in benign TURP chips. Interestingly, similar to the malignant samples the BNT biopsies also had increased methylation at the promoter of GSTP1 (78.8%) and RARβ2 (34.6%). However, despite these epigenetic alterations none of these BNT patients developed prostate cancer, and those who underwent repeat mpMRI (n = 8) demonstrated either radiological regression or stability. CONCLUSIONS: Histologically benign PI-RADS 4 and 5 lesions harbor prostate cancer-associated epigenetic alterations.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".