One of the central hallmarks of cancer is the rapid and infinite cellular proliferation. In order to cope with increased requirement for building blocks and energy, cancer cells develop abnormal metabolic properties. Detailed assessment of cancer cell metabolism can provide biological information for use in both drug discovery and development of personalized cancer therapy. Analysis of intact tissue using high resolution magic angle spinning (HR MAS) magnetic resonance spectroscopy (MRS) gives qualitative and quantitative metabolite measures with minimal sample preparation. Multivariate statistical methods are important tools for analysis of complex MR data and have in recent years been used for analysis of HR MAS data from intact tissue. HR MAS analysis of intact tissue allows combination of metabolomic data with genomic or proteomic data, and can therefore be used both for exploring the molecular biology of cancer and for clinical improvements in cancer diagnostics, prognostics and treatment planning. In this review, the basic concepts of HR MAS are presented, and its use in characterisation of cancer metabolism is discussed with specific focus on selected pathways such as choline metabolism and glycolysis. The use of HR MAS in analysis of amino acids and lipid metabolism in cancer is also reviewed. Finally, the expected role of HR MAS in metabolic characterisation in the near future is discussed.
Keywords: Amino acids, choline, citrate, glycolysis, lactate, lipids, metabolomics, multivariate analysis, magic angle spinning, magnetic resonance spectroscopy, MAS technique, trimethylsilylpropionic acid, Electronic REference To access In-vivo Concentrations, ERETIC, minimum-maximum-relevance (mRMR), Principal component analysis, PCA, soft independent modelling of class analogy, SIMCA, linear discriminant analysis (LDA), support vector macine (SVM), PLS discriminant analysis, radiation therapy, Phospatidylcholine, choline-containing compounds, phosphocholine, cytidine diphosphocholine, choline-phosphate cytidylyltransferase, glycerophosphocholine, choline metabolism, transrectal ultrasound, mitochondrial aconitase, glioblastoma multiforme, astrocytomas, schwannomas, Taurine, terminal end labeling, hematoxylin/erythrosine, liposarcomas, Pulse length based concentration determination, PULCON, Hierarchical cluster analysis, Invasive ductal carcinoma, Organic cation transporter 2, Soft independent modeling of class analogy, Variable stability scaling, Vascular disrupting agent
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