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

项目总和 通过激酶抑制剂靶向调节异常的磷酸化信号是一种成熟的策略，也是目前研究的一个重点。 抗癌治疗的发展。然而，患者反应的变异性和耐药性限制了 而且往往会导致治疗失败。决定药物疗效的潜在机制是 多方面的，包括药物靶标本身以及相关的信号通路。例如，突变 或靶向激酶的扩增，相关激酶的功能补偿，激酶的重新编程 信号和磷酸酶信号网络中拮抗底物磷酸化或 直接调节激酶活性是很常见的。 在破译癌症基因组及其对抗癌的反应方面取得了巨大的进展 治疗。这些研究是由一系列创新技术实现的，包括一种化学蛋白质组学 利用固定在珠子上的激酶抑制剂和质谱仪(MS)的策略。 大部分蛋白质去磷酸化是由磷酸蛋白磷酸酶(PPPs)完成的。购买力平价 家族由9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 数以百计的多亚单位酶和功能作为不同的，选择性的信号实体。令人兴奋的是，这个角色和 在正常和癌症组织中，PPP在细胞信号中的调节开始出现。 虽然动态组图谱提供了有关磷酸化反应的全球信息，但目前还没有这样的技术用于 因此，我们对未被充分研究但同样重要的去磷酸化反应缺乏了解。 在癌症中。为了解决这一能力差距，我们建立了一种名为“PIB--”的化学蛋白质组学策略。 MS“，用于有效地捕获、鉴定和量化所有内源性表达的PPP及其 结合蛋白(PPPome)在从有限的细胞蛋白量中进行的单一质谱分析中， 组织和肿瘤裂解物。在这一应用中，我们进一步开发和成熟了这项技术，并评估了其 在药物治疗的干扰下，在乳腺癌细胞系中识别和量化PPPome的性能， 和乳腺癌PDX肿瘤模型，以及人乳腺癌原发肿瘤。我们将评估 这项技术在实验室间进行了性能比较，实现了广泛的实施。 关于潜在影响的声明。PPP已成为癌症中的关键信号实体。不过，目前 没有一种方法可以快速、定量和全面地评估内源性PPPome及其 与细胞应激、抗癌药物短期和长期治疗有关的动态变化，或 耐药性的发展。PIB-MS是一种高度创新的技术，它为 分析细胞系、小鼠疾病模型和人类原发肿瘤。PIB-MS将加速和增强 通过快速和定量的方法在基础、翻译和临床研究中对癌症进行分子分析 PPP信号、变化及其在代偿通路中的作用分析 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.