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IMAT-ITCR Collaboration: Hyperplex lineage analysis of tumor heterogeneity and interactions with the microenvironment

IMAT-ITCR 合作：肿瘤异质性及其与微环境相互作用的 Hyperplex 谱系分析

基本信息

批准号：
10677105
负责人：
Joshua Clair Snyder
金额：
$ 7.83万
依托单位：
DUKE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-04-01 至 2025-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10677105
关键词：
Address Algorithms Atlas of Cancer Mortality in the United States Award Bar Codes Benchmarking Biology Cancer Biology Cancer Model Cancer cell line Cell Line Cell Lineage Cells Clone Cells Cloning Collaborations Color Communities Data Data Set Development Dimensions Experimental Models Funding Genomic approach Genomics Goals Grant Growth Heritability Heterogeneity Image In Situ In Vitro Interferons Laboratories Link Machine Learning Malignant neoplasm of ovary Measurement Measures Messenger RNA Methodology Methods Modeling Mouse Cell Line Neighborhoods Neoplasm Metastasis Organism Output Paint Parents Process Proteins Resolution Resources S-nitro-N-acetylpenicillamine SCID Mice Sampling System T-Lymphocyte Technology Time Tissues Transplantation Universities anticancer research base bioinformatics tool cancer cell cancer initiation combinatorial experimental study expression vector genomic data in vivo insight macrophage medical schools mouse model neoplastic cell novel research study response single-cell RNA sequencing spatial relationship therapy resistant tool transcriptomics tumor tumor heterogeneity tumor initiation tumor microenvironment tumorigenesis tumorigenic

项目摘要

ABSTRACT Tumor cell heterogeneity and dynamic changes to tumor cell states are major contributors to tumor initiation, growth, metastasis, and treatment resistance. The Snyder lab and the Yanai lab are each developing their own technologies in separate NCI funded studies for respectively visualizing tumor heterogeneity in mouse models with hyperspectral lineage tracing (NCI IMAT, Snyder, MousePaint) or reconstructing spatial relationships and cancer cell states using single cell genomics technology (NCI ITCR, Yanai, SNAP). Our hypothesis is that application of the MousePaint and SNAP technologies on the same dataset will benchmark these technologies for (1) viewing thousands of colors (i.e. clones) in vivo and for (2) inferring tumor neighborhoods from scRNAseq data. Two aims are proposed. Aim 1. To generate MousePaint cell lines for assessing color diversity and clonal neighborhoods using hyperspectral imaging. Aim 2. Benchmarking SNAP and MousePaint by coregistering single cell genomics data with MousePaint imaging data. The collaborative supplement will have substantial positive impact on each parent award by providing new models and algorithms for benchmarking Dr. Snyder’s hyperplex lineage tracing strategies as well as providing experimental models for Dr. Yanai’s SNAP single cell genomics approaches. We expect these studies to 1) validate resources for the research community to study tumor heterogeneity and 2) provide new insight into the early changes that occur in the tumor microenvironment during cancer initiation and growth.

摘要肿瘤细胞的异质性和肿瘤细胞状态的动态变化是导致肿瘤发生的主要因素。起始、生长、转移和治疗抗性。斯奈德实验室和柳井实验室分别是在NCI资助的独立研究中开发自己的技术，分别可视化肿瘤高光谱谱系示踪小鼠模型的异质性（NCI IMAT，Snyder，MousePaint）或使用单细胞基因组学技术（NCI）重建空间关系和癌细胞状态 ITCR，柳井，SNAP）。我们的假设是，应用MousePaint和SNAP技术，相同的数据集将对这些技术进行基准测试，用于（1）查看数千种颜色（即克隆），体内和（2）从scRNAseq数据推断肿瘤邻域。提出了两个目标。目标1.到生成MousePaint细胞系，用于评估颜色多样性和克隆邻域，超光谱成像目标2.通过配准单个单元格对SNAP和MousePaint进行基准测试基因组学数据与MousePaint成像数据。合作补充将有大量的通过提供新的模型和算法，对每个家长奖产生积极的影响。 Snyder的超复杂谱系追踪策略以及为柳井博士的 SNAP单细胞基因组学方法。我们希望这些研究1）验证研究资源社区研究肿瘤异质性和2）提供新的见解发生在早期的变化，在癌症发生和生长期间的肿瘤微环境。