Quantitative two‐dimensional HRMAS 1H‐NMR spectroscopy‐based metabolite profiling of human cancer cell lines and response to chemotherapy

NMR spectroscopy‐based metabolomics still needs development in quantification procedures. A method was designed for quantitative two‐dimensional high resolution magic angle spinning (HRMAS) proton‐NMR spectroscopy‐based metabolite profiling of intact cells. It uses referencing of metabolite‐related NMR signals to protein‐related NMR signals and yields straightforward and automatable metabolite profiling. The method enables exploitation of only two‐dimensionally visible metabolites and combination of one‐ and two‐dimensional spectra, thus providing an appreciable number of screened metabolites. With this procedure, 32 intracellular metabolites were attributed and quantified in human normal fibroblasts and tumor cells. The phenotype of several tumor cell lines (MCF7, PC3, 143B, and HepG2) was characterized by high levels of glutathione in cell lines with the higher proliferation rate, high levels of creatine, low levels of free amino acids, increased levels of phospholipid derivatives (mostly phosphocholine), and lower lactate content in cell lines with the higher proliferation rate. Other metabolites such as fatty acids differed widely among tumor cell lines. The response of tumor cell lines to chemotherapy also was evaluated by differential metabolite profiling, bringing insights into drug cytotoxicity and tumor cell adaptive mechanisms. The method may prove widely applicable to tumor cell phenotyping. Magn Reson Med 63:1172–1183, 2010. © 2010 Wiley‐Liss, Inc.

[1]  Y. Mardor,et al.  Levels of phospholipid metabolites in breast cancer cells treated with antimitotic drugs: a 31P-magnetic resonance spectroscopy study. , 2001, Cancer research.

[2]  M. Cascante,et al.  The Stable Isotope-based Dynamic Metabolic Profile of Butyrate-induced HT29 Cell Differentiation* , 2003, Journal of Biological Chemistry.

[3]  P. Kehrli,et al.  Toward improved grading of malignancy in oligodendrogliomas using metabolomics , 2008, Magnetic resonance in medicine.

[4]  Z. Bhujwalla,et al.  Molecular Causes of the Aberrant Choline Phospholipid Metabolism in Breast Cancer , 2004, Cancer Research.

[5]  D. Morvan,et al.  Mitochondrial bioenergetic background confers a survival advantage to HepG2 cells in response to chemotherapy , 2009, Molecular carcinogenesis.

[6]  O. Ohlenschläger,et al.  NMR secondary structure of the plasminogen activator protein staphylokinase , 1997, Journal of biomolecular NMR.

[7]  S. Canevari,et al.  Alterations of choline phospholipid metabolism in ovarian tumor progression. , 2005, Cancer research.

[8]  S. Jackowski,et al.  Cellular Responses to Excess Phospholipid* , 1999, The Journal of Biological Chemistry.

[9]  David Gallego-Ortega,et al.  Choline kinase as a link connecting phospholipid metabolism and cell cycle regulation: implications in cancer therapy. , 2008, The international journal of biochemistry & cell biology.

[10]  B. Halliwell,et al.  Human skin keloid fibroblasts display bioenergetics of cancer cells. , 2008, The Journal of investigative dermatology.

[11]  T. Ebbels,et al.  Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts , 2007, Nature Protocols.

[12]  Daniel Raftery,et al.  Use of selective TOCSY NMR experiments for quantifying minor components in complex mixtures: application to the metabonomics of amino acids in honey. , 2005, Analytical chemistry.

[13]  M. Medina,et al.  Glutamine, as a precursor of glutathione, and oxidative stress. , 1999, Molecular genetics and metabolism.

[14]  J. Lindon,et al.  Metabonomics: a platform for studying drug toxicity and gene function , 2002, Nature Reviews Drug Discovery.

[15]  Theodoros N. Arvanitis,et al.  An algorithm for the automated quantitation of metabolites in in vitro NMR signals , 2006, Magnetic resonance in medicine.

[16]  D. Morvan,et al.  Methionine‐dependence phenotype of tumors: Metabolite profiling in a melanoma model using L‐[methyl‐13C]methionine and high‐resolution magic angle spinning 1H–13C nuclear magnetic resonance spectroscopy , 2006, Magnetic resonance in medicine.

