Existing epidemiological evidence regarding the potential role of (poly)phenol intake in prostate cancer (PCa) risk is scarce and, in the case of flavonoids, it has been suggested that their intake may increase PCa risk. We investigated the associations between the intake of the total and individual classes and subclasses of (poly)phenols and the risk of PCa, including clinically relevant subtypes. The European Prospective Investigation into Cancer and Nutrition (EPIC) cohort included 131,425 adult men from seven European countries. (Poly)phenol intake at baseline was assessed by combining validated center/country-specific dietary questionnaires and the Phenol-Explorer database. Multivariable-adjusted Cox proportional hazards models were used to estimate the hazard ratios (HR) and 95% confidence intervals (CI). In total, 6939 incident PCa cases (including 3501 low-grade and 710 high-grade, 2446 localized and 1268 advanced, and 914 fatal Pca cases) were identified during a mean follow-up of 14 years. No associations were observed between the total intake of (poly)phenols and the risk of PCa, either overall (HR_log2 = 0.99, 95% CI 0.94–1.04) or according to PCa subtype. Null associations were also found between all classes (phenolic acids, flavonoids, lignans, and stilbenes) and subclasses of (poly)phenol intake and the risk of PCa, overall and according to PCa subtype. The results of the current large prospective cohort study do not support any association between (poly)phenol intake and PCa incidence.

This study analyzed the correlations between the acute and habitual intake of dietary tyrosols, their main food sources, and 24 h urine excretions of tyrosol (Tyr) and hydroxytyrosol (OHTyr) in participants from the European Prospective Investigation into Cancer and Nutrition study (EPIC). Participants (n = 419) were healthy men and women aged from 34 to 73 years from 8 EPIC centers belonging to France, Italy, and Germany. Acute and habitual dietary data were collected using a standardized 24 h dietary recall software and validated country-specific dietary questionnaires, respectively. The intake of 13 dietary tyrosols was estimated using the Phenol-Explorer database. Excretions of Tyr and OHTyr in a single 24 h urine sample were analyzed using tandem mass spectrometry. Urinary excretions of Tyr, OHTyr, and their sum (Tyr + OHTyr) correlated more strongly with their corresponding acute (rho_partial~0.63) rather than habitual intakes (rho_partial~0.47). In addition, individual and combined urinary excretions of Tyr and OHTyr were weakly to moderately correlated with the acute and habitual intake of other individual tyrosol precursors (rho_partial = 0.10–0.44) and especially with major food sources, such as wine (rho_partial = 0.41–0.58), olive oil (rho_partial = 0.25–0.44), and beer (rho_partial = 0.14–0.23). Urinary Tyr + OHTyr excretions were similarly correlated with the acute intake of total tyrosols but differently correlated with food sources among countries. Based on these results, we conclude that 24 h urinary excretions of Tyr + OHTyr could be proposed as biomarkers of total tyrosol intake, preferably for acute intakes.

Background and Objective: Nutrimetabolomics may reveal novel insights into early metabolic alterations and the role of dietary exposures on prostate cancer (PCa) risk. We aimed to prospectively investigate the associations between plasma metabolite concentrations and PCa risk, including clinically relevant tumor subtypes. Methods: We used a targeted and large-scale metabolomics approach to analyze plasma samples of 851 matched PCa case–control pairs from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Associations between metabolite concentrations and PCa risk were estimated by multivariate conditional logistic regression analysis. False discovery rate (FDR) was used to control for multiple testing correction. Results: Thirty-one metabolites (predominately derivatives of food intake and microbial metabolism) were associated with overall PCa risk and its clinical subtypes (p < 0.05), but none of the associations exceeded the FDR threshold. The strongest positive and negative associations were for dimethylglycine (OR = 2.13; 95% CI 1.16–3.91) with advanced PCa risk (n = 157) and indole-3-lactic acid (OR = 0.28; 95% CI 0.09–0.87) with fatal PCa risk (n = 57), respectively; however, these associations did not survive correction for multiple testing. Conclusions: The results from the current nutrimetabolomics study suggest that apart from early metabolic deregulations, some biomarkers of food intake might be related to PCa risk, especially advanced and fatal PCa. Further independent and larger studies are needed to validate our results.

Polyphenols represent the largest and most diverse class of dietary antioxidants. Epidemiological evidence linking specific (poly)phenol classes, such as flavonoids and lignans, to breast cancer (BC) risk remains limited and largely inconclusive in prospective studies. The aim of this study is to examine the association between the intake of total (poly)phenols—and its classes and subclasses—and BC risk—overall and by subtypes (estrogen, progesterone, and human epidermal growth factor receptor 2 (HER2))—in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. The EPIC cohort includes 257,960 adult women from seven European countries. During a mean follow-up of 14 years, there were 10,722 incident overall BC cases. Associations were computed using Cox regression models adjusted for potential confounders. No significant associations were found between total (poly)phenol intake and overall BC risk (HR_{Q5 vs. Q1} = 1.02; 95% CI: 0.95–1.11). In addition, null associations were mostly found between classes and subclasses of (poly)phenols and BC subtypes. After stratifying by menopausal status, no significant associations were observed. In conclusion, this study found no evidence of associations between the intake of any class or subclass of (poly)phenols and BC risk in the European population.