Validation of an in vitro model of progressive fibrosis that mimics Idiopathic Pulmonary Fibrosis

模拟特发性肺纤维化的进行性纤维化体外模型的验证

• 批准号: 10542830
• 负责人: JOHN A BELPERIO
• 金额: $ 63.04万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-02-15 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10542830
• 关键词: 3-Dimensional; Affect; Age; Algorithmic Analysis; Alveolar; Animal Model; Apoptosis; Architecture; Biological Assay; Biological Models; Biological Process; Biology; Biomedical Engineering; CASP3 gene; Cell Aging; Cell Differentiation process; Cell Line; Cells; Characteristics; Chronic; Collection; Data; Disease; Disease model; Drug Modelings; Drug Screening; Epithelial Cells; Epithelium; Ethnic Origin; Etiology; Extracellular Matrix; Fibroblasts; Fibrosis; Gender; Goals; Health; Heterogeneity; Host Defense; Human; Image; Image Analysis; Inflammatory; International; Interstitial Lung Diseases; Lung; Lung diseases; MUC5B gene; Measures; Mesenchymal; Methods; Michigan; Modeling; Molecular; Pathogenesis; Pathologist; Patients; Phenocopy; Phenotype; RNA analysis; Race; Reporter; Reporting; Research; Research Personnel; Running; Signal Transduction; Standardization; Structure of parenchyma of lung; System; Techniques; Tissues; Validation; airway epithelium; analysis pipeline; antifibrotic treatment; cell type; chemokine; clinically relevant; curative treatments; cytokine; deep learning; drug discovery; drug use screening; efficacy study; fibrotic lung; genetic risk factor; genetic variant; high-throughput drug screening; human model; idiopathic pulmonary fibrosis; image processing; improved; in vitro Model; induced pluripotent stem cell; innovation; machine learning algorithm; novel therapeutics; precision medicine; prevent; senescence; single-cell RNA sequencing; small molecule; stem cell model; success; three-dimensional modeling

Abstract We have developed a 3D bioengineered human induced pluripotent stem cell (iPSC) derived model of IPF that displays progressive fibrosis and closely phenocopies several characteristics associated with IPF. This model is an extension of our 2D model of progressive fibrosis (Vijayaraj et al., Cell Reports – in press). To make our progressive fibrosis model specific to IPF, we have developed it into a model system that utilizes the lung 3D architecture and specific cell types. Our 3D model displays additional features of IPF such as airway epithelial cell (AEC) apoptosis, epithelial-mesenchymal transition (EMT) and replacement of alveolar architecture. Our proposal aims to improve and validate this 3D model such that it will be amenable to a high throughput drug discovery platform in a patient specific manner for precision medicine. Our project aims to use our unique stem/progenitor cell models of IPF to increase our understanding of the disease and for drug discovery. Specific Aim 1. To improve and validate the 3D bioengineered human iPSC derived model of IPF A. To validate the 3D model of IPF by performing extensive characterization of the model compared to human IPF lung tissue. B. To characterize the heterogeneity of IPF seen across different patients. C. To characterize the 3D IPF model by known genetic risk factors. Specific Aim 2 – To use our 3D bioengineered iPSC-derived model to study cellular plasticity in IPF To profile cellular plasticity of AECs in our 3D model of IPF and compare it to human IPF tissue using single cell RNA sequencing. Specific Aim 3 – To develop and standardize a high throughput drug screening (HTS) platform to identify new anti-fibrotic therapies using the 3D model of IPF A. To develop a HTS using the 3D model of IPF. B. To develop robust, image analysis pipelines that employ a combination of advanced deep learning techniques and traditional image processing methods to generate quantitative measures of tissue health. C. To develop and run a pilot HTS to identify small molecules that will perform one or more of the following a) prevent apoptosis of AEC; b) enhance apoptosis of mesenchymal cells; c) decrease expression of -SMA. Our team includes international experts who study lung biology (Gomperts, UCLA), biology of fibrosis (Vijayaraj, UCLA), an IPF clinician and researcher (Belperio, UCLA), lung pathologist (Wallace, USC), iPSC airway epithelial cell differentiation (Spence, Michigan), single cell RNA seq and analysis (Plath, UCLA), and high throughput drug discovery (Damoiseaux, UCLA) with machine learning algorithms for analysis (Shattuck, UCLA). We are a highly collaborative team that is working together using innovative, patient relevant research approaches to tackle the challenges of modeling IPF to identify new therapies.

抽象的 我们已经开发了3D生物工程的人类诱导的多能干细胞（IPSC）衍生的IPF模型 展示进行性纤维化和紧密的表演与IPF相关的几个特征。这个模型是 我们的2D进行性纤维化模型的扩展（Vijayaraj等，细胞报告 - 印刷中）。让我们的 渐进性纤维化模型特定于IPF，我们将其开发为使用肺3D的模型系统 体系结构和特定的单元格类型。我们的3D模型显示IPF的其他功能，例如气道上皮 细胞（AEC）细胞凋亡，上皮 - 间质转变（EMT）和肺泡结构的替代。 我们的建议旨在改进和验证该3D模型，以便它可以适应高通量药物 以患者的特定方式进行精确医学的发现平台。我们的项目旨在使用我们的独特 IPF的茎/祖细胞模型，以增加我们对疾病和药物发现的理解。 特定目标1。改善和验证IPF的3D生物工程人IPSC衍生模型 答：通过与人类相比，通过对模型进行广泛的表征来验证IPF的3D模型 IPF肺组织。 B.表征不同患者的IPF的异质性。 C.通过已知的遗传风险因素来表征3D IPF模型。 特定目标2 - 使用我们的3D生物工程IPSC衍生的模型研究IPF中的细胞可塑性 在我们的IPF的3D模型中介绍AEC的细胞可塑性，并使用单细胞将其与人类IPF组织进行比较 RNA测序。 特定目标3 - 开发和标准化高通量药物筛查（HTS）平台以识别 使用IPF的3D模型的新抗纤维化疗法 答：使用IPF的3D模型开发HTS。 B.为了开发强大的图像分析管道，采用了高级深度学习的组合 技术和传统图像处理方法，以生成组织健康的定量测量。 C.开发和运行一个飞行员HTS来识别将执行以下一个或多个a的小分子） 防止AEC凋亡； b）增强间充质细胞的凋亡； c）降低-SMA的表达。 我们的团队包括研究肺部生物学（Gomperts，UCLA）的国际专家，纤维化生物学（Vijayaraj， UCLA），IPF临床和研究人员（Belperio，UCLA），肺病理学家（Wallace，USC），IPSC Airway 上皮细胞分化（Spence，Michigan），单细胞RNA SEQ和分析（PLATH，UCLA）和高 吞吐药物发现（Damoiseaux，UCLA）具有用于分析的机器学习算法（Shattuck，UCLA）。 我们是一支高度协作的团队，正在使用创新的，患者相关的研究一起合作 解决IPF建模以识别新疗法的挑战的方法。