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Purpose: Genetic variations among prostate cancer (PCa) patients who underwent radical prostatectomy (RP) and pelvic lymphnode dissection were evaluated to predict lymph node invasion (LNI). Exome arrays were used to develop a clinicogenetic modelthat combined clinical data related to PCa and individual genetic variations. Materials and Methods: We genotyped 242,186 single-nucleotide polymorphisms (SNPs) by using a custom HumanExome Bead-Chip v1.0 (Illumina Inc.) from the blood DNA of 341 patients with PCa. The genetic data were analyzed to calculate an odds ratio asan estimate of the relative risk of LNI. We compared the accuracies of the multivariate logistic model incorporating clinical factorsbetween the included and excluded selected SNPs. The Cox proportional hazard models with or without genetic factors for predictingbiochemical recurrence (BCR) were analyzed. Results: The genetic analysis indicated that five SNPs (rs75444444, rs8055236, rs2301277, rs9300039, and rs6908581) were significantfor predicting LNI in patients with PCa. When a multivariate model incorporating clinical factors was devised to predict LNI,the predictive accuracy of the multivariate model was 80.7%. By adding genetic factors in the aforementioned multivariate model,the predictive accuracy increased to 93.2% (p=0.006). These genetic variations were significant factors for predicting BCR after adjustmentfor other variables and after adding the predictive gain to BCR. Conclusions: Based on the results of the exome array, the selected SNPs were predictors for LNI. The addition of individualized geneticinformation effectively enhanced the predictive accuracy of LNI and BCR among patients with PCa who underwent RP.

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