Purpose It is clinically challenging to integrate genomic-classifier results that report a numeric risk of recurrence into treatment recommendations for localized prostate cancer, which are founded in the framework of risk groups. We aimed to develop a novel clinical-genomic risk grouping system that can readily be incorporated into treatment guidelines for localized prostate cancer. Materials and Methods Two multicenter cohorts (n = 991) were used for training and validation of the clinical-genomic risk groups, and two additional cohorts (n = 5,937) were used for reclassification analyses. Competing risks analysis was used to estimate the risk of distant metastasis. Time-dependent c-indices were constructed to compare clinicopathologic risk models with the clinical-genomic risk groups. Results With a median follow-up of 8 years for patients in the training cohort, 10-year distant metastasis rates for National Comprehensive Cancer Network (NCCN) low, favorable-intermediate, unfavorable-intermediate, and high-risk were 7.3%, 9.2%, 38.0%, and 39.5%, respectively. In contrast, the three-tier clinical-genomic risk groups had 10-year distant metastasis rates of 3.5%, 29.4%, and 54.6%, for low-, intermediate-, and high-risk, respectively, which were consistent in the validation cohort (0%, 25.9%, and 55.2%, respectively). C-indices for the clinical-genomic risk grouping system (0.84; 95% CI, 0.61 to 0.93) were improved over NCCN (0.73; 95% CI, 0.60 to 0.86) and Cancer of the Prostate Risk Assessment (0.74; 95% CI, 0.65 to 0.84), and 30% of patients using NCCN low/intermediate/high would be reclassified by the new three-tier system and 67% of patients would be reclassified from NCCN six-tier (very-low- to very-high-risk) by the new six-tier system. Conclusion A commercially available genomic classifier in combination with standard clinicopathologic variables can generate a simple-to-use clinical-genomic risk grouping that more accurately identifies patients at low, intermediate, and high risk for metastasis and can be easily incorporated into current guidelines to better risk-stratify patients.

BACKGROUNDPatients with prostate cancer and their providers face uncertainty as they consider adjuvant radiotherapy (ART) or salvage radiotherapy (SRT) after undergoing radical prostatectomy. The authors prospectively evaluated the impact of the Decipher test, which predicts metastasis risk after radical prostatectomy, on decision making for ART and SRT.METHODSA total of 150 patients who were considering ART and 115 who were considering SRT were enrolled. Providers submitted a management recommendation before processing the Decipher test and again at the time of receipt of the test results. Patients completed validated surveys on prostate cancer (PCa)‐specific decisional effectiveness and PCa‐related anxiety.RESULTSBefore the Decipher test, observation was recommended for 89% of patients considering ART and 58% of patients considering SRT. After Decipher testing, 18% (95% confidence interval [95% CI], 12%‐25%) of treatment recommendations changed in the ART arm, including 31% among high‐risk patients; and 32% (95% CI, 24%‐42%) of management recommendations changed in the salvage arm, including 56% among high‐risk patients. Decisional Conflict Scale (DCS) scores were better after viewing Decipher test results (ART arm: median DCS before Decipher, 25 and after Decipher, 19 [P<.001]; SRT arm: median DCS before Decipher, 27 and after Decipher, 23 [P<.001]). PCa‐specific anxiety changed after Decipher testing; fear of PCa disease recurrence in the ART arm (P = .02) and PCa‐specific anxiety in the SRT arm (P = .05) decreased significantly among low‐risk patients. Decipher results reported per 5% increase in 5‐year metastasis probability were associated with the decision to pursue ART (odds ratio, 1.48; 95% CI, 1.19‐1.85) and SRT (odds ratio, 1.41; 95% CI, 1.09‐1.81) in multivariable logistic regression analysis.CONCLUSIONSKnowledge of Decipher test results was associated with treatment decision making and improved decisional effectiveness among men with PCa who were considering ART and SRT. Cancer 2017;123:2850–59. © 2017 American Cancer Society.

