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.

概括项目2-定义肿瘤组成，空间异质石，药物输送之间的关系，和药物疗效这是设计调节治疗分布和的物理因素的最终目标脑肿瘤的治疗功效。定量图的治疗分布，具有肿瘤结构的空间注册表征和治疗功效，都在给定的肿瘤标本内。 MALDI-MSI用于量化药物分布，刺激拉曼散射成像，用于标记肿瘤的无标记分析具有光学成像分辨率的体系结构，免疫组织化学，以确定肿瘤细胞状态和靶标分布，接近连接的攻击空间空间分辨率对治疗的信号反应和激光 - 捕获显微解剖的RNASEQ，以量化所有这些方法将在单个肿瘤的串行秒内执行，从而取消运行的集成基于质谱的磷光蛋白质组学和RNASEQ分析的空间注册数据量化对定义药物谱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，项目中生成的数据将（1）在空间上映射异质药物分布和药物疗效，（2）启用物理的计算建模控制分布并调节细胞和分子重新恢复到不同局部药物的因素浓度。尖端成像和系统生物学方法的新颖集成应用于相同的肿瘤与计算模型相结合以识别有关药物的物理因素分布和肿瘤细胞反应，将在复杂的动态行为中提供未经预科的已培养体内肿瘤细胞响应于空间异质水平的疗法。