A Predictive Model for Selective Targeting of the Warburg Effect through GAPDH Inhibition with a Natural Product.
A Predictive Model for Selective Targeting of the Warburg Effect through GAPDH Inhibition with a Natural Product.
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DOI：
10.1016/j.cmet.2017.08.017
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发表时间：
2017-10-03
期刊：
影响因子：
29
通讯作者：
Locasale JW
中科院分区：
文献类型：
--
作者：
Liberti MV;Dai Z;Wardell SE;Baccile JA;Liu X;Gao X;Baldi R;Mehrmohamadi M;Johnson MO;Madhukar NS;Shestov AA;Chio IIC;Elemento O;Rathmell JC;Schroeder FC;McDonnell DP;Locasale JW
利用遗传学的靶向癌症治疗是成功的，但选择性靶向同样依赖于环境的肿瘤代谢的原理仍然未知。我们现在表明，在Warburg效应（We）期间，速率控制酶的差异，癌细胞代谢的最显著标志，可以用来预测靶向糖代谢的反应。我们建立了一种天然产物，koningic acid (KA)，作为GAPDH的选择性抑制剂，GAPDH是一种酶，我们表征在We期间对代谢具有不同的控制特性。通过机器学习和整合药物基因组学和代谢组学，我们证明了KA的疗效不是由单个基因的状态决定的，而是由体内we的定量程度决定的。因此，WE靶向的基础可以通过超越单个基因状态的分子原理进行编码。Liberti等人利用代谢控制分析和多组学方法表明，GAPDH酶对癌细胞中的Warburg效应具有限速作用。他们确定了一个治疗窗口，其中部分GAPDH抑制对高度糖酵解性肿瘤更具选择性，强调了代谢是精准医学的一个组成部分。
Targeted cancer therapies that use genetics are successful, but principles for selectively targeting tumor metabolism that is also dependent on the environment remain unknown. We now show that differences in rate-controlling enzymes during the Warburg Effect (WE), the most prominent hallmark of cancer cell metabolism, can be used to predict a response to targeting glucose metabolism. We establish a natural product, koningic acid (KA), to be a selective inhibitor of GAPDH, an enzyme we characterize to have differential control properties over metabolism during the WE. With machine learning and integrated pharmacogenomics and metabolomics, we demonstrate that KA efficacy is not determined by the status of individual genes, but by the quantitative extent of the WE leading to a therapeutic window in vivo. Thus, the basis of targeting of the WE can be encoded by molecular principles that extend beyond the status of individual genes. Liberti et al. use metabolic control analysis and multi-omics approaches to show that the enzyme GAPDH is rate limiting for the Warburg effect in cancer cells. They identify a therapeutic window where partial GAPDH inhibition is more selective for highly glycolytic tumors, highlighting how metabolism is an integral part of precision medicine.
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