Digital pathology for defining myeloid cell-mediated lung injury during acute SARS CoV-2 Infection in hamsters

用于定义仓鼠急性 SARS CoV-2 感染期间骨髓细胞介导的肺损伤的数字病理学

基本信息

批准号：
10348996
负责人：
Amanda Martinot
金额：
$ 24.75万
依托单位：
TUFTS UNIVERSITY BOSTON
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-08 至 2024-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10348996
关键词：
2019-nCoV Acute Acute Respiratory Distress Syndrome Agreement Algorithmic Analysis Animal Model Antibodies Antibody Therapy Antibody-Dependent Enhancement Area Benchmarking COVID-19 COVID-19 complications COVID-19 patient COVID-19 therapeutics Cells Cessation of life Clinical Complement Activation Data Development Disease Disease Outcome Disease Progression Endothelium Future Hamsters Human Image Analysis Immune Immunologic Monitoring Inflammation Inflammatory Inflammatory Infiltrate Inflammatory Response Institution Intervention Laboratories Lead Lung Malignant Neoplasms Measures Mediating Mesocricetus auratus Modeling Monoclonal Antibodies Myelogenous Myeloid Cells New England Outcome Pathologic Pathology Pathway interactions Persons Pharmaceutical Preparations Phase II Clinical Trials Population Pre-Clinical Model Preventive Pulmonary Pathology Reagent Reproducibility of Results Research Design SARS-CoV-2 infection SARS-CoV-2 pathogenesis Solid Neoplasm Standardization Testing Therapeutic antibodies Time Tissues Titrations Treatment Efficacy Triage Tumor-infiltrating immune cells Vaccines Variant Viral Load result cellular targeting digital pathology drug candidate drug efficacy efficacy trial immunohistochemical markers improved inhibitor lung injury macrophage multiple omics neutralizing antibody neutrophil nonhuman primate novel therapeutics novel vaccines pathogen phosphatidylinositol 3-kinase gamma pre-clinical promoter quantitative imaging response small molecule inhibitor targeted treatment therapy outcome tool trafficking vaccination outcome vaccine candidate vaccine efficacy vaccine-induced antibodies

项目摘要

Project Summary Macrophages and neutrophils are implicated in SARS CoV-2 pathogenesis in people and non-human primates but their contribution to SARS CoV-2 pathology in the hamster model is poorly defined. We hypothesize that myeloid cells can be targeted therapeutically to improve COVID-19 outcomes and we will explore this in the hamster model of COVID-19 infection. The hamster model is a tractable small animal model for COVID-19 that models severe clinical disease in humans yet, variations in study design, tissue and time-points assessed limit cross-institutional comparison of results and result reproducibility. We propose that quantitative image analysis can be used to effectively monitor immune cell infiltrates and define mechanisms of disease progression in the hamster model, but pathologic correlates of clinical disease need to be established. More broadly, there is a need to standardize quantitative pathologic endpoints in animal models of SARS CoV-2 infection in order to benchmark study quality, improve cross-institutional comparison of data, validate cellular targets, and assess therapeutic efficacy such that potential drugs for SARS CoV-2 can rapidly advance. We will use quantitative image analysis to explore mechanisms of myeloid mediated tissue damage such as antibody dependent enhancement of disease (ADE) and the PI3K inflammatory pathway. Using the Syrian hamster model and digital pathology we will assess the relative contribution of myeloid cell populations to disease pathology in SARS CoV- 2 infection and explore mechanisms of myeloid-mediated lung damage. We will develop image analysis tools to quantify inflammatory infiltrates and define pathologic correlates of clinical disease in the hamster model of SARS CoV-2 infection. We will perform titration studies to establish pathologic endpoints that correlate with clinical disease and viral load to better understand vaccine and therapeutic outcomes in this model. We will also define mechanisms of myeloid-mediated tissue damage in SARS CoV-2 infected hamsters using an optimized image analysis toolset. We will explore subtherapeutic monoclonal Ab (MAb) treatment and non-protective levels of vaccine-induced neutralizing antibodies to establish pathologic metrics for assessing iADE and use a PI3K-γ inhibitor currently in Phase II clinical trials for solid tumors, to determine whether myeloid cell trafficking can be modulated by inhibiting the PI3K-γ pathway. Development of validated and standardized quantitative image analysis end-points that correlate with clinical and virologic control in hamsters will more rapidly advance pre- clinical drug and vaccine efficacy trials for development of SARS CoV-2 therapeutics and preventives. These tools can also be used to explore pathologic mechanisms of disease in COVID-19. 1

项目摘要巨噬细胞和中性粒细胞在人和非人类隐私的SARS COV-2发病机理中实施但是，它们对仓鼠模型中SARS COV-2病理的贡献的定义很差。我们假设这一点可以将髓样细胞靶向治疗，以改善19.19的结果，我们将在 COVID-19感染的仓鼠模型。仓鼠模型是Covid-19的可拖动小动物模型模型在人类中严重的临床疾病模型，研究设计，组织和时间点的变化评估了极限结果跨机构比较结果和结果繁殖。我们提出了定量图像分析可用于有效监测免疫孔浸润并定义疾病进展的机制仓鼠模型，但需要建立临床疾病的病理相关性。更广泛地说，有一个需要在SARS COV-2感染的动物模型中标准化定量病理终点基准研究质量，改善数据的跨机构比较，验证细胞目标和评估治疗效率使得SARS COV-2的潜在药物可以迅速发展。我们将使用定量图像分析以探索髓样介导的组织损伤的机制，例如抗体依赖性增强疾病（ADE）和PI3K炎症途径。使用叙利亚仓鼠模型和数字病理学我们将评估髓样细胞群体对SARS COV-中疾病病理学的相对贡献 2感染和探索髓样介导的肺损伤的机制。我们将开发图像分析工具量化炎症性浸润并定义SARS仓鼠模型中临床疾病的病理相关性 COV-2感染。我们将进行滴定研究以建立与临床相关的病理终点疾病和病毒负荷以更好地了解该模型中的疫苗和治疗结果。我们还将定义使用优化图像分析工具集。我们将探索亚治性单克隆AB（mAb）治疗和非保护水平疫苗诱导的中和抗体建立病理指标，以评估IADE并使用PI3K-γ 目前正在针对实体瘤的II期临床试验中的抑制剂，以确定髓样细胞运输是否可以是通过抑制PI3K-γ途径进行调节。开发经过验证和标准化的定量图像与仓鼠中与临床和病毒学控制相关的分析终点将更迅速地促进 SARS COV-2疗法和预防剂开发的临床药物和疫苗效率试验。这些工具也可用于探索Covid-19中疾病的病理机制。 1