TECH Core

技术核心

基本信息

批准号：
10374452
负责人：
Kevin William Eliceiri
金额：
$ 41.31万
依托单位：
UNIVERSITY OF MINNESOTA
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-12-09 至 2026-11-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10374452
关键词：
3-Dimensional Algorithms Animal Model Architecture Beds Binding Biochemical Cancer Model Cell model Cells Cellular Morphology Collagen Collagen Fiber Communities Complement Computer Analysis Computer software Computing Methodologies Data Analyses Development Extracellular Matrix Fiber Fluorescence Fluorescence Resonance Energy Transfer Foundations Generations Glioblastoma Goals Image Imaging technology Immune In Vitro Individual Investigation Label Machine Learning Malignant Neoplasms Malignant neoplasm of pancreas Measurement Metabolic Metabolism Methods Minnesota Mission Modeling Molecular Optical Coherence Tomography Photochemistry Prognosis Protocols documentation Research Research Personnel Resources Role Signal Transduction Solid Neoplasm Sorting - Cell Movement Spectrum Analysis T-Lymphocyte Techniques Technology Testing Time Tissue Model Tissues Tumor Immunity Tumor Tissue Tumor-infiltrating immune cells Universities Wisconsin base cancer imaging candidate marker cell behavior cell type crosslink design fluorescence lifetime imaging fluorophore human data imaging approach imaging biomarker imaging modality imaging platform improved insight microscopic imaging multiparametric imaging multiphoton microscopy neoplasm immunotherapy new technology open source optical imaging physical property second harmonic second harmonic generation imaging technology development tumor microenvironment tumor-immune system interactions

项目摘要

This TECH core of the U54 Center for Multiparametric Imaging of Tumor Immune Microenvironments (C-MITIE) will develop an integrated toolkit of advanced imaging and data analysis to power quantitative, mechanistic investigations of immune-microenvironment dynamics in poor prognosis solid tumors. There is great need for improved imaging methods that can advance understanding of the physical and molecular mechanisms governing immune infiltration, distribution, and function in native tumor microenvironments. We propose a number of multiparametric imaging and computational methods for the two research test beds that seek to define the physical and molecular barriers to effective anti-tumor immunity and immunotherapies. A major theme of the TECH approach is to use label-free imaging approaches that can characterize and quantitate the interactions between immune cells and the tumor microenvironment. These label free methods are largely built on the platform method of multiphoton microscopy and can be used on intact cell and tissue models with minimal perturbation. T-cell identity and activation will be tracked by metabolic profiling using new fluorescence lifetime (FLIM) and hyperdimensional imaging (HDIM) approaches. These metabolically sensitive methods will be complemented by Full-Field Optical Coherence Tomography (FFOCT) to reveal new insight into metabolically relevant architecture. FLIM based FRET can be used to yield new insights into signaling molecular interactions relevant to immune-microenvironment dynamics The collagen rich extracellular matrix (ECM) will be queried with Second Harmonic Generation (SHG) imaging for collagen fiber topology measurement and collagen cross- linking measurements with Enhanced Backscattering Spectroscopy (EBS). Multiphoton Excitation (MPE) photochemistry fabrication can be used to create in vitro cell ready models of collagen fiber organization that are directly based on human data blueprints. Advanced computational analysis methods including algorithmic and machine learning approaches will be used to examine all multiparametric signals and make correlation between immune and microenvironment interactions. All imaging and computational methods will be shared not only widely within the UW and UMN research teams but importantly with the general cancer imaging community using established hardware and open source software dissemination protocols.

U54肿瘤免疫微环境多参数成像中心的技术核心（C-MITIE）将开发一个高级成像和数据分析的集成工具包，以供电定量，机械对预后较差的实体瘤的免疫微环境动力学的研究。非常需要改进的成像方法可以提高对物理和分子机制的理解管理天然肿瘤微环境中的免疫浸润，分布和功能。我们提出了一个试图定义的两个研究测试床的多参数成像和计算方法的数量有效抗肿瘤免疫和免疫疗法的物理和分子障碍。一个主要主题技术方法是使用可以表征和定量交互的无标签成像方法免疫细胞和肿瘤微环境之间。这些免费标签方法主要建立在多光子显微镜的平台方法，可用于最少的完整细胞和组织模型扰动。 T细胞的身份和激活将通过使用新的荧光寿命进行代谢分析来跟踪（FLIM）和高维成像（HDIM）方法。这些代谢敏感的方法将是补充全场光学相干断层扫描（FFOCT），以揭示对代谢的新见解相关架构。基于FLIM的FRET可用于产生有关信号传导分子相互作用的新见解与免疫微环境动力学相关，富含胶原蛋白的细胞外基质（ECM）将被查询进行第二次谐波产生（SHG）成像进行胶原蛋白纤维拓扑测量和胶原蛋白交叉将测量值与增强的反向散射光谱（EBS）联系起来。多光子激发（MPE）光化学制造可用于创建胶原纤维组织的体外细胞现成模型直接基于人类数据蓝图。高级计算分析方法，包括算法和机器学习方法将用于检查所有多参数信号，并在免疫和微环境相互作用。所有成像和计算方法不仅将共享在UW和UMN研究团队中广泛，但重要的是使用一般的癌症成像社区建立的硬件和开源软件传播协议。