Resolution of the function of cancer cells and the application for tailor-made therapy using bio-simulation analysis

近年来，代谢组学分析技术得到了长足的发展，不仅应用于细菌和植物的研究，还应用于包括癌症科学在内的临床和药物疗效研究。在代谢组学分析的多种分析方法中，我们特别选择了毛细管电泳质谱（CE-MS），并建立了一种基于CE-MS的方法来全面分析带电的低分子量化合物。CE-MS代谢组分析的目标是糖酵解、戊糖磷酸途径、TCA和尿素循环中涉及的化合物，以及涉及氨基酸、多胺、嘌呤和嘧啶代谢的中间体，因此，最适合于表征细胞能量代谢的代谢物的综合量化。同时，药物敏感性研究主要采用基因组学和转录组学方法进行；然而，很少有研究对化合物进行代谢组尺度的分析，并根据细胞代谢的时间变化来研究药物敏感性。因此，为了阐明吉西他滨对癌细胞代谢的影响，阐明潜在的耐药机制，我们对胰腺癌细胞系Panc-1进行了吉西他滨治疗后的时程代谢组分析。通过使用CE-MS对经吉西他滨处理的Panc-1中239种代谢物的时间变化进行量化，我们观察到主要是嘧啶代谢物的预测波动和意想不到的变化，如TCA中间体、氨基酸和嘌呤代谢物的显著增加。未来我们将尝试利用比较代谢组学方法，利用耐药和敏感菌株来阐明细胞对吉西他滨的耐药机制。此外，我们的目标是通过分析血液和尿液样本的代谢组来预测化疗过程中耐药特性的变化。此外，我们还将研究多种药物给药对代谢的影响以及与副作用相关的代谢变化，这在单一药物治疗下是无法观察到的。因此，我们将有助于建立一种基于代谢组分析的易于使用的个体化治疗方法。少

Metabolome analysis technology has been dramatically improved in recent years and applied not only to the research in bacteria and plants but also to clinical and drug efficacy studies including cancer science. Among various analytical methods available for metabolome analysis, we particularly selected capillary electrophoresis mass spectrometry (CE-MS) and established a CE-MS-based method to comprehensively analyze charged, low-molecular-weight compounds. Metabolome analysis by CE-MS targets the compounds involved in glycolysis, the pentose phosphate pathway, the TCA and urea cycles, and the intermediates involved in amino acid, polyamine, purine, and pyrimidine metabolisms, and thus, is best-suited for the integrative quantification of metabolites that characterize the energy metabolism of cells. Meanwhile, research in drug sensitivity has been conducted mainly by applying genomics and transcriptomics approaches; however, few studies conducted metabolome-scale analysis of compounds a … More nd examined the property of drug sensitivity based on the time-change of cell metabolism. Accordingly, in order to elucidate the effect of gemcitabine on the metabolism of cancer cells and clarify the potential drug resistance mechanisms, we conducted time-course metabolome analysis of Panc-1 (a pancreatic cancer cell line) after the treatment with gemcitabine. As a result of quantifying the time-change of 239 metabolites in gemcitabine-treated Panc-1 by using CE-MS, we observed both predicted fluctuations primarily in the pyrimidine metabolites and unexpected changes such as the significant increase of TCA intermediates, amino acids, and purine metabolites. We will attempt to elucidate the resistance mechanism of cells against gemcitabine using the drug-resistant and sensitive strains by exploiting a comparative metabolomics approach in future. Moreover, we aim to predict the change in drug resistance property in the course of chemotherapy treatment by profiling the metabolome of blood and urine samples. Furthermore, we will also investigate the effects of multidrug administrations on the metabolism and the metabolic changes associated with side effects, which cannot be observed under a single drug treatment. We will thus contribute to the establishment of an easy-to-use approach in individualized therapy based on metabolome analysis. Less