Amino Acid Metabolomics Using LC-MS/MS: Assessment of Cancer-Cell Resistance in a Simulated Tumor Microenvironment

• Published in: Analytical Sciences Vol. 32; no. 8; pp. 893 - 900
• Main Authors: TOMITA, Ryoko, TODOROKI, Kenichiro, MARUOKA, Hiroshi, YOSHIDA, Hideyuki, FUJIOKA, Toshihiro, NAKASHIMA, Manabu, YAMAGUCHI, Masatoshi, NOHTA, Hitoshi
• Format: Journal Article
• Language: English
• Published: Singapore The Japan Society for Analytical Chemistry 2016; Springer Nature Singapore
• Subjects: 5-fluorouracil; Amino acid metabolomics; Analytical Chemistry; Chemistry; hypoglycemia; hypoxia; liquid chromatography–tandem mass spectrometry; 5-fluorouracil; hypoxia; Amino acid metabolomics; liquid chromatography–tandem mass spectrometry; hypoglycemia
• ISSN: 0910-6340; 1348-2246
• DOI: 10.2116/analsci.32.893

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.