权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

RTB 1

实时TB 1

基本信息

批准号：
10532386
负责人：
Laura DeLong Wood
金额：
$ 37.55万
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/10532386
关键词：
3-Dimensional Antibodies Area Automobile Driving Beds Biological Cells Cellular Assay Cellular biology Clinical Collaborations Complex Cytometry Development Dimensions Disease Distant Metastasis Epithelium Event Fibroblasts Foundations Frequencies Gene Expression Profiling Goals Human Image Imaging technology Immune Inflammatory Invaded Label Liver Malignant - descriptor Malignant Neoplasms Malignant neoplasm of pancreas Maps Mesenchymal Molecular Molecular Analysis Morphology Neoplasm Metastasis Pancreas Pancreatic Ductal Adenocarcinoma Performance Population Primary Neoplasm Process Prognosis Proteomics Research Resolution Sampling Stromal Cells Structure Techniques Testing Three-Dimensional Imaging Tissue Model Tissue Sample Tissues Validation Veins Venous Work cancer cell cancer imaging cell type deep learning dimensional analysis high dimensionality human tissue imaging platform improved insight multi-scale modeling multiple omics new therapeutic target novel novel strategies pancreatic ductal adenocarcinoma cell pancreatic neoplasm pancreatic tumorigenesis prevent programs reconstruction synergism technology development tool transcriptome transcriptomics tumor microenvironment

项目摘要

Project Summary Pancreatic cancer is a deadly disease with a dismal prognosis and a high frequency of distant metastasis. One likely reason for the frequent metastases in pancreatic cancer is the ability of malignant cells in the primary tumor to invade veins, providing direct access to the liver. While this intravasation is a key first step in metastasis, little is known about the molecular and cellular alterations that underlie this process. Foci of cancer cell intravasation are small and complex, requiring high-resolution three-dimensional (3D) approaches to study them. In this Research Test Bed of our Center for 3D Multiscale Cancer Imaging, we will comprehensively characterize the morphological, cellular, and molecular alterations of foci of intravasation in 3D in human pancreatic cancer samples. In collaboration with Technology Development Unit 1, we will employ our novel deep learning 3D reconstruction approach CODA to serially sectioned pancreatic cancer samples with venous invasion to quantify morphological and cellular features of intravasation. We will also perform multi-dimensional immune profiling of these intravasation foci in 3D using imaging mass cytometry, which can label with 40 antibodies on each tissue section. These analyses will allow us to compare the tumor microenvironment in foci of intravasation to that in other areas of cancer and in uninvolved veins. In collaboration with Technology Development Unit 2, we will analyze the gene expression changes in these intravasation foci by applying a newly developed spatial transcriptomics/proteomics approach (DBit-Seq) to pancreatic cancer samples previously reconstructed by CODA. This approach will provide the first 3D multi-scale models of venous invasion in human pancreatic cancer, providing unprecedented morphological, cellular, and molecular detail of the process of intravasation and initiation of metastasis. In addition, our Research Test Bed will provide a critical opportunity to implement, validate, and iteratively improve the novel approaches from the two Technology Development Centers. We will work closely with these Technology Development Centers in order to evaluate the performance of CODA and DBit-Seq in our human pancreatic tissue samples, allowing validation of the cell type identification and molecular alterations by complementary techniques. The studies in our Research Test Bed will promote significant improvement of the CODA and DBit-Seq imaging platforms while also providing important biological insights into the initiation of metastasis in pancreatic cancer.

项目概要胰腺癌是一种致命的疾病，预后不佳，远处转移频率高。一胰腺癌频繁转移的可能原因是原发肿瘤中恶性细胞的能力侵入静脉，直接进入肝脏。虽然这种内渗是转移的关键第一步，但很少众所周知，这一过程背后的分子和细胞变化。癌细胞浸润灶它们小而复杂，需要高分辨率三维 (3D) 方法来研究它们。在这个我们的 3D 多尺度癌症成像中心的研究试验台，我们将全面表征人胰腺癌 3D 内浸润病灶的形态、细胞和分子变化样品。与技术开发单元 1 合作，我们将采用我们新颖的深度学习 3D CODA 重建方法对具有静脉侵犯的连续切片胰腺癌样本进行量化内渗的形态和细胞特征。我们还将进行多维免疫分析使用成像质量流式细胞术以 3D 形式显示这些血管内浸润灶，可以在每个组织上标记 40 种抗体部分。这些分析将使我们能够将浸润灶中的肿瘤微环境与内部浸润灶中的肿瘤微环境进行比较。其他癌症区域和未受累的静脉。与技术开发单位 2 合作，我们将通过应用新开发的空间分析这些内渗灶的基因表达变化以前重建的胰腺癌样本的转录组学/蛋白质组学方法 (DBit-Seq) 结尾。该方法将提供首个人类胰腺癌静脉侵犯的 3D 多尺度模型，提供前所未有的形态学、细胞和分子细节的内渗和转移的开始。此外，我们的研究测试台将提供一个重要的机会来实施，验证并迭代改进两个技术开发中心的新方法。我们将与这些技术开发中心密切合作，以评估 CODA 的绩效和在我们的人类胰腺组织样本中进行 DBit-Seq，可验证细胞类型识别和分子水平通过补充技术进行改变。我们的研究试验台中的研究将显着促进改进 CODA 和 DBit-Seq 成像平台，同时还提供重要的生物学见解胰腺癌转移的开始。