Impact of Oxidative Stress Biomarkers and Carboxymethyllysine (an Advanced Glycation End Product) on Prostate Cancer: A Prospective Study.

Clin Genitourin Cancer

Department of Environmental Health, Division of Epidemiology and Biostatistics, University of Cincinnati Medical Center, Cincinnati, OH; Cincinnati Cancer Center, Cincinnati, OH. Electronic address:

Published: October 2015

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Objective: Biomarkers of oxidative stress and advanced glycation end products (AGE) have been linked to the development of prostate cancer, but evidence from human studies is scarce or controversial.

Methods: We conducted a prospective nested case-control study among 48 men (24 prostate cancer cases and 24 controls) aged 48 to 76 years at baseline. The participants of our study were a part of the Fernald Community Cohort. Prostate cancer cases and controls were matched individually on age (± 3 years) with a 1:1 ratio. Biomarkers included urine F2-isoprostanes (markers of lipid oxidation), plasma fluorescent oxidation products (markers of global oxidation), and carboxymethyllysine (CML) (a major end-stage AGE).

Results: At baseline, cases had similar age, body mass index, proportion of family history of prostate cancer, history of benign prostatic hyperplasia, history of hypertension, history of diabetes, number of smokers, and plasma glucose levels compared with controls. Levels of plasma CML were significantly higher in cases than in controls (182 vs. 152 μg/mL, P < .05). In the conditional logistic regression model, an increase in CML equivalent to 1 standard deviation was associated with an increased risk of incident prostate cancer (relative risk, 1.79; 95% confidence interval, 1.00-3.21) and accounted for approximately 8% variance of prostate cancer liability. Urine F2-isoprostanes and plasma fluorescent oxidation products were not associated with prostate cancer incidence.

Conclusions: Higher levels of plasma CML were associated with increased risk of prostate cancer. This suggests a potential new pathway for prostate cancer prediction and treatment.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4564335PMC
http://dx.doi.org/10.1016/j.clgc.2015.04.004DOI Listing

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