Single-Cell Protein Activity Profiling in Breast Cancer Cells and Tissues

乳腺癌细胞和组织中的单细胞蛋白质活性分析

• 批准号: 10640998
• 负责人: Raymond E Moellering
• 金额: $ 38.19万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-08 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10640998
• 关键词: Address; Advanced Development; Atlas of Cancer Mortality in the United States; Benchmarking; Biological; Biological Markers; Biopsy; Breast; Breast Cancer Cell; Breast Cancer Patient; Cancer cell line; Cell Line; Cells; Chemicals; Clinic; Clinical; Complex; Data; Development; Diagnosis; Disease; Early Intervention; Elements; Enzymes; Family; Future; Goals; Grant; Human; Image; In Situ; Individual; Knowledge; Ligation; Malignant Neoplasms; Mammary Neoplasms; Maps; Measurement; Measures; Messenger RNA; Methods; Microfluidics; Molecular; Molecular Probes; Molecular Profiling; Neoplasm Circulating Cells; Neoplasm Metastasis; Operative Surgical Procedures; Organism; Outcome; Patient Care; Patients; Phosphotransferases; Positioning Attribute; Primary Neoplasm; Protein Family; Proteins; Proteome; Proteomics; Publishing; Punch Biopsy; Reagent; Reporting; Research; Resolution; Sampling; Services; Severity of illness; Signal Transduction; Specimen; Technology; Testing; Therapeutic; Tissue Sample; Tissues; Tumor Tissue; Validation; Visualization; anticancer research; cancer cell; chemoproteomics; clinical application; design; detection platform; enzyme activity; human disease; improved; innovation; malignant breast neoplasm; molecular phenotype; novel; protein biomarkers; single cell proteins; technology platform; technology validation; translational applications; treatment response; tumor

Project Summary Advances in molecular profiling technologies have enabled the identification of ever-increasing numbers of disease biomarkers, each raising the potential for more precise, and possibly even patient-specific, diagnoses. Current methods of quantifying protein biomarkers, however, are slow and laborious, often require large quantities of biopsied tissues, and ultimately fail to provide a complete, intact quantification of functional protein activity. To address these limitations, we have developed an innovative activity dependent proximity ligation platform (ADPL), with the ultimate goal of obtaining multiplexed, ultrasensitive quantification of protein activity directly in complex biological samples. In the context of cancer specimens, we hypothesize that defining a molecular profile based on protein activity – the end result of biologic signaling – can more precisely and accurately inform diagnoses and treatment regimes, allowing early intervention and improving clinical outcomes. This proposal outlines the advanced development and validation of two reliable, high-resolution ADPL-based platforms, with the power to alternately visualize and quantify dozens of active enzymes simultaneously from tumor tissue, cells and biofluids. Our current knowledge and expertise in the use of this integrated platform will be leveraged in the service of the following aims: 1) development of novel chemoproteomic probes for multiplexed, family-wide activity mapping of cancer-relevant enzymes, including kinases; 2) advanced development of on-tissue Exchange-ADPL and on-chip single-cell ADPL (scADPL) platforms for simultaneous, high resolution visualization and quantification of a panel of active enzymes in situ; and 3) applying these technologies to breast cancer tissues and cells to create accurate and precise activity signatures and identify potential correlations between these signatures and clinical outcomes. To accomplish these aims we will develop new chemical proteomic molecular probes, validate a panel of ADPL reagents for cancer-associated enzyme biomarkers, and perform rigorous, metric-driven benchmarking analyses in cell lines and tumor tissues. Completion of this project will validate ADPL platforms for use in diverse cancers, provide the first single-cell activity profiles of breast tumors, and provide novel correlations between breast cancer tumor activity signatures, disease severity and response to therapy.

项目摘要 分子谱分析技术的进步使得能够鉴定越来越多的 疾病生物标志物，每一个都提高了更精确的潜力，甚至可能是患者特异性的诊断。 然而，目前的定量蛋白质生物标志物的方法缓慢且费力，通常需要大量的时间和精力。 大量的活组织检查的组织，并最终不能提供一个完整的，完整的定量功能蛋白质 活动为了解决这些限制，我们开发了一种创新的活性依赖性邻近连接， 平台（ADPL），最终目标是获得多路复用的，超灵敏的蛋白质活性定量 直接在复杂的生物样品中。在癌症标本的背景下，我们假设定义一个 基于蛋白质活性的分子图谱--生物信号的最终结果--可以更精确， 准确地告知诊断和治疗方案，允许早期干预和改善临床结果。 该提案概述了两个可靠的、基于高分辨率ADPL的 平台，具有交替可视化和定量数十种活性酶同时从 肿瘤组织、细胞和生物流体。我们目前在使用这一综合平台方面的知识和专长将 1）开发新的化学蛋白质组学探针， 癌症相关酶（包括激酶）的多路、全家族活性图谱; 2）先进的 开发组织上交换-ADPL和芯片上单细胞ADPL（scADPL）平台， 一组活性酶原位的高分辨率可视化和定量;以及3）应用这些 乳腺癌组织和细胞的技术，以创建准确和精确的活动签名，并确定 这些特征和临床结果之间的潜在相关性。为了实现这些目标，我们将开发 新的化学蛋白质组分子探针，验证一组ADPL试剂用于癌症相关酶 生物标志物，并在细胞系和肿瘤组织中进行严格的、度量驱动的基准分析。 该项目的完成将验证ADPL平台用于各种癌症，提供第一个单细胞 乳腺肿瘤的活性谱，并提供了乳腺癌肿瘤活性特征之间的新的相关性， 疾病严重程度和对治疗的反应。