Differential metabolic activity and discovery of therapeutic targets using summarized metabolic pathway models.,npj Systems Biology and Applications

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Differential metabolic activity and discovery of therapeutic targets using summarized metabolic pathway models.
npj Systems Biology and Applications ( IF 3.5 ) Pub Date : 2019-03-01 , DOI: 10.1038/s41540-019-0087-2
Cankut Çubuk ₁ , Marta R Hidalgo ₂ , Alicia Amadoz ₃ , Kinza Rian ₁ , Francisco Salavert ₄ , Miguel A Pujana ₅ , Francesca Mateo ₅ , Carmen Herranz ₅ , Jose Carbonell-Caballero ₆ , Joaquín Dopazo _{1,

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Affiliation

In spite of the increasing availability of genomic and transcriptomic data, there is still a gap between the detection of perturbations in gene expression and the understanding of their contribution to the molecular mechanisms that ultimately account for the phenotype studied. Alterations in the metabolism are behind the initiation and progression of many diseases, including cancer. The wealth of available knowledge on metabolic processes can therefore be used to derive mechanistic models that link gene expression perturbations to changes in metabolic activity that provide relevant clues on molecular mechanisms of disease and drug modes of action (MoA). In particular, pathway modules, which recapitulate the main aspects of metabolism, are especially suitable for this type of modeling. We present Metabolizer, a web-based application that offers an intuitive, easy-to-use interactive interface to analyze differences in pathway metabolic module activities that can also be used for class prediction and in silico prediction of knock-out (KO) effects. Moreover, Metabolizer can automatically predict the optimal KO intervention for restoring a diseased phenotype. We provide different types of validations of some of the predictions made by Metabolizer. Metabolizer is a web tool that allows understanding molecular mechanisms of disease or the MoA of drugs within the context of the metabolism by using gene expression measurements. In addition, this tool automatically suggests potential therapeutic targets for individualized therapeutic interventions.

中文翻译：

使用总结的代谢途径模型进行差异代谢活动和治疗靶点的发现。

尽管基因组和转录组数据的可用性不断增加，但在检测基因表达扰动和理解它们对最终解释所研究表型的分子机制的贡献之间仍然存在差距。新陈代谢的改变是许多疾病（包括癌症）的发生和进展的原因。因此，关于代谢过程的大量现有知识可用于推导机制模型，将基因表达扰动与代谢活动的变化联系起来，从而为疾病的分子机制和药物作用模式（MoA）提供相关线索。特别是，概括代谢主要方面的途径模块特别适合此类建模。我们推出了 Metabolizer，这是一款基于网络的应用程序，它提供了直观、易于使用的交互界面来分析途径代谢模块活动的差异，也可用于类别预测和敲除 (KO) 效应的计算机预测。此外，Metabolizer 可以自动预测恢复患病表型的最佳 KO 干预措施。我们对 Metabolizer 做出的一些预测提供不同类型的验证。Metabolizer 是一种网络工具，可以通过使用基因表达测量来了解代谢背景下疾病的分子机制或药物的 MoA。此外，该工具会自动建议个体化治疗干预的潜在治疗目标。

更新日期：2019-03-01

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