High Content Representation and Association of 3D Cell Culture Models

3D 细胞培养模型的高内涵表示和关联

• 批准号: 8445168
• 负责人: Bahram A. Parvin
• 金额: $ 57.49万
• 依托单位: UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-04-01 至 2015-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8445168
• 关键词: Affect; Algorithms; Area; Atlases; Behavior; Bioinformatics; Biological; Biological Assay; Biological Markers; Biological Models; Biological Process; Biology; Breast; Cancer Diagnostics; Cell Culture Techniques; Cell Line; Cells; Cellular biology; Clinical; Commit; Complex; Computer software; Confocal Microscopy; Data; Development; Disease; Engineering; Environment; Epithelial Cells; Epithelial-Stromal Communication; Extracellular Matrix; Fluorescence Microscopy; Focal Adhesions; Gene Expression; Generations; Genes; Genetic; Genome; Genomics; Goals; Graph; Grouping; Growth Factor; Homeostasis; Image; Image Analysis; Imagery; Knowledge; Laboratories; Libraries; Malignant - descriptor; Malignant Neoplasms; Mammary Neoplasms; Mammary gland; Measures; Mechanics; Methods; Modeling; Molecular; Morphology; Non-Malignant; Oncogenic; Online Systems; Outcome; Output; Phenotype; Preclinical Drug Evaluation; Property; Publishing; Research; Sampling; Signal Pathway; Signal Transduction; Stress; System; Systems Integration; Technology; Testing; Therapeutic Intervention; Tissue Differentiation; Tissues; Validation; Voting; Work; base; computerized data processing; design; extracellular; genetic manipulation; genome wide association study; improved; in vivo; in vivo Model; indexing; meetings; next generation; novel; open source; outcome forecast; public health relevance; research study; response; screening; small hairpin RNA; software development; three-dimensional modeling; tumor; tumor progression; two-dimensional; usability

DESCRIPTION (provided by applicant): High-Content Representation and Association of Three-Dimensional Cell Culture Models We will develop a platform for morphometric profiling of three-dimensional (3D) cell culture models. Multicellular systems will be imaged with confocal microscopy in full 3D; cellular organization and a number of other end points will be computed; and multidimensional phenotypic signatures will be associated with genomic data. The potential results of this initiative are (i) a basic understanding of the biological processes in a model system that is a better predictor of in vivo models, (ii) a template for drug screening against tumor lines with desirable reversion properties, and (iii) a template for hypothesis generation and validation through associations of genomic and phenotypic data. More importantly, we will design experiments that involve the alteration of mechanical properties of the microenvironment (e.g., matrix stiffness) of mammary epithelial cells. We have established that cells tune their response to matrix stiffness, proportionally increase their contractibility, promote focal adhesion assembly, and enhance growth factor signaling. The end result is that cancer-activated signaling pathways and extracellular matrix (ECM) stiffness collaborate to enhance cell tension, which compromises tissue morphology and induces malignant behavior. Therefore, identification of tension-regulated genes that are also elevated in breast tumors can serve as biomarkers for cancer diagnostic and potential therapy. Our goal is to (i) couple advanced image analysis algorithms with a bioinformatics system for high-content screening of 3D cell culture models, (ii) develop novel ways to integrate phenotypic and molecular information, and (iii) test the hypothesis that modified stromal-epithelial interactions promote tumor behavior by compromising cell and tissue phenotypes as a result of changes in the matrix stiffness. We will meet these goals in the context of a set of nonmalignant and transformed breast cell lines with significant molecular diversity and engineered matrices that induce diverse changes in cell and tissue morphology. Three-dimensional cell culture models have emerged as effective systems to study tissue differentiation and cancer behavior. If cancer is fundamentally a disease of aberrant multicellular organization, then understanding the effects of the tissue microenvironment, cellular and molecular variables, and possible therapeutic interventions on the oncogenic phenotype requires the development and use of more sophisticated models that can approximate cell-cell and cell-matrix interactions in vivo. We will develop unique technologies with important biological questions to develop the next generation of systems cell biology platforms for use with 3D cell culture assays. The deliverables of our proposed efforts are (i) a validated open source platform for routine phenotypic representation of 3D cell culture models at multiple endpoints, (ii) a seamless association of phenotypic indices with the corresponding genomic data, and (iii) an open distribution of annotated raw and processed data.

描述（由申请人提供）：三维细胞培养模型的高内容表示和关联我们将开发一个用于三维（3D）细胞培养模型的形态测定分析的平台。多细胞系统将用共聚焦显微镜进行全3D成像;细胞组织和许多其他终点将被计算;多维表型特征将与基因组数据相关联。这一举措的潜在结果是（i）在一个模型系统，是一个更好的预测体内模型的生物过程的基本理解，（ii）针对肿瘤细胞系的药物筛选具有理想的逆转属性的模板，和（iii）通过基因组和表型数据的关联的假设生成和验证的模板。更重要的是，我们将设计涉及改变微环境机械特性的实验（例如，基质硬度）。我们已经确定，细胞调整其对基质硬度的反应，成比例地增加其收缩性，促进粘着斑组装，并增强生长因子信号传导。最终的结果是，癌症激活的信号通路和细胞外基质（ECM）的硬度合作，以提高细胞张力，这损害组织形态和诱导恶性行为。因此，鉴定在乳腺肿瘤中也升高的张力调节基因可以作为癌症诊断和潜在治疗的生物标志物。我们的目标是（i）将先进的图像分析算法与生物信息学系统结合起来，用于3D细胞培养模型的高内容筛选，（ii）开发整合表型和分子信息的新方法，以及（iii）测试修饰的基质-上皮相互作用通过损害细胞和组织表型作为基质刚度变化的结果来促进肿瘤行为的假设。我们将在一组具有显著分子多样性和工程基质的非恶性和转化乳腺细胞系的背景下实现这些目标，这些细胞系诱导细胞和组织形态的不同变化。三维细胞培养模型已成为研究组织分化和癌症行为的有效系统。如果癌症从根本上说是一种异常多细胞组织的疾病，那么了解组织微环境，细胞和分子变量的影响，以及可能的治疗干预对致癌表型需要开发和使用更复杂的模型，可以近似细胞-细胞和细胞-基质相互作用在体内。我们将针对重要的生物学问题开发独特的技术，以开发下一代系统细胞生物学平台，用于3D细胞培养分析。我们所提出的努力的可交付成果是：（i）一个经过验证的开源平台，用于在多个终点进行3D细胞培养模型的常规表型表示;（ii）表型指数与相应基因组数据的无缝关联;以及（iii）注释原始数据和处理数据的开放分布。