Novel exosomal niches for alveolar stem cell-bassed repair of ARDS

用于 ARDS 肺泡干细胞修复的新型外泌体生态位

• 批准号: 10836707
• 负责人: HONG-LONG JI
• 金额: $ 48.02万
• 依托单位: LOYOLA UNIVERSITY CHICAGO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10836707
• 关键词: 3-Dimensional; Acute Respiratory Distress Syndrome; Alveolar; Bacterial Infections; Bass; Bioinformatics; Biological Markers; Biological Specimen Banks; Biomedical Engineering; Biometry; Bronchoalveolar Lavage; Bronchoalveolar Lavage Fluid; Catalysis; Cell Lineage; Cells; Classification; Clinical; Clinical Data; Clinical Research; Clinical Trials; Data; Disease; Double-Blind Method; Drug Targeting; Early Diagnosis; Enzymes; Epithelial Cells; Epithelium; Etiology; Gastrointestinal tract structure; Goals; Hospital Mortality; Human; Impairment; In Vitro; Infection; Influenza; Irrigation; Kidney; Liver; Lung; Mediating; Mediator; Methodology; Modeling; Multiple Organ Failure; Mus; National Heart, Lung, and Blood Institute; Natural regeneration; Organ; Organoids; Outcome; Oxygen; Paracrine Communication; Pathogenesis; Pathologic Processes; Pathway interactions; Patients; Pharmacologic Substance; Pharmacy (field); Pneumonia; Process; Prognosis; Proteins; Proteomics; Randomized Controlled Clinical Trials; Recovery; Regulation; Role; Sampling; Sepsis; Septic Shock; Severities; Signal Pathway; Signal Transduction; Signaling Molecule; Stratification; Testing; Tissues; United States National Institutes of Health; Validation; Virus Diseases; alveolar epithelium; autocrine; biomarker identification; candidate marker; cohort; data repository; design; differential expression; druggable target; epithelial injury; epithelial stem cell; epithelium regeneration; exosome; extracellular; extracellular vesicles; in vivo; in vivo Model; injury and repair; lung injury; lung regeneration; lung repair; machine learning algorithm; mortality; novel; novel marker; organ injury; paracrine; preclinical study; protein biomarkers; regenerative; repaired; sepsis induced ARDS; septic; stem cell fate; stem cell therapy; stem cells; success; supervised learning; urogenital tract

Summary. The regulation of alveolar regeneration of injured lungs by exosomal signals in acute respiratory distress syndrome (ARDS) are incompletely studied. We have identified exosomal proteins in bronchoalveolar lavage fluid (BALF) of ARDS patients that are closely association with the severity of lung injury. In ARDS, clinical severity is graded by the ratio of arterial oxygen tension (PaO2 in mmHg) to the fraction of inspired oxygen (FiO2). We have identified stem cell-related niche proteins that are present in mild (200£PaO2/FiO2<300 mmHg) to moderate ARDS (100£PaO2/FiO2<200 mmHg) but reduced in severe ARDS (PaO2/FiO2<100 mmHg). A key pathological process in ARDS is damage to the alveolar epithelium, which has been demonstrated in numerous preclinical and clinical studies to be associated with ARDS severity. Therefore, we hypothesize that exosomal signals for lung stem cell-mediated re-alveolarization are determinants of ARDS outcomes. Several findings support this hypothesis. 1) Exosomes are effective autocrine/paracrine pathways for stem cell lineage in injured organs. 2) Exosomal proteins are protected from catalysis by enzymes in inflamed tissues. 3) Unbiased high throughput proteomic analysis and advanced bioinformatic platforms have successfully identified novel biomarkers for other diseases. 4) Although the etiologies of ARDS are diverse, the repair processes mediated by epithelial stem/progenitor cells regulated by niches seem to be similar based on preclinical studies. Our objective is to test this hypothesis with BALF samples and patients' clinical data from NIH/NHLBI-supported clinical trials, prioritize niche molecules, and validate the results in genetically bioengineered mice and organoids of alveolar type 2 (AT2) epithelial cells. We will apply novel “exosomics” approaches, cutting-edge bioinformatics, three-dimensional culture models, robust cell origin tracking, and supervised machine learning algorithms. There are three specific aims: Aim 1 is designed to identify exosomal signaling pathways and networks in lavage that regulate the lineage of lung stem cells for re-alveolarization. We hypothesize that stem cell-mediated re- alveolarization has been suppressed in severe ARDS patients due to the disruption of key exosomal niches. We will prioritize differentially expressed exosomal proteins and related signaling pathways and networks using R packages. Aim 2 is designed to detect and optimize regenerative predictors for re-alveolarization of injured lungs. We hypothesize that the significantly differential exosomal molecules in lavage will be associated with clinical data in ARDS patients. We will perform unbiased clustering and supervised machine learning algorithms to develop models for discovering critical signals for lung regeneration. The prioritized exosomal predictors will be compared with traditional whole-protein markers for accuracy and applicability. Aim 3 will validate selected exosomal signals for AT2-mediated re-alveolarization. We will confirm that the exosomal molecules regulate the lineage of human and mouse AT2 cells in 3D organoids and mice. These studies will identify stem cell-specific exosomal molecules as potential pharmaceutic targets for ARDS.

