Association of PTEN protein loss with upgrading of prostate cancer from biopsy to radical prostatectomy.
Bibliographic record
Abstract
127 Background: Active surveillance is increasingly recommended for men with low-risk Gleason Score 3+3=6 (GS 6) prostate cancer. Yet, approximately one-third of patients with GS 6 cancer on biopsy are upgraded to higher GS at radical prostatectomy (RP). Previous studies have shown that clinical-pathologic parameters (age, prostate-specific antigen [PSA], prostate volume, extent of disease) are weak predictors of GS6 tumor upgrade. Our goal was to investigate the utility of PTEN as a molecular marker to predict upgrading in GS 6 biopsies. Methods: In a retrospective case-control study, 71 patients with GS 6 tumors on needle biopsy that were upgraded to GS 7 or higher cancer at RP (cases) were compared to 103 patients whose GS 6 tumors on needle biopsy were not upgraded at RP (controls). The most extensively involved needle core biopsy from each case was immunostained and scored for PTEN protein loss using a previously validated immunohistochemical (IHC) assay and binary scoring system. Confirmatory fluorescence in situ hybridization (FISH) was used to assess for PTEN gene deletion in biopsies with PTEN protein loss. The correlation of upgrading with PTEN loss and with clinical-pathologic variables was assessed by logistic regression. Results: Patients with upgraded cancers were older than controls (61.8 vs. 59.3 years), had higher mean pre-operative PSA levels (6.53 vs. 5.26 ng/mL), and a higher fraction of biopsy cores involved by tumor (0.42 vs, 0.36). However, of all pathologic variables, PTEN protein loss by IHC was most predictive of upgrading. Overall, PTEN protein loss was found in 18.3% (13 out of 71) of upgraded cases compared to 6.8% (7 out of 103) of controls (p=0.02). In the cases with PTEN protein loss, FISH confirmed homozygous PTEN deletion in 90% (9 out of 10) of upgraded tumors compared to 67% (4 out of 6) of interpretable not upgraded controls. On multivariate analyses, even after adjusting for age, preoperative PSA, clinical stage and race, GS 6 tumors with PTEN protein loss on biopsy were significantly more likely to be upgraded at RP compared to those without PTEN loss with odds ratio (OR) = 3.04 (1.08-8.55; p=0.035). Conclusions: In prostate needle biopsies, PTEN IHC may help distinguish men with low risk cancer from men with intermediate or higher risk cancers.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".