Massive single cell proteomics for cancer biology

用于癌症生物学的大规模单细胞蛋白质组学

• 批准号: 10707321
• 负责人: Ljiljana Pasa-Tolic
• 金额: $ 64.75万
• 依托单位: BATTELLE PACIFIC NORTHWEST LABORATORIES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-20 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10707321
• 关键词: Address; Architecture; Benchmarking; Bone Marrow; Cancer Biology; Cell Separation; Cell physiology; Cells; Cellular biology; Clinical; Clinical Treatment; Collaborations; Communities; Coupling; Data; Diagnosis; Digestion; Disease Progression; Disease Resistance; Environment; Evolution; Genomics; Goals; Hematopoietic Neoplasms; Heterogeneity; Human; Immune; Individual; Isotope Labeling; Knowledge; Label; Laboratories; Liquid substance; Malignant - descriptor; Malignant Neoplasms; Mass Spectrum Analysis; Methods; Microfluidics; Molecular; Multiple Myeloma; Nature; Outcome; Pathogenesis; Pathologic; Patients; Performance; Peripheral Blood Mononuclear Cell; Phenotype; Plasma; Plasma Cells; Population; Post-Translational Protein Processing; Preparation; Process; Proteins; Proteome; Proteomics; RNA; Research; Resistance; Running; Sampling; Somatic Cell; Specimen; System; Technology; Therapeutic; Transcript; Universities; Washington; Yeasts; cancer proteomics; cell preparation; chimeric antigen receptor T cells; computational pipelines; cost efficient; data acquisition; density; improved; individual variation; innovation; insight; microchip; nanoDroplet; neoplastic cell; next generation; next generation sequencing; personalized medicine; protein biomarkers; protein expression; protein profiling; relapse patients; single cell technology; single-cell RNA sequencing; success; therapy resistant; transcriptomics; tumor; tumor heterogeneity; tumor progression; tumor-immune system interactions

PROJECT SUMMARY/ABSTRACT Single-cell technologies have become the cornerstone of biomedical and cell biology research. Next- generation sequencing-based technologies have enabled large-scale characterization of transcript expressions in single cells from clinical specimens and reveal unexpected cellular heterogeneity related to pathogenesis. However, many integrative studies have shown only low to moderate correlations between the abundance of RNA transcripts and their corresponding proteins, the main determinants of cell phenotype. We hypothesize mass spectrometry-based single-cell proteomics could provide direct insight on the cellular heterogeneity and inform protein markers related to disease progression and resistance to therapy. The overall objective of this project is to develop a high throughput single-cell proteomics (scProteomics) platform to enable the routine analysis of >10,000 single cells at a depth of 2000 proteins in a cost-efficient way. The developed technology will be disseminated to the research community through close collaboration with a commercial partner. We will also apply scProteomics to interrogate the heterogeneity of both malignant plasma cell and immune cell populations from multiple myeloma patients. We will pursue these goals through three specific aims: 1) To establish an ultra-high throughput single-cell preparation method by coupling an enhanced multiplexing method with high-density nested nanoPOTS chips and multi-channel droplet dispensing system; We aim to process >2000 cells in a single microchip, and multiplex-label 36 single cells for a single LC-MS analysis; 2) To advance the throughput, sensitivity, and quantitation accuracy of LC-MS system. A dual-column nanoLC system and a FAIMS-based MS acquisition method will be developed to enable the analysis of >860 cells per day with high quantitation precision; 3) To apply scProteomics to profile ~10,000 plasma and immune cells from MM patients. We will integrate scProteomics with existing scRNA-seq data to explore tumor heterogeneity, chimeric antigen receptor T-cells (CAR-T) markers, and the immune microenvironment in multiple myeloma. This research is highly innovative because the proposed single-cell proteomics platform will be the first of its kind to routinely and reliably characterize > 10,000 single cells at a throughput comparable to single-cell transcriptomics. It is also the first scProteomics study of primary liquid tumor cells isolated from the pathological environment, e.g. bone marrow of MM patients. Statement of Impact: Tumor heterogeneity has indispensable implications in cancer evolution, tumoral spatial organization, and clinical treatment. Single-cell proteomics could provide a basis to unravel these complicated relationships and to clarify the mechanisms of cancer progression and subclone resistance to therapeutic treatments.

项目摘要/摘要 单细胞技术已成为生物医学和细胞生物学研究的基石。下一个- 基于生成测序的技术已实现了成绩单表达式的大规模表征 在临床标本的单个细胞中，揭示了与发病机理有关的意外细胞异质性。 但是，许多综合研究仅显示丰度之间的相关性低到中等相关性 RNA转录本及其相应的蛋白质，是细胞表型的主要决定因素。我们假设 基于质谱的单细胞蛋白质组学可以直接了解细胞异质性和 告知与疾病进展和对治疗抗性有关的蛋白质标志物。总体目标 项目将开发高吞吐量单细胞蛋白质组学（SCProteomics）平台以启用例程 以经济高效的方式分析在2000蛋白质深度的> 10,000个单元。开发的技术 通过与商业合作伙伴的密切合作，将传播到研究社区。我们将 还应应用ScProteomics询问恶性血浆细胞和免疫细胞的异质性 来自多个骨髓瘤患者的种群。我们将通过三个具体目标来追求这些目标：1） 通过耦合增强的多路复用方法来建立超高吞吐量的单细胞制备方法 具有高密度的嵌套纳米芯片和多通道液滴分配系统；我们的目标是处理 单个微芯片中的> 2000个细胞和多路标签36个单细胞用于单个LC-MS分析； 2）到 提高LC-MS系统的吞吐量，灵敏度和定量精度。双列纳米克 将开发系统和基于FAIMS的MS采集方法，以实现对> 860个单元的分析 日常精确度； 3）将SCPROTEOMICS应用于概述〜10,000个血浆和免疫细胞 来自MM患者。我们将将ScProteomics与现有的SCRNA-SEQ数据集成以探索肿瘤 异质性，嵌合抗原受体T细胞（CAR-T）标记和免疫微环境 多发性骨髓瘤。这项研究具有很高的创新性，因为拟议的单细胞蛋白质组学平台将 成为同类中的第一个常规和可靠地表征> 10,000个单元格的吞吐量 单细胞转录组学。这也是对从中分离的原发性液体肿瘤细胞的首次Scproteomics研究 病理环境，例如MM患者的骨髓。影响声明：肿瘤异质性具有 对癌症进化，肿瘤空间组织和临床治疗的不可或缺的影响。单细胞 蛋白质组学可以提供基础来揭示这些复杂的关系，并阐明 癌症进展和亚克隆对治疗治疗的抗性。