An integrated microtechnology platform for spatially resolved mass spectrometry-based proteomics

用于基于空间分辨质谱的蛋白质组学的集成微技术平台

• 批准号: 10564117
• 负责人: Sindy Kam-Yan Tang
• 金额: $ 63.98万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-06 至 2027-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10564117
• 关键词: Acceleration; Address; Antibodies; Biological; Biomedical Research; Cancer Biology; Cell physiology; Cells; Couples; Data; Development; Devices; Diagnosis; Disease; Dissection; Early Diagnosis; Ethanol; Extracellular Protein; Functional disorder; Goals; Heterogeneity; Human; Immunosuppression; Intervention; Label; Liquid Chromatography; Manuals; Maps; Mass Spectrum Analysis; Measures; Methods; Microdissection; Microfluidic Microchips; Microfluidics; Molecular; Neoplasm Metastasis; Outcome; Pathology; Pathway interactions; Pharmaceutical Preparations; Play; Post-Translational Protein Processing; Preparation; Process; Proteins; Proteome; Proteomics; Publishing; RNA; Resolution; Role; Running; Sampling; Site; Slice; Spatial Distribution; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; Technology; Tissue Preservation; Tissues; Tumor Tissue; Work; biomarker identification; cancer initiation; clinical diagnostics; design; fabrication; imaging approach; innovation; innovative technologies; laser capture microdissection; mass spectrometric imaging; meter; nano; nanoDroplet; nanofabrication; new technology; new therapeutic target; novel; novel marker; novel therapeutic intervention; preservation; protein biomarkers; response; skin squamous cell carcinoma; spatial integration; tandem mass spectrometry; technology platform; therapeutic target; tissue fixing; tissue mapping; transcriptomics; tumor; tumor heterogeneity; tumor initiation; tumor microenvironment; tumor progression

Project Summary The spatial organization of cells and molecules in biological tissues plays a critical role in pathophysiology. For example, spatial heterogeneity in the tumor microenvironment determines tumor initiation, metastasis, and drug response. Despite advances in spatial transcriptomics to map RNA in tissues, it is proteins, rather than RNA, that drive most cellular processes and determine disease state. As protein abundance cannot be inferred precisely from transcriptomic data, it is important to measure protein abundance and their spatial distribution to better predict pathophysiological phenomena, as well as to identify biomarkers and therapeutic targets. Previous work on spatial proteomics is based on antibody recognition, mass spectrometry imaging, or physical dissection of the tissue followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Antibody-based and mass spectrometry imaging approaches have low proteome coverage (<100 proteins). The only approach with deep coverage (>3000 proteins) is tissue dissection followed by LC-MS/MS. This method leverages the power of state-of-the-art LC-MS/MS to achieve in-depth quantification of thousands of proteins along with their post-translational modifications. However, this approach is limited by current dissection methods. Manual dissection has low throughput and poor spatial resolution. Laser capture microdissection (LCM) has high resolution, but the isolation of many pixels, required for tissue mapping, is tedious and suffers from sample loss. The goal of this project is to develop a high throughput and scalable technology to perform tissue microdissection that preserves tissue spatial information and couples directly to established LC-MS/MS workflow for deep and unbiased spatial mapping of the proteome. We will demonstrate our technology on tumor slices of cutaneous squamous cell carcinoma. Our approach integrates a novel tissue micro-dicing device (“µDicer”), a nanodroplet sample preparation platform (“nanoPOTS”) for LC-MS/MS analysis with single-cell sensitivity, and a microfluidic device (“µMapper”) to transfer the diced tissue pixels from the µDicer to the nanoPOTS array while preserving their spatial order. Our approach is innovative because no technology currently exists to perform tissue micro-dissection and their transfer to macroscopic wells in parallel for LC-MS/MS while preserving spatial information. The specific aims are to optimize the µDicer for dicing fixed tissue slices into 10-100 µm micro-tissue pixels, develop and validate the µMapper to transfer tissue pixels from the µDicer onto nanoPOTS chips, and develop a high throughput and integrated spatial proteomics workflow and apply it to map human tumor slices. The project is significant because it will accelerate mass spectrometry-based spatial proteomics, thereby advancing our understanding of the role of tissue heterogeneity in pathophysiology, such as the role of the tumor microenvironment on cancer progression, and will enable the identification of novel protein biomarkers and therapeutic targets to facilitate the early detection, diagnosis, and intervention of diseases.

项目摘要 生物组织中细胞和分子的空间组织在病理生理学中起关键作用。为了 例如，肿瘤微环境中的空间异质性决定了肿瘤的启动，转移和药物 回复。尽管空间转录组学的进步是在组织中绘制RNA，但它是蛋白质，而不是RNA，而不是RNA， 这推动了大多数细胞过程并确定疾病状态。因为无法推断蛋白质丰度 准确地说是从转录组数据中，测量蛋白质丰度及其空间分布至关重要 更好地预测病理生理现象，并确定生物标志物和治疗靶标。 先前关于空间蛋白质组学的工作基于抗体识别，质谱成像或 组织的物理解剖，然后进行液相色谱串联质谱法（LC-MS/MS）。 基于抗体和质谱成像方法的蛋白质组覆盖率低（<100蛋白）。这 只有深层覆盖范围（> 3000蛋白）的方法是组织解剖，其次是LC-MS/MS。此方法 利用最先进的LC-MS/MS的功能，以实现数千种蛋白质的深入量化 以及他们的翻译后修改。但是，这种方法受当前解剖方法的限制。 手动解剖的吞吐量较低，空间分辨率差。激光捕获显微解剖（LCM）具有高 分辨率，但是组织映射所需的许多像素的隔离是乏味的，并且遭受样本损失的困扰。 该项目的目的是开发高通量和可扩展技术来执行组织 微分辨率可保留组织空间信息，并直接伴侣与已建立的LC-MS/MS工作流程 用于蛋白质组的深层和无偏的空间映射。我们将在肿瘤切片上演示我们的技术 皮肤鳞状细胞癌。我们的方法整合了一种新型的组织微涂料装置（“ µdicer”） 用于LC-MS/MS分析单细胞灵敏度的Nanodroplet样品制备平台（“纳米机”），并且 微流体设备（“ µmapper”）将切成丁的组织像素从µdicer传递到纳米型阵列 保留其空间命令。我们的方法具有创新性，因为目前没有任何技术可以执行 在保留空间的同时，在LC-MS/MS的同时，组织微脱落及其转移到宏观井中 信息。具体的目的是优化µDICER，以将固定组织切片切成10-100 µm微问题 像素，开发和验证µmapper以将组织像素从µdicer转移到纳米芯片上，然后 开发高通量和集成的空间蛋白质组学工作流程，并将其应用于映射人类肿瘤切片。 该项目很重要，因为它将加速基于质谱的空间蛋白质组学，从而加速 促进我们对组织异质性在病理生理学中的作用的理解，例如肿瘤的作用 关于癌症进展的微环境，并将鉴定出新的蛋白质生物标志物和 促进疾病的早期发现，诊断和干预的治疗靶标。