概括。急性呼吸中外泌体信号对受伤肺肺泡再生的调节 遇险综合征（ARDS）不完全研究。我们已经确定了支气管肺泡中的外泌体蛋白 与肺损伤严重程度密切相关的ARDS患者的灌洗液（BALF）。在ARDS中，临床 严重程度通过动脉氧张力（MMHG中的PAO2）与启发的氧（FIO2）的比例进行分级。 我们已经确定了与温和细胞相关的小众蛋白（200£pao2/fio2 <300 mmHg）， 中度ARDS（100£PAO2/FIO2 <200 mmHg），但在严重的ARDS（PAO2/FIO2 <100 mmHg）中降低。钥匙 ARDS中的病理过程是对肺泡上皮的损害，这在许多人中已证明 与ARDS严重程度相关的临床前和临床研究。因此，我们假设外泌体 肺干细胞介导的重新肺泡的信号由ARDS结果确定。一些 发现支持这一假设。 1）外泌体是干细胞谱系的有效自分泌/旁分泌途径 在受伤器官中。 2）外泌体蛋白受到发炎组织中的酶的催化。 3）公正 高通量蛋白质组学分析和先进的生物信息学平台已成功鉴定 其他疾病的生物标志物。 4）尽管ARDS的病因是潜水员，但修复过程介导 根据临床前研究，通过受壁ches调控的上皮干/祖细胞似乎相似。我们的 目的是用BALF样品和NHLBI支持的患者的临床数据检验该假设 临床试验，优先考虑利基分子，并验证一般生物工程的小鼠和器官的结果 2型肺泡2（AT2）上皮细胞。我们将采用新颖的“外电子学”方法，尖端的生物信息学， 三维文化模型，健壮的细胞起源跟踪和受监管的机器学习算法。那里 是三个特定的目标：AIM 1旨在识别灌洗中的外泌体信号通路和网络 调节肺部干细胞的谱系进行重新肺泡化。我们假设干细胞介导的重新 由于关键的外泌体壁ches的破坏，严重的ARDS患者已抑制牙槽化。我们 使用R 软件包。 AIM 2旨在检测和优化可再生预测因子，以重新肺泡的肺肺泡化。 我们假设灌洗中的显着差异外泌体分子将与临床有关 ARDS患者的数据。我们将执行公正的聚类和监督的机器学习算法 开发用于发现肺部再生关键信号的模型。优先的外座子体预测指标将是 与传统的全蛋白标记物相比，准确性和适用性。 AIM 3将验证选定 AT2介导的重新肺泡化的外泌体信号。我们将确认外泌体分子调节 3D器官和小鼠中的人和小鼠AT2细胞的谱系。这些研究将确定干细胞特异性 外泌体分子作为ARDS的潜在药物靶标。