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首页> 外文期刊>BMC Cancer >Computational models applied to metabolomics data hints at the relevance of glutamine metabolism in breast cancer
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Computational models applied to metabolomics data hints at the relevance of glutamine metabolism in breast cancer

机译:应用于乳腺癌谷氨酰胺代谢相关性的代谢组合数据提示

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摘要

Metabolomics has a great potential in the development of new biomarkers in cancer and it has experiment recent technical advances. In this study, metabolomics and gene expression data from 67 localized (stage I to IIIB) breast cancer tumor samples were analyzed, using (1) probabilistic graphical models to define associations using quantitative data without other a priori information; and (2) Flux Balance Analysis and flux activities to characterize differences in metabolic pathways. On the one hand, both analyses highlighted the importance of glutamine in breast cancer. Moreover, cell experiments showed that treating breast cancer cells with drugs targeting glutamine metabolism significantly affects cell viability. On the other hand, these computational methods suggested some hypotheses and have demonstrated their utility in the analysis of metabolomics data and in associating metabolomics with patient’s clinical outcome. Computational analyses applied to metabolomics data suggested that glutamine metabolism is a relevant process in breast cancer. Cell experiments confirmed this hypothesis. In addition, these computational analyses allow associating metabolomics data with patient prognosis.
机译:代谢组学在癌症新生物标志物的发展中具有巨大潜力,并且它具有最近的技术进步。在该研究中,分析了来自67个局部化(阶段I至IIIB)乳腺癌肿瘤样本的代谢组合和基因表达数据,使用(1)概率图形模型来定义使用定量数据的关联,没有其他先验信息; (2)助焊剂平衡分析和助焊剂活动,以表征代谢途径的差异。一方面,两次分析都突出了谷氨酰胺在乳腺癌中的重要性。此外,细胞实验表明,用靶向谷氨酰胺代谢的药物治疗乳腺癌细胞显着影响细胞活力。另一方面,这些计算方法提出了一些假设,并证明了它们在分析代谢组织数据和与患者的临床结果相关的代谢组科的效用。应用于代谢组的计算分析表明谷氨酰胺代谢是乳腺癌的相关过程。细胞实验证实了这一假设。此外,这些计算分析允许将代谢组科数据与患者预后相关联。

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