Ørntoft, Torben F.

Abstract Background: Genome-wide association studies have identified multiple genetic variants associated with prostate cancer risk which explain a substantial proportion of familial relative risk. These variants can be used to stratify individuals by their risk of prostate cancer. Methods: We genotyped 25 prostate cancer susceptibility loci in 40,414 individuals and derived a polygenic risk score (PRS). We estimated empirical odds ratios (OR) for prostate cancer associated with different risk strata defined by PRS and derived age-specific absolute risks of developing prostate cancer by PRS stratum and family history. Results: The prostate cancer risk for men in the top 1% of the PRS distribution was 30.6 (95% CI, 16.4–57.3) fold compared with men in the bottom 1%, and 4.2 (95% CI, 3.2–5.5) fold compared with the median risk. The absolute risk of prostate cancer by age of 85 years was 65.8% for a man with family history in the top 1% of the PRS distribution, compared with 3.7% for a man in the bottom 1%. The PRS was only weakly correlated with serum PSA level (correlation = 0.09). Conclusions: Risk profiling can identify men at substantially increased or reduced risk of prostate cancer. The effect size, measured by OR per unit PRS, was higher in men at younger ages and in men with family history of prostate cancer. Incorporating additional newly identified loci into a PRS should improve the predictive value of risk profiles. Impact: We demonstrate that the risk profiling based on SNPs can identify men at substantially increased or reduced risk that could have useful implications for targeted prevention and screening programs. Cancer Epidemiol Biomarkers Prev; 24(7); 1121–9. ©2015 AACR.

Abstract Background: Because of the faltering sensitivity and/or specificity, urine-based assays currently have a limited role in the management of patients with bladder cancer. The aim of this study was to externally validate our previously reported protein biomarker panel from multiple sites in the United States and Europe. Methods: This multicenter external validation study included a total of 320 subjects (bladder cancer = 183). The 10 biomarkers (IL8, MMP9, MMP10, SERPINA1, VEGFA, ANG, CA9, APOE, SDC1, and SERPINE1) were measured using commercial ELISA assays in an external laboratory. The diagnostic performance of the biomarker panel was assessed using receiver operator curves (ROC) and descriptive statistical values. Results: Utilizing the combination of all 10 biomarkers, the area under the ROC for the diagnostic panel was noted to be 0.847 (95% confidence interval, 0.796–0.899), outperforming any single biomarker. The multiplex assay at optimal cutoff value achieved an overall sensitivity of 0.79, specificity of 0.79, positive prediction value of 0.73, and negative prediction value of 0.84 for bladder cancer classification. Sensitivity values of the diagnostic panel for high-grade bladder cancer, low-grade bladder cancer, muscle invasive bladder cancer, and non-muscle invasive bladder cancer were 0.81, 0.90, 0.95, and 0.77, respectively. Conclusions: Urinary levels of the biomarker panel enabled discrimination of patients with bladder cancer and controls, and the levels of biomarker subsets were associated with advancing tumor grade and stage. Impact: If proven to be reliable, urinary diagnostic biomarker assays can detect bladder cancer in a timely manner such that the patient can expect improvements in overall survival and quality of life. Cancer Epidemiol Biomarkers Prev; 23(9); 1804–12. ©2014 AACR.