Project 2: Tumor characteristics and their effect on therapeutic distribution and efficacy

摘要 项目2--确定肿瘤成分、空间异质性、药物输送、 和药效 这个项目的最终目标是确定调节治疗分配和治疗的物理因素 治疗脑肿瘤的疗效。为此，我们制定了高度创新的综合战略，以 用肿瘤结构的空间注册特征定量绘制治疗分布图 和治疗效果，都在给定的肿瘤标本中。具体地说，在这种方法中，我们将结合 MALDI-MSI用于定量药物分布，受激拉曼散射成像用于肿瘤的无标记分析 具有光学成像分辨率的架构，免疫组织化学来确定肿瘤细胞的状态和靶点 分布，邻近连接分析细胞对治疗反应信号的空间分辨率，以及激光- 捕获显微切割RNAseq以量化空间分辨的对治疗的转录反应。所有这些都是 入路将在单个肿瘤的连续切片上进行，从而使 空间注册数据。结合基于质谱学的磷酸蛋白质组学和RNAseq分析 对特定药物光谱的动态信号和转录网络反应进行量化 在其他肿瘤标本中的浓度，本项目中产生的数据将(1)在空间上映射 异质药物分布和药物疗效以及(2)实现物理的计算建模 控制细胞和分子对不同药物的分布和反应的因素 浓度。 尖端成像和系统生物学方法的新集成适用于不同的节段 同样的肿瘤，结合计算模型来确定控制药物的物理因素 分布和肿瘤细胞反应，将提供前所未有的洞察复杂的动态行为 体内肿瘤细胞对空间异质性治疗水平的反应。

Summary Project 2– Defining the relationship between tumor composition, spatial heterogeneity, drug delivery, and drug efficacy The ultimate goal of this project is to determine the physical factors regulating therapeutic distribution and therapeutic efficacy in brain tumors. To this end, we have developed a highly innovative integrated strategy to quantitatively map therapeutic distribution with spatially registered characterization of the tumor architecture and therapeutic efficacy, all within a given tumor specimen. Specifically, in this approach we will combine MALDI-MSI to quantify drug distribution, stimulated Raman scattering imaging for label free analysis of tumor architecture with optical imaging resolution, immunohistochemistry to determine the tumor cell state and target distribution, proximity ligation assays for cellular spatial resolution of signaling response to therapy, and laser- capture microdissection RNASeq to quantify spatially resolved transcriptional response to therapy. All of these approaches will be performed in serial sections from individual tumors, thereby enabling the integration of spatially registered data. Together with mass spectrometry based phosphoproteomics and RNASeq analysis to quantify the dynamic signaling and transcriptional network response to a spectrum of defined drug concentrations in additional tumor specimens, the data generated in this project will (1) map spatially heterogeneous drug distribution and drug efficacy and (2) enable the computational modeling of the physical factors governing distribution and regulating the cellular and molecular response to different local drug concentrations. The novel integration of cutting-edge imaging and systems biology approaches applied to different sections of the same tumor, combined with computational models to identify the physical factors governing drug distribution and tumor cell response, will provide unprecedented insight into the complex dynamic behavior of tumor cells in vivo in response to spatially heterogeneous levels of therapeutics.