Background Metabolomics is a promising molecular tool to identify novel etiologic pathways leading to cancer. Using a targeted approach, we prospectively investigated the associations between metabolite concentrations in plasma and breast cancer risk. Methods A nested case-control study was established within the European Prospective Investigation into Cancer cohort, which included 1624 first primary incident invasive breast cancer cases (with known estrogen and progesterone receptor and HER2 status) and 1624 matched controls. Metabolites (n = 127, acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexose, sphingolipids) were measured by mass spectrometry in pre-diagnostic plasma samples and tested for associations with breast cancer incidence using multivariable conditional logistic regression. Results Among women not using hormones at baseline (n = 2248), and after control for multiple tests, concentrations of arginine (odds ratio [OR] per SD = 0.79, 95% confidence interval [CI] = 0.70–0.90), asparagine (OR = 0.83 (0.74–0.92)), and phosphatidylcholines (PCs) ae C36:3 (OR = 0.83 (0.76–0.90)), aa C36:3 (OR = 0.84 (0.77–0.93)), ae C34:2 (OR = 0.85 (0.78–0.94)), ae C36:2 (OR = 0.85 (0.78–0.88)), and ae C38:2 (OR = 0.84 (0.76–0.93)) were inversely associated with breast cancer risk, while the acylcarnitine C2 (OR = 1.23 (1.11–1.35)) was positively associated with disease risk. In the overall population, C2 (OR = 1.15 (1.06–1.24)) and PC ae C36:3 (OR = 0.88 (0.82–0.95)) were associated with risk of breast cancer, and these relationships did not differ by breast cancer subtype, age at diagnosis, fasting status, menopausal status, or adiposity. Conclusions These findings point to potentially novel pathways and biomarkers of breast cancer development. Results warrant replication in other epidemiological studies.

BackgroundLittle is known about how pre-diagnostic metabolites in blood relate to risk of prostate cancer. We aimed to investigate the prospective association between plasma metabolite concentrations and risk of prostate cancer overall, and by time to diagnosis and tumour characteristics, and risk of death from prostate cancer.MethodsIn a case-control study nested in the European Prospective Investigation into Cancer and Nutrition, pre-diagnostic plasma concentrations of 122 metabolites (including acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexose and sphingolipids) were measured using targeted mass spectrometry (AbsoluteIDQ p180 Kit) and compared between 1077 prostate cancer cases and 1077 matched controls. Risk of prostate cancer associated with metabolite concentrations was estimated by multi-variable conditional logistic regression, and multiple testing was accounted for by using a false discovery rate controlling procedure.ResultsSeven metabolite concentrations, i.e. acylcarnitine C18:1, amino acids citrulline and trans-4-hydroxyproline, glycerophospholipids PC aa C28:1, PC ae C30:0 and PC ae C30:2, and sphingolipid SM (OH) C14:1, were associated with prostate cancer (p < 0.05), but none of the associations were statistically significant after controlling for multiple testing. Citrulline was associated with a decreased risk of prostate cancer (odds ratio (OR1SD) = 0.73; 95% confidence interval (CI) 0.62–0.86; p trend = 0.0002) in the first 5 years of follow-up after taking multiple testing into account, but not after longer follow-up; results for other metabolites did not vary by time to diagnosis. After controlling for multiple testing, 12 glycerophospholipids were inversely associated with advanced stage disease, with risk reduction up to 46% per standard deviation increase in concentration (OR1SD = 0.54; 95% CI 0.40–0.72; p trend = 0.00004 for PC aa C40:3). Death from prostate cancer was associated with higher concentrations of acylcarnitine C3, amino acids methionine and trans-4-hydroxyproline, biogenic amine ADMA, hexose and sphingolipid SM (OH) C14:1 and lower concentration of glycerophospholipid PC aa C42:4.ConclusionsSeveral metabolites, i.e. C18:1, citrulline, trans-4-hydroxyproline, three glycerophospholipids and SM (OH) C14:1, might be related to prostate cancer. Analyses by time to diagnosis indicated that citrulline may be a marker of subclinical prostate cancer, while other metabolites might be related to aetiology. Several glycerophospholipids were inversely related to advanced stage disease. More prospective data are needed to confirm these associations.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-017-0885-6) contains supplementary material, which is available to authorized users.

Metabolomics may reveal novel insights into the etiology of prostate cancer, for which few risk factors are established. We investigated the association between patterns in baseline plasma metabolite profile and subsequent prostate cancer risk, using data from 3,057 matched case–control sets from the European Prospective Investigation into Cancer and Nutrition (EPIC). We measured 119 metabolite concentrations in plasma samples, collected on average 9.4 years before diagnosis, by mass spectrometry (AbsoluteIDQ p180 Kit, Biocrates Life Sciences AG). Metabolite patterns were identified using treelet transform, a statistical method for identification of groups of correlated metabolites. Associations of metabolite patterns with prostate cancer risk (OR1SD) were estimated by conditional logistic regression. Supplementary analyses were conducted for metabolite patterns derived using principal component analysis and for individual metabolites. Men with metabolite profiles characterized by higher concentrations of either phosphatidylcholines or hydroxysphingomyelins (OR1SD = 0.77, 95% confidence interval 0.66–0.89), acylcarnitines C18:1 and C18:2, glutamate, ornithine and taurine (OR1SD = 0.72, 0.57–0.90), or lysophosphatidylcholines (OR1SD = 0.81, 0.69–0.95) had lower risk of advanced stage prostate cancer at diagnosis, with no evidence of heterogeneity by follow‐up time. Similar associations were observed for the two former patterns with aggressive disease risk (the more aggressive subset of advanced stage), while the latter pattern was inversely related to risk of prostate cancer death (OR1SD = 0.77, 0.61–0.96). No associations were observed for prostate cancer overall or less aggressive tumor subtypes. In conclusion, metabolite patterns may be related to lower risk of more aggressive prostate tumors and prostate cancer death, and might be relevant to etiology of advanced stage prostate cancer.

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Plasma metabolites and colorectal cancer stage