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Updated: Apr 11, 2026
Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
Tissue-based Genomics Augments Post-prostatectomy Risk Stratification in a Natural History Cohort of Intermediate-
Ashley E Ross1, Michael H Johnson2, Kasra Yousefi3
1James Buchanan Brady Urological Institute, Johns Hopkins Hospital, Baltimore, MD, USA; Department of Pathology, Johns Hopkins Hospital, Baltimore, MD, USA; Department of Oncology, Johns Hopkins Hospital, Baltimore, MD, USA.
The Decipher test accurately predicts metastatic progression in prostate cancer patients after radical prostatectomy. Higher Decipher scores correlate with increased risk, improving prognostic models for better patient identification.
Area of Science:
- Oncology
- Genomics
- Prognostic Biomarkers
Background:
- Radical prostatectomy (RP) is a key treatment for intermediate/high-risk prostate cancer.
- Men undergoing RP face risks of recurrence and metastasis.
- The Decipher test has shown promise in predicting metastasis in treated cohorts.
Purpose of the Study:
- To assess the Decipher genomic classifier's predictive value in a natural history cohort.
- To evaluate Decipher in men who received no treatment until metastasis.
Main Methods:
- Retrospective case-cohort study of 356 men post-RP (1992-2010) with intermediate/high-risk features.
- Inclusion criteria: CAPRA-S score ≥3, Gleason score ≥7, PSA nadir <0.2 ng/ml.
- Primary endpoint: metastasis; analysis included ROC curves, decision curve analysis, and Cox models.
Main Results:
- Decipher scores were obtained for 260 patients; 99 experienced metastasis.
- Higher Decipher scores correlated with increased metastasis and mortality (p<0.01).
- Decipher improved risk model discrimination (c-index to 0.86-0.87) and independently predicted metastasis.
Conclusions:
- In untreated men post-RP, Decipher scores correlate with clinical events.
- Incorporating Decipher enhances the prognostic accuracy of existing risk models.
- The findings confirm Decipher's utility in identifying patients at high risk of metastasis.
