Abstract
Metabolomics technologies continue to develop not only to study endpoint steady-state concentrations of numerous metabolites in normal and cancer cells but also to examine metabolic flux and networks. These techniques are of importance for understanding tumor cell metabolism and for the development of new drugs and treatment strategies. The choice of tracer substrates is central as 13C-labeled substrates readily improve real-time reaction visibility by increasing metabolic network transparencies in cancer metabolomics. In this chapter, targeted [1,2- 13C2]-d-glucose single tracer fate associations are compared with the external [U- 13C18]-stearate oxidation model for thiazolidinedione efficacy testing in primary liver tumor cells. Although the externally supplied [U- 13C18]-stearate tracer readily labels multiple products by acetyl-CoA exchange, parallel stearate synthesis and mobilization from unlabeled intracellular pools disrupt its uptake after drug treatment. This can be overcome by using cross-labeled 13C-stearate from [1,2- 13C2]-d-glucose as the internal tracer and the independent explanatory variable to study associations among markers of rosiglitazone-induced stearate breakdown in a single [1,2- 13C2]-d-glucose tracer experiment during drug efficacy testing in cultured cells.
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References
Beger RD, Colatsky T (2011) Metabolomics data and the biomarker qualification process. Metabolomics 8:2–7
Beger RD et al (2009) Single valproic acid treatment inhibits glycogen and RNA ribose turnover while disrupting glucose-derived cholesterol synthesis in liver as revealed by the [U- 13C6]-d-glucose tracer in mice. Metabolomics 5:336–345
Boros LG, Cascante M, Lee WN (2002) Metabolic profiling of cell growth and death in cancer: applications in drug discovery. Drug Discov Today 7:364–372
Boros LG, Serkova NJ, Laderoute KR, Linehan WM, Meuillet MJ (2013) Stable 13C isotope enriched metabolome (isotopolome) wide associations (IWAS) improve system wide association studies (SWAS) for phenotype and drug research. World Biotechnology Congress 4:A29, SL-31. http://www.worldbiotechcongress.com/files/Abstract-Book-GBC-(2013).pdf
Chang CH, Lin JW, Wu LC, Lai MS, Chuang LM, Chan KA (2012) Association of thiazolidinediones with liver cancer and colorectal cancer in type 2 diabetes mellitus. Hepatology 55:1462–72. doi:10.1002/hep.25509
Darmaun D, Matthews DE, Desjeux JF, Bier DM (1988) Glutamine and glutamate nitrogen exchangeable pools in cultured fibroblasts: a stable isotope study. J Cell Physiol 134:143–148
Haber S, Lapidot A (2001) Energy fuel utilization by fetal versus young rabbit brain: a 13C MRS isotopomer analysis of [U-13C6]glucose metabolites. Brain Res 896:102–117
Harrigan GG, Colca JR, Szalma S, Boros LG (2006) PNU-91325 increases fatty acid synthesis from glucose and mitochondrial long chain fatty acid degradation: a comparative tracer-based metabolomics study with rosiglitazone and pioglitazone in HepG2 cells. Metabolomics 2:21–29. doi:10.1007/s11306-006-0015-5
Hellerstein MK (1991) Relationship between precursor enrichment and ratio of excess M2/excess M1 isotopomer frequencies in a secreted polymer. J Biol Chem 266:10920–10924
Holleran AL, Briscoe DA, Fiskum G, Kelleher JK (1995) Glutamine metabolism in AS-30D hepatoma cells. Evidence for its conversion into lipids via reductive carboxylation. Mol Cell Biochem 152:95–101
Katz J, Wals P, Lee WN (1993) Isotopomer studies of gluconeogenesis and the Krebs cycle with 13C-labeled lactate. J Biol Chem 268:25509–25521
Lee WN, Bergner EA, Guo ZK (1992) Mass isotopomer pattern and precursor-product relationship. Biol Mass Spectrom 21:114–122
Lee WN, Edmond J, Bassilian S, Morrow JW (1996) Mass isotopomer study of glutamine oxidation and synthesis in primary culture of astrocytes. Dev Neurosci 18:469–477
Lee WN, Lim S, Bassilian S, Bergner EA, Edmond J (1998a) Fatty acid cycling in human hepatoma cells and the effects of troglitazone. J Biol Chem 273:20929–20934
