Plasma metabolomic signatures associated with long-term breast cancer risk in the SU.VI.MAX prospective cohort.

Abstract : Background: Breast cancer is a major cause of death in occidental women. Mechanisms involved in its etiology remain misunderstood. Metabolomics is a powerful tool which may help elucidating novel biological pathways and identify new biomarkers in order to predict breast cancer well before symptoms appear. The aim of this project was to investigate whether untargeted metabolomic signatures from blood draws of healthy women could contribute to better understand and predict the long-term risk of developing breast cancer. Methods: A nested case-control study was conducted within the SU.VI.MAX prospective cohort (13 years of follow-up) to analyze baseline plasma samples of 211 incident breast cancer cases and one or two matched controls by case using LC-MS mass spectrometry and NMR. Multivariable conditional logistic regression models were computed. Results: Several metabolites were associated with breast cancer risk. Notably, we observed that lower plasma levels of O-succinyl-homoserine (microbial metabolite), lipoproteins, lipids, glycoproteins, acetone, glycerol-derived compounds and unsaturated lipids and higher plasma levels of valine/norvaline, glutamine/isoglutamine, lysine, arginine, creatine, creatinine, 5-aminovaleric acid, phenylalanine, tryptophan, γ-glutamyl-threonine, ATBC (acetyltributylcitrate – a plasticizer contaminant), 2-amino-cyanobutanoic acid (microbial metabolite), pregnene-triol sulfate, and glucose were associated with an increased risk of developing breast cancer during follow-up. Conclusions: Several pre-diagnostic plasmatic metabolites are strongly associated with long-term breast cancer risk. If confirmed in other independent cohort studies, these results could help to identify healthy women at higher risk of developing breast cancer in the subsequent decade and to propose a better understanding of the complex mechanisms involved in its etiology. We are studying the role of diet (a modifiable risk factor) on metabolism and breast cancer etiology using notably penalized regression methods (LASSO, Elastic Net) which could help to improve personalized prevention strategies.
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Contributor : Lucie Lécuyer <>
Submitted on : Thursday, August 1, 2019 - 2:53:11 PM
Last modification on : Saturday, August 3, 2019 - 1:37:07 AM


  • HAL Id : hal-02239018, version 1


M. Touvier, Lucie Lecuyer. Plasma metabolomic signatures associated with long-term breast cancer risk in the SU.VI.MAX prospective cohort.. 3rd edition of Cancer and Metabolism symposium, Apr 2019, Marseille, France. ⟨hal-02239018⟩



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