Assessment of the efficacy of anticancer drugs by amino acid metabolomics using fluorescence derivatization-HPLC.

Metabolomic studies conducted for evaluating cancer pathogenesis and progression by monitoring the amino acids metabolic balance hold great promise for assessing current and future anticancer treatments. We performed a comprehensive quantification of 21 amino acids concentrations in cultured human colorectal adenocarcinoma cells treated with the anticancer drugs 5-fluorouracil, irinotecan, and cisplatin. A precolumn fluorescence derivatization-HPLC method involving 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate was used. Amino acid concentration data were analyzed by principal-component analysis and partial least-squares multivariate statistical methods to represent samples on two-dimensional graphs. The hierarchical cluster analysis and linear discriminant analysis were used to classify the samples on the score plots. Unlike the cluster analysis approach, the linear discrimination analysis classification successfully distinguished anticancer drug-treated samples from the untreated controls. Moreover, three candidate amino acids (serine, aspartic acid, and methionine) were identified from the loading plots as potential biomarkers. Our proposed method might be able to evaluate the effectiveness of anticancer therapy even in small laboratories or medical institutions.