CEEPC/IPM/CMSC - Abstrakt prezentace

(Česká konference hmotnostní spektrometrie 2017 - PL-2)
Mass spectrometry based lipidomic quantitation and applications in cancer biomarker research

Michal Holčapek 1 *, Miroslav Lísa 1, Eva Cífková 1, Robert Jirásko 1, Maria Khalikova 1, Bohuslav Melichar 2, David Vrána 2

  1. University of Pardubice, Faculty of Chemical Technology, Pardubice
  2. Palacký University, Medical School and Teaching Hospital, Olomouc

Abstrakt

Lipids are major building blocks of membranes of cells and intracellular compartments and they also fulfil numerous crucial cell functions. Their dysregulation is related with some serious human diseases including cancer, because tumor and normal cells have different proteomic, metabolomic and lipidomic composition. We demonstrate that the lipidomic composition of tumor and normal cell lines shows statistically significant differences for several tumor types [1]. The same differences are also found in tumor and normal tissues obtained after the oncological surgery and tumor/normal differentiation is verified for plasma samples of inbred mice. The last and the most difficult step is the search for statistically relevant lipidomic differences for human plasma. This type of research requires high-throughput, robust and validated MS assays for the quantitation of large number of lipids from multiple lipid categories and classes. Shotgun ESI-MS/MS is used for the direct quantitation of several phospholipid and sphingolipid classes in total lipid extracts without a chromatographic separation. Separation - MS approaches can increase the sensitivity due to the reduction of matrix effects and improve the confidence of lipid identification. HILIC [2] or ultrahigh-performance supercritical fluid chromatography [3] methods are convenient for the separation of various lipid classes, where the coelution of class internal standards and analytes guarantee the same ionization efficiencies. Negative-ion MALDI is used for semi-quantitation of some negatively charged lipids, such as sulfatides and related compounds. Finally, the multivariate data analysis using nonsupervised and supervised methods is performed to find the main differences between tumor and normal samples.

* Korespondující autor: Michal.Holcapek@upce.cz

Literatura

  1. Cífková E. et al.: Rapid Commun. Mass Spectrom. 31(3), 253-263 (2017).
  2. Cífková, E. et al.: J. Chromatogr. B 1000, 14-21 (2015).
  3. Lísa, M. et al.: Anal. Chem. 87, 7187-7195 (2015).

Poděkování:

This work was supported by ERC CZ project No. LL1302 (MSMT, Czech Republic).


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