IMAT-ITCR Collaboration: Hyperplex lineage analysis of tumor cell states in vivo

IMAT-ITCR 合作：体内肿瘤细胞状态的 Hyperplex 谱系分析

• 批准号: 10678070
• 负责人: ITAI YANAI
• 金额: $ 8.46万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10678070
• 关键词: Algorithms; Award; Benchmarking; Cell Line; Cells; Collaborations; Color; Communities; Data; Data Set; Experimental Models; Funding; Genomic approach; Genomics; Growth; Heterogeneity; Image; Laboratories; Modeling; Neighborhoods; Neoplasm Metastasis; Parents; Resources; S-nitro-N-acetylpenicillamine; Technology; Universities; cancer cell; cancer initiation; genomic data; in vivo; insight; medical schools; mouse model; neoplastic cell; novel; research study; spatial relationship; therapy resistant; tool; tumor; tumor heterogeneity; tumor initiation; tumor microenvironment

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.

抽象的 肿瘤细胞异质性和对肿瘤细胞态的动态变化是肿瘤的主要因素 起始，生长，转移和治疗耐药性。 Snyder Lab和Yanai实验室每个 在单独的NCI资助研究中开发自己的技术，以分别可视化肿瘤 具有高光谱谱系跟踪的小鼠模型中的异质性（NCI IMAT，SNYDER，MOUSEPAINT）或 使用单细胞基因组技术（NCI）重建空间关系和癌细胞态 ITCR，Yanai，Snap）。我们的假设是，在 相同的数据集将对（1）查看成千上万种颜色（即克隆）基准基准 体内和（2）从Scrnaseq数据中推断肿瘤邻域。提出了两个目标。目标1 生成用于评估颜色多样性和克隆邻居的慕斯细胞系 高光谱成像。 AIM 2。通过将单个单元组合起来的基准测试和鼠标 带有慕斯成像数据的基因组学数据。协作补充剂将具有丰富的 通过提供新的模型和算法来基准测试博士，对每个父母奖的积极影响 Snyder的Hyperplex谱系追踪策略，并为亚奈博士提供实验模型 SNAP单细胞基因组学接近。我们希望这些研究对1）验证研究资源 研究肿瘤异质性的社区和2）对发生的早期变化提供了新的见解。 癌症开始和生长期间的肿瘤微环境。