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Current Metabolomics

Editor-in-Chief

ISSN (Print): 2213-235X
ISSN (Online): 2213-2368

Lipidomic Analysis of Glioblastoma Multiforme Using Mass Spectrometry

Author(s): Soo Jung Ha, Gordon Showalter, Shanbao Cai, Haiyan Wang, Wei Michael Liu, Aaron A. Cohen-Gadol, Jann N. Sarkaria, Jenna Rickus, John Springer, Jiri Adamec, Karen E. Pollok and Kari L. Clase

Volume 2 , Issue 2 , 2014

Page: [132 - 143] Pages: 12

DOI: 10.2174/2213235X02666141107215357

Price: $65

Abstract

Glioblastoma multiforme (GBM) is the most common and malignant form of primary brain tumors. It is highly invasive and current treatment options have not improved the survival rate over the past twenty years. Novel approaches and technologies from systems biology have the potential to identify biomarkers that could serve as new therapeutic targets for GBM. This study employed lipid profiling technology to investigate lipid biomarkers in ectopic and orthotopic human GBM xenograft models. Primary patient cell lines, GBM10 and GBM43, were injected into the flank and the right cerebral hemisphere of NOD/SCID mice. Tumors were harvested from the brain and flank and proteins, metabolites, and lipids extracted from each sample. Reverse phase based high performance liquid chromatography coupled with Fourier transform ion cyclotron resonance mass spectrometry (LC-FTMS) was used to analyze the lipid profiles of tumor samples. Statistical and clustering analyses were performed to detect differences. Over 500 lipids were identified in each tumor model and lipids with the greatest fold effect in the comparison of ectopic versus orthotopic tumor models fell predominantly into four main classes of lipids: glycosphingolipids, glycerophoshpoethanolamines, triradylglycerols, and glycerophosphoserines. Lipidomic analysis revealed differences in glycosphingolipid and triglyceride profiles when the same tumor was propagated in the flank versus the brain. These results underscore the importance of the surrounding physiological environment on tumor development and are consistent with the hypothesis that specific classes of lipids are critical for GBM tumor growth in different anatomical sites.

Keywords: Biomarkers, cancer, glioblastoma multiforme, lipid profiling, mass spectrometry.

Graphical Abstract

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