Developing an in vitro to in vivo pipeline of mammary gland exposure-response relationships to per- and poly-fluoroalkyl substances (PFAS)

开发乳腺对全氟烷基物质和多氟烷基物质 (PFAS) 的暴露-反应关系的体外到体内管道

• 批准号: 10654671
• 负责人: Matthew Ryen Lockett
• 金额: $ 49.43万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-28 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10654671
• 关键词: 3-Dimensional; Acids; Affect; Animals; Architecture; Biological Assay; Biology; Biometry; Breast Cancer Epidemiology; Breast Epithelial Cells; Cell Culture Techniques; Cell Line; Cells; Cellular Morphology; Characteristics; Chemical Exposure; Chemicals; Clinical Trials; Coculture Techniques; Complex; Data; Data Set; Development; Endocrine Disruptors; Environment; Environmental Exposure; Epithelium; Estrogen receptor positive; Exposure to; Family; Fiber; Fibroblasts; Functional Imaging; Future; Genes; Gland; Growth; Health; Hormones; Imaging Techniques; In Vitro; Incidence; Industrialization; Invaded; Investments; Label; Libraries; Link; Maintenance; Malignant Neoplasms; Mammary gland; Manufacturer; Mesenchymal; Methods; Modeling; Molecular; Morphology; Mus; National Institute of Environmental Health Sciences; Nature; North Carolina; Odds Ratio; Optical Coherence Tomography; Optics; Output; Paper; Pathology; Physiological; Poly-fluoroalkyl substances; Predisposition; Proliferating; Property; Public Health; Rattus; Research Personnel; Research Project Grants; Resources; Risk; Rodent; Rodent Model; S-Phase Fraction; Scanning; Scoring Method; Signal Transduction; Speed; Structure; System; Techniques; Technology; Testing; Time; Tissue Model; Tissues; Toxic Environmental Substances; Up-Regulation; Visualization; Work; assay development; carcinogenesis; carcinogenicity; cell motility; chemical stability; data modeling; deep learning; deep learning algorithm; high throughput screening; imaging capabilities; in vitro Assay; in vitro Model; in vivo; intercellular communication; machine learning algorithm; malignant breast neoplasm; malignant phenotype; mammary; mammary epithelium; mammary gland development; man; model design; non-invasive imaging; novel; optical imaging; premalignant; protein biomarkers; response; screening; small molecule libraries; temporal measurement; three dimensional cell culture; three-dimensional modeling; tool; toxicant

Project Abstract Per- and polyfluoroalkyl substances (PFAS) are a family of over 5000 man-made chemicals that are ubiquitous in the environment, due to their chemical stability and bioaccumulative properties. Many of these “forever chemicals” have been linked with health concerns, including strong evidence of developmental health and harm to hormone-sensitive tissues. Manufacturers continue to substitute new PFAS for which exposure- based health risks are unknown. There is an urgent public health need to determine the effects of PFAS in use on both mammary gland development and increased breast cancer incidence. Current exposure studies use rodent models that require cumbersome end-point analyses as well as large monetary and time investments. Our proposal is aimed at developing an in vitro to in vivo extrapolation (IVIVE) pipeline of mammary gland development and maintenance to identify and prioritize potentially toxic PFAS, to ultimately mitigate number of animals needed for environmental exposure studies. Our approach is to develop in vitro models of the mammary gland of increasing complexity but decreasing throughput, identifying links between high-throughput and high- complexity model endpoint readouts to best prioritize large chemical libraries. A key technology to establish links across multiple in vitro culture platforms is optical coherence tomography-based structural-functional imaging (OCT-SFI), developed by MPI Oldenburg, which non-invasively visualizes label-free cells, their intracellular motility, and morphology of formed spheroids, within optically turbid tissue models. Our first specific aim advances a high-throughput paper-based culture system, developed by MPI Lockett, to study mammary epithelial cell invasion in physiologically relevant tissue microenvironments. The platform will evaluate 96 different exposure conditions in parallel. Our second specific aim employs 3D co-culture models that include fibroblasts to model stromal signaling known to affect mammary gland development. OCT-SFI will provide cellular motility and morphology of the organotypic spheroids that form in these cultures. Finally, our third aim will screen a library of 40 PFAS, with a particular focus on the perfluoroethercarboxylic acids (PFECAs) currently used in industrial coatings. In addition, 12 PFAS will be screened for which there is existing in vivo rodent model data available, and comparisons between in vitro assay outputs and in vivo gland remodeling will be used to refine the assay models and establish initial thresholds for screening. The models developed as part of this proposal will thus be predictive of biology, enabling the high-throughput capability needed for future screening of all PFAS as well as other emerging endocrine disruptors. The project’s risk is balanced by the known imaging capabilities of OCT-SFI to probe responses in 3D spheroid and paper- based co-cultures. The high-throughput nature of this IVIVE pipeline makes it ideal for screening libraries of potential toxicants, providing information-rich datasets of spatially and temporally resolved morphological and molecular changes across the tissue-like structures.

项目摘要 全氟烷基和多氟烷基物质（PFAS）是一个超过5000种人造化学品的家族， 由于其化学稳定性和生物累积特性，在环境中普遍存在。许多这些 “永久性化学物质”与健康问题有关，包括发育健康的有力证据 并对皮肤敏感组织造成伤害。制造商继续使用新的PFAS， 健康风险未知。公共卫生迫切需要确定PFAS的使用效果 对乳腺发育和乳腺癌发病率的影响。目前的接触研究使用 啮齿动物模型需要繁琐的终点分析以及大量的金钱和时间投资。 我们的建议旨在开发一个体外到体内外推（IVIVE）的乳腺管道 开发和维护，以识别和优先考虑潜在的有毒PFAS，以最终减少 环境暴露研究所需的动物。我们的方法是建立乳腺癌的体外模型， 复杂性增加但吞吐量降低的腺体，确定高吞吐量和高吞吐量之间的联系， 复杂性模型终点读数，以最佳地优先化大型化学品库。建立链接的关键技术 基于光学相干断层扫描的结构-功能成像 （OCT-SFI），由MPI Oldenburg开发，它非侵入性地可视化无标记细胞，其细胞内 运动性和形成的球状体的形态，在光学混浊组织模型。 我们的第一个具体目标是推进由MPI Lockett开发的高通量纸基培养系统， 研究乳腺上皮细胞在生理相关组织微环境中的侵袭。该平台将 同时评估96种不同的暴露条件。我们的第二个具体目标采用3D共文化模型， 包括成纤维细胞以模拟已知影响乳腺发育基质信号传导。OCT-SFI将 提供在这些培养物中形成的器官型球状体的细胞运动性和形态。最后，我们的第三 aim将筛选一个包含40种PFAS的库，特别关注全氟醚羧酸（PFECA） 目前用于工业涂料。此外，还将筛选12种PFAS， 啮齿动物模型数据可用，体外测定输出和体内腺体重塑之间的比较将 可用于改进分析模型并建立筛选的初始阈值。 因此，作为该提案的一部分开发的模型将预测生物学，从而实现高通量 未来筛查所有PFAS以及其他新出现的内分泌干扰物所需的能力。该项目的 通过已知的OCT-SFI成像能力来平衡风险，以探测3D球体和纸中的响应， 基于共同文化。这种IVIVE管道的高通量性质使其成为筛选以下文库的理想选择： 潜在的毒物，提供信息丰富的数据集的空间和时间分辨形态和 组织样结构的分子变化。