Sorting and characterization of cancer cells based on metabolic phenotype

项目总结/摘要 代谢改变是癌症的标志，对这种改变特征的治疗干预正在出现， 拥有巨大的潜力最近的研究发现，乳腺癌细胞在它们的 糖酵解与氧化磷酸化（OXPHOS）代谢表型在原发性肿瘤， 转移，以及不同器官的转移之间。这种代谢表型的异质性可能是一种 遗传异质性或细胞可塑性和代谢适应局部微环境的结果。 代谢的异质性和可塑性可能导致对靶向特定代谢物的治疗的治疗抗性。 代谢途径该领域通常认为，细胞代谢适应性和可塑性促进了它们的生长。 转移期间的存活和定殖。然而，目前尚不清楚是否代谢表型的变化， 原发肿瘤可以预测转移结果。在这个项目中，我们建议对乳腺癌进行表型分类， 细胞分成具有不同糖酵解或OXPHOS表型的亚群，并使用这些分选的亚群 为了检验初始代谢表型和异质性决定转移结果的假设， 反对另一种假设，即代谢适应当地的微环境和表型 无论初始代谢异质性如何，转换都有助于转移结果。通过表达 荧光生物传感器在细胞中的细胞糖酵解与OXPHOS的依赖，我们已经获得了初步的 支持基于该代谢特征的细胞分选的可行性的数据。在目标1中，我们将优化 基于细胞代谢表型的细胞分选的工程方法。荧光激活细胞分选 （流式细胞仪）将与代谢生物传感器，自动显微镜，光活化和荧光 标记细胞用于细胞分离。在目标2中，我们将使用排序的代谢亚群来测试我们的总体 体外和体内初步代谢表型预测转移结果假说。工程系统 模仿在主要和次要网站的环境条件，并在流通将被设计 表征亚群的细胞迁移、增殖和存活，以及它们的代谢 适应我们将在小鼠模型中检查这些亚群的转移潜力， 它们在转移级联反应的沿着不同阶段的代谢适应。创新的方面， 建议是按代谢表型分类的概念和揭示初始代谢表型的作用的目标。 表型在更广泛的转移级联。该项目将使用新的工程细胞分选方法， 剖析代谢异质性和适应性在乳腺癌转移中的各自作用， 为未来确定精确靶向癌症代谢的关键分子途径的工作奠定基础 疗法

PROJECT SUMMARY/ABSTRACT Altered metabolism is a hallmark of cancer, and therapeutic intervention of this altered feature is emerging and holds significant potential. Recent work has found that breast cancer cells exhibit dramatic differences in their glycolysis versus oxidative phosphorylation (OXPHOS) metabolic phenotype within the primary tumor and metastases, and between metastases at different organs. This heterogeneity in metabolic phenotype may be a result of genetic heterogeneity or cellular plasticity and metabolic adaptation to the local microenvironment. Metabolic heterogeneity and plasticity may contribute to therapeutic resistance to treatments that target a specific metabolic pathway. The field generally believes that cellular metabolic adaptation and plasticity facilitate their survival and colonization during metastasis. However, it not clear whether a change in metabolic phenotype in the primary tumor can predict metastatic outcome. In this project, we propose to phenotypically sort breast cancer cells into subpopulations with distinct glycolysis or OXPHOS phenotypes, and use these sorted subpopulations to test the hypothesis that the initial metabolic phenotype and heterogeneity determine the metastatic outcome against the alternative hypothesis that metabolic adaptation to the local microenvironment and phenotypical switching contribute to metastatic outcome regardless of the initial metabolic heterogeneity. By expressing a fluorescent biosensor in the cells for cellular glycolysis versus OXPHOS reliance, we have obtained preliminary data supporting the feasibility of cell sorting based on this metabolic feature. In Aim 1, we will optimize the engineering approach for cell sorting based on cellular metabolic phenotype. Fluorescence-activated cell sorting (FACS) will be coupled with metabolic biosensors, and automated microscopy, photoactivation and fluorescent labeling of cells for cell separation. In Aim 2, we will use the sorted metabolic subpopulations to test our overall hypotheses in vitro and in vivo that initial metabolic phenotype predicts metastatic outcome. Engineered systems mimicking the environmental conditions at the primary and secondary sites, and in circulation will be designed to characterize cell migration, proliferation, and survival of the subpopulations, as well as their metabolic adaptation. We will examine the metastatic potential of these subpopulations in a mouse model and determine their metabolic adaptations at different stages along the metastatic cascade. The innovative aspects of this proposal are the concept to sort by metabolic phenotype and the goal of uncovering the role of initial metabolic phenotype in the broader metastatic cascade. This project will use the novel engineered cell sorting approach to dissect the respective roles of metabolic heterogeneity and adaptability in breast cancer metastasis, thus laying the foundation for future work to identify the key molecular pathways to precisely target for cancer metabolic therapy.