Davis, John W.

The NCCN Guidelines for Prostate Cancer Early Detection provide recommendations for individuals with a prostate who opt to participate in an early detection program after receiving the appropriate counseling on the pros and cons. These NCCN Guidelines Insights provide a summary of recent updates to the NCCN Guidelines with regard to the testing protocol, use of multiparametric MRI, and management of negative biopsy results to optimize the detection of clinically significant prostate cancer and minimize the detection of indolent disease.

PURPOSE Pretreatment estimates of seminal vesicle invasion (SVI) are challenging and significantly influence the management of prostate cancer. We sought to improve current models to predict SVI through the development of an SVI prediction genomic signature. PATIENTS AND METHODS A total of 15,889 patients who underwent radical prostatectomy (RP) with available baseline clinical, pathology, and transcriptome data were retrieved from the GRID registry (ClinicalTrials.gov identifier: NCT02609269 ) and other retrospective cohorts. These data were divided into a training (n = 6,766), test (n = 3,363), and two validation (n = 5,062 and 698) cohorts. Multivariable logistic regression was performed to assess the predictive effect of the genomic SVI (gSVI) classifier in the presence of established nomograms (Partin Tables and Memorial Sloan Kettering Cancer Center [MSKCC]). RESULTS In the training cohort, univariable filtering identified 2,132 genes that were differentially expressed between RP tumors with and without SVI. Model parameters were tuned to maximize the area under the curve (AUC) in the testing cohort, resulting in a logistic generalized linear model with 581 genes. The gSVI model scores range from 0 to 1. In the first validation set, gSVI showed superior discrimination of patients with and without SVI at RP compared with other prognostic signatures trained to predict distant metastasis or clinical recurrence. Of the 698 patients in the second validation set, gSVI combined with the MSKCC nomogram had a superior AUC (0.86) compared with either nomogram individually (0.81). CONCLUSION The gSVI represents a novel and validated expression signature to predict the presence of SVI before treatment with surgery. This genomic tool adds discriminatory power to existing clinical predictive nomograms and may help with pretreatment counseling and decision making.

5078 Background: Strategies integrating androgen targeted and locoregional therapies are being increasingly used in PCa with regional spread, but are rarely curative. Angiogenesis inhibitors delay progression in castration resistant PCa and may synergize with ADT through endothelial cell apoptosis in hormone naïve patients (pts). We hypothesized that the frontline combination of ADT with the potent VEGF inhibitor Axi would improve PCa control relative to ADT alone and allow for meaningful time off systemic therapy after surgical consolidation. Methods: Pts with either clinically detected LN+ (TxN1M0 or TxNxM1a) or very high risk for LN PCa were treated with ADT for 2 mos and then randomized 2:1 to respectively add open label Axi (5 mg PO bid) vs. continue ADT alone for 4 mos until surgery. Those responding with PSA ≤5 ng/mL were offered prostatectomy and extended pelvic lymphadenectomy (RP). ADT +/- Axi was withheld postoperatively and PSA measured q3 mos until 1 y. Primary objective: proportion of pts progression free (FFP) 12 mos after RP, defined as PSA ≤1.0 ng/mL and no radiation or ADT, aiming to detect a 35% difference favoring ADT+Axi. Results: 72 pts completed accrual. We report on the 54 pts with LN+ disease: median age 62 y (range 42-76), pretreatment PSA 22.9 ng/mL (range 3.6 - 404.4), 38 N1 / 16 M1a. Table shows presurgical therapy outcomes. Path responses in the prostate were similar between arms, but in 5 ADT+Axi vs. 0 ADT LN+ pts there was no residual nodal disease. Testosterone recovery: 24/26 ADT+Axi and 9/9 ADT RP pts by 6 mos. 21/36 ADT+Axi and 15/18 ADT pts have failed; 1 y FFP estimates 48.0% (SE 8.6%) and 16.7% (SE 8.3%), respectively (p = 0.02). 1 y undetectable PSA 9 pts (6 ADT+Axi). No grade 4 toxicities or unexpected side-effects were observed. Conclusions: 1 year after RP, ADT+Axi resulted in proportionally greater number of LN+ PCa pts off treatment and progression free than ADT alone. Tissue analysis is evaluating predictors of benefit to further develop angiogenesis inhibition as part of combination strategies for hormone naïve PCa. Clinical trial information: NCT01409200. [Table: see text]

