Abstract
BackgroundMetabolomics has a great potential in the development of new biomarkers in cancer and it has experiment recent technical advances.MethodsIn this study, metabolomics and gene expression data from 67 localized (stage I to IIIB) breast cancer tumor samples were analyzed, using (1) probabilistic graphical models to define associations using quantitative data without other a priori information; and (2) Flux Balance Analysis and flux activities to characterize differences in metabolic pathways.ResultsOn the one hand, both analyses highlighted the importance of glutamine in breast cancer. Moreover, cell experiments showed that treating breast cancer cells with drugs targeting glutamine metabolism significantly affects cell viability. On the other hand, these computational methods suggested some hypotheses and have demonstrated their utility in the analysis of metabolomics data and in associating metabolomics with patient’s clinical outcome.ConclusionsComputational analyses applied to metabolomics data suggested that glutamine metabolism is a relevant process in breast cancer. Cell experiments confirmed this hypothesis. In addition, these computational analyses allow associating metabolomics data with patient prognosis.
Highlights
Metabolomics has a great potential in the development of new biomarkers in cancer and it has experiment recent technical advances
A computational analytical workflow for the management and study of metabolomics data was proposed. This workflow allowed global metabolic characterization, beyond analyses based on unique metabolites. This workflow pointed out the relevance of glutamine metabolism in breast cancer, a hypothesis that was confirmed by cellular experiments
probabilistic graphical models (PGMs) reveal their utility in the analysis of metabolomics data from a functional point of view, metabolomics data alone, and in combination with flux or gene expression data
Summary
Metabolomics has a great potential in the development of new biomarkers in cancer and it has experiment recent technical advances. Metabolomics, a technique focused in the holistic study of the metabolites present in a biological system, is considered the most recent -omics It consists of measuring the entire set of metabolites present in a biological sample [2]. The most common techniques in metabolomics experiments are mass spectrometry-related methods, which are based on the mass/charge relationships of each metabolite or its fragments [3]. Recent advances in this technique allow the measurement of thousands of metabolites from minimal amounts of biological samples [3, 4]. In early breast cancer, a previous study identified an association between levels of choline, glycine, and lactate and histopathological grades and tumor size [7, 8]
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