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Purpose: Prostate cancer aggressiveness and appropriate therapy are routinely determined following biopsy sampling. Current clinical and pathologic parameters are insufficient for accurate risk prediction leading primarily to overtreatment and also missed opportunities for curative therapy.Experimental Design: An 8-biomarker proteomic assay for intact tissue biopsies predictive of prostate pathology was defined in a study of 381 patient biopsies with matched prostatectomy specimens. A second blinded study of 276 cases validated this assay's ability to distinguish “favorable” versus “nonfavorable” pathology independently and relative to current risk classification systems National Comprehensive Cancer Network (NCCN and D'Amico).Results: A favorable biomarker risk score of ≤0.33, and a nonfavorable risk score of >0.80 (possible range between 0 and 1) were defined on “false-negative” and “false-positive” rates of 10% and 5%, respectively. At a risk score ≤0.33, predictive values for favorable pathology in very low-risk and low-risk NCCN and low-risk D'Amico groups were 95%, 81.5%, and 87.2%, respectively, higher than for these current risk classification groups themselves (80.3%, 63.8%, and 70.6%, respectively). The predictive value for nonfavorable pathology was 76.9% at biomarker risk scores >0.8 across all risk groups. Increased biomarker risk scores correlated with decreased frequency of favorable cases across all risk groups. The validation study met its two coprimary endpoints, separating favorable from nonfavorable pathology (AUC, 0.68; P < 0.0001; OR, 20.9) and GS-6 versus non–GS-6 pathology (AUC, 0.65; P < 0.0001; OR, 12.95).Conclusions: The 8-biomarker assay provided individualized, independent prognostic information relative to current risk stratification systems, and may improve the precision of clinical decision making following prostate biopsy. Clin Cancer Res; 21(11); 2591–600. ©2015 AACR.

Supplementary Methods, Table S1, Figures S1-7. Methods for quantitative multiplex proteomics imaging (QMPI) Clinical studies: Statistical plan Table S1. Clinical Validation Study. Comparison of Predictive Value of the 8-Biomarker Assay for Favorable Pathology with D'Amico Risk Categories. Figure S1. Outline of all four quantitative multiplex immunofluorescence triplex assay formats Figure S2. Clinical validation study, full cohort (N=276): performance for "GS 6" pathology (surgical Gleason =3+3 and localized {less than or equal to}T3a). A) Sensitivity (P[risk score> threshold| "non-GS 6" pathology]) of the assay, as a function of medical decision level. Figure S3. Clinical validation study, full cohort (N=274): performance for prediction of favorable pathology (surgical Gleason {less than or equal to}3+4 and organ-confined {less than or equal to}T2). Figure S4. Clinical validation study, Subset of validation cohort that contained sufficient annotation for National Comprehensive Cancer Network (NCCN) and D'Amico categorization (N=256) Figure S5. Clinical validation study: performance for prediction of favorable pathology. Figure S6. Net Reclassification Index analysis illustrates how biomarker assay categories of favorable (risk score {less than or equal to}0·33) and non-favorable (risk score >0·8) may supplement NCCN Figure S7. Decision Curve Analysis provides another method for characterizing performance of different risk systems and at different cut points.