Typically has a poor prognosis, a substratification of high-risk patients based on the metastasis status at diagnosis was performed. The combined genotypes particularly had significant effects on PCSM in patients with distant metastasis (P for trend = 0.007; Figure 1 right), Ornipressin suggesting that these two polymorphisms might be independent predictors of clinical outcomes following ADT along with currently used prognostic factors in high-risk patients. CYP19A1 rs700519 was nominally associated with time to ACM in the univariate analysis (P = 0.050), and had a q value of 0.436 (Table 4). However, CYP19A1 rs700519 did not reach significance after adjusting for known predictors in the multivariate analysis, possibly due to the correlations of CYP19A1 rs700519 with clinical stage and time to PSA nadir (data not shown). We further used survival tree analysis to explored higher order SNP-SNP interactions among the SNPs that were associated with PCSM. The tree structure was first split by AKR1C3 rs12529, following by AR-CAG repeat length, and resulted in 3 terminal nodes with low-, medium-, and high-risk for PCSM (Figure 2A). When using low risk node 4 as the reference group (GG/GC genotypes of AKR1C3 rs12529 and AR-CAG repeat length ,21), the HR was 1.77 (95 CI, 0.96?.28, P = 0.069) for medium risk node 3, and 9.11 (95 CI, 2.47?3.6, P = 0.001) for high risk node1. The time to PCSM decreased as the increase in risk classification (log-rank P = 0.008, Figure 2B). After adjusting for known variables, the genetic interaction profile between AKR1C3 rs12529 and AR-CAG repeat length remained significant predictors for PCSM in patients 374913-63-0 receiving ADT (P for trend = 0.013).DiscussionWe have identified two genetic polymorphisms, rs12529 in AKR1C3 and CAG repeat in AR, retained their associations with PCSM after ADT while controlling for known prognostic factors, age at diagnosis, clinical stage, Gleason score, PSA level at ADT initiation, PSA nadir, and time to PSA nadir, suggesting that these host genetic factors add information above and beyond currently used predictors. Intriguingly, patients possessing a greater number of unfavorable alleles had a shorter survival following ADT. A critical step in the synthesis of AR ligands involves the conversion of androstenedione to testosterone, which is catalyzed by 17b-hydroxysteroid dehydrogenases type 3 (HSD17B3) and type 5, also called aldo-keto reductase (AKR) 1C3. HSD17B3 is the predominant enzyme in catalyzing testosterone formation in testis, but synthesis of active androgens proceeds via AKR1C3 in prostate [21]. Several studies indicate that AKR1C3 is over-Figure 1. The influence of the genetic loci of interest on PCSM. Kaplan-Meier curves of time to PCSM during ADT 23977191 for patients with 0, 1, or 2 unfavorable genotypes at the 2 genetic loci of interest in all patients (left), in patients without distant metastasis (middle), or in patients with distant metastasis (right). Numbers in parentheses indicate the number of patients. doi:10.1371/journal.pone.0054627.gBiomarkers Predict the Efficacy of ADTTable 3. Genotyping frequencies and the association of genotype with PCSM during ADT.P{Gene PolymorphismGenotype No. of patientsNo. of eventsEstimated mean (months)P*qHR (95 CI)AKR1CrsGG/GC CC ,21 21 22?3 .23 P-trend632 8 137 91 165{110 3 12 18 30137 43 143 131 1270.0.1.00 5.23 (1.60?7.1) 0.ARCAG repeats0.0.1.00 1.62 (0.77?.44) 1.80 (0.91?.56) 2.02 (1.04?.91) 1.22 (1.01?.48) 0.206 0.092 0.037 0.No. of unfavorable g.Typically has a poor prognosis, a substratification of high-risk patients based on the metastasis status at diagnosis was performed. The combined genotypes particularly had significant effects on PCSM in patients with distant metastasis (P for trend = 0.007; Figure 1 right), suggesting that these two polymorphisms might be independent predictors of clinical outcomes following ADT along with currently used prognostic factors in high-risk patients. CYP19A1 rs700519 was nominally associated with time to ACM in the univariate analysis (P = 0.050), and had a q value of 0.436 (Table 4). However, CYP19A1 rs700519 did not reach significance after adjusting for known predictors in the multivariate analysis, possibly due to the correlations of CYP19A1 rs700519 with clinical stage and time to PSA nadir (data not shown). We further used survival tree analysis to explored higher order SNP-SNP interactions among the SNPs that were associated with PCSM. The tree structure was first split by AKR1C3 rs12529, following by AR-CAG repeat length, and resulted in 3 terminal nodes with low-, medium-, and high-risk for PCSM (Figure 2A). When using low risk node 4 as the reference group (GG/GC genotypes of AKR1C3 rs12529 and AR-CAG repeat length ,21), the HR was 1.77 (95 CI, 0.96?.28, P = 0.069) for medium risk node 3, and 9.11 (95 CI, 2.47?3.6, P = 0.001) for high risk node1. The time to PCSM decreased as the increase in risk classification (log-rank P = 0.008, Figure 2B). After adjusting for known variables, the genetic interaction profile between AKR1C3 rs12529 and AR-CAG repeat length remained significant predictors for PCSM in patients receiving ADT (P for trend = 0.013).DiscussionWe have identified two genetic polymorphisms, rs12529 in AKR1C3 and CAG repeat in AR, retained their associations with PCSM after ADT while controlling for known prognostic factors, age at diagnosis, clinical stage, Gleason score, PSA level at ADT initiation, PSA nadir, and time to PSA nadir, suggesting that these host genetic factors add information above and beyond currently used predictors. Intriguingly, patients possessing a greater number of unfavorable alleles had a shorter survival following ADT. A critical step in the synthesis of AR ligands involves the conversion of androstenedione to testosterone, which is catalyzed by 17b-hydroxysteroid dehydrogenases type 3 (HSD17B3) and type 5, also called aldo-keto reductase (AKR) 1C3. HSD17B3 is the predominant enzyme in catalyzing testosterone formation in testis, but synthesis of active androgens proceeds via AKR1C3 in prostate [21]. Several studies indicate that AKR1C3 is over-Figure 1. The influence of the genetic loci of interest on PCSM. Kaplan-Meier curves of time to PCSM during ADT 23977191 for patients with 0, 1, or 2 unfavorable genotypes at the 2 genetic loci of interest in all patients (left), in patients without distant metastasis (middle), or in patients with distant metastasis (right). Numbers in parentheses indicate the number of patients. doi:10.1371/journal.pone.0054627.gBiomarkers Predict the Efficacy of ADTTable 3. Genotyping frequencies and the association of genotype with PCSM during ADT.P{Gene PolymorphismGenotype No. of patientsNo. of eventsEstimated mean (months)P*qHR (95 CI)AKR1CrsGG/GC CC ,21 21 22?3 .23 P-trend632 8 137 91 165{110 3 12 18 30137 43 143 131 1270.0.1.00 5.23 (1.60?7.1) 0.ARCAG repeats0.0.1.00 1.62 (0.77?.44) 1.80 (0.91?.56) 2.02 (1.04?.91) 1.22 (1.01?.48) 0.206 0.092 0.037 0.No. of unfavorable g.