Metabolome analysis has emerged as a powerful technique for detecting and define specific physio-pathological phenotypes. In this investigation the diagnostic potential of metabolomics has been applied to better characterize the multiple biochemical alterations that concur in the definition of the frailty phenotype observed in elderly breast cancer patients. The study included 89 women with breast cancer (range 70-97 years) classified as Fit (n=49), Unfit (n=23), or Frail (n=17) according to comprehensive geriatric assessment. The serum metabolomic profile was performed by tandem mass spectrometry and included different classes of metabolites such as amino acids, acylcarnitines, sphingo-, and glycerol-phospolipids. ANOVA was applied to identify the metabolites differing significantly among Fit, Unfit, and Frail patients. In patients carrying the frail phenotype, the amino acid perturbations involve serine, tryptophan, hydroxyproline, histidine, its derivate 3-methyl-hystidine, cystine, and β-aminoisobutyric acid. With regard to lipid metabolism, the frailty phenotype was characterized by a decrease of a wide number of glycerol- and sphingo-phospholipid metabolites. These metabolomics biomarkers may give a further insight into the biochemical processes involved in the development of frailty in breast cancer patients. Moreover, they might be useful to refine the comprehensive geriatric assessment model. J. Cell. Physiol. 229: 898-902, 2014. © 2013 Wiley Periodicals, Inc.
Metabolomics biomarkers of frailty in elderly breast cancer patients
RIZZOLIO, Flavio;
2014-01-01
Abstract
Metabolome analysis has emerged as a powerful technique for detecting and define specific physio-pathological phenotypes. In this investigation the diagnostic potential of metabolomics has been applied to better characterize the multiple biochemical alterations that concur in the definition of the frailty phenotype observed in elderly breast cancer patients. The study included 89 women with breast cancer (range 70-97 years) classified as Fit (n=49), Unfit (n=23), or Frail (n=17) according to comprehensive geriatric assessment. The serum metabolomic profile was performed by tandem mass spectrometry and included different classes of metabolites such as amino acids, acylcarnitines, sphingo-, and glycerol-phospolipids. ANOVA was applied to identify the metabolites differing significantly among Fit, Unfit, and Frail patients. In patients carrying the frail phenotype, the amino acid perturbations involve serine, tryptophan, hydroxyproline, histidine, its derivate 3-methyl-hystidine, cystine, and β-aminoisobutyric acid. With regard to lipid metabolism, the frailty phenotype was characterized by a decrease of a wide number of glycerol- and sphingo-phospholipid metabolites. These metabolomics biomarkers may give a further insight into the biochemical processes involved in the development of frailty in breast cancer patients. Moreover, they might be useful to refine the comprehensive geriatric assessment model. J. Cell. Physiol. 229: 898-902, 2014. © 2013 Wiley Periodicals, Inc.
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