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

项目2：肿瘤特征及其对治疗分布和疗效的影响

基本信息

批准号：
9187651
负责人：
Forest M White
金额：
$ 55.35万
依托单位：
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-08-29 至 2021-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9187651
关键词：
Address Affect Affinity Apoptosis Architecture Behavior Blood Blood - brain barrier anatomy Blood Vessels Brain Brain Neoplasms Brain Pathology Cell Death Inhibition Cells Cellular Assay Cellular biology Central Nervous System Neoplasms Characteristics Complex Computer Simulation Data Detection Diffusion Dose Drug Delivery Systems Edema Event Failure Generations Goals Heterogeneity Hypoxia Image Immunohistochemistry Individual Kinetics Label Lead Ligation Maps Mass Spectrum Analysis Modeling Molecular Necrosis Neuraxis Oncogenic Oncologist Outcome Pathway interactions Patients Pharmaceutical Preparations Proteomics Resistance Resolution Scientist Signal Transduction Specimen Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization System Systems Biology Techniques Therapeutic Therapeutic Agents Transcript Treatment Efficacy Tumor Tissue Work base cancer genomics chemical property drug distribution drug efficacy effective therapy imaging system improved in vivo innovation insight laser capture microdissection molecular dynamics neoplastic cell neovasculature novel optical imaging pharmacodynamic model phosphoproteomics physical property physical science precision medicine response senescence targeted treatment therapeutic target transcriptome sequencing tumor tumor growth

项目摘要

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.

总结项目2-定义肿瘤组成、空间异质性、药物递送、和药物功效该项目的最终目标是确定调节治疗分布的物理因素，脑肿瘤的治疗效果。为此，我们制定了一项高度创新的综合战略，通过肿瘤结构的空间配准表征定量绘制治疗分布图和治疗效果的差异。具体来说，在这种方法中，我们将联合收割机 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结构与光学成像分辨率，免疫组织化学，以确定肿瘤细胞的状态和目标分布、用于对治疗的信号传导响应的细胞空间分辨率的邻近连接测定，以及激光- 捕获显微切割RNASeq以量化对治疗的空间分辨转录应答。所有这些方法将在单个肿瘤的连续切片中进行，从而能够整合空间配准数据。结合基于质谱的磷酸化蛋白质组学和RNASeq分析为了量化对一系列确定的药物的动态信号传导和转录网络响应，在其他肿瘤标本中的浓度，该项目中生成的数据将（1）空间映射非均匀药物分布和药物功效，以及（2）使得能够对药物的物理性质进行计算建模。控制分布和调节对不同局部药物的细胞和分子应答的因素浓度的新的整合尖端成像和系统生物学方法应用于不同的部分，相同的肿瘤，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水平的治疗剂的响应。