Goltsov Alexey, Tashkandi Ghassan, Langdon Simon P, Harrison David J, Bown James L
School of Science, Engineering and Technology, University of Abertay, Dundee, UK.
Division of Pathology, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.
Eur J Pharm Sci. 2017 Jan 15;97:170-181. doi: 10.1016/j.ejps.2016.11.008. Epub 2016 Nov 8.
The phosphatidylinositide 3-kinases (PI3K) and mammalian target of rapamycin-1 (mTOR1) are two key targets for anti-cancer therapy. Predicting the response of the PI3K/AKT/mTOR1 signalling pathway to targeted therapy is made difficult because of network complexities. Systems biology models can help explore those complexities but the value of such models is dependent on accurate parameterisation. Motivated by a need to increase accuracy in kinetic parameter estimation, and therefore the predictive power of the model, we present a framework to integrate kinetic data from enzyme assays into a unified enzyme kinetic model. We present exemplar kinetic models of PI3K and mTOR1, calibrated on in vitro enzyme data and founded on Michaelis-Menten (MM) approximation. We describe the effects of an allosteric mTOR1 inhibitor (Rapamycin) and ATP-competitive inhibitors (BEZ235 and LY294002) that show dual inhibition of mTOR1 and PI3K. We also model the kinetics of phosphatase and tensin homolog (PTEN), which modulates sensitivity of the PI3K/AKT/mTOR1 pathway to these drugs. Model validation with independent data sets allows investigation of enzyme function and drug dose dependencies in a wide range of experimental conditions. Modelling of the mTOR1 kinetics showed that Rapamycin has an IC independent of ATP concentration and that it is a selective inhibitor of mTOR1 substrates S6K1 and 4EBP1: it retains 40% of mTOR1 activity relative to 4EBP1 phosphorylation and inhibits completely S6K1 activity. For the dual ATP-competitive inhibitors of mTOR1 and PI3K, LY294002 and BEZ235, we derived the dependence of the IC on ATP concentration that allows prediction of the IC at different ATP concentrations in enzyme and cellular assays. Comparison of drug effectiveness in enzyme and cellular assays showed that some features of these drugs arise from signalling modulation beyond the on-target action and MM approximation and require a systems-level consideration of the whole PI3K/PTEN/AKT/mTOR1 network in order to understand mechanisms of drug sensitivity and resistance in different cancer cell lines. We suggest that using these models in a systems biology investigation of the PI3K/AKT/mTOR1 signalling in cancer cells can bridge the gap between direct drug target action and the therapeutic response to these drugs and their combinations.
磷脂酰肌醇3激酶（PI3K）和雷帕霉素哺乳动物靶蛋白1（mTOR1）是抗癌治疗的两个关键靶点。由于网络复杂性，预测PI3K/AKT/mTOR1信号通路对靶向治疗的反应变得困难。系统生物学模型有助于探索这些复杂性，但此类模型的价值取决于准确的参数化。出于提高动力学参数估计准确性从而提高模型预测能力的需求，我们提出了一个框架，将酶活性测定的动力学数据整合到一个统一的酶动力学模型中。我们展示了基于体外酶数据校准并基于米氏（MM）近似建立的PI3K和mTOR1的典型动力学模型。我们描述了变构mTOR1抑制剂（雷帕霉素）和ATP竞争性抑制剂（BEZ235和LY294002）的作用，这些抑制剂对mTOR1和PI3K具有双重抑制作用。我们还对磷酸酶和张力蛋白同源物（PTEN）的动力学进行了建模，PTEN可调节PI3K/AKT/mTOR1通路对这些药物的敏感性。使用独立数据集进行模型验证，可以在广泛的实验条件下研究酶功能和药物剂量依赖性。mTOR1动力学建模表明，雷帕霉素的半数抑制浓度（IC）与ATP浓度无关，并且它是mTOR1底物S6K1和4EBP1的选择性抑制剂：相对于4EBP1磷酸化，它保留了40%的mTOR1活性，并完全抑制S6K1活性。对于mTOR1和PI3K的双重ATP竞争性抑制剂LY294002和BEZ235，我们推导了IC与ATP浓度的依赖性，这使得能够预测在酶和细胞实验中不同ATP浓度下的IC。酶实验和细胞实验中药物有效性的比较表明，这些药物的一些特性源于靶点作用和MM近似之外的信号调节，需要从系统层面考虑整个PI3K/PTEN/AKT/mTOR1网络，以便了解不同癌细胞系中药物敏感性和耐药性的机制。我们建议，在对癌细胞中PI3K/AKT/mTOR1信号进行系统生物学研究时使用这些模型，可以弥合直接药物靶点作用与对这些药物及其组合的治疗反应之间的差距。