Despite documented oncologic benefit, use of postoperative adjuvant radiotherapy (aRT) in patients with prostate cancer is still limited in the United States. We aimed to develop and internally validate a risk-stratification tool incorporating the Decipher score, along with routinely available clinicopathologic features, to identify patients who would benefit the most from aRT. Patient and MethodsOur cohort included 512 patients with prostate cancer treated with radical prostatectomy at one of four US academic centers between 1990 and 2010. All patients had $ pT3a disease, positive surgical margins, and/or pathologic lymph node invasion. Multivariable Cox regression analysis tested the relationship between available predictors (including Decipher score) and clinical recurrence (CR), which were then used to develop a novel risk-stratification tool. Our study adhered to the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis guidelines for development of prognostic models. ResultsOverall, 21.9% of patients received aRT. Median follow-up in censored patients was 8.3 years. The 10-year CR rate was 4.9% vs. 17.4% in patients treated with aRT versus initial observation (P , .001). Pathologic T3b/T4 stage, Gleason score 8-10, lymph node invasion, and Decipher score . 0.6 were independent predictors of CR (all P , .01). The cumulative number of risk factors was 0, 1, 2, and 3 to 4 in 46.5%, 28.9%, 17.2%, and 7.4% of patients, respectively. aRT was associated with decreased CR rate in patients with two or more risk factors (10-year CR rate 10.1% in aRT v 42.1% in initial observation; P = .012), but not in those with fewer than two risk factors (P = .18). ConclusionUsing the new model to indicate aRT might reduce overtreatment, decrease unnecessary adverse effects, and reduce risk of CR in the subset of patients (approximately 25% of all patients with aggressive pathologic disease in our cohort) who benefit from this therapy.

BackgroundProstate cancer antigen 3 (PCA3) is a prostate cancer diagnostic biomarker that has been clinically validated. The limitations of the diagnostic role of PCA3 in initial biopsy and the prognostic role are not well established. Here, we elucidate the limitations of tissue PCA3 to predict high grade tumors in initial biopsy.ResultsPCA3 has a bimodal distribution in both biopsy and radical prostatectomy (RP) tissues, where low PCA3 expression was significantly associated with high grade disease (p<0.001). PCA3 had a poor performance of predicting high grade disease in initial biopsy (GS≥8) with 55% sensitivity and high false negative rates; 42% of high Gleason (≥8) samples had low PCA3. In RP, low PCA3 is associated with adverse pathological features, clinical recurrence outcome and greater probability of metastatic progression (p<0.001).Materials and MethodsA total of 1,694 expression profiles from biopsy and 10,382 from RP patients with high risk tumors were obtained from the Decipher Genomic Resource Information Database (GRIDTM)prostate cancer database. The primary clinical endpoint was distant metastasis-free survival for RP and high Gleason grade for biopsy. Logistic regression analyses and Cox proportional hazards models were used to evaluate the association of PCA3 with clinical variables and risk of metastasis.ConclusionsThere is high prevalence of high grade tumors with low PCA3 expression in the biopsy setting. Therefore, urologists should be warned that using PCA3 as stand-alone test may lead to high rate of under-diagnosis of high grade disease in initial biopsy setting.

Background:Currently, there are multiple commercially available RNA-based biomarkers that are Medicare approved and suggested for use by the National Comprehensive Cancer Network guidelines. There is uncertainty as to which patients benefit from genomic testing and for whom these tests should be ordered. Here, we examined the correlation patterns of Decipher assay to understand the relationship between the Decipher and patient tumor characteristics.Methods:De-identified Decipher test results (including Decipher risk scores and clinicopathologic data) from 2 342 consecutive radical prostatectomy (RP) patients tested between January and September 2015 were analyzed. For clinical testing, tumor specimen from the highest Gleason grade was sampled using a 1.5 mm tissue punch. Decipher scores were calculated based on a previously locked model. Correlations between Decipher score and clinicopathologic variables were computed using Spearman's rank correlation. Mixed-effect linear models were used to study the association of practice type and Decipher score. The significance level was 0.05 for all tests.Results:Decipher score had a positive correlation with pathologic Gleason score (PGS; r=0.37, 95% confidence interval (CI) 0.34−0.41), pathologic T-stage (r=0.31, 95% CI 0.28−0.35), CAPRA-S (r=0.32, 95% CI 0.28−0.37) and patient age (r=0.09, 95% CI 0.05-0.13). Decipher reclassified 52%, 76% and 40% of patients in CAPRA-S low-, intermediate- and high-risk groups, respectively. We detected a 28% incidence of high-risk disease through the Decipher score in pT2 patients and 7% low risk in pT3b/pT4, PGS 8−10 patients. There was no significant difference in the Decipher score between patients from community centers and those from academic centers (P=0.82).Conclusions:Although Decipher correlated with baseline tumor characteristics for over 2 000 patients, there was significant reclassification of tumor aggressiveness as compared to clinical parameters alone. Utilization of the Decipher genomic classifier can have major implications in assessment of postoperative risk that may impact physician-patient decision making and ultimately patient management.

