Massive single cell proteomics for cancer biology

项目总结/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。下一篇： 基于世代测序的技术使得能够大规模表征转录物表达 在来自临床标本的单细胞中，并揭示了与发病机制相关的意想不到的细胞异质性。 然而，许多综合性研究表明， RNA转录物及其相应的蛋白质，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提供对细胞异质性的直接洞察， 告知与疾病进展和对治疗的抗性相关的蛋白质标志物。本报告的总体目标 一个项目是开发一个高通量的单细胞蛋白质组学（scProteomics）平台，使常规 以具有成本效益的方式在2000种蛋白质的深度分析> 10，000个单细胞。研究开发成果 将通过与商业伙伴的密切合作向研究界传播。我们将 并将scProteomics应用于探讨恶性浆细胞和免疫细胞的异质性 来自多发性骨髓瘤患者的人群。我们将通过三个具体目标来实现这些目标： 结合增强型多重方法建立超高通量单细胞制备方法 高密度嵌套nanoPOTS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>2000个细胞，并且多重标记36个单细胞用于单个LC-MS分析; 2） 提高LC-MS系统的通量、灵敏度和定量准确度。双柱纳米LC 系统和基于FAIMS的MS采集方法将被开发，以使分析>860个细胞/ 3）应用scProteomics分析~ 10，000个血浆和免疫细胞 MM患者。我们将整合scProteomics与现有的scRNA-seq数据，以探索肿瘤 异质性、嵌合抗原受体T细胞（CAR-T）标志物和免疫微环境， 多发性骨髓瘤这项研究具有高度创新性，因为所提出的单细胞蛋白质组学平台将 成为同类产品中第一个常规和可靠地表征> 10，000个单细胞的能力， 单细胞转录组学这也是第一个对从大肠杆菌中分离的原发性液体肿瘤细胞进行的scProteomics研究。 病理环境，例如MM患者的骨髓。影响声明：肿瘤异质性 在癌症演变、肿瘤空间组织和临床治疗中具有不可或缺的意义。单细胞 蛋白质组学可以提供一个基础，以解开这些复杂的关系，并澄清机制， 癌症进展和亚克隆对治疗性治疗的抗性。

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.