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.

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的主要因素 起始、生长、转移和治疗耐药。斯奈德实验室和柳井实验室分别是 在NCI资助的分别用于肿瘤可视化的单独研究中开发自己的技术 高光谱谱系追踪小鼠模型的异质性(NCI IMAT、Snyder、MousePaint)或 利用单细胞基因组学技术(NCI)重建空间关系和癌细胞状态 ITCR、Yanai、SNAP)。我们的假设是，鼠标绘制和快照技术在 相同的数据集将对这些技术进行基准测试，以(1)查看数千种颜色(即克隆) 用于(2)从scRNAseq数据推断肿瘤邻域。提出了两个目标。目标1.目标 生成MousePaint细胞系，用于评估颜色多样性和克隆邻域 高光谱成像。目标2.通过共注册单细胞对SNAP和MousePaint进行基准测试 基因组数据与MousePaint成像数据。协作性补充将有实质性的 通过提供新的模型和算法对每个家长奖项产生积极影响，以确定DR的基准。 Snyder的超复合体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)验证研究的资源 社区来研究肿瘤的异质性和2)提供了对发生在 肿瘤起始和生长过程中的微环境。