Single-Cell Transcriptomic Analysis to Identify Drivers of Pulmonary Fibrosis

单细胞转录组分析识别肺纤维化的驱动因素

基本信息

批准号：
9892329
负责人：
Paul A Reyfman
金额：
$ 16.33万
依托单位：
NORTHWESTERN UNIVERSITY AT CHICAGO
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-02-20 至 2025-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/9892329
关键词：
Address Aging Alveolar Alveolar Macrophages Automobile Driving Award Biochemical Biological Process Bleomycin Bronchoalveolar Lavage Fluid Cell Nucleus Cells Chronic lung disease Cicatrix Clinical Data Communities Computing Methodologies Connective Tissue Diseases Cryopreservation Data Data Analyses Data Set Development Diagnosis Diagnostic Digestion Disease Donor person Drug Exposure Ensure Environmental Exposure Epithelial Cells Fibroblasts Fibrosis Foundations Funding Future Gases Gene Expression Gene Expression Profiling Genes Genomics Goals Gold Health Heterogeneity Human Image Immunohistochemistry Impairment In Situ Hybridization Individual Investigation Knowledge Laboratories Lead Lung Lung Compliance Lung Transplantation Machine Learning Mentors Molecular Mus Occupational Exposure Patient Selection Patients Physicians Population Prediction of Response to Therapy Protocols documentation Pulmonary Fibrosis RNA Reporting Research Personnel Risk stratification Sampling Scientist Selection for Treatments Small Nuclear RNA Specimen Structure of parenchyma of lung System Systemic Scleroderma Systems Biology Techniques Technology Testing Tissues Training Training Programs Work base biomarker development career career development cell type clinical care clinical phenotype clinical practice computerized tools design differential expression effective therapy experimental study genomic data idiopathic pulmonary fibrosis improved individual patient insight macrophage monocyte mouse model new therapeutic target novel novel marker novel strategies outcome forecast personalized approach predicting response recruit single cell analysis single-cell RNA sequencing skills tool transcriptome sequencing transcriptomics treatment response

项目摘要

PROJECT SUMMARY This proposal for a K08 Award is motivated by two overarching goals: 1) to support the scientific and professional development of the candidate, Dr. Paul Reyfman, towards achieving his career goal of succeeding as a physician scientist and independent investigator with expertise in systems biology approaches applied to the study of chronic lung disease, and 2) to investigate whether single-cell transcriptomic profiling can provide novel insights into the pathobiology of pulmonary fibrosis. Pulmonary fibrosis is a deadly and progressive condition for which diagnostic approaches remain imprecise and effective therapies are lacking. Together with his mentors, Drs. Scott Budinger and Luís Amaral, the candidate has developed a comprehensive training plan that will ensure Dr. Reyfman acquires new knowledge and proficiencies in developing hypotheses, designing and completing experiments, analyzing data, and communicating findings to the scientific community. As an essential component of this training plan, the candidate will employ systems biology approaches to developing tools for analysis of single-cell transcriptomic datasets generated from patients with pulmonary fibrosis. Single-cell transcriptomic profiling is increasingly used to investigate the pathobiology of disease in humans and as a basis for developing novel biomarkers of disease. Developing and validating tools for analyzing the rapidly growing quantity of single-cell transcriptomic data is as much of a challenge as refining techniques for generating data from healthy and diseased tissues. In particular, it is not known whether analysis of single-cell RNA sequencing (scRNA-Seq) and single-nucleus RNA sequencing (snRNA-Seq) data can be used to quantify accurately the cellular composition of the lung and to identify gene expression differences between health and pulmonary fibrosis. Our preliminary data suggest that scRNA-Seq of lung identifies profibrotic gene expression in patients with pulmonary fibrosis that is heterogeneous between individuals. We also found that scRNA-Seq undersampled certain constituent lung cellular populations. Accordingly, we designed this proposal to test the hypothesis that single-cell transcriptomic analysis of lung samples from patients with pulmonary fibrosis can be used to identify disease endotypes. In Specific Aim 1, the candidate will determine whether snRNA-Seq enables quantification of the cellular composition of the lung during pulmonary fibrosis. In Specific Aim 2, the candidate will develop tools for using scRNA-Seq performed on specimens obtained from patients with SSc-ILD and normal controls to gain novel insights into disease pathobiology. Over the course of this award, the candidate will gain new skills including in generating snRNA-Seq from cryopreserved lung tissue, in lung stereology, in RNA in situ hybridization, in analysis of complementary genomic datasets, and in incorporation of clinical phenotypic information into genomic analyses. Accomplishing the proposed work will provide a rigorous training program for Dr. Reyfman and will provide insights that could lead to improved therapies for patients with pulmonary fibrosis.

项目概要 K08 奖的提议有两个总体目标：1) 支持科学和专业候选人 Paul Reyfman 博士的发展，以实现他作为一名成功的医生的职业目标科学家和独立研究者，拥有系统生物学方法的专业知识，应用于研究慢性肺病，2) 研究单细胞转录组分析是否可以提供新的见解肺纤维化的病理学是一种致命的、进行性的疾病。诊断方法仍然不精确，并且缺乏有效的治疗方法。候选人斯科特·巴丁格 (Scott Budinger) 和路易斯·阿马拉尔 (Luís Amaral) 制定了一项全面的培训计划，以确保博士。雷夫曼在提出假设、设计和完成方面获得了新知识和熟练程度实验、分析数据以及向科学界传达研究结果是一个重要组成部分。在该培训计划中，候选人将采用系统生物学方法来开发分析工具从肺纤维化患者生成的单细胞转录组数据集。单细胞转录组分析越来越多地用于研究人类疾病的病理学和作为开发新型疾病生物标志物的基础，开发和验证快速分析疾病的工具。单细胞转录组数据数量的不断增长与完善生成数据的技术一样是一个挑战。特别是，尚不清楚是否可以分析来自健康和患病组织的数据。测序 (scRNA-Seq) 和单核 RNA 测序 (snRNA-Seq) 数据可用于定量准确地检测肺部的细胞组成，并识别健康和健康之间的基因表达差异我们的初步数据表明，肺的 scRNA-Seq 可以识别促纤维化基因的表达。我们还发现 scRNA-Seq 在肺纤维化患者中存在个体差异。因此，我们设计了这个提案来测试某些肺细胞群体的样本。假设对肺纤维化患者的肺样本进行单细胞转录组分析可以用于识别疾病内型在特定目标 1 中，候选人将确定 snRNA-Seq 是否启用。肺纤维化期间肺细胞组成的量化在特定目标 2 中，候选者。将开发使用 scRNA-Seq 的工具，对从 SSc-ILD 患者和正常人身上获得的样本进行分析控制以获得对疾病病理学的新颖见解在该奖项的过程中，候选人将获得新技能包括从冷冻肺组织生成 snRNA-Seq、肺体视学、RNA 原位杂交、互补基因组数据集分析以及临床表型的纳入完成拟议的工作将为基因组分析提供严格的培训计划。雷夫曼博士将提供一些见解，从而改善肺纤维化患者的治疗方法。