Mouse Paint: A massively combinatorial approach for illuminating tumor heterogeneity in True Color

Mouse Paint：一种以真彩色阐明肿瘤异质性的大规模组合方法

• 批准号: 10589030
• 负责人: Joshua Clair Snyder
• 金额: $ 18.27万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 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/10589030
• 关键词: 3-Dimensional; Animal Model; Atlas of Cancer Mortality in the United States; Atlases; Benchmarking; Big Data; Biological; Cancer Biology; Cancer Model; Cell Lineage; Cells; Color; Data Analyses; Developmental Biology; Elements; Engineering; Epithelium; Evolution; Feasibility Studies; Fluorescence Microscopy; Future; Genetic; Genetic Research; Genetically Engineered Mouse; Genome; Genomic approach; Green Fluorescent Proteins; Growth; Heterogeneity; Histopathology; Human; Image; Imaging Device; In Situ; In Vitro; Label; Laboratories; LacZ Genes; Malignant - descriptor; Malignant Neoplasms; Maps; Measurement; Measures; Methods; Modeling; Mus; Natural History; Neoplasm Metastasis; Organ; Output; Paint; Pathologist; Performance; Phase; Proteins; Proteomics; Public Health; Reagent; Recurrence; Registries; Reproducibility; Research Personnel; Resistance; Resolution; System; Techniques; Technology; Testing; Therapeutic; Tissue Model; Tissues; Training; Transgenic Organisms; Translating; Visualization; Visualization software; anticancer research; cancer imaging; cancer invasiveness; cell type; combinatorial; falls; fitness; high reward; high risk; human data; in vivo; in vivo imaging; interest; logarithm; molecular pathology; mouse model; neoplastic cell; premalignant; programs; stem cell biology; therapy resistant; tool; transcriptomics; tumor; tumor heterogeneity; tumor progression; tumor-immune system interactions; tumorigenesis

ABSTRACT Hundreds to thousands of malignant epithelial clones with unique genetic compositions and fitness potentials are present in lethal cancers. Each clone competes against one another and also against a hostile immune microenvironment. Remarkable selective forces establish reservoirs of therapeutically resistant tumor cells and lethal metastases. Mechanistically mapping the evolution of tumor heterogeneity is the next great challenge in cancer research. Genomics approaches have been developed for digitizing heterogeneity in tumors and inferring lineage trajectories. However, gold-standard spatial information relied upon by pathologists for centuries is lost in these techniques and the inferred lineage relationships must still be proven experimentally. For almost three decades, genetically encodable protein tags have been invaluable for lineage tracing cell-fate in vivo. The discovery of green fluorescent protein (GFP) added the benefit of fluorescence microscopy. Spectrally resolvable GFP derivatives further increased the combinatorial potential of lineage tracing. Using techniques like “confetti” labelling, four clones are now commonly traced in most laboratories. Other approaches have successfully traced a hundred clones (“Brainbow”). These status quo approaches have remained unchanged for over a decade and still fall significantly short of the thousands of colors needed for quantitatively mapping tumor heterogeneity. This proposal provides a solution in the form of a massively combinatorial lineage tracing strategy in mice, termed “MousePaint”. This high-risk and high-reward IMAT project is based upon decades of genetic research from a team with an established track-record in combinatorial lineage tracing and hyperspectral imaging. MousePaint utilizes fluorescent proteins spanning the entire visible spectrum. Downstream hyperspectral imaging is used to image thousands of lineages and theoretically approach True Color imaging of >1 million colors. The objective of this proposal is to perform feasibility studies on a “MousePaint” technology that can be used to paint and visualize thousands of tumor clones during the natural history of a cancer – including initiation, growth, and metastasis. Two Aims are proposed. (Aim 1) To optimize a MousePaint strategy for combinatorial imaging in vivo and (Aim 2) To engineer and test a genetically encodable MousePaint for quantitatively visualizing the evolution of intratumor heterogeneity. Completing these aims will deliver MousePaints for imaging tumor cell heterogeneity. Hyperspectral imaging and big data analysis will benchmark MousePaint lineage tracing and color-depth. Co-registry of MousePaint with in situ transcriptomics, molecular pathology, histopathology, and scRNAseq compatibilities will be directly tested. MousePaint is expected to transform cancer research by providing a simple mouse tool for True Color imaging tumor evolution at least 100 to 1000 times the resolution of available methods.

摘要 数以百计到数以千计的恶性上皮细胞克隆具有独特的遗传组成和适应性潜力 存在于致命的癌症中。每一个克隆体都要互相竞争，同时也要和一个敌对的免疫体竞争 微环境显著的选择力建立了治疗抗性肿瘤细胞的储存库， 致命的转移。机械地绘制肿瘤异质性的演变是肿瘤学中的下一个巨大挑战。 癌症研究。已经开发了基因组学方法用于数字化肿瘤中的异质性， 推断血统轨迹然而，病理学家所依赖的黄金标准空间信息， 在这些技术中丢失了几个世纪的时间，并且推断的谱系关系仍然必须通过实验来证明。 近三十年来，遗传编码的蛋白质标签对于追踪细胞命运的谱系是非常宝贵的 in vivo.绿色荧光蛋白（GFP）的发现增加了荧光显微镜的优势。 光谱可分辨的GFP衍生物进一步增加了谱系追踪的组合潜力。使用 利用“五彩纸屑”标记等技术，现在大多数实验室通常都能追踪到四种克隆体。其他 方法已经成功地追踪了100个克隆人（“Brainbow”）。这些维持现状的方法 十多年来一直保持不变，仍然远远低于所需的数千种颜色。 定量绘制肿瘤异质性。该提案提供了一种大规模的形式的解决方案， 在小鼠中的组合谱系追踪策略，称为“MousePaint”。这种高风险高回报的IMAT 该项目是基于一个团队几十年的遗传研究，该团队在以下方面有着良好的记录： 组合谱系追踪和高光谱成像。MousePaint利用荧光蛋白跨越 整个可见光谱。下游高光谱成像用于对数千个谱系进行成像， 理论上接近> 100万色的真彩色成像。本提案的目的是执行 关于“MousePaint”技术的可行性研究，该技术可用于绘制和可视化数千个肿瘤 克隆在癌症的自然发展过程中-包括起始、生长和转移。两个目标是 提出了(Aim 1）为了优化用于体内组合成像的MousePaint策略， 2)为了设计和测试一个基因编码的MousePaint， 肿瘤内异质性的演变。完成这些目标将提供用于成像的MousePaints 肿瘤细胞异质性高光谱成像和大数据分析将成为MousePaint谱系的基准 跟踪和颜色深度。MousePaint与原位转录组学、分子病理学的共同注册， 组织病理学和scRNAseq相容性将被直接测试。MousePaint有望将 癌症研究提供了一个简单的鼠标工具，真彩色成像肿瘤演变至少100至1000 乘以可用方法的分辨率。