Technical Development Unit 2: Intelligent Hyperspectral Imaging of Subcellular Molecular States at the Whole Organ Level

技术开发单元2：全器官水平亚细胞分子态智能高光谱成像

• 批准号: 10491350
• 负责人: Kevin Michael Dean
• 金额: $ 47.54万
• 依托单位: UT SOUTHWESTERN MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-24 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10491350
• 关键词: 3-Dimensional; Address; Automation; Automobile Driving; Back; Biochemical; Biological; Biological Assay; Biosensor; CRISPR/Cas technology; Cell Line; Cells; Cellular Morphology; Chemicals; Chemistry; Communities; Computer Systems; Computer Vision Systems; Computer software; Computing Methodologies; Cues; Data Analyses; Development; Dimensions; Dyes; Electromagnetics; Engineering; Event; Feedback; Fostering; Frequencies; Goals; Heterogeneity; Image; Immunofluorescence Immunologic; In Situ; Intelligence; Interleukin-2; Intrinsic factor; Label; Laboratories; Light; Liquid substance; Malignant Neoplasms; Maps; Measurement; Mechanics; Mediating; Metabolic; Methods; Microscope; Microscopy; Microtomy; Molecular; Molecular Analysis; Morphology; Neoplasm Metastasis; Nodule; Nutrient; Optics; Organ; Organism; Oxidation-Reduction; Performance; Periodicity; Physics; Preparation; Process; Proteins; Proteomics; Reagent; Refractive Indices; Resolution; Risk; Robotics; Sampling; Signal Transduction; Site; Slice; Solid Neoplasm; Solvents; Specimen; Speed; Technology; Testing; Thick; Thinness; Three-Dimensional Imaging; Tissue Preservation; Tissue imaging; Tissues; Transcript; Travel; Validation; automated analysis; base; cancer cell; cancer initiation; design; fluorescence imaging; high resolution imaging; imaging approach; imaging system; improved; innovation; insight; instrument; multiplexed imaging; next generation; programs; stressor; usability

PROJECT SUMMARY/ABSTRACT Cancers of different types preferentially metastasize to different tissues and specific sites in these tissues. Why this is true remains poorly understood but is likely to involve a combination of cell intrinsic factors (e.g., the ability of a cell to survive differences in mitogenic factors, nutrient availability, or context-specific stressors) and extrinsic effects (tissue-specific mechanical and biochemical cues). Gaining molecular insight into events involved in metastatic colonization is challenging, because such events are rare, colonies are initially small, and potential sites of colonization are widely distributed. The focus of this TDU is the development, validation and dissemination of innovative toolkits for deep multiplexed tissue imaging; these toolkits will be developed in close association with our RTBs and provided to the wider CCBIR consortium. When mature, the methods we described will enable quantitative measurement of molecular processes involving ~60 proteins or other biomolecules at subcellular resolution in a preserved tissue context. In Aim 1 we will assemble a self-driving multiscale microscope that leverages advances in tissue clearing, fully automated high-speed and high- resolution light-sheet fluorescence imaging, and computer vision, to identify the earliest events in metastasis, including the colonization of a tissue by a single metastatic cell. This microscope will have mesoscopic and nanoscopic imaging modes. The mesoscopic module has computationally controlled magnification (0.63X to 6.3X) and provides ~5-10 µm isotropic resolution throughout a 2.1-21mm field of view. The nanoscopic module provides ~330nm isotropic resolution throughout a 300 µm field of view. Biological features (metastatic colonies) will be rapidly and efficiently identified with the mesoscopic module and interrogated at high resolution using the nanoscopic module. Aim 2 will involve development of physically and chemically accelerated 60-plex cyclic immunofluorescence assays of tissue sections thick enough(~200 µm) to fully encompass a metastatic colony and its tissue niche. Thick section highly multiplexed and high-resolution imaging will then be combined with CRISPR-Cas9 engineered cell lines from the RTBs to test specific hypotheses about signaling, differentiation, and morphological mechanisms involved in metastasis. Support for spatial transcript profiling and tissue proteomics will aid with integration into more gnomically focused NCI programs. Aim 3 will develop a fully automated multi-technology microscope able to accurately describe metastatic heterogeneity in a statistically robust fashion. The instrument will combine deep isotropic resolution imaging with highly multiplexed methods via automated sample handling, labeling, imaging and analysis. This next-generation microscope will involve several generalizable technologies for comprehensively profiling rare events in metastasis and also cancer initiation, which is another rare event. Together, the approaches we describe are expected to substantially advance our understanding of one of the least characterized and most lethal features of solid tumors.

项目总结/文摘