Spectroscopy and spectrometry approaches to elucidating the anti-cancer immune response

阐明抗癌免疫反应的光谱学和光谱测定方法

• 批准号: 2120257
• 金额: --
• 依托单位: Swansea University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2120257
• 关键词: Spectroscopy; spectrometry; approaches; elucidating; anti

Hypothesis: Tissue scanning Raman spectroscopy and mass spectrometry imaging coupled to biological informatics can reveal functional differences in immune checkpoint pathways and their role in the tumour microenvironment.Objectives: 1. To use Raman spectroscopy and biological informatics of single cancer and immune cells to prepare an atlas of characteristic immune checkpoint molecular and chemical signatures. 2. To use this atlas to identify the immune checkpoints active in tumour tissue by adopting a combined Raman imaging and mathematical biology approach. 3. To use mass spectrometry imaging to annotate the Raman-generated spectral fingerprint from tumour tissues on a cell-by-cell basis.Overview: This project proposes the use of tissue scanning and imaging modalities - specifically Raman spectroscopy and mass spectrometry - to elucidate key molecular and chemical pathways operational within tumour tissue that can be aligned to specific immune checkpoint strategies co-opted to counteract any beneficial anti-cancer immune response. The overarching goal is to overcome the limitations of the need to disrupt tumour tissue to understand cellular and chemical interactions between cancer, immune and other cells. This would improve our understanding of the role of the tumour microenvironment in regulating the anti-tumour immune response for detrimental or beneficial effect. Tissue scanning and imaging techniques coupled to biological informatics will enable the whole tissue section approach proposed here. By providing information about the spatial relationship of cells and the molecular and cellular pathways active within intact tumour tissue from patients with pancreatic cancer, new approaches to the design and development of immunotherapeutics can be pursued. Additional to the scanning/imaging and bioinformatic techniques proposed, complementary cellular, molecular and chemical analysis approaches will be used. Firstly, a mathematical biology approach will be used to create an atlas of response patterns linked to activation of different immune checkpoint pathways. These measures will be generated in vitro using cancer cell lines and primary human T cells interrogated with Raman spectroscopy and data processed using AI-based machine learning strategies. This atlas will then be used to inform analysis and interpretation of data from tumour tissue sections interrogated using scanning/imaging Raman spectroscopy to detect active immune checkpoint pathways in tumours ex vivo. This is a novel use for Raman spectroscopy. Identification and annotation of pathway components will be made by mass spectrometry imaging. The spatial alignment of Raman spectroscopy and mass spectrometry data from tissue sections can only be achieved through an AI-based bioinformatic approach. The Raman spectroscopy atlas generated as pivotal to this project will be disseminated for use by other investigators and could be applied to a wider variety of solid tumour types beyond pancreatic cancer as to be studied here. Outcomes: The proposed project will enhance our understanding of the anti-tumour capacity of the tumour microenvironment to inform developments in immunotherapy and precision medicine. It will exploit analytical science approaches that have their foundations in the physical sciences and now are utilised at the interface between chemical biology and clinical technologies. EPSRC Research AreasAnalytical scienceBiological informaticsChemical biology and biological chemistryClinical technologiesMathematical biology

假设：组织扫描拉曼光谱和质谱成像结合生物信息学可以揭示免疫检查点通路的功能差异及其在肿瘤微环境中的作用。使用单个癌症和免疫细胞的拉曼光谱和生物信息学来制备特征性免疫检查点分子和化学签名的图谱。2.采用拉曼成像和数学生物学相结合的方法，利用该图谱识别肿瘤组织中活跃的免疫检查点。3.使用质谱成像来逐个细胞地注释来自肿瘤组织的拉曼生成的光谱指纹。概述：该项目提议使用组织扫描和成像方式--特别是拉曼光谱法和质谱法--来阐明肿瘤组织内运行的关键分子和化学途径，这些途径可以与特定的免疫检查点策略相匹配，以抵消任何有益的抗-癌症免疫反应总体目标是克服需要破坏肿瘤组织的限制，以了解癌症，免疫和其他细胞之间的细胞和化学相互作用。这将提高我们对肿瘤微环境在调节抗肿瘤免疫应答中的作用的理解，以产生有害或有益的效果。结合生物信息学的组织扫描和成像技术将使这里提出的整个组织切片方法成为可能。通过提供有关胰腺癌患者完整肿瘤组织内细胞空间关系以及分子和细胞途径活性的信息，可以寻求设计和开发免疫治疗药物的新方法。除了所提出的扫描/成像和生物信息学技术外，还将使用补充的细胞、分子和化学分析方法。首先，将使用数学生物学方法来创建与不同免疫检查点途径激活相关的反应模式图谱。这些测量将使用癌细胞系和用拉曼光谱询问的原代人类T细胞在体外生成，并使用基于AI的机器学习策略处理数据。然后，该图谱将用于分析和解释来自使用扫描/成像拉曼光谱法询问的肿瘤组织切片的数据，以检测离体肿瘤中的活性免疫检查点途径。这是拉曼光谱学的一个新用途。将通过质谱成像对途径组分进行鉴定和注释。来自组织切片的拉曼光谱和质谱数据的空间对准只能通过基于AI的生物信息学方法来实现。拉曼光谱图谱产生的关键，这个项目将被传播，供其他研究人员使用，并可应用于更广泛的实体肿瘤类型以外的胰腺癌，如在这里进行研究。成果：拟议的项目将提高我们对肿瘤微环境抗肿瘤能力的理解，为免疫治疗和精准医学的发展提供信息。它将利用在物理科学中有基础的分析科学方法，现在用于化学生物学和临床技术之间的接口。EPSRC研究领域分析科学生物信息学化学生物学和生物化学临床技术数学生物学