Genomic Analysis of Tissue and Cellular Heterogeneity in IPF

 描述（由申请方提供）：特发性肺纤维化（IPF）是一种慢性进行性肺部疾病，具有显著的发病率和死亡率。目前没有有效的 肺移植以外的治疗IPF肺表现出不同的mRNA和microRNA表达模式以及DNA甲基化的整体变化。最近的观察，主要是在肺纤维化的动物模型中，表明畸变在多个途径中的作用，如凝血、凋亡、氧化应激、上皮细胞表型的变化、内质网应激和发育途径。该授权的基础假设是IPF的独特组织病理学特征-时间异质性、肺泡细胞增生、肌成纤维细胞灶丰富和异常重塑-代表了IPF特有的分子疾病机制。因此，了解这些特征背后的分子网络将有助于更好地了解IPF，并最终导致更合理的基于疾病机制的治疗干预。为此，我们组建了一个多学科专家团队，包括肺纤维化、基因组学、计算生物学、计算机科学、细胞和分子生物学、统计学、高通量筛选和生物信息学。 该研究将承担以下具体目标：1）鉴定组织学定义的肺微环境的独特基因组学和转录组学特征。这一目标将包括使用microCT引导的显微切割、下一代测序和激光捕获显微切割-还原亚硫酸氢盐测序（LCM-RRBS）生成组织学上不同的、差异受影响的肺区域的mRNA、microRNA和表观基因组谱。2)通过结合LCM指导的IPF肺中不同细胞群（肌成纤维细胞、增生性上皮细胞）的采样、从患者分离的原代细胞（肺泡II型和成纤维细胞）的转录组学分析，确定细胞对IPF肺中基因组和表观基因组变化的贡献 基线时伴和不伴IPF以及对纤维化相关扰动的应答。将通过定量免疫组织化学和原位杂交在IPF肺中验证、定位和定量细胞特征。3)基于基因组数据生成IPF的动态调控模型，并对模型预测进行初步实验验证。该目标包括生成整合的IPF基因组和表观基因组数据概要，应用新的分析方法来鉴定关键调节因子，以及通过测试潜在的干扰效应来进行预测的初步验证。 分析将被纳入一个简单，直观，基于网络的界面，IPFmap，这将使研究人员能够交互式地挖掘数据，使用分析工具，将自己的数据整合到这些分析中，并提供无缝访问补充数据库，使治疗的发展。

 DESCRIPTION (provided by applicant): Idiopathic Pulmonary Fibrosis (IPF) is a chronic and progressive lung disease with significant morbidity and mortality. At present there is no effective treatment other than lung transplantation. The IPF lung displays distinct patterns of mRNA and microRNA expression patterns and global changes in DNA methylation. Recent observations, mainly in animal models of lung fibrosis, suggest a role for aberrations in multiple pathways such as coagulation, apoptosis, oxidative stress, shifts in epithelial cell phenotypes, endoplasmic reticulum stress, and developmental pathways. The hypothesis underlying this grant is that the unique histopathologic features of IPF-temporal heterogeneity, alveolar cell hyperplasia, abundance of myofibroblast foci and aberrant remodeling-represent a molecular disease mechanism specific to IPF. Therefore, understanding the molecular networks that underlie these characteristics will lead to better understanding of IPF and eventually more rational, disease mechanism based therapeutic interventions. For this purpose we have assembled a multi-disciplinary team of experts in lung fibrosis, genomics, computational biology, computer science, cell and molecular biology, statistics, high-throughput screening and bioinformatics. The study will undertake the following specific aims: 1) Identification of the unique genomic and transcriptomics characteristics of histologically defined lung microenvironments. This aim will include generation of mRNA, microRNA and epigenomic profiles of histologically distinct, differentially affected regions of the lung using microCT guidd microdissection, next generation sequencing and laser capture microdissection-reduced representation bisulfite sequencing (LCM-RRBS). 2) Determination of the cellular contribution to the genomic and epigenomic changes in the IPF lung by a combination of LCM guided sampling of distinct cell populations in the IPF lung (myofibroblasts, hyperplastic epithelial cells), transcriptomic profiling of primary cells (alveolar type II and fibroblasts) isolated from patients with and without IPF at baseline and in response to fibrosis relevant perturbations. Cellular signatures will be validated, localized and quantified in IPF lungs by quantitative immunohistochemistry and in-situ hybridization. 3) Generate a dynamic regulatory model of IPF based on genomic data and perform preliminary experimental validation of model predictions. This aim includes generation of an integrated IPF genomic and epigenomic data compendium, application of novel analytic approaches to identify key regulators and performance of preliminary validation of predictions by testing effect of perturbations of potential The data and analyses will be incorporated into a simple, intuitive, web-based interface, IPFmap, that will allow investigators to interactively mine the data, use analytical tools, integrate their own data into these analyses, and provide seamless access to complementary databases enabling development of therapies.