Androgen receptor activity in biopsy specimens at initial diagnosis of prostate cancer and correlation with outcomes and treatment response.
Bibliographic record
Abstract
409 Background: Androgen receptor activity (AR-A) has been described after radical prostatectomy (RP) and metastatic castration-sensitive prostate cancer (mCSPC). In RP specimens low AR-A is associated with basal subtypes, decreased DNA repair and increased immune activity. In mCSPC, low AR-A is associated with poor overall survival (OS) and time to progression to CRPC. However, AR-A has not been well characterized in localized disease at initial diagnosis. Here we sought to assess AR-A signatures in biopsy samples from patients across the prostate cancer risk continuum and assess correlations between AR-A and outcomes. Methods: We analyzed 150,162 biopsy samples tested (2016-2024) with the Decipher prostate genomic classifier (Veracyte, Inc. San Diego, CA). Transcriptome-wide expression data and clinical factors were retrieved from the Decipher GRID (NCT02609269). Patients with low and high AR-A expression as defined by Spratt et al 2019 were compared using Chi-square tests. Clinical and pathologic outcomes for specific cohorts in the overall sample population were analyzed using Cox regression. Results: Overall, 11,752 (7.8%) patients had low AR-A expression. 9.8% of patients > 70 years of age had low AR-A compared to 7.6% of patients <70 (p<0.0001). Low AR-A was enriched in samples with poor prognostic clinical factors such as very high Decipher (p<0.0001), Grade Group (GG) 5 (p<0.0001) and very high NCCN risk (p<0.0001). The same differences were present when looking only at patients with a PSA <4 ng/mL. Like in RP samples, AR-A expression in biopsy samples positively correlated with intact DNA repair and negatively correlated with basal subtypes, PORTOS and immune infiltration scores (all p<0.001). Low AR-A was prognostic of poor clinical outcomes across 4 independent retrospective cohorts. In cohort 1, intermediate risk disease (n=647), low AR-A correlated with adverse pathology at time of RP (p <0.05). In cohort 2, intermediate risk disease treated with radiation therapy (RT) (n=121), low AR-A correlated with biochemical failure (p<0.05). In cohort 3, high risk disease (n=405), low AR-A correlated with decreased OS (p<0.05) in all patients and metastasis (p<0.05) after RT and androgen deprivation therapy (ADT). Finally, in cohort 4, high risk disease treated with RT+ADT (n=100), low AR-A correlated with metastasis (p<0.01). Conclusions: Overall, in a large cohort of biopsy specimens, low AR-A was associated with increased age, very high Decipher score, very high NCCN risk, and GG5 disease. Subpopulation analyses suggest that low AR-A portends a poor prognosis. Given that patients with low AR-A had decreased DNA repair activity and increased PORTOS scores, clinicians should consider post-operative RT and novel clinical trials with PARP inhibitors for these patients.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".