Biosensor Assay to Screen for Signaling Pathway Inhibition in Cancer

描述(申请人提供)：激酶抑制剂在化疗中创造了一种新的范例，是肿瘤新药开发的主要焦点，但开发成功率很低(5-10%)。对激酶抑制剂的耐药性是通过靶点依赖机制(例如，取消药物结合的点突变)和靶点非依赖机制(例如，替代信号通路上调，称为“动态组重编程”)发生的。因此，一次针对几个激酶的抑制剂组合是可取的，以有更好的机会避免耐药/复发循环。检测活细胞(而不是裂解物或重组系统)中的蛋白激酶活性对于了解激酶抑制剂的药物敏感性和耐药机制非常重要，并将导致更好地筛选可能通过开发过程的抑制剂。我们将开发对抑制反应和动态组重新编程重要的特定激酶活性的多路、基于细胞的分析，并使用它们来检测患者细胞中的激酶激活情况和进行抑制剂筛选。生物传感器的磷酸化是通过时间分辨的稀土发光测量来检测的，其中Tb3+的发射能量是通过小分子荧光团直接测量的，从而根据荧光团的不同而给出不同的发射颜色。在目标1中，我们将建立药物敏感和耐药CML细胞中关键激酶活性(从而抑制)的定量分析，描述与治疗相关的细胞状态下的通路激活表型。我们将使用我们在前期工作中已经建立的一套生物传感器，并在开发其他激酶时添加生物传感器。这些检测将以CML患者的细胞系和样本(与健康对照组相比)为基础，并通过RT-qPCR和SWATH蛋白质组学进行验证。在目标2中，我们将筛选现有的激酶抑制剂药物和新化合物之间的协同作用(通过文库)。我们还将利用从稀土元素到有机染料的能量转移，开发生物传感器磷酸化的均相多重分析。在目标3中，我们扩展了生物传感器设计流水线，以开发新的、非天然的多肽底物，用作其他酶的生物传感器。这一目标中描述的工作将增加我们现有的一套生物传感器。这项提议中所描述的工作的完成将为我们提供一种新的多种激酶的分析方法，一套新的生物传感器，以及用于筛查的新的和改进的检测策略。药物发现将受益于这项技术通过一次瞄准几个激酶来解决动态组重新编程机制的能力。药物开发将受益于对多个靶点的伴随分析，这些靶点可以跟随药物或药物组合通过HIT过渡到主导过渡、靶点验证、临床前研究、临床试验，甚至更多地进入治疗管理。这项测试及其相关工具将通过在药物筛选和开发过程中对疾病环境进行建模的能力取得新的突破，为下一代癌症靶向治疗的开发做出贡献。

DESCRIPTION (provided by applicant): Kinase inhibitors created a new paradigm in chemotherapy and are a major focus of new oncology drug development, but developmental success rates are low (5-10%). Resistance to kinase inhibitors occurs through target-dependent mechanisms (e.g. point mutations that abrogate drug binding) and target-independent mechanisms (e.g. upregulation of alternative signaling pathways, termed "kinome reprogramming"). Therefore, combinations of inhibitors that target several kinases at once are desirable to have a better chance of avoiding the resistance/relapse cycle. Detecting protein kinase activity inside living cells (rather than in lysates or reconstituted systems) is important or understanding kinase inhibitor drug sensitivity and resistance mechanisms, and would lead to better screening for inhibitors likely to make it through the development process. We will develop multiplexed, cell-based assays for specific kinase activities that are important to inhibitor response and kinome reprogramming, and use them to detect kinase activation profiles in patient cells and for inhibitor screens. Phosphorylation of the biosensors is detected using time-resolved lanthanide luminescence measurements, in which Tb3+ emission energy is measured directly via small molecule fluorophores to give different emission colors depending on the fluorophore. In Aim 1, we will establish quantitative assays for activity (and therefore inhibition) of key kinases in drug sensitive and drug resistant CML cells, profiling the pathway activation phenotypes in therapeutically relevant cellular states. We will use the set of biosensors we have already established in preliminary work, and add biosensors for other kinases as they are developed. The assays will be established with cell lines and samples from CML patients (comparing to healthy controls), and validated with RT-qPCR and SWATH" proteomics. In Aim 2, we will screen for synergies between existing kinase inhibitor drugs and new compounds (via libraries). We will also develop homogenous multiplexed analysis of biosensor phosphorylation using energy transfer from lanthanides to organic dyes. In Aim 3, we expand the biosensor design pipeline to develop new, non-natural peptide substrates to use as biosensors for other kinases. The work described in this aim will add to the set of biosensors we already have available. Completion of the work described in this proposal will give us a novel assay for multiple kinases, a suite of new biosensors as well as new and refined detection strategies to use in screening. Drug discovery will benefit from this technology's ability to address kinome reprogramming mechanisms by targeting several kinases at a time. Drug development will benefit from companion assays for multiple targets that could follow a drug or drug combination through the hit to lead transition, target validation, pre-clinical studies, clinial trials, and beyond into treatment management. This assay and its associated tools will contribute to the next generation of targeted therapy development in cancer by breaking new ground in our ability to model the disease environment during drug screening and development.