The prognostic significance of combined ERG and androgen receptor expression in patients with prostate cancer managed by androgen deprivation therapy
Bibliographic record
Abstract
ERG and androgen receptor (AR) are known to function cooperatively in prostate cancer (PCa) progression. However, the prognostic value of combined ERG and AR expression and potential pathways are not well characterized. We assessed ERG and AR protein expression by immunohistochemistry in a cohort of 312 men with PCa diagnosed by transurethral resection of the prostate (TURP). Patients were divided into those with no prior hormonal treatment (designated as PCa/AdvPCa) vs. those with castrate-resistant PCa (CRPC) undergoing channel TURP to relieve obstructive symptoms. The expression status was correlated with various clinical-pathological parameters. The Swedish watchful-waiting cohort was used for validation and characterization of potential gene signatures associated with ERG and AR. Patients with combined ERG-positive/AR high expression profile demonstrated higher rates of PCa-specific mortality (PCSM) compared with patients with ERG-negative/AR low in patients with no prior treatment (n = 90, P = 0.032), but this was attenuated in the overall cohort which included the CRPC subgroup (n = 125, P = 0.096). The prognostic significance to PCSM was validated in the Swedish watchful waiting cohort in univariate (HR: 3.3; 95% CI: 1.9-5.6, P = 4.25E-5) and multivariate analysis (HR: 2; 95% CI: 0.97-4.1, P = 0.057), which included Gleason score. ERG/AR overexpression status characterized 152 genes signatures including WNT, PI3K/AKT and chemokine signaling pathways known to be deregulated in PCa. In conclusion, combined ERG/AR overexpression signifies a class of patients at highest-risk of PCSM with specific key genetic alteration likely responsible for disease progression. The prognostic value of combined ERG/AR overexpression and its associated genes should be further investigated as potential prognostic and therapeutic targets in prostate cancer progression.
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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".