Optogenetic engineering of tumor topography in native tissue environments

项目概述：几乎在每一种癌症中，肿瘤都表现出对组织内某些位置的偏好 这与独特的临床表型有关。例如，在胰腺癌中， 胰头的预后和组织学亚型较好， 在尾部发育。因此，肿瘤在器官内的解剖学位置可以提供其上的背景， 突变用于定义临床和分子表型。尽管具有临床意义，但 确定肿瘤表型的区域差异仍然是个谜。本提案的总体目标是 开发新的方法，以获得解剖位置如何指导肿瘤表型的机制见解。 我们在疾病进展中询问肿瘤地形图能力的一个主要技术差距是缺乏 相关的遗传模型，概括了人类癌症的空间模式和行为。比如说， 胰腺肿瘤可以容易地在多种鼠模型中产生。然而，将肿瘤形成定位于 胰腺的头部或尾部是不可能的。这源于目前使用Cre重组酶的肿瘤模型 通过激活癌基因或删除组织中的肿瘤抑制因子来诱导致癌转化的技术。 虽然在某些情况下可以实现组织特异性，但靶向Cre活性并通过延伸致癌 突变到组织中的特定解剖位置是不可能的，并且限制了肿瘤形成的空间控制。 为了克服这些局限性，我们建议在肿瘤诱导中增加一层空间/区域控制， 基因工程鼠模型（GEMM）。我们通过开发和利用光遗传学 用于癌症研究的技术。光遗传学涉及引入遗传编码的光敏蛋白 涉及一种可以被光激活并能够在组织中进行空间限定的蛋白质调节的细胞。在这里我们建议 设计一个光遗传重组酶平台，允许用靶向光束控制Cre活性， 以实现对肿瘤形成的精确空间和时间控制。虽然有风险，但我们采用了系统的策略 来实现这一点。首先，我们将联合收割机与体内条形码筛选方法相结合， 能够消除背景重组酶活性同时保持稳健的 与光复合。其次，我们将把这个构建体发展成光遗传学-Cre GEMM，并优化 参数，以实现在区域和单细胞水平上的精确基因激活。最后，我们将整合这 系统转化为Cre可诱导的癌基因模型，以在限定的解剖位置内产生肿瘤， 用单细胞测序技术来表征它们的表型和分子特征。 在体内控制肿瘤发展的时空模式的潜力将是一个主要的 癌症研究的成就。这将改变我们对人类癌症的空间模式建模的能力， 研究对肿瘤生物学的影响。此外，我们的技术可以推动癌症以外的研究， 许多疾病的生物学受解剖位置的影响，但不能用现有的模型来询问。

Project Summary: In nearly every cancer, tumors demonstrate a predilection for certain locations within a tissue and this is associated with unique clinical phenotypes. For example, in pancreatic cancer, lesions that arise in the head of the pancreas have a better prognosis and favorable histological subtypes compared to those developing in the tail. Thus, the anatomic position of a tumor within an organ can provide the context on which mutations act to define clinical and molecular phenotypes. Despite the clinical significance, the mechanisms that determine regional differences in tumor phenotypes remains enigmatic. The overall goal of this proposal is to develop novel approaches to gain mechanistic insights into how anatomic position directs tumor phenotypes. A major technical gap in our ability to interrogate tumor topography in disease progression is the lack of relevant genetic models that recapitulate spatial patterns and behaviors of human cancers. For example, pancreatic tumors can be readily generated in multiple murine models. However, localizing tumor formation to the head or tail of the pancreas is not possible. This stems from current tumor models that use Cre-recombinase technology to induce oncogenic transformation by activating oncogenes or deleting tumor suppressors in tissues. While tissue specificity can be achieved in some cases, targeting Cre activity and by extension oncogenic mutations to specific anatomic locations in a tissue is not possible and limits spatial control of tumor formation. To overcome these limitations, we propose to add a layer of spatial/regional control to tumor induction in genetically engineered murine models (GEMMs). We accomplish this by developing and leveraging optogenetic technologies for cancer research. Optogenetics involves introducing genetically encoded light sensitive proteins to a cell that can be activated by light and enables spatially defined protein regulation in tissues. Here we propose to engineer an optogenetic recombinase platform that allows for control of Cre activity with targeted light beams to enable precise spatial and temporal control of tumor formation. Though risky, we employ a systematic strategy to accomplish this. First, we will combine protein engineering with in vivo barcoded screening methods to develop a novel photoactivable Cre capable of eliminating background recombinase activity while maintaining robust recombination with light. Second, we will develop this construct into an optogenetic-Cre GEMM and optimize parameters to enable precise gene activation at a regional and single-cell level. Finally, we will integrate this system into Cre inducible oncogene models to generate tumors within defined anatomic locations and characterize their phenotypes and molecular features with single-cell sequencing technologies. The potential to control spatiotemporal patterns of tumor development in vivo would be a major achievement in cancer research. This will transform our ability to model spatial patterns of human cancers and study the impact on tumor biology. Furthermore, our technology could advance research beyond cancer, as the biology of many diseases are influenced by anatomic location but cannot be interrogated with existing models.