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  4. Investigating the Metabolic Heterogeneity of Cancer Cells Using Functional Single-Cell Selection and nLC Combined with Multinozzle Emitter Mass Spectrometry
 
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Investigating the Metabolic Heterogeneity of Cancer Cells Using Functional Single-Cell Selection and nLC Combined with Multinozzle Emitter Mass Spectrometry

Journal
Analytical chemistry
Journal Volume
96
Journal Issue
2
Pages
624
Date Issued
2024-01-16
Author(s)
Cheng, Kai-Wen
Su, Pin-Rui
Feller, Kate Jo-Ann
Chien, Miao-Ping
CHENG-CHIH HSU  
DOI
10.1021/acs.analchem.3c03688
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/638844
URL
https://api.elsevier.com/content/abstract/scopus_id/85181578416
Abstract
Tumor metastasis and cancer recurrence are often a result of cell heterogeneity, where specific subpopulations of tumor cells may be resistant to radio- or chemotherapy. To investigate this physiological and phenotypic diversity, single-cell metabolomics provides a powerful approach at the chemical level, where distinct lipid profiles can be found in different tumor cells. Here, we established a highly sensitive platform using nanoflow liquid chromatography (nLC) combined with multinozzle emitter electrospray ionization mass spectrometry for more in-depth metabolomics profiling. Our platform identified 15 and 17 lipids from individual osteosarcoma (U2OS) and glioblastoma (GBM) cells when analyzing single-cell samples. Additionally, we used the functional single-cell selection (fSCS) pipeline to analyze the subpopulations of cells with a DNA damage response (DDR) in U2OS cells and fast migration in GBM cells. Specifically, we observed a down-regulation of polyunsaturated fatty acids (PUFAs) in U2OS cells undergoing DDR, such as fatty acids FA 20:3; O2 and FA 17:4; O3. Furthermore, ceramides (Cer 38:0; O3) and triglycerides (TG 36:0) were found to be down-regulated in fast-migrating GBM cells compared to the slow-migrating subpopulation. These findings suggest the potential roles of these metabolites and/or lipids in the cellular behavior of the subpopulations.
Type
journal article

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