title: LC-based targeted metabolomics analysis of nucleotides and identification of biomarkers associated with chemotherapeutic drugs in cultured cell models.
abstract: Treatment of mammalian cells with chemotherapeutic drugs can result in perturbations of nucleotide pools. Monitoring these perturbations in cultured tumor cells from human sources is useful for assessment of the effect of drug therapy and a better understanding of the mechanism of action of these drugs. In this study, three classes of chemotherapeutic drugs with different mechanisms of action were used in the development of drug-treated cell models. The LC-based targeted metabolomics analysis of nucleotides in cells of the control group and the drug-treated group was carried out. Several data processing methods were combined for the identification of potential biomarkers associated with the action of drugs, including one-way analysis of variance, principal component analysis, and receiver operating characteristic curves. Intriguingly, tumor cells of both the control group and the drug-treated groups can be distinguished from each other, and several variables were recognized as potential biomarkers, such as ATP, GMP, and UDP for antimetabolite agents, ATP, GMP, and CTP for DNA-damaging agents, as well as GMP, ATP, UDP, and GDP for the mitotic spindle agents. Further validation of the potential biomarkers was performed using the receiver operating characteristic curve. Considering their corresponding area under the curve, which was larger than 0.9, it can be concluded that GMP and ATP are the best potential biomarkers for DNA-damaging drugs, as well as GMP, ATP, and UDP for the other two classes of drugs. This limited nucleotide approach cannot completely distinguish the mechanisms of the nine drugs, but it provides preliminary evidence for the role of pharmacometabolomics in the preclinical development of drugs at least.
authors.affiliation: aDepartment of Pharmaceutical Analysis, School of Pharmacy bGLP Center, School of Life Science and Bio-pharmaceutics cDepartment of Mathematics dDepartment of Computer Science, School of Medical Devices, Shenyang Pharmaceutical University, Shenyang, China.
authors.forename: Xi
authors.initials: X
authors.lastname: Liu
authors.forename: Chen-chen
authors.initials: CC
authors.lastname: Zhang
authors.forename: Zheng
authors.initials: Z
authors.lastname: Liu
authors.forename: Lan
authors.initials: L
authors.lastname: Wei
authors.forename: Yan-jie
authors.initials: YJ
authors.lastname: Liu
authors.forename: Jing
authors.initials: J
authors.lastname: Yu
authors.forename: Li-xin
authors.initials: LX
authors.lastname: Sun
mesh_terms: D000704:Analysis of Variance; D000970:Antineoplastic Agents / Q000494:pharmacology*; D054316:Biomarkers, Pharmacological / Q000032:analysis / Q000378:metabolism; D045744:Cell Line, Tumor; D002853:Chromatography, Liquid; D006801:Humans; D055442:Metabolome; D009711:Nucleotides / Q000032:analysis* / Q000378:metabolism; D025341:Principal Component Analysis; D012372:ROC Curve
chemical_list: D000970:Antineoplastic Agents; D054316:Biomarkers, Pharmacological; D009711:Nucleotides