Using a robust and validated prognostic signature we found that a small but not insignificant proportion of histological Gleason 6 tumors harbored molecular characteristics of aggressive cancer. Molecular profiling of such tumors at diagnosis may better select patients for active surveillance at diagnosis and trigger appropriate intervention during followup.

38 Background: The Androgen-receptor (AR) signaling plays a pivotal role in prostate cancer initiation and progression. AR amplification and overexpression have been associated with lethal PCa and CRPC; however, much of the impact of these events on cancer progression is poorly understood with an unclear prognostic significance of down-stream targets of AR. Methods: A total of 2,555 RP expression profiles were extracted from the Decipher GRID database; 262 of which were from retrospective natural history cohort with known metastasic outcomes and the remaining from anonymized prospective cases with basic demographic and pathological data available. We built a 9 gene AR-output signature (ARoS) score based on canonical androgen regulated genes to represent AR-output activity in RP tissues. The 9 genes were weighted based on their distribution skewness in the prospective data (n = 2,293) and then scores were calculating by summing the weighted expression of the 9 genes. Results: AR expression and ARoS score were not strongly correlated with approximately 50% of samples with low ARoS have relatively high AR expression. In a prospective cohort of 2,293 patients, low ARoS was associated with higher Decipher metastasis risk scores (OR: 3.1, p < 0.001), higher Gleason grade (OR: 2.4, p < 0.001), ERG-fusion negative (OR: 1.8, p < 0.001) and SVI (OR: 2.1, p < 0.001). Additionally, low ARoS was associated with higher expression of neuroendocrine biomarkers (NCAM1, ENO2). In a large retrospective cohort with long term clinical follow-up, patients with low ARoS score had a higher probability of 10-year metastasis rate (p = 0.002). In 55 patients from this cohort who received ADT post metastasis, the ARoS signature derived from primary tissue was lower in patients who developed CRPC (p < 0.001). Furthermore, ARoS was significantly lower in mCRPC samples (p < 0.001) compared to primary PCa tissues. Conclusions: ARoS derived from primary prostate cancer tissue is correlated with metastatic outcomes and progression to CRPC. With further validation, such a signature may better predict those patients which require early intensification of systemic therapy.

OBJECTIVES To determine the prognostic potential of Sig24 for identifying prostate cancer patients at risk of developing metastases or experiencing PCSM following radical prostatectomy. SUBJECTS AND METHODS Sig24 scores were calculated from previously collected gene expression microarray data from the Cleveland Clinic and Mayo Clinic (I and II). The performance of Sig24 was determined using time-dependent c-index analysis, Cox proportional hazards regression and Kaplan-Meier survival analysis. RESULTS Higher Sig24 scores were significantly associated with higher pathologic Gleason scores (GS) in all three cohorts. Analysis of the Mayo Clinic II cohort, which included time to event information, indicated that patients with high Sig24 scores also had an increased risk of developing metastasis (HR: 3.78, 95% CI: 1.96–7.29, p < 0.001) or experiencing PCSM (HR: 6.54, 95% CI: 2.16–19.83, p < 0.001). CONCLUSIONS The findings of this study demonstrate the applicability of Sig24 for the prognosis of metastasis or PCSM following radical prostatectomy. Future studies investigating the combination of Sig24 with available prognostic tests may provide new approaches to improve risk stratification for patients with prostate cancer.