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

• 批准号: 10700811
• 负责人: Amanda Martinot
• 金额: $ 20.63万
• 依托单位: TUFTS UNIVERSITY BOSTON
• 依托单位国家: 美国
• 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/10700811
• 关键词: 2019-nCoV; Acute; Acute Respiratory Distress Syndrome; Agreement; Algorithmic Analysis; Animal Model; Antibodies; Antibody Therapy; Antibody-Dependent Enhancement; Area; Assessment tool; 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; Lung; Macrophage; Malignant Neoplasms; Measures; Mediating; Mesocricetus auratus; Modeling; Monoclonal Antibodies; Myelogenous; Myeloid Cells; New England; Outcome; PIK3CG gene; Pathologic; Pathology; Pathway interactions; Persons; Pharmaceutical Preparations; Phase II Clinical Trials; Population; Pre-Clinical Model; Preventive; Pulmonary Pathology; Reagent; Reproducibility; Reproducibility of Results; Research Design; SARS-CoV-2 infection; SARS-CoV-2 pathogenesis; Solid Neoplasm; Standardization; Testing; Therapeutic; Therapeutic antibodies; Time; Tissues; Titrations; Treatment Efficacy; Triage; Vaccines; Variant; Viral Load result; cellular targeting; digital pathology; drug candidate; drug efficacy; efficacy trial; immune cell infiltrate; immunohistochemical markers; improved; inhibitor; lung injury; 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

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

项目概要 巨噬细胞和中性粒细胞与人和非人灵长类动物的 SARS CoV-2 发病机制有关 但它们对仓鼠模型中 SARS CoV-2 病理学的贡献尚不清楚。 可以通过治疗靶向骨髓细胞来改善 COVID-19 的结果，我们将在 COVID-19 感染的仓鼠模型 仓鼠模型是一种易于处理的 COVID-19 小动物模型。 尚未对人类严重临床疾病进行建模，研究设计、组织和时间点的变化评估限制 我们建议进行跨机构结果比较和结果再现性。 可用于有效监测免疫细胞浸润并确定疾病进展机制 仓鼠模型，但需要建立临床疾病的病理相关性。 需要标准化 SARS CoV-2 感染动物模型的定量病理终点，以便 基准研究质量，改进数据的跨机构比较，验证细胞目标并评估 我们将使用定量方法来快速提高针对 SARS CoV-2 的潜在药物的治疗效果。 图像分析以探索骨髓介导的组织损伤的机制，例如抗体依赖性 使用叙利亚仓鼠模型和数字来增强疾病（ADE）和 PI3K 炎症通路。 病理学 我们将评估骨髓细胞群对 SARS 冠状病毒疾病病理学的相对贡献 2 感染并探索骨髓介导的肺损伤机制 我们将开发图像分析工具。 量化 SARS 仓鼠模型中的炎症浸润并确定临床疾病的病理相关性 我们将进行 CoV-2 感染滴定研究，以确定与临床相关的病理终点。 我们还将在此模型中定义疾病和病毒载量，以便更好地了解疫苗和治疗结果。 使用优化图像研究 SARS CoV-2 感染仓鼠中骨髓介导的组织损伤机制 我们将探索亚治疗单克隆抗体 (MAb) 治疗和非保护水平。 疫苗诱导的中和抗体建立评估 iADE 的病理指标并使用 PI3K-γ 抑制剂目前正在进行实体瘤的 II 期临床试验，以确定骨髓细胞运输是否可以 通过抑制 PI3K-γ 通路进行调节，开发经过验证的标准化定量图像。 与仓鼠临床和病毒学控制相关的分析终点将更快地推进预 开发 SARS CoV-2 治疗剂和预防剂的临床药物和疫苗功效试验。 工具还可用于探索 COVID-19 疾病的病理机制。 1

项目成果

Reduced SARS-CoV-2 disease outcomes in Syrian hamsters receiving immune sera: Quantitative image analysis in pathologic assessments.

接受免疫血清的叙利亚