Imaging the native 3D architecture of pancreatic and breast tumor patient tissue at single-cell resolution

以单细胞分辨率对胰腺和乳腺肿瘤患者组织的天然 3D 结构进行成像

基本信息

批准号：
10300193
负责人：
James Alexander Fitzpatrick
金额：
$ 36.03万
依托单位：
WASHINGTON 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：
2021-08-03 至 2023-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10300193
关键词：
3-Dimensional Address Adult Architecture Atlases Breast Breast Cancer Patient CD8B1 gene CXCL14 gene Cancerous Cell Nucleus Cells Cessation of life Collagen Complex Cystic Fibrosis Transmembrane Conductance Regulator DNA Data Data Set Detection Diagnosis Extracellular Matrix FBXW7 gene Fluorescence Microscopy Genomics Growth Human Image Imaging Techniques Immune Immunofluorescence Immunologic In Situ Hybridization Inter-tumoral heterogeneity Label Lymphatic Malignant Neoplasms Malignant neoplasm of pancreas Maps Methods Microscopy Molecular Neoplasm Metastasis Optics PECAM1 gene Pancreas Pancreatic Ductal Adenocarcinoma Patients Population Proteomics Quality of life RNA Reporter Research Resolution Route Sampling Solid Solid Neoplasm Spatial Distribution Specimen Speed Stains Stromal Cells Techniques Technology Thinness Three-Dimensional Imaging Tissue Sample Tissues Transcript Tumor Tissue United States Universities Vimentin Visualization Washington Woman Work analysis pipeline breast malignancies cell type cellular imaging computational pipelines computational suite computerized tools dimensional analysis experimental study human tissue imaging approach improved innovation insight lymphatic vasculature men molecular imaging mortality neoplastic cell pancreatic ductal adenocarcinoma cell pancreatic neoplasm protein biomarkers protein expression reconstruction single cell sequencing spatial relationship therapeutic target therapy resistant triple-negative invasive breast carcinoma tumor tumor heterogeneity tumor microenvironment two-dimensional

项目摘要

PROJECT SUMMARY Cancer remains the second-leading cause of adult death in the United States, yet the mechanisms by which cancerous growths are initiated and how crucial transitions such as metastasis and therapeutic resistance occur are not well understood. Significant progress has been made in the multiplexed analysis of solid tumors through the use of single-cell sequencing and spatio-molecular mapping techniques. However, despite the unique insights into tumor heterogeneity these methods have afforded, they are limited to two-dimensional (2D) thin analyses which provide little information on the native three-dimensional architecture of the tumor. Serial reconstruction can provide some three-dimensional context, but such approaches are both inefficient in terms of sample throughput and are inherently destructive to the tissue architecture. We propose a cross-disciplinary, approach to quantitatively characterize the native three-dimensional architecture of human solid tumor tissue from triple negative breast cancer (TNBC) and pancreatic ductal adenocarcinoma (PDAC) patients using a combination of the state-of-the art, yet mature technologies of tissue clearing, immunofluorescence and in situ hybridization labeling, and high-resolution lightsheet fluorescence microscopy. Analysis of these tissue volumes will enable the elucidation of the spatial interactome of different tumor, immune and stromal cells that give rise to tumor heterogeneity as well as their interactions with components of the tumor microenvironment. Our Specific Aims are (1) to image the three-dimensional spatial distribution of tumor, immune and stromal cells in relation to vasculature, lymphatics and the extracellular matrix in native solid tumor tissue from human pancreatic and breast malignancies using a combination of tissue clearing, immunofluorescence, in situ hybridization and 3D lightsheet microscopy, and (2) to develop a computational pipeline to build three-dimensional spatial maps of protein expression and RNA transcript localization in intact solid tumor tissue from human pancreatic and breast malignancies. The innovation of the proposed work lies in our cross-disciplinary strategy of combining the cutting- edge tissue clearing, multiplexed labelling and high-resolution lightsheet microscopy to better understand the native three-dimensional architecture of solid tumors. Specifically, by classifying and quantitating previously unknown three-dimensional features of solid tumor tissue we will be able to relate the spatial organization of the tumor to genomic and proteomic data taken from the same specimen. The significance of this proposal is that successful three-dimensional characterization of human tumor tissues will enable key insights to be derived on both intra- and inter-tumor heterogeneity thus facilitating the identification of cell-cell and cell-microenvironment interactions that could serve as potential therapeutic targets thus providing new routes to treatments to decrease patient mortality and improve quality of life.

项目概要癌症仍然是美国成年人死亡的第二大原因，但其机制癌性生长的开始以及转移和治疗耐药等关键转变是如何发生的没有被很好地理解。通过以下方法，实体瘤的多重分析取得了重大进展使用单细胞测序和空间分子作图技术。然而，尽管有独特的这些方法提供了对肿瘤异质性的洞察，但它们仅限于二维（2D）薄层分析提供的有关肿瘤天然三维结构的信息很少。串行重建可以提供一些三维背景，但这些方法在以下方面都是低效的：样品通量并且对组织结构具有固有的破坏性。我们提出一个跨学科的、定量表征人类实体瘤组织天然三维结构的方法来自三阴性乳腺癌 (TNBC) 和胰腺导管腺癌 (PDAC) 患者，使用结合了最先进且成熟的组织透明化、免疫荧光和原位技术杂交标记和高分辨率光片荧光显微镜。对这些组织体积的分析将能够阐明不同肿瘤、免疫和基质细胞的空间相互作用组肿瘤异质性及其与肿瘤微环境成分的相互作用。我们的具体目的是 (1) 对肿瘤、免疫和基质细胞的三维空间分布进行成像来自人类胰腺和胰腺的天然实体瘤组织中的脉管系统、淋巴管和细胞外基质结合组织透明化、免疫荧光、原位杂交和 3D 技术来诊断乳腺恶性肿瘤光片显微镜，以及（2）开发计算管道来构建三维空间图人胰腺和乳腺完整实体瘤组织中的蛋白质表达和 RNA 转录本定位恶性肿瘤。所提出的工作的创新在于我们将前沿技术结合起来的跨学科策略边缘组织清除、多重标记和高分辨率光片显微镜，以更好地了解实体瘤的天然三维结构。具体来说，通过之前的分类和量化实体瘤组织的未知三维特征，我们将能够将其空间组织联系起来肿瘤与取自同一样本的基因组和蛋白质组数据。这个提案的意义在于人类肿瘤组织的成功三维表征将能够得出关键见解肿瘤内和肿瘤间的异质性，从而促进细胞间和细胞微环境的识别相互作用可以作为潜在的治疗靶点，从而提供新的治疗途径，以减少患者死亡率并提高生活质量。