使用活性分析、体外筛选和弹性网络回归预测激酶抑制剂反应
Prediction of kinase inhibitor response using activity profiling, in-vitro screening, and elastic net regression
摘要：
许多激酶抑制剂已被批准作为癌症治疗。最近，激酶抑制剂库已被广泛剖析，从而提供了每种化合物对大量靶标的作用强度的图谱。这些分析库定义了药物-激酶网络，可以预测新的未经测试的药物的有效性，并阐明特定激酶在不同细胞系统中所起的作用。基于细胞信号传导的综合网络模型预测药物有效性是困难的，这是由于我们对靶向激酶下游复杂生物过程的部分了解。我们开发了激酶抑制剂弹性网络（KIEN）方法，该方法将药物-激酶网络中包含的信息与体外筛选相结合。该方法使用单个药物和药物对组合的体外细胞反应作为训练集来构建线性和非线性回归模型。除了预测未经测试的药物的有效性外，该方法还鉴定了与给定细胞系中的药物敏感性统计学相关的激酶组。我们比较不同版本的方法，这是基于一个回归技术称为弹性网络。来自两种药物组合的数据导致预测模型，并且可以通过对数据应用对数变换来提高预测性。该方法应用于A549肺癌细胞系。通过该方法鉴定的激酶组的途径富集分析显示，轴突引导、Rac活化和脑信号蛋白相互作用途径与该细胞系中对治疗干预的选择性应答相关。
英文摘要：
Many kinase inhibitors have been approved as cancer therapies. Recently, libraries of kinase inhibitors have been extensively profiled, thus providing a map of the strength of action of each compound on a large number of its targets. These profiled libraries define drug-kinase networks that can predict the effectiveness of new untested drugs and elucidate the role played by specific kinases in different cellular systems. Predictions of drug effectiveness based on a comprehensive network model of cellular signalling are difficult, due to our partial knowledge of the complex biological processes downstream of the targeted kinases. We have developed the Kinase Inhibitors Elastic Net (KIEN) method, which integrates information contained in drug-kinase networks with in vitro screening. The method uses the in vitro cell response of single drugs and drug pair combinations as a training set to build linear and nonlinear regression models. Besides predicting the effectiveness of untested drugs, the method identifies sets of kinases that are statistically associated to drug sensitivity in a given cell line. We compare different versions of the method, which is based on a regression technique known as elastic net. Data from two-drug combinations leads to predictive models, and predictivity can be improved by applying logarithmic transformation to the data. The method is applied to the A549 lung cancer cell line. A pathway enrichment analysis of the set of kinases identified by the method shows that axon guidance, activation of Rac, and semaphorin interactions pathways are associated to a selective response to therapeutic intervention in this cell line.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
