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

代谢物组分析技术近年来得到了极大的改进，不仅应用于细菌和植物的研究，而且还应用于包括癌症科学在内的临床和药物疗效研究。在可用于代谢组分析的各种分析方法中，我们特别选择了毛细管电泳质谱法（CE-MS），并建立了基于CE-MS的方法，以全面分析带电的低分子量化合物。CE-MS代谢物组分析的目标是参与糖酵解、磷酸戊糖途径、TCA和尿素循环的化合物，以及参与氨基酸、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定量。同时，药物敏感性的研究主要采用基因组学和转录组学的方法进行，但很少有研究对化合物进行代谢组尺度的分析， ...更多信息 并根据细胞代谢的时间变化来检测药物敏感性。因此，为了阐明吉西他滨对癌细胞代谢的影响并阐明潜在的耐药机制，我们在吉西他滨治疗后对Panc-1（胰腺癌细胞系）进行了时程代谢组学分析。作为使用CE-MS定量吉西他滨处理的Panc-1中239种代谢物的时间变化的结果，我们观察到主要在嘧啶代谢物中的预测波动和意外变化，例如TCA中间体、氨基酸和嘌呤代谢物的显著增加。我们将尝试利用比较代谢组学的方法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治疗过程中耐药性的变化。此外，我们还将研究多药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无法观察到。因此，我们将有助于建立一个易于使用的方法，在个性化治疗的基础上代谢组学分析。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