Journal Highlight: Correlation of lipidomic composition of cell lines and tissues of breast cancer patients using hydrophilic interaction liquid chromatography/electrospray ionization mass spectrometry and multivariate data analysis

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  • Published: Feb 6, 2017
  • Author: separationsNOW
  • Channels: Laboratory Informatics
thumbnail image: Journal Highlight: Correlation of lipidomic composition of cell lines and tissues of breast cancer patients using hydrophilic interaction liquid chromatography/electrospray ionization mass spectrometry and multivariate data analysis

The lipidomic compositions of human cell lines derived from normal and cancerous breast tissues, as well as tissues obtained before and after breast cancer surgery, have been compared by multivariate data analysis methods.

Correlation of lipidomic composition of cell lines and tissues of breast cancer patients using hydrophilic interaction liquid chromatography/electrospray ionization mass spectrometry and multivariate data analysis

Rapid Communications in Mass Spectrometry, 2017, 31, 253-263
Eva Cífková, Miroslav Lísa, Roman Hrstka, David Vrána, Jiří Gatěk, Bohuslav Melichar and Michal Holčapek

Abstract: The goal of this work is the comparison of differences in the lipidomic compositions of human cell lines derived from normal and cancerous breast tissues, and tumor vs. normal tissues obtained after the surgery of breast cancer patients. Hydrophilic interaction liquid chromatography/electrospray ionization mass spectrometry (HILIC/ESI-MS) using the single internal standard approach and response factors is used for the determination of relative abundances of individual lipid species from five lipid classes in total lipid extracts of cell lines and tissues. The supplementary information on the fatty acyl composition is obtained by gas chromatography/mass spectrometry (GC/MS) of fatty acid methyl esters. Multivariate data analysis (MDA) methods, such as nonsupervised principal component analysis (PCA), hierarchical clustering analysis (HCA) and supervised orthogonal partial least-squares discriminant analysis (OPLS-DA), are used for the visualization of differences between normal and tumor samples and the correlation of similarity between cell lines and tissues either for tumor or normal samples. MDA methods are used for differentiation of sample groups and also for identification of the most up- and downregulated lipids in tumor samples in comparison to normal samples. Observed changes are subsequently generalized and correlated with data from tumor and normal tissues of breast cancer patients. In total, 123 lipid species are identified based on their retention behavior in HILIC and observed ions in ESI mass spectra, and relative abundances are determined. MDA methods are applied for a clear differentiation between tumor and normal samples both for cell lines and tissues. The most upregulated lipids are phospholipids (PL) with a low degree of unsaturation (e.g., 32:1 and 34:1) and also some highly polyunsaturated PL (e.g., 40:6), while the most downregulated lipids are PL containing polyunsaturated fatty acyls (e.g., 20:4), plasmalogens and ether lipids.

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