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: 8607905
• 负责人: Bahram A. Parvin
• 金额: $ 59.23万
• 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 2017-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8607905
• 关键词: Affect; Algorithms; Area; Atlases; Behavior; Bioinformatics; Biological; Biological Assay; Biological Markers; Biological Models; Biological Process; Biology; Breast; Breast Epithelial Cells; Cancer Diagnostics; Cell Culture Techniques; Cell Line; Cells; Cellular biology; Clinical; Commit; Complex; Computer software; Confocal Microscopy; Data; Development; Disease; Engineering; Environment; 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; 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(申请人提供)：三维细胞培养模型的高含量表示和关联我们将开发一个三维(3D)细胞培养模型的形态计量学分析平台。多细胞系统将用共聚焦显微镜全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。这一倡议的潜在结果是：(I)对模型系统中的生物学过程有了基本的了解，该模型系统是体内模型的更好预测者；(Ii)用于针对具有理想逆转特性的肿瘤株进行药物筛选的模板；以及(Iii)用于通过基因组和表型数据的关联来产生和验证假说的模板。更重要的是，我们将设计涉及改变乳腺上皮细胞微环境机械特性(例如，基质硬度)的实验。我们已经证实，细胞调整其对基质刚性的反应，按比例增加其收缩能力，促进局部黏附组装，并增强生长因子信号转导。最终的结果是，癌症激活的信号通路和细胞外基质(ECM)的僵硬共同增强了细胞的张力，从而损害了组织形态，并诱导了恶性行为。因此，确定张力调节基因在乳腺肿瘤中也升高，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相结合，用于高含量的3D细胞培养模型的筛选，(Ii)开发整合表型和分子信息的新方法，以及(Iii)检验如下假设：由于基质硬度的变化，改良的间质-上皮相互作用通过影响细胞和组织的表型而促进肿瘤行为。我们将在一系列具有显著分子多样性的非恶性和转化的乳腺细胞系以及诱导细胞和组织形态多样化的工程基质的背景下实现这些目标。三维细胞培养模型已经成为研究组织分化和癌症行为的有效系统。如果癌症本质上是一种异常的多细胞组织疾病，那么理解组织微环境、细胞和分子变量以及可能的治疗干预对致癌表型的影响需要开发和使用更复杂的模型来近似体内细胞-细胞和细胞-基质的相互作用。我们将开发具有重要生物学问题的独特技术，以开发用于3D细胞培养分析的下一代系统细胞生物学平台。我们建议的成果是(I)一个经过验证的开源平台，用于在多个端点进行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)带注释的原始和处理数据的开放分发。