Volume 72, Issue 1, Pages 22-31 (July 2017) Translating a Prognostic DNA Genomic Classifier into the Clinic: Retrospective Validation in 563 Localized Prostate Tumors  Emilie Lalonde, Rached Alkallas, Melvin Lee Kiang Chua, Michael Fraser, Syed Haider, Alice Meng, Junyan Zheng, Cindy Q. Yao, Valerie Picard, Michele Orain, Helène Hovington, Jure Murgic, Alejandro Berlin, Louis Lacombe, Alain Bergeron, Yves Fradet, Bernard Têtu, Johan Lindberg, Lars Egevad, Henrik Grönberg, Helen Ross-Adams, Alastair D. Lamb, Silvia Halim, Mark J. Dunning, David E. Neal, Melania Pintilie, Theodorus van der Kwast, Robert G. Bristow, Paul C. Boutros  European Urology  Volume 72, Issue 1, Pages 22-31 (July 2017) DOI: 10.1016/j.eururo.2016.10.013 Copyright © 2016 European Association of Urology Terms and Conditions

Fig. 1 Genomic classifier reduction and signature-estimated percent genome alteration. (A) The center panel illustrates the 31-locus genomic classifier in the training cohort. Patients (columns) are sorted according to biochemical recurrence (BCR) status, then by the number of copy number alterations (CNAs) in the 31 loci (rows). A univariate Cox proportional hazard model was fit to each feature in the training cohort only. The hazard ratio and Wald p value are displayed on the right. The red vertical line indicates p=0.05. The 31 loci are sorted according to hazard ratio. Clinical variables for patients are shown in the top covariate bar. (B) The Spearman correlation between signature-estimated percent genome alteration (PGA) using the reduced 31-locus and 100-locus genomic classifiers. Signature-estimated PGA is calculated by the fraction of genomic base pairs involved in a region of CNA when considering the 109 and 276 genes in the 31-locus and 100-locus genomic classifiers, respectively. (C) The Spearman correlation between global PGA and signature-estimated PGA using the reduced 31-locus genomic classifier. Signature-estimated PGA is calculated by the fraction of genomic base pairs involved in a region of CNA when considering the 109 genes in the 31-locus genomic classifier only. (D) The Spearman correlation between global PGA and signature-estimated PGA using the reduced 31-locus genomic classifier plus an additional 30 genes which were previously selected to maximize PGA estimation [12]. European Urology 2017 72, 22-31DOI: (10.1016/j.eururo.2016.10.013) Copyright © 2016 European Association of Urology Terms and Conditions

Fig. 2 Genomic and clinico-genomic classifier performance. Cox models are adjusted for clinical variables as in Supplementary Table 3. (A) The 100-locus and the 31-locus genomic classifiers effectively stratify patients from the combined-arrays cohort. (B) The 31-locus genomic classifier effectively predicts which patients from the Taylor cohort will develop metastasis. (C) The 31-locus clinico-genomic classifier effectively stratifies all patients from the combined-arrays cohort. (D) The 31-locus clinico-genomic classifier effectively predicts which patients from the Taylor cohort will develop metastasis. (E) The 31-locus clinico-genomic classifiers effectively stratifies low to intermediate risk patients from the combined-arrays cohort. (F) The 31-locus clinico-genomic classifiers effectively stratifies high risk patients from the combined-arrays cohort. HR=hazard ratio; RFR=relapse-free rate. European Urology 2017 72, 22-31DOI: (10.1016/j.eururo.2016.10.013) Copyright © 2016 European Association of Urology Terms and Conditions

Fig. 3 Clinical utility of the reduced 31-locus genomic classifier. (A) Receiver operator curve analysis for predicting biochemical recurrence (BCR) at 5 yr with the 31-locus genomic classifier, clinical model, and clinico-genomic model. The “31 loci+Gleason score/prostate-specific antigen/T-category” (“31 loci+GS/PSA/T”) model includes the continuous 31-locus risk score, diagnostic GS, clinical T-category, and pretreatment PSA. (B) Receiver operator curve analysis for predicting metastasis at 10 yr with the 31-locus genomic classifier, clinical model, and clinico-genomic model in the Taylor cohort. The “31 loci+GS/PSA/T” model includes the continuous 31-locus risk score, diagnostic GS, clinical T-category, and pretreatment PSA. (C) The net reclassification index (NRI) based on using the clinico-genomic model in comparison to the clinical model only for predicting BCR in the combined-Arrays cohort. (D) The NRI based on using the clinico-genomic model in comparison to the clinical model with GS/PSA/T only for predicting metastasis in the Taylor cohort. The overall NRI is indicated in the legend. AUC=area under the curve; CI=confidence interval; mets=metastasis. European Urology 2017 72, 22-31DOI: (10.1016/j.eururo.2016.10.013) Copyright © 2016 European Association of Urology Terms and Conditions

Fig. 4 Validation of reduced 31-locus genomic classifier in the Canadian Prostate Cancer Genome Network (CPC-GENE) cohort using the NanoString platform. (A) The Kaplan-Meir curves for the CPC-GENE cohort stratified by the reduced 31-locus+Gleason score/prostate-specific antigen/T-category (GS/PSA/T) clinico-genomic classifier. (B) Receiver operator curve analysis for predicting biochemical recurrence at 5 yr with the 31-locus genomic classifier, clinical model, and clinico-genomic model. The “31 loci+GS/PSA/T” model includes the continuous 31-locus risk score, diagnostic GS, clinical T-category, and pretreatment PSA. AUC=area under the curve; HR=hazard ratio; RFR=relapse-free rate. European Urology 2017 72, 22-31DOI: (10.1016/j.eururo.2016.10.013) Copyright © 2016 European Association of Urology Terms and Conditions