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Lipidomic Analysis of Cancer Cell and Tumor Tissues

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Cancer Metabolism

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1928))

Abstract

Due to their role in cellular structure, energetics, and signaling, characterization of changes in cellular and extracellular lipid composition is of key importance to understand cancer biology. In addition, several mass spectrometry-based profiling as well as imaging studies have indicated that lipid molecules may be useful to augment existing biochemical and histopathological methods for diagnosis, staging, and prognosis of cancer. Therefore, analysis of lipidomic changes associated with cancer cells and tumor tissues can be useful for both fundamental and translational studies. Here, we provide a high-throughput single-extraction-based method that can be used for simultaneous lipidomic and metabolomic analysis of cancer cells or healthy or tumor tissue samples. In this chapter, a modified Bligh-Dyer method is described for extraction of lipids followed by analysis of fatty acid composition by gas chromatography-mass spectrometry (GC-MS) or untargeted lipidomics using electrospray ionization mass spectrometry (ESIMS) coupled with reverse-phase (RP) ultraperformance liquid chromatography (UPLC) followed by multivariate data analysis to identify features of interest.

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Acknowledgment

Authors would like to sincerely acknowledge the contribution of Mr. Kristopher W. Krausz in developing these methods and Dr. Frank J. Gonzalez (Laboratory of Metabolism, Center for Cancer Research, National Cancer Institute, Bethesda, USA) for his encouragement and support. This work was supported by Saha Institute of Nuclear Physics, Kolkata, India.

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Correspondence to Soumen Kanti Manna .

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Islam, S.R., Manna, S.K. (2019). Lipidomic Analysis of Cancer Cell and Tumor Tissues. In: Haznadar, M. (eds) Cancer Metabolism. Methods in Molecular Biology, vol 1928. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-9027-6_11

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  • DOI: https://doi.org/10.1007/978-1-4939-9027-6_11

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