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: 10440478
• 负责人: Matthew Ryen Lockett
• 金额: $ 49.96万
• 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/10440478
• 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; Epithelial; Estrogen receptor positive; Exposure to; Family; Fiber; Fibroblasts; Functional Imaging; Future; Gene Proteins; Gland; Growth; Health; Hormones; Imaging Techniques; In Vitro; Incidence; Industrialization; Investments; Label; Libraries; Link; Maintenance; Malignant Neoplasms; Mammary gland; Manufacturer Name; 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; 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; Work; assay development; base; 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; 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 全氟和多氟烷基物质(PFAS)是5000多种人造化学品的家族，它们是 由于其化学稳定性和生物累积性，在环境中无处不在。其中许多 “永久化学品”被认为与健康问题有关，包括发育健康的有力证据。 以及对荷尔蒙敏感组织的伤害。制造商继续用新的全氟辛烷磺酸取代暴露于- 基于健康的风险是未知的。公共卫生迫切需要确定使用中的全氟辛烷磺酸的影响 对乳腺发育和乳腺癌发病率增加的影响。目前的暴露研究使用 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种体外到体内外推(IVE)的乳腺管道 开发和维护以识别潜在有毒的全氟辛烷磺酸并确定其优先顺序，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的体外模型 增加复杂性但减少吞吐量，识别高吞吐量和高吞吐量之间的链路 复杂性模型端点读数，以最好地确定大型化学库的优先级。建立链接的关键技术 跨越多个体外培养平台的是基于光学相干层析成像的结构-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，它们的细胞内 光学混浊组织模型中形成的球体的运动性和形态。 我们的第一个具体目标是将MPI Lockett开发的高通量纸基培养系统推进到 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是采用3D协同文化模型 包括成纤维细胞，以模拟已知的影响乳腺发育的基质信号。OCT-SFI将 提供在这些培养物中形成的器官型球体的细胞运动性和形态。最后，我们的第三个 AIM将筛选40个PFA的文库，重点放在全氟醚羧酸(PFECA)上 目前用于工业涂料。此外，还将对体内存在的12种PFA进行筛查 啮齿动物模型数据可用，体外检测结果和体内腺体重塑之间的比较将 用于改进检测模型并建立筛查的初始阈值。 因此，作为该提议的一部分而开发的模型将是生物学的预测性的，从而使高通量 未来筛查所有全氟辛烷磺酸以及其他新出现的内分泌干扰物所需的能力。该项目的 OCT-SFI已知的成像能力可以探测3D球体和纸张中的响应，从而平衡了风险- 以共同文化为基础的。这种IVIVE管道的高通量特性使其成为筛选文库的理想选择 潜在的毒物，提供了空间和时间分辨的形态和 整个组织状结构的分子变化。