@misc{10481/64846,
year = {2017},
month = {1},
url = {http://hdl.handle.net/10481/64846},
abstract = {Purpose: Metabolomics is the comprehensive global study of metabolites in
biological samples. In this retrospective pilot study we explored whether serum
metabolomic profile can discriminate the presence of human breast cancer irrespective
of the cancer subtype.
Methods: Plasma samples were analyzed from healthy women (n = 20) and
patients with breast cancer after diagnosis (n = 91) using a liquid chromatographymass
spectrometry platform. Multivariate statistics and a Random Forest (RF) classifier
were used to create a metabolomics panel for the diagnosis of human breast cancer.
Results: Metabolomics correctly distinguished between breast cancer patients
and healthy control subjects. In the RF supervised class prediction analysis comparing
breast cancer and healthy control groups, RF accurately classified 100% both samples
of the breast cancer patients and healthy controls. So, the class error for both group
in and the out-of-bag error were 0. We also found 1269 metabolites with different
concentration in plasma from healthy controls and cancer patients; and basing on
exact mass, retention time and isotopic distribution we identified 35 metabolites.
These metabolites mostly support cell growth by providing energy and building
stones for the synthesis of essential biomolecules, and function as signal transduction
molecules. The collective results of RF, significance testing, and false discovery rate
analysis identified several metabolites that were strongly associated with breast
cancer.
Conclusions: In breast cancer a metabolomics signature of cancer exists and can
be detected in patient plasma irrespectively of the breast cancer type.},
organization = {Spanish Ministry of Economy and Competitiveness, Institute Carlos III (FIS grant) 	
PI14/00328},
organization = {Generalitat de Catalunya
	
2014SGR168},
organization = {FEDER funds from the European Union ('Una manera de hacer Europa')},
publisher = {Impact Journals},
keywords = {Breast cancer},
keywords = {Biomarker},
keywords = {Mass spectrometry},
keywords = {Metabolite},
keywords = {Metabolomics},
title = {A plasma metabolomic signature discloses human breast cancer},
doi = {10.18632/oncotarget.14521},
author = {Jové, Mariona and Quiles Morales, José Luis and Ramírez Tortosa, María Carmen and Ramírez Tortosa, César Luis},
}