[17]  J. Lindon,et al.  Pharmaco-metabonomic phenotyping and personalized drug treatment , 2006, Nature.

[18]  G. Yancey Gillespie,et al.  Glucose Metabolism Heterogeneity in Human and Mouse Malignant Glioma Cell Lines , 2005, Journal of Neuro-Oncology.

[19]  Daniel Morvan,et al.  Pharmacometabolomics of docetaxel-treated human MCF7 breast cancer cells provides evidence of varying cellular responses at high and low doses , 2010, Breast Cancer Research and Treatment.

[20]  K. Willison,et al.  Substantial CCT activity is required for cell cycle progression and cytoskeletal organization in mammalian cells. , 2006, Experimental cell research.

[21]  Julian L. Griffin,et al.  Metabolic profiles of cancer cells , 2004, Nature Reviews Cancer.

[22]  Adam L. Meadows,et al.  Metabolic and Morphological Differences between Rapidly Proliferating Cancerous and Normal Breast Epithelial Cells , 2008, Biotechnology progress.

[23]  C. Mountford,et al.  Tetraphenylphosphonium chloride induced mr‐visible lipid accumulation in a malignant human breast cell line , 1996, International journal of cancer.

[24]  Gema Moreno-Bueno,et al.  Telling Cells How to Die: Docetaxel Therapy in Cancer Cell Lines , 2007, Cell cycle.

[25]  C. Arús,et al.  1H MRS markers of tumour growth in intrasplenic tumours and liver metastasis induced by injection of HT‐29 cells in nude mice spleen , 1998, NMR in biomedicine.

[26]  D. Cory,et al.  Biochemical correlates of thiazolidinedione‐induced adipocyte differentiation by high‐resolution magic angle spinning NMR spectroscopy , 2002, Magnetic resonance in medicine.

[27]  D. Morvan,et al.  Metabolomics by proton nuclear magnetic resonance spectroscopy of the response to chloroethylnitrosourea reveals drug efficacy and tumor adaptive metabolic pathways. , 2007, Cancer research.

[28]  D. Morvan,et al.  Melanoma tumors acquire a new phospholipid metabolism phenotype under cystemustine as revealed by high-resolution magic angle spinning proton nuclear magnetic resonance spectroscopy of intact tumor samples. , 2002, Cancer research.

[29]  D. Wallace,et al.  Mitochondria and cancer: Warburg addressed. , 2005, Cold Spring Harbor symposia on quantitative biology.

[30]  W. Mackinnon,et al.  Correlation of cellular differentiation in human colorectal carcinoma and adenoma cell lines with metabolite profiles determined by 1H magnetic resonance spectroscopy , 1994, International journal of cancer.

[31]  D. Morvan,et al.  Quantitative HRMAS proton total correlation spectroscopy applied to cultured melanoma cells treated by chloroethyl nitrosourea: Demonstration of phospholipid metabolism alterations , 2003, Magnetic resonance in medicine.

[32]  F. Howe,et al.  Toward accurate quantification of metabolites, lipids, and macromolecules in HRMAS spectra of human brain tumor biopsies using LCModel , 2008, Magnetic resonance in medicine.

[33]  V. Raman,et al.  RNA interference-mediated choline kinase suppression in breast cancer cells induces differentiation and reduces proliferation. , 2005, Cancer research.

[34]  C. Pannecouque,et al.  1H-13C nuclear magnetic resonance assignment and structural characterization of HIV-1 Tat protein. , 2000, Comptes rendus de l'Academie des sciences. Serie III, Sciences de la vie.

[35]  R. Pankov,et al.  Ha‐ ras‐TRANSFORMATION ALTERS THE METABOLISM OF PHOSPHATIDYLETHANOLAMINE AND PHOSPHATIDYLCHOLINE IN NIH 3T3 FIBROBLASTS , 1999, Cell biology international.

[36]  N. Michel,et al.  The application of the ERETIC method to 2D-NMR. , 2004, Journal of magnetic resonance.