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

摘要 成百上千个具有独特遗传组成和适应潜力的恶性上皮克隆 都存在于致命性癌症中。每个克隆人都会相互竞争，也会与敌意免疫系统竞争。 微环境。显著的选择性力量建立了具有治疗耐药性的肿瘤细胞储存库 致命的转移。机械绘制肿瘤异质性进化的图谱是下一个巨大的挑战 癌症研究。基因组学方法已经被开发用于数字化肿瘤和 推断血统轨迹。然而，病理学家所依赖的黄金标准空间信息 在这些技术中已经消失了几个世纪，所推断的血统关系仍然必须通过实验来证明。 近三十年来，可遗传编码的蛋白质标签在追踪细胞命运的谱系方面一直是无价的。 在活体内。绿色荧光蛋白(GFP)的发现增加了荧光显微镜的好处。 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。vbl.使用 像“五彩纸屑”标签这样的技术，现在大多数实验室通常都可以追踪到四个克隆。其他 这些方法已经成功地追踪了100个克隆人(“脑弓”)。这些维持现状的方法有 十多年来保持不变，仍然远远达不到所需的数千种颜色 定量绘制肿瘤异质性图谱。该提案提供了一个大规模的解决方案 小鼠的组合谱系追踪策略，称为“老鼠画”。这个高风险、高回报的IMAT 该项目基于一个团队数十年的基因研究，该团队在 组合谱系追踪和高光谱成像。MousePaint利用跨越的荧光蛋白 整个可见光光谱。下游的高光谱成像被用来对数千个血统和 理论上接近&gt；100万色的真彩色成像。这项提议的目标是履行 一种可用于绘制和可视化数千个肿瘤的“老鼠画”技术的可行性研究 癌症自然发展过程中的克隆--包括起始、生长和转移。两个目标是 建议。(目标1)优化用于体内组合成像的MousePaint策略和(Aim 2)设计和测试一种可遗传编码的MousePaint，用于定量显示 肿瘤内异质性的演变。完成这些目标将为成像提供MousePaints 肿瘤细胞异质性。高光谱成像和大数据分析将作为MousePaint谱系的基准 描摹和色彩深度。MousePaint与原位转录学、分子病理学、 组织病理学和scRNAseq的兼容性将直接测试。MousePaint有望转型 通过提供简单的鼠标工具进行真彩色成像的癌症研究肿瘤进化至少100到1000 乘以可用方法的分辨率。

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.