5000 Background: It is clinically challenging to integrate genomic classifier results that report a continuous numerical risk of recurrence into treatment decisions for prostate cancer (PCa). We aimed to develop a novel clinical-genomic risk system that can readily be incorporated into treatment guidelines for localized PCa. Methods: Four multi-center cohorts (n = 6928 men; 5937 prospective samples and 991 retrospective samples with long-term follow-up) were utilized to identify and validate our clinical-genomic risk system in radical prostatectomy (RP) samples and subsequently in pre-treatment biopsy samples. All patients’ FFPE tissue underwent microarray analysis, and the expression values for 22 prespecified biomarkers that constitute Decipher were extracted. Cumulative incidence curves were constructed to estimate metastasis risk. C-indices were calculated to compare NCCN and CAPRA score to our clinical-genomic system. Results: With a median follow-up of 8 years for men in our RP cohort, the 10-year distant metastasis rates for NCCN low, favorable-intermediate, unfavorable-intermediate, and high-risk were 7.8%, 9.4%, 40.1%, and 41.4%, respectively. Our 3-tier clinical-genomic risk groups had 10-year distant metastasis rates of 3.7%, 30.7%, and 57.7%, for low, intermediate, and high-risk, which were validated in our pre-treatment biopsy cohort with 10-year rate of distant metastasis of 0%, 30.3%, and 63.2%, respectively. C-indices for the clinical-genomic system (0.84, 95%CI 0.62-0.92) were significantly improved over NCCN (0.71, 95%CI 0.59-0.84) and CAPRA (0.71, 95%CI 0.60-0.81) score. A total of 33.4% of men would be reclassified by the clinical-genomic system, and specifically 17.1%, 41.3%, and 19.4% of men in NCCN low, intermediate and high risk groups would be reclassified by our new system. Conclusions: The use of a readily available genomic classifier in combination with clinicopathologic variables can generate a simple to use 3-tier clinical-genomic risk system that is highly prognostic for distant metastasis, is more accurate than clinical risk, and can be easily incorporated into NCCN guidelines to inform treatment decisions.

125 Background: Men with lymph node involvement (LNI) at prostatectomy (RP) are at high risk of dying from prostate cancer. However, survival following RP is highly variable, with some men apparently cured. Nomograms developed for men with LNI have been based on series where all or the vast majority of men received adjuvant treatment. Because administration of adjuvant treatment is not universal, even for LNI, we evaluated whether the Decipher genomic classifier (GC) can improve upon clinical models to predict metastasis within 5 years (MET5) and prostate cancer specific mortality within 10 years (PCSM10) in a cohort of LNI patients, the majority of whom did not receive adjuvant treatment. Methods: 141 patients from 4 institutions (Johns Hopkins, Mayo Clinic, Leuven, MD Anderson) had LNI at RP, had adequate tissue and clinical data for analysis of MET5, and 86 were analyzed for PCSM10. 43% of men received adjuvant therapy. RP tumor tissue was analyzed by Affymetrix Human Exon 1.0 ST GeneChip; the GC was calculated based on 22 genes in the previously trained and validated algorithm. Logistic regression evaluated whether the GC, dichotomized as high risk (GC score > 0.6) vs low-intermediate risk (≤0.6), improved prediction of MET5 and PCSM10 beyond that achieved with established clinical prognostic factors. Results: 62 men (43%) developed MET5, and 35 (41%) developed PCSM10. For both MET5 and PCSM10 CAPRA-S, number of positive lymph nodes, and age were significant; adjuvant therapy was not significant. GC was a significant independent strong prognostic factor when added to the clinical model for prediction of MET5, odds ratio = 4.04 (95% CI: 1.48, 11.02), p = 0.006, and prediction of PCSM10, odds ratio = 6.71 (95% CI: 2.01, 22.38), p = 0.002. Addition of GC to the clinical model improved the AUC from 0.77 to 0.79 for MET5, and from 0.65 to 0.74 for PCSM10. Conclusions: The Decipher GC significantly improves upon clinical variables to predict metastasis and prostate cancer specific mortality in men at high risk due to LNI. This is the first study to show a genomic classifier predicts outcomes in men with LNI; validation is needed to determine if Decipher can improve treatment decisions in men with LNI.