Table 2 shows the patient demographic data pertaining to age, cancer status, GS and benign classification for the samples analyzed in this study. The Prostate Cancer Biomarker Panel, (biomarkers FLNA, FLNB, Age and PSA) improved the classification of prediction of prostate cancer over PSA alone (AUC=0.64, [0.59, 0.69], vs 0.58) (Figure 1A). The predictive algorithm was set to have a cutoff=0.45, which is based on the regression model achieving sensitivity equivalent to PSA=4 ng/ml. The distribution of predicted probabilities for patients with and without PrCa are shown in Figure 2A. This evidence concerns the gene KLK3 and Familial prostate cancer.