Activity based profiling of Phosphoprotein phosphatases in cancer using mass spectrometry-based proteomics

项目概要 通过激酶抑制剂靶向失调的磷酸化信号传导是一种行之有效的策略，也是该领域的焦点 抗癌治疗的发展。然而，患者反应的变异性和耐药性限制了 疗效不佳，常常导致治疗失败。决定药物功效的根本机制是 多方面的，包括药物靶点本身，以及相关的信号通路。例如，突变 或目标激酶的扩增、相关激酶的功能补偿、激酶的重编程 信号传导，以及磷酸酶信号传导网络的改变，拮抗底物磷酸化或 直接调节激酶活性很常见。 在破译癌症激酶组及其抗癌反应方面取得了巨大进展 治疗。这些研究是通过一系列创新技术实现的，包括化学蛋白质组学 利用固定在珠子上的激酶抑制剂和质谱 (MS) 的策略。 大多数蛋白质去磷酸化是由磷蛋白磷酸酶（PPP）进行的。购买力平价 该家族由九个催化亚基组成，它们与调节亚基和支架亚基结合并组装成 数百种多亚基酶并作为独特的选择性信号实体发挥作用。令人兴奋的是，角色和 PPPs 对正常组织和癌组织细胞信号传导的调节已经开始出现。 虽然激酶组分析提供了有关磷酸化反应的全局信息，但尚不存在这样的技术 磷酸酶；因此，我们缺乏对未充分研究但同样重要的去磷酸化反应的了解 在癌症中。为了解决这一能力差距，我们建立了一种化学蛋白质组学策略，称为“PIB- MS”，用于有效亲和捕获、鉴定和定量所有内源表达的 PPP 及其 对有限蛋白质量的细胞进行单次质谱分析中的相关蛋白质（“PPPome”）， 组织和肿瘤裂解物。在此应用中，我们进一步开发和成熟该技术并评估其 在药物治疗的干扰下，识别和量化乳腺癌细胞系中的 PPPome 的性能， 和乳腺癌 PDX 肿瘤模型，以及原发性人类乳腺癌肿瘤。我们将评估 通过实验室间比较该技术的性能以实现广泛实施。 潜在影响声明。 PPP 已成为癌症中的关键信号实体。然而，目前 目前还没有方法可以快速、定量和全面地评估内源性 PPome 及其 与细胞应激、短期和长期抗癌药物治疗相关的动态变化，或 耐药性的发展。 PIB-MS 是一项高度创新的技术，可为 细胞系、小鼠疾病模型和原发性人类肿瘤的分析。 PIB-MS 将加速和增强 通过快速、定量的方式对基础、转化和临床研究中的癌症进行分子分析 分析 PPP 信号传导、其变化及其对补偿途径之前、期间和之后的影响 抗癌治疗和耐药性的发展。

PROJECT SUMARRY Targeting dysregulated phosphorylation signaling by kinase inhibitors is a proven strategy and a focus in the development of anti-cancer treatments. However, variability in patient responses and drug resistance limit efficacy and often lead to therapy failure. The underlying mechanisms that determine drug efficacy are multifaceted and include the drug target itself, as well as associated signaling pathways. For instance, mutation or amplification of the targeted kinase, functional compensation by related kinases, reprograming of kinase signaling, and alterations in phosphatase signaling networks that antagonize substrate phosphorylation or directly modulate kinase activity are common. Tremendous progress has been made in deciphering the cancer kinome and its response to anti-cancer treatment. These studies were enabled by an array of innovative technologies, including a chemical proteomics strategy that utilizes kinase inhibitors immobilized on beads and mass spectrometry (MS). The majority of protein dephosphorylation is carried out by phosphoprotein phosphatases (PPPs). The PPP family consists of nine catalytic subunits that bind to regulatory and scaffolding subunits and assemble into hundreds of multi-subunit enzymes and function as distinct, selective signaling entities. Excitingly, the role and regulation of PPPs in cellular signaling in normal and cancerous tissue is beginning to emerge. While kinome profiling provides global information on phosphorylation reactions, no such technology exists for phosphatases; thus, we lack knowledge of the understudied, but equally important, dephosphorylation reaction in cancer. To address this gap in capability, we have established a chemical proteomics strategy called “PIB- MS” for efficient affinity-capture, identification, and quantification of all endogenously expressed PPPs and their associated proteins (“PPPome”) in a single mass spectrometry analysis from limited protein amounts of cell, tissue, and tumor lysate. In this application, we further develop and mature this technology and assess its performance to identify and quantify the PPPome in breast cancer cell lines, upon perturbation by drug treatment, and breast cancer PDX tumor models, and in primary human breast cancer tumors. We will assess the performance of this technology in an inter-laboratory comparison to achieve broad implementation. Statement of Potential Impact. PPPs have emerged as critical signaling entities in cancer. However, currently no approach exists for rapid, quantitative, and comprehensive assessment of the endogenous PPPome and its dynamic changes associated with cellular stress, short- and long-term treatment with anti-cancer drugs, or development of drug resistance. PIB-MS is a highly innovative technology that provides these capabilities for the analysis of cell lines, mouse models of disease, and primary human tumors. PIB-MS will accelerate and enhance the molecular analysis of cancer in basic, translational, and clinical research through rapid and quantitative analysis of PPP signaling, its alterations, and its effects on compensatory pathways before, during, and after anti-cancer treatment and upon development of resistance.