Lee WN, Boros LG, Puigjaner J, Bassilian S, Lim S, Cascante M (1998b) Mass isotopomer study of the nonoxidative pathways of the pentose cycle with [1,2-13C2]glucose. Am J Physiol 274:E843–E851
Leimer KR, Rice RH, Gehrke CW (1977) Complete mass spectra of N-trifluoroacetyl-n-butyl esters of amino acids. J Chromatogr 141:121–144
Lowenstein JM, Brunengraber H, Wadke M (1975) Measurement of rates of lipogenesis with deuterated and tritiated water. Methods Enzymol 35:279–287
Metallo CM, Walther JL, Stephanopoulos GJ (2009) Evaluation of 13C isotopic tracers for metabolic flux analysis in mammalian cells. J Biotechnol 144:167–174. doi:10.1016/j.ymben.2011.12.004
Mullen AR, Wheaton WW, Jin ES, Chen PH, Sullivan LB, Cheng T, Yang Y, Linehan WM, Chandel NS, DeBerardinis RJ (2011) Reductive carboxylation supports growth in tumour cells with defective mitochondria. Nature 481:385–388
Otto C, Lehrke M, Goke B (2002) Novel insulin sensitizers: pharmacogenomic aspects. Pharmacogenomics 3:99–116
Sabate L, Franco R, Canela EI, Centelles JJ, Cascante M (1995) A model of the pentose phosphate pathway in rat liver cells. Mol Cell Biochem 142:9–17
Son J, Lyssiotis CA, Ying H, Wang X, Hua S, Ligorio M, Perera RM, Ferrone CR, Mullarky E, Shyh-Chang N, Kang Y, Fleming JB, Bardeesy N, Asara JM, Haigis MC, DePinho RA, Cantley LC, Kimmelman AC (2013) Glutamine supports pancreatic cancer growth through a KRAS-regulated metabolic pathway. Nature 496:101–105. doi:10.1038/nature12040
Sonko BJ, Schmitt TC, Guo L, Shi Q, Boros LG, Leakey JE, Beger RD (2011) Assessment of usnic acid toxicity in rat primary hepatocytes using 13C isotopomer distribution analysis of lactate, glutamate and glucose. Food Chem Toxicol 49:2968–2974
Vance DE, Vance KE (2002) Biochemistry of lipids, lipoproteins and membranes, 4th edn. Elsevier Science, New York, pp 183–187
Vamecq J, Colet J-M, Vanden Eynde JJ, Briand G, Porchet N, Rocchi S (2012) PPARs: interference with Warburg’ effect and clinical anticancer trials. PPAR Res Article ID 304760
Walther JL, Metallo CM, Zhang J, Stephanopoulos G (2012) Optimization of 13C isotopic tracers for metabolic flux analysis in mammalian cells. Metab Eng 14:162–171
Wong DA, Bassilian S, Lim S, Lee WN (2004) Coordination of peroxisomal beta-oxidation and fatty acid elongation in HepG2 cells. J Biol Chem 279:41302–41309
Yang Y, Lane AN, Ricketts C, Wei M-H, Pike L, Wu M, Rouault TA, Boros LG, Fan TW-M, Linehan WM (2013) Metabolic reprogramming for producing energy and reducing power in Fumarate Hydratase null cells from hereditary leiomyomatosis renal cell carcinoma. PLoS One 8:e72179. doi:10.1371/journal.pone.0072179
Acknowledgments
Isotopolome-wide mathematical fitting of GC-MS data involving 13C-glucose with 13C-stearate to product processing was supported by the Hirshberg Foundation for Pancreatic Cancer Research and the UCLA Clinical and Translational Science Institute (UL1TR000124) to LGB and EJM. Targeted 13C tracer drug efficacy marker data diagnostics for cancer were partially supported by the European Regional Development Fund, Central Hungary Operative Program, and New Széchenyi Plan (KMOP-1.1.4-11/A-2011-01-05) to GS. We thank Eszter Boros and Ferenc Nádudvari for their technical help in registering additional 13C tracer presentation by LGB on the World Wide Web at http://youtu.be/GkYAjabGxJs regarding mammalian cell mitochondria.
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The authors declare no conflict of financial interest.
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Boros, L.G. et al. (2015). Targeted 13C-Labeled Tracer Fate Associations for Drug Efficacy Testing in Cancer. In: Mazurek, S., Shoshan, M. (eds) Tumor Cell Metabolism. Springer, Vienna. https://doi.org/10.1007/978-3-7091-1824-5_15
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DOI: https://doi.org/10.1007/978-3-7091-1824-5_15
Publisher Name: Springer, Vienna
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