Identification and characterization of cancer cell states by novel computational and experimental technologies - Resubmission - 1

总结 肿瘤是由遗传和转录异质性细胞组成的复杂系统， 异质性被认为是耐药性和总体死亡率的原因。了解内部 因此，肿瘤异质性可能具有广泛的影响，包括基础和临床。的出现 单细胞RNA-Seq已经导致在整个肿瘤细胞中检测到转录上不同的状态。 广泛的肿瘤类型和阶段。然而，该领域缺乏强大的计算和实验 这些技术可以在功能上识别和表征这些癌细胞状态。在这个项目中，我们将一个基因 以模块为中心的视图，以严格和广泛适用的方式定义单元状态。我们将验证 使用人类样本和斑马鱼黑色素瘤模型，每个细胞状态的重要性， 在整个肿瘤进展和转移过程中成像和扰动细胞状态的能力。到 系统地表征这些细胞状态的实验，我们提出了方法来测定其 肿瘤内的相互依赖性和微环境的元素。我们的基因工程 斑马鱼将用荧光报告子和消融盒标记每个癌细胞状态， 灵活的实验平台，以研究和扰动每个细胞的状态。这位记者将使我们能够将癌症 细胞状态，并单独研究它们，特别强调它们的可塑性。通过系统地 破坏癌细胞状态，我们将进一步阐明它们对肿瘤起始的单独贡献， 进展和转移。使用空间转录组学方法并与单细胞RNA-seq整合 数据，我们将绘制癌细胞状态与其微环境的关系，以筛选假定的相互作用。 最后，我们将直接测试特定癌细胞状态和免疫系统之间的预测相互作用。 使用T细胞缺陷的鱼的隔室。在我们的三个目标中，我们采用了系统生物学工作流程， 迭代循环通过模式的观察，扰动，并完善我们的模型的功能 癌细胞状态在肿瘤进展中的作用。我们的建议将互补的 白色和柳井实验室的专业知识，并着手显着提高我们对肿瘤内 通过癌细胞状态的透镜的异质性。

SUMMARY Tumors are complex systems composed of genetically and transcriptionally heterogeneous cells, and this heterogeneity has been implicated as a cause of drug resistance and overall mortality. Understanding intra- tumor heterogeneity is therefore likely to have widespread impact, both fundamental and clinical. The advent of single-cell RNA-Seq has led to the detection of transcriptionally distinct states among cancer cells across a wide range of tumor types and stages. However, the field lacks robust computational and experimental technologies to functionally identify and characterize these cancer cell states. In this project, we take a gene module-centric view to define cell states in a rigorous and widely applicable manner. We will validate the importance of each cell state using human samples and the zebrafish melanoma model, which has exceptional capabilities for imaging and perturbation of cell states throughout tumor progression and metastasis. To systematically characterize these cell states experimentally, we propose methods to assay their interdependencies within the tumor and with elements of the microenvironment. Our genetically engineered zebrafish will mark each cancer cell state with a fluorescent reporter and an ablation cassette, providing a flexible experimental platform to study and perturb each cell state. The reporter will enable us to sort cancer cell states and study them individually, with a particular emphasis on their plasticity. By systematically disrupting cancer cell states, we will further elucidate their individual contributions to tumor initiation, progression and metastasis. Using a spatial transcriptomics approach and integrating with single-cell RNA-seq data, we will map cancer cell states in relation to their microenvironment to screen for putative interactions. Finally, we will directly test predicted interactions between specific cancer cell states and the immune compartment using T cell-deficient fish. Throughout our three Aims, we adopt a systems biology workflow that iteratively cycles through modes of observations, perturbations, and refinement of our model of the functional role of cancer cell states during tumor progression. Our proposal collectively integrates the complementary expertise of the White and Yanai labs and sets out to significantly improve our understanding of intratumoral heterogeneity through the lens of cancer cell states.