Abstract − Analytical Sciences, 32(8), 893 (2016).
Amino Acid Metabolomics Using LC-MS/MS: Assessment of Cancer-Cell Resistance in a Simulated Tumor Microenvironment
Ryoko TOMITA,* Kenichiro TODOROKI,** Hiroshi MARUOKA,* Hideyuki YOSHIDA,* Toshihiro FUJIOKA,* Manabu NAKASHIMA,* Masatoshi YAMAGUCHI,* and Hitoshi NOHTA*
*Faculty of Pharmaceutical Sciences, Fukuoka University, 8-19-1 Nanakuma, Johnan, Fukuoka 814-0180, Japan
**Laboratory of Analytical and Bio-Analytical Chemistry, School of Pharmaceutical Sciences, University of Shizuoka, 52-1 Yada, Suruga, Shizuoka 422-8526, Japan
**Laboratory of Analytical and Bio-Analytical Chemistry, School of Pharmaceutical Sciences, University of Shizuoka, 52-1 Yada, Suruga, Shizuoka 422-8526, Japan
We performed a comprehensive quantification of 20 amino acids in RPMI 1640 medium-cultured human colorectal adenocarcinoma cells to evaluate the efficacy of 5-fluorouracil treatment under hypoxic and hypoglycemic conditions, which mimic the tumor microenvironment. In this study, we developed a simple and comprehensive analytical method by using LC-MS/MS connected to the Intrada amino acid column, which eluted amino acids within 9 min. The present method covered a linearity range of 3.6 – 1818 μM, except for Gly (227 – 1818 μM), Ala, Asp, His (7.1 – 1818 μM each), and Trp (3.6 – 909 μM). The limits of detection were in the range of 0.02 – 38.0 pmol per injection in a standard solution. Amino acid concentration data were analyzed using principal-component analysis to represent samples on two-dimensional graphs. Linear discriminant analysis was used to classify samples on the score plots. Using this approach, the effect of 5-fluorouracil treatment could be successfully discriminated at high discrimination rates. Moreover, several amino acids were extracted from corresponding loading plots as candidate markers for distinguishing the effects of the 5-fluorouracil treatment or tumor microenvironmental conditions. These results suggest that our proposed method might be a useful tool for evaluating the efficacy of anticancer drugs in the tumor microenvironment.
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