Patterns in metabolite profile are associated with risk of more aggressive prostate cancer: A prospective study of 3,057 matched case–control sets from EPIC

Abstract

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.

Identification of metabolites associated with prostate cancer risk: a nested case-control study with long follow-up in the Northern Sweden Health and Disease Study

“…The positive association between LPC C18:0 and risk of overall prostate cancer (Table 3) in the present study was not observed in any of the EPIC-multicentre studies (ORs close to one) [13,15]. In the EPIC-Heidelberg study, an inverse association between LPC C18:0 and overall prostate cancer risk (p < 0.05) was observed, but the association was no longer significant after correction for multiple testing or adjusting for confounding factors in that case-cohort study [10].…”

“…Seven previous studies have investigated the association between metabolite levels and the risk of prostate cancer incidence in prospectively collected human blood samples [9][10][11][12][13][14][15]. Three of these studies were nested within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (ATBC) [11,12,14]; one within the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO) [9]; one within the European Prospective Investigation into Cancer and Nutrition study (EPIC) in Heidelberg [10]; and two within the EPIC-multicentre cohort (Germany, Greece, Italy, the Netherlands, Spain and the UK) [13,15]. The ABTC and PLCO studies used untargeted metabolomics to non-quantitatively measure many metabolites, many not targeted in the present study.…”

“…A number of studies have shown altered metabolic regulation in relation to the development [9][10][11][12][13][14][15] and progression [46] of prostate cancer. It would be of great interest to acquire insights into the genes involved in controlling these metabolic alterations.…”

“…To the best of our knowledge, seven previous studies, conducted within three cohorts, have investigated the association between pre-diagnostic levels of plasma and serum metabolites and the risk of prostate cancer incidence [9][10][11][12][13][14][15]. The results of these studies differ somewhat as regards metabolites associated with disease risk.…”

Resolving Metabolic Heterogeneity in Experimental Models of the Tumor Microenvironment from a Stable Isotope Resolved Metabolomics Perspective

“…Metabolic profiling of tissues and biofluids including blood plasma [80][81][82][83], urine [84][85][86], and cerebrospinal fluid (CSF) [86][87][88][89] using NMR and MS in the past decade has been shown to be very valuable for reporting disease states and drug responses. This is due to metabolic reprogramming in • C/5% CO 2 before fixing in 4% buffered formalin, embedded in paraffin block, and sectioned into 4 µm slices for H&E staining in (A) and IF staining for cancer cells (panCytokeratin or panCK), CD8 (cytotoxic T cells), and CD68 (Mφ) in (B).…”