Precision lung cancer therapy design through multiplexed adapter measurement

项目摘要 联合治疗对于克服靶向药物的内在和获得性耐药性具有相当大的希望。 但是，这将依赖于我们精确识别特定肿瘤的最佳药物组合的能力。而 人们非常关注使用基因组信息指导治疗方法，但许多阻力 这些机制不依赖于遗传变化，事实上，可以完全由肿瘤内部的外在因素引起。 微环境。例如，尽管受体酪氨酸激酶（RTK）AXL广泛涉及 对靶向治疗如针对EGFR的治疗的抗性，其通过磷脂酰丝氨酸的调节， 相对于突变，扩增或自分泌配体，使识别肿瘤，将响应AXL- 靶向治疗尤其具有挑战性。 我们建议研究旁路阻力过程中的下游和受体近端信号传导 由AXL介导，然后跨越更广泛的RTK面板。将这些测量与定量 建模将识别受体、相互作用的适配器和下游信号之间的连接 事件，从而定义了肿瘤细胞存活所需的信号网络变化的基本集合。 对靶向治疗的反应。然后，我们将通过测量RTK适配器来应用这种理解 使用邻近连接的相互作用来预测RTK驱动旁路阻力，并在一个实验中测试这些预测。 一组患者来源的异种移植肿瘤。 这项工作将大大提高我们确定有效药物组合的能力， 一种基于机制的测定法，用于鉴定肿瘤细胞依赖于许多RTK中的哪一种存活， (b)提高我们对网络级旁路电阻如何由于激活而产生的确切基本理解 在受体近端和下游信号层的非靶向RTK，以及（c）扩大我们的 了解RTK AXL与耐药性、肿瘤扩散和免疫回避的联系。

Project Summary Combination therapy holds considerable promise for overcoming intrinsic and acquired resistance to targeted therapies but will rely on our ability to precisely identify the best drug combination for particular tumors. While immense focus exists on using genomic information to direct therapeutic approach, many resistance mechanisms do not rely on genetic changes and, in fact, can arise from entirely tumor-extrinsic factors within the microenvironment. For example, though the receptor tyrosine kinase (RTK) AXL is widely implicated in resistance to targeted therapies such as those directed against EGFR, its regulation by phosphatidylserine, as opposed to mutation, amplification or autocrine ligand, make identifying the tumors that will respond to AXL- targeted therapy especially challenging. We propose to study both downstream and receptor-proximal signaling during bypass resistance mediated by AXL, and then across a wider panel of RTKs. Integrating these measurements with quantitative modeling will identify the connectivity between receptors, interacting adapters, and downstream signaling events, thereby defining the essential set of signaling network changes required for tumor cell survival in response to targeted therapeutics. We will then apply this understanding by measuring RTK-adapter interaction using proximity ligation to predict the RTKs driving bypass resistance and test these predictions in a panel of patient-derived xenograft tumors. This work will considerably improve our ability to identify effective drug combinations by (a) developing a mechanism-based assay for identifying which among many RTKs tumor cells are relying upon for survival, (b) improving our basic understanding of exactly how network-level bypass resistance arises due to activation of non-targeted RTKs both at the receptor-proximal and downstream signaling layer, and (c) expanding our understanding of the RTK AXL with links to resistance, tumor spread, and immune avoidance.