4.7 Article

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

Journal

INTERNATIONAL JOURNAL OF CANCER
Volume 146, Issue 3, Pages 720-730

Publisher

WILEY
DOI: 10.1002/ijc.32314

Keywords

epidemiology; metabolomics; prostate cancer risk; treelet transform

Categories

Funding

  1. Cancer Research UK [C8221/A19170, C570/A16491, 14136]
  2. World Cancer Research Fund (WCRF) [2014/1183]
  3. Medical Research Council [MR/M012190/1, 1000143]
  4. ISCIII Health Research Funds [RD12/0036/0018]
  5. Health Research Fund (FIS) [PI13/01162, PI13/00061]
  6. Regional Government of Andalucia
  7. Regional Government of Asturias
  8. Regional Government of Basque Country
  9. Regional Government of Murcia
  10. Regional Government of Navarra
  11. Statistics Netherlands
  12. Dutch ZON (Zorg Onderzoek Nederland)
  13. Dutch Prevention Funds
  14. LK Research Funds
  15. Netherlands Cancer Registry (NKR)
  16. Dutch Ministry of Public Health, Welfare and Sports (VWS)
  17. National Research Council
  18. Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy
  19. Hellenic Health Foundation
  20. Federal Ministry of Education and Research (BMBF)
  21. Deutsches Krebsforschungszentrum
  22. Deutsche Krebshilfe
  23. Federal Ministry of Education and Research
  24. German Cancer Research Center (DKFZ)
  25. German Cancer Aid
  26. European Commission (DG-SANCO)
  27. International Agency for Research on Cancer

Ask authors/readers for more resources

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 (OR 1SD = 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. 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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available