Pharmaco Response Signatures and Disease Mechanism

药物反应特征和疾病机制

• 批准号: 8545951
• 负责人: Timothy J Mitchison
• 金额: $ 22.5万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-27 至 2014-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8545951
• 关键词: Algorithms; Apoptosis; Area; Behavior; Biochemical; Biochemistry; Biological; Biological Assay; Cell Cycle; Cell Line; Cell Survival; Cell physiology; Cells; Chemistry; Clinical; Collection; Communities; Complex; Data; Data Analyses; Data Collection; Data Provenance; Data Quality; Data Set; Disease; Dose; Drug resistance; Epithelial; Experimental Designs; Extensible Markup Language; Flow Cytometry; Genome; Genomics; Genotype; Goals; Growth Factor; Human; Image Cytometry; Immunoassay; Informatics; Institution; Investigational Drugs; Kinetics; Knowledge; Libraries; Life; Ligands; Link; Logic; Malignant Neoplasms; Maps; Measures; Mesenchymal; Methodology; Methods; Modeling; Molecular Profiling; Normal Cell; Output; Pathway interactions; Patients; Pharmaceutical Chemistry; Pharmaceutical Preparations; Phase; Phenotype; Phosphotransferases; Physiology; Process; Production; Proteins; Reporting; Resistance; Resolution; Running; Sampling; Series; Signal Pathway; Signal Transduction; Signaling Protein; Software Tools; Specificity; Stem cells; Structure; System; Techniques; Therapeutic; Time; Tumor Cell Line; base; cancer cell; cellular imaging; computer based Semantic Analysis; cytokine; drug mechanism; flexibility; heuristics; information processing; inhibitor/antagonist; insight; interest; kinase inhibitor; large scale production; large-scale database; malignant breast neoplasm; mathematical model; medical schools; meetings; movie; neoplastic cell; novel; open source; programs; public health relevance; response; senescence; small molecule; small molecule libraries; tool

DESCRIPTION (provided by applicant): This proposal will create a center for Large Scale Production of Perturbagen-lnduced Cellular Signatures at Harvard Medical School and collaborating institutions, with a focus on perturbations provoked by small molecule drugs and cellular signatures measured using diverse biochemical and single-cell assays. The result will be a large, self-consistent and diverse set of network-centric Pharmacological Response Signatures that provide unique insight into disease processes, drug mechanism/selectivity and ultimately patient-specific responses to therapy. The initial focus of the Center will be small molecule kinase inhibitors, versatile perturbagens with high translational potential. We will use known inhibitors and also expand dramatically the publicly documented collection of inhibitors through new medicinal chemistry and use of kinome-wide selectivity assays. The responses of a large collection of human tumor cells and some primary cells to kinase inhibitors, will be assayed using multiplex biochemical assays (for 20-100 proteins) involving bead-based sandwich immunoassays and reverse-phase lysate microarrays, and single-cell assays (using imaging and flow cytometry) for cell cycle state, commitment to senescence or apoptosis, mesenchymal vs. epithelial phenotype and markers of primitive (stem-cell) status. Data will be collected, integrated and distributed using a series of novel, interoperable software tools that manipulate semantically-typed data arrays based on a new XML/HDF5 format. A multi-faceted informatics program will link these phenotypic and biochemical measures of cellular response to a rich and growing set of genomic data being collected by others. These goals will be met through pursuit of six linked specific aims. Aim 1 will focus on existing - largely clinical grade - kinase inhibitors and a set of 45 cell lines that are known to display diverse drug responses and for which extensive genomic data are available. Aim 2 will enlarge the set of perturbagens by developing a large library of kinase inhibitors using new and existing chemistry and profiling biochemical specificity across the kinome. Aim 3 will combine existing and novel compounds in a dose-response analysis across a set of >1000 tumor cell lines to identify representative cell lines and outliers which, in Aim 4, will subjected to detailed analysis at a single-cell level. Aims 5-6 will develop and deploy the information processing systems needed to collect, systematize and distribute diverse data types. This will involve a novel set of interoperable software tools that incorporate emerging no-SQL and semantic web concepts. Methods for adaptive experimental design will be developed to focus data collection on those areas of the dose response landscape where signatures are most informative. The final product will be a large publicly available data set radically different from, but highly complementary to, the expression profiles and genome data that are the primary focus of current high-throughput biological studies on perturbagen-induced cellular signatures.

描述（由申请人提供）：该提案将为哈佛医学院和合作机构的大规模生产扰动性的细胞签名而大规模生产中心，重点是用小分子药物和使用多样的生物化学和单细胞分析测量的小分子药物和细胞签名引起的扰动。结果将是一组以网络为中心的药理学反应特征的庞大，自以为是和多样化的集合，可为疾病过程，药物机制/选择性以及最终对患者特定的治疗反应提供独特的见解。该中心的初始焦点是小分子激酶抑制剂，具有高转化潜力的多功能性扰动者。我们将使用已知的抑制剂，并通过新的药物化学和对范围内的选择性分析的使用大大扩展抑制剂的收集。将使用多重生物化学测定（对于20-100个蛋白质）测定大量人类肿瘤细胞和某些主要细胞对激酶抑制剂的反应，涉及基于珠的三明治免疫测定和反相裂解的裂解物微阵列，以及单细胞的分析（使用成像和流动式均量表或流动的状态量），将其分析。原始表型和原始（Stem细胞）状态的标记。数据将使用一系列新颖的，可互操作的软件工具收集，集成和分发，该工具可以根据新的XML/HDF5格式操纵语义型数据阵列。一个多方面的信息学计划将将这些表型和生化措施的细胞反应测量与其他人收集的丰富且不断增长的基因组数据联系起来。这些目标将通过追求六个链接的特定目标实现。 AIM 1将集中于现有的 - 主要临床级 - 激酶抑制剂和一组45个细胞系，这些细胞系列显示出多种药物反应，并为此提供广泛的基因组数据。 AIM 2通过使用新的化学和现有化学和分析整个Kinome的生化特异性来开发大型激酶抑制剂图书馆，从而扩大了肌扰动物的集合。 AIM 3将在一组> 1000个肿瘤细胞系的剂量反应分析中结合现有化合物和新型化合物，以识别代表性的细胞系和异常值，在AIM 4中，将在单细胞水平上进行详细的分析。 AIMS 5-6将开发和部署收集，系统化和分发各种数据类型所需的信息处理系统。这将涉及一组新型的可互操作软件工具，这些工具结合了新兴的No-SQL和语义Web概念。将开发用于自适应实验设计的方法，以将数据收集重点放在剂量响应格局的那些区域，这些区域最有用。最终产品将是一个与表达曲线和基因组数据完全不同但高度互补的公共可用数据集，这是当前高通量生物学研究的主要重点，这些研究是对厌氧诱导的细胞特征的主要重点。