HPLC/MS-based Metabolic Profiling and Quantification of Urine Free Amino Acids as Potential Biomarkers for Breast Cancer Diagnosis and Progression

Florina Elena Roamanciuc, Dan Eniu, Adelina Staicu, Claudiu Rachieru, Rareș Buiga, Carmen Socaciu


Considering the key role of free amino acids in cell metabolism and their predictive role as biomarkers in breast cancer by alteration of their metabolic pathways, the purpose of this study was to identify and quantify the urine amino acids from healthy and breast cancer women, diagnosed in different histological stages. Using advanced LC-QTOF-(ESI+)-MS technique and EZ:faast kit, based on derivatization of free aminoacids, 16 amino acids from control and breast cancer groups, preliminarily classified in I-IIIA and II-IIIB stages were identified and quantified. The general LC/MS fingerprint showed significant quantitative differences, especially for serine, lysine, tyrosine and leucine and asparagine, which decreased or increased, respectively. The multivariate analysis (PCA) showed good discrimination between normal and pathological groups, with best discrimination by essential amino acids. Cluster Analysis confirmed three discrimination regions, a major BC group, the control-group and a minor five patient-group. When the mean values of essential and non-essential amino acids were represented, in relation to cancer stages, gradual decreases of non-essential and essential amino acids were observed, from stage I to IIIA and from II to IIIB, in a parallel manner, non-essential amino acids having 3.5 times higher values than essential amino acids, the decreases being more relevant for non-essential amino acids. Serine had the steepest decrease, followed by Tyrosine, both being recommended as good biomarker candidates. By ROC curves, lysine and isoleucine showed highest AUC values and confidence intervals to provide good diagnostic between healthy and BC groups. Nonetheless, in agreement with quantitative data and correlations with the breast cancer stages, serine and tyrosine had better potential to offer a good diagnosis and confidence in discriminating among different cancer progression stages.



urine amino acids, LC-QTOF-(ESI+)-MS, breast cancer, biomarker

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DOI: http://dx.doi.org/10.15835/buasvmcn-asb:11588

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