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. Issue 3 (29th April 2019)

• Record Type: Journal Article
• Authors: Schmidt, Julie A.; Fensom, Georgina K.; Rinaldi, Sabina; Scalbert, Augustin; Appleby, Paul N.; Achaintre, David; Gicquiau, Audrey; Gunter, Marc J.; Ferrari, Pietro; Kaaks, Rudolf; Kühn, Tilman; Boeing, Heiner; Trichopoulou, Antonia; Karakatsani, Anna; Peppa, Eleni; Palli, Domenico; Sieri, Sabina; Tumino, Rosario; Bueno‐de‐Mesquita, Bas; Agudo, Antonio; Sánchez, Maria‐Jose; Chirlaque, María‐Dolores; Ardanaz, Eva; Larrañaga, Nerea; Perez‐Cornago, Aurora; Assi, Nada; Riboli, Elio; Tsilidis, Konstantinos K.; Key, Timothy J.; Travis, Ruth C.
• Is Part Of: International journal of cancer. Volume 146:Issue 3(2020)
• Page Start: 720
• Page End: 730
• Publication Date: 2019-04-29
• Subjects: epidemiology -- metabolomics -- prostate cancer risk -- treelet transform; Cancer -- Periodicals; Cancer -- Prevention -- Periodicals; 616.994
• DOI: 10.1002/ijc.32314
• Languages: English
• ISSNs: 0020-7136

Abstract

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 (Absolute IDQ 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. Abstract : What's new? This prospective study is the largest investigation of metabolite profile and prostate cancer risk, to date. We found that patterns in plasma metabolite profile (characterized by higher concentrations of phosphatidylcholines and hydroxysphingomyelins; specific acylcarnitines, amino acids and a biogenic amine; and lysophosphatidylcholines, respectively) were associated with subsequent lower risk of more aggressive tumor subtypes and prostate cancer death. Moreover, the results suggest that metabolite profile may be relevant to the etiology of advanced stage disease.