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Comparative metabolic and lipidomic profiling of human breast cancer cells with different metastatic potentials

Authors
Kim, Hye-YounLee, Kyung-MinKim, So-HyunKwon, Yeo-JungChun, Young-JinChoi, Hyung-Kyoon
Issue Date
11-Oct-2016
Publisher
IMPACT JOURNALS LLC
Keywords
metastasis; breast cancer cells; metabolomics; lipidomics; PLSR
Citation
ONCOTARGET, v.7, no.41, pp 67111 - 67128
Pages
18
Journal Title
ONCOTARGET
Volume
7
Number
41
Start Page
67111
End Page
67128
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/1682
DOI
10.18632/oncotarget.11560
ISSN
1949-2553
1949-2553
Abstract
This study conducted comprehensive and comparative metabolic and lipidomic profiling of a human epithelial breast cell line (MCF-10A), a slightly metastatic (MCF-7), and a highly metastatic (MDA-MB-231) breast cancer cell line using gas chromatography mass spectrometry (GC-MS) and direct infusion mass spectrometry (DI-MS). Among 39 metabolites identified by GC-MS analysis, xanthine, glucose-6-phosphate, mannose-6-phosphate, guanine, and adenine were selected as prognostic markers of breast cancer metastasis. Major metabolic pathways involved in differentiation of the cell lines were alanine, aspartate, and glutamate metabolism, purine metabolism and glycine, serine, and threonine metabolism. Among 44 intact lipid species identified by DI-MS analysis, the levels of most phospholipids were higher in both metastatic groups than in normal cells. Specifically, the levels of phosphatidylserine (PS) 18: 0/20: 4, phosphatidylinositol (PI) 18: 0/20: 4, and phosphatidylcholine (PC) 18: 0/20: 4 were markedly higher while those of phosphatidylethanolamine (PE) 18: 1/18: 1 and PI 18: 0/18: 1 were lower in MDA-MB-231 cells than in MCF-7 cells. A partial-least-squares regression model was developed and validated for predicting the metastatic potential of breast cancer cells. The information obtained in this study will be useful when developing diagnostic tools and for identifying potential therapeutic targets for metastatic breast cancer.
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