High Content Screening of Multicellular Invasion with 3D Traction Force Microscopy

项目总结： 恶性肿瘤通过协调的过程传播单个细胞和多细胞簇 细胞脱离和运动。这些机械的细胞-细胞和细胞-基质相互作用可以不同 在不同的细胞中是不同的，而且随着时间的推移也会有可塑性的变化。然而，细胞产生的力量是 通常从蛋白质表达和细胞形态间接推断。此外，经典的迁徙分析 在解决单细胞动力学和利用2D单层培养方面能力有限 与肿瘤微环境的相关性。因此，迫切需要对细胞进行精确测量 仿生三维微环境中的迁移和力学。 我们的长期目标是开发能够在体外对肿瘤侵袭进行生物力学分析和 筛选对靶向抑制剂的反应。技术挑战包括1)跟踪导致 侵袭性表型，2)解决细胞产生的力量，3)利用3D培养模型和4)放大 更高的吞吐量分析。为了应对这些挑战，本提案的目标是对单个细胞进行分析 嵌入在三维微环境中的多细胞集群的迁移、形态和力学。 我们的方法集成了两种互补的精密测量技术。少年派：王之前 展示了集体和个人迁徙的自动化和全面的单细胞跟踪。CO-I： 弗兰克展示了3D牵引力显微镜(TFM)和3D平均变形度量(MDM) 细胞生成的矩阵变形。在此IMAT R21的支持下，我们将在 基于诱导三维多细胞簇上皮-间充质转化(EMT)的模型系统。目标 1将开发定量分析和指标，以分析表型异质性和可塑性在 过渡到入侵。一旦建立，AIM 2将在96%的时间内将这种方法扩大到高内容筛选 好的车牌。我们将首先实现计算效率高的算法来纠正阶段中的不一致 使用图形处理单元(GPU)进行定位。接下来，我们将筛选靶向抑制剂的小组，以对抗 不同浓度下的迁移和EMT，以衡量单细胞迁移和力学的程度 心烦意乱。我们设想这项技术将揭示癌细胞如何异常的新的基本见解。 就像一个复杂的系统一样相互作用。此外，这种综合方法可以应用于患者的体外样本作为 一种早期的、无标签的预后指标，用于预测药物反应和临床前治疗筛查。

PROJECT SUMMARY: Malignant carcinomas disseminate individual cells and multicellular clusters through coordinated processes of cellular detachment and motility. These mechanical cell-cell and cell-matrix interactions can vary heterogeneously across different cells and also vary plastically over time. However, cell-generated forces are often inferred indirectly from protein expression and cell morphology. Moreover, classical migration assays have limited capabilities for resolving single cell dynamics and utilize 2D monolayer culture with questionable relevance for the tumor microenvironment. Thus, there is a critical need for precision measurements of cell migration and mechanics in biomimetic 3D microenvironments. Our long-term goal is to develop technologies that enable biomechanical profiling of tumor invasion ex vivo and screen the response to targeted inhibitors. Technical challenges include 1) tracking rare events that result in invasive phenotypes, 2) resolving cell-generated forces, 3) utilizing 3D culture models and 4) scale-up for higher throughput assays. To address these challenges, the objective of this proposal is to profile single cell migration, morphology and mechanics in multicellular clusters embedded within 3D microenvironments. Our approach integrates two complementary techniques for precision measurement. PI: Wong has previously demonstrated automated and comprehensive single cell tracking of collective and individual migration. Co-I: Franck has demonstrated 3D traction force microscopy (TFM) and 3D mean deformation metrics (MDM) for cell-generated matrix deformations. With the support of this IMAT R21, we will develop this approach in a model system based on inducing the epithelial-mesenchymal transition (EMT) in 3D multicellular clusters. AIM 1 will develop quantitative analyses and metrics for profiling phenotypic heterogeneity and plasticity during the transition to invasion. Once established, AIM 2 will scale up this approach for high-content screening in a 96 well plate. We will first implement computationally efficient algorithms to correct for inconsistencies in stage positioning using graphics processing units (GPUs). Next, we will screen panels of targeted inhibitors against migration and EMT at varying concentrations to measure how single cell migration and mechanics are perturbed. We envision this technology will reveal new fundamental insights into how cancer cells aberrantly interact as a complex system. Moreover, this integrated approach can be applied to patient samples ex vivo as an early, label-free prognostic indicator, to predict drug response and for preclinical therapeutic screens.