Issue 39, 2017, Issue in Progress

LC-MS-based metabolomics reveals metabolic signatures related to glioma stem-like cell self-renewal and differentiation

Abstract

Gliomas are the most common and lethal primary malignant brain tumors. Recent studies implicate an important role for a rare population of glioma stem cells (GSCs) in glioma maintenance and recurrence. New therapeutic strategies are desperately needed requiring insights into the biological and molecular mechanisms underlying the self-renewal and differentiation of GSCs. We now investigate the metabolic signatures of three glioma cell lines with different stemness using a liquid chromatography-mass spectrometry (LC-MS)-based metabolomics approach. Cellular metabolites differentially expressed in U87MG stem-like cells (SLCs) relative to U87 malignant glioma cells (GCs) and U87MG stem-like cell differentiation cells (SLCDCs) were identified. The specific and significant alterations including nucleotide metabolism, glycerophospholipid metabolism, glutathione metabolism, carnitine metabolism and tryptophan metabolism were characterized. Cell function assays were further used to evaluate the self-renewal ability of SLCs treated with differential metabolites, indicating that these metabolites are involved in the maintenance of stemness. The results provide valuable information on the association of the significantly altered metabolites and metabolic pathways with SLC self-renewal and differentiation.

Graphical abstract: LC-MS-based metabolomics reveals metabolic signatures related to glioma stem-like cell self-renewal and differentiation

Supplementary files

Article information

Article type
Paper
Submitted
01 Apr 2017
Accepted
24 Apr 2017
First published
03 May 2017
This article is Open Access
Creative Commons BY license

RSC Adv., 2017,7, 24221-24232

LC-MS-based metabolomics reveals metabolic signatures related to glioma stem-like cell self-renewal and differentiation

R. Zhang, P. Hu, Q. Zang, X. Yue, Z. Zhou, X. Xu, J. Xu, S. Li, Y. Chen, B. Qiang, X. Peng, W. Han, R. Zhang and Z. Abliz, RSC Adv., 2017, 7, 24221 DOI: 10.1039/C7RA03781C

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