Published in:
01-08-2015 | Original Article – Clinical Oncology
Genome-wide detection of allelic genetic variation to predict biochemical recurrence after radical prostatectomy among prostate cancer patients using an exome SNP chip
Published in: Journal of Cancer Research and Clinical Oncology | Issue 8/2015
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Purposes
Genetic variations among prostate cancer patients who underwent radical prostatectomies were evaluated to predict biochemical recurrence, and used to develop a clinical-genetic model that combines data on clinicopathological factors of prostate cancer and individual genetic variations.
Materials and methods
We genotyped 242,186 SNPs on a custom HumanExome BeadChip v1.0 (Illuminam Inc.) from the blood DNA of 776 PCa patients who underwent radical prostatectomy. Genetic data were analyzed to calculate an odds ratio as an estimate of the relative risk of biochemical recurrence. And we compared accuracies from the multivariate model incorporating clinicopathological factors between included and excluded selected lead single nucleotide polymorphisms. Biochemical recurrence-free survival outcomes also analyzed using these genetic variations.
Results
Genetic array analysis indicated that eight single nucleotide polymorphisms (rs77080351, rs200944490, rs2071292, rs117237810, rs191118242, rs4965121, rs61742396, and rs6573513) were significant to predict biochemical recurrence after radical prostatectomy. When a multivariate model incorporating clinicopathological factors was devised to predict biochemical recurrence, the predictive accuracy of model was 85.1 %. By adding in two individual variations of single nucleotide polymorphisms in the multivariate model, the predictive accuracy increased to 87.7 % (P = 0.045). With three variations of single nucleotide polymorphisms, the predictive accuracy further improved to 89.0 % (P = 0.025). These genetic variations had a significantly decreased biochemical recurrence-free survival rate.
Conclusions
Based on exome array, the selected single nucleotide polymorphisms were predictors for biochemical recurrence. The addition of individualized genetic information effectively enhanced the predictive accuracy of biochemical recurrence among prostate cancer patients who underwent radical prostatectomy.