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

使用基于质谱的蛋白质组学对癌症中磷蛋白磷酸酶进行基于活性的分析

• 批准号: 9917701
• 负责人: Scott A. Gerber
• 金额: $ 39.22万
• 依托单位: DARTMOUTH COLLEGE
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9917701
• 关键词: Address; Affinity; Antineoplastic Agents; Basic Science; Binding; Breast Cancer cell line; Calcineurin; Cancer Etiology; Cancerous; Catalytic Domain; Cell Line; Cells; Cellular Stress; Chemicals; Clinical Research; Development; Disease; Disease model; Drug Targeting; Drug resistance; Enzymes; Equilibrium; Family; Family member; Financial compensation; Holoenzymes; Human; Immobilization; Injections; Knowledge; Laboratories; Lead; Malignant Neoplasms; Mass Spectrum Analysis; Modeling; Modification; Molecular Analysis; Mus; Mutation; PDPK1 gene; Pathway interactions; Patients; Performance; Pharmacotherapy; Phosphoric Monoester Hydrolases; Phosphorylated Peptide; Phosphorylation; Phosphotransferases; Plant Resins; Post-Translational Protein Processing; Protein Dephosphorylation; Protein Kinase; Protein Phosphatase 2A Regulatory Subunit PR53; Protein phosphatase; Proteins; Proteomics; Reaction; Regulation; Research; Resistance development; Role; Sampling; Signal Pathway; Signal Transduction; Simian virus 40; Small T Antigen; Technology; Testing; Therapeutic Intervention; Tissues; Translational Research; Treatment Failure; Tumor Suppressor Proteins; Xenograft Model; anticancer treatment; base; cyanoginosin LR; drug development; drug efficacy; human disease; innovation; innovative technologies; kinase inhibitor; malignant breast neoplasm; mouse model; new therapeutic target; patient response; phosphatase inhibitor; protein phosphatase 6; response; scaffold; tumor

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.

Sumarry项目 针对激酶抑制剂靶向失调的磷酸化信号传导是一种经过验证的策略，并且重点是 抗癌治疗的发展。但是，患者反应和耐药性极限的变化 功效，通常导致治疗失败。确定药物效率的基本机制是 多方面，包括药物靶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，重新编程激酶 信号传导以及拮抗底物磷酸化或拮抗磷酸酶信号网络的改变或 直接调节激酶活性是常见的。 在破译癌症的癌症及其对抗癌的反应方面已经取得了巨大进展 治疗。这些研究是通过一系列创新技术来实现的，包括化学蛋白质组学 利用固定在珠子和质谱法（MS）上的激酶抑制剂的策略。 大多数蛋白质去磷酸化是通过磷酸蛋白磷酸酶（PPP）进行的。 家庭由九种催化亚基组成，这些亚基与调节和脚手架结合并组装成 数百种多生子酶，并且起着独特的选择性信号传导实体的作用。令人兴奋的是角色和 正常组织和取消组织中细胞信号中PPP的调节开始出现。 尽管Kinome分析提供了有关磷酸化反应的全球信息，但没有这样的技术 磷酸酶；因此，我们缺乏对所理解但同样重要的，去磷酸化反应的了解 在癌症中。为了解决能力差距，我们建立了一种称为“ PIB-的化学蛋白质组学策略” MS”，用于有效的亲和力符号，识别和定量所有内源性表达的PPP及其 来自有限蛋白质量细胞的单个质谱分析中的相关蛋白（“ PPPOME”）， 组织和肿瘤裂解物。在此应用中，我们进一步开发和成熟了这项技术并评估 识别和量化乳腺癌细胞系中PPPOME的性能，在药物治疗扰动后， 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 该技术在实验室间比较中的性能以实现广泛的实施。 潜在影响声明。 PPP已成为癌症中的关键信号传导实体。但是，目前 对于内源性Pppome及其ITS的快速，定量和全面评估，没有任何方法 与细胞应激，抗癌药物的短期和长期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 分析细胞系，小鼠疾病模型和原发性人类肿瘤。 PIB-MS将加速并增强 通过快速和定量的基础，翻译和临床研究中癌症的分子分析 PPP信号的分析，其改变及其对补偿途径的影响 抗癌治疗和抗药性发展。