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Tech Core 1

技术核心1

基本信息

批准号：
10532382
负责人：
Pei-Hsun wu
金额：
$ 35.85万
依托单位：
JOHNS HOPKINS UNIVERSITY
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：
2021-12-01 至 2026-11-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10532382
关键词：
3-Dimensional Address Algorithms Antibodies Architecture Blood Vessels Breast Cancer Cell Breast cancer metastasis Bypass Cancerous Cell Density Cells Cellular biology Circulation Collagen Fiber Color Complex Cytometry Detection Development Distant Metastasis Duct (organ) structure Evaluation Event Extravasation Fibroblasts Histologic Human Image Imaging Device Immune Immunofluorescence Immunologic Immunohistochemistry Individual Invaded Label Lateral Liver Malignant Neoplasms Malignant neoplasm of pancreas Mammary Gland Parenchyma Mammary Neoplasms Maps Metastatic breast cancer Methods Microanatomy Microscopy Microtomy Molecular Molecular Analysis Neoplasm Metastasis Operative Surgical Procedures Optics Outcome Pancreas Pathologic Penetration Phenotype Portal vein structure Process Prognosis Resected Resolution Route Sampling Scheme Semantics Site Slide Stains Survival Rate Testing Three-Dimensional Imaging Tissue imaging Tissues Training Validation Veins Venous cancer cell cancer imaging deep learning deep learning algorithm diagnostic tool histological stains human tissue imaging modality immunocytochemistry improved lymphatic Invasion malignant breast neoplasm molecular imaging mortality multiplexed imaging pancreatic cancer cells pancreatic neoplasm preservation reconstruction segmentation algorithm serial imaging tissue reconstruction tumor tumor heterogeneity tumor microenvironment

项目摘要

Project Summary – Tech 1 The identification of key molecular and cellular events that drive the progression of metastatic breast and pancreatic cancer could lead to improved mechanistic understanding and diagnostic tools and treatments. However, the micro-anatomy of human pancreatic/breast tumors – their spatial organization and associated content in cellular and non-cellular components – is poorly understood as it is intrinsically three-dimensional, non-symmetric, and highly heterogeneous. Three-dimensional imaging tools that combine structural and spatial omic information in large volumes are required to locate these metastatic driver events in cancerous tissue. Specifically, we aim to investigate venous invasion, which is a common route of metastasis of breast and pancreatic cancer cells. In Tech1, we propose to develop a new 3D multiscale imaging method, CODA, which will allow us to probe the phenotypic heterogeneity of tumors from the multi-cm to the micron scale via multiplexing serial imaging and registration/deep-learning algorithms. Our proposed repertoire of CODA imaging methods addresses deficiencies of state-of-art tissue clearing and 3D imaging methods, including inconsistent clearing and staining, lack of validation, poor antibody penetration and limited multiplexing capabilities. CODA bypasses the limitations of optical microscopy, allowing for large volumetric imaging while achieving micron resolution regardless of the volume of the imaged tissue. Another key advantage of CODA, which is based on serially cut H&E sections, is that it can readily incorporate other imaging modalities to extract high cellular/molecular content from the 3D samples. These include immunocytochemistry (CODA+IHC), immunofluorescence (CODA+IF), and imaging mass cytometry (CODA+IMC). This is particularly important as many potential molecular and cellular contributors of intravasation/extravasation and cancer cell invasion into veins, including immune cells and cancer-associated fibroblasts, require specific labels that cannot be detected in H&E slides. These proposed expanded versions of CODA offer a unique opportunity to produce new 3D multiplex maps of human PDAC and breast tumors near and far from blood vessels. CODA and its integrated versions CODA+X will be tested in the RTB units of the Center.

项目摘要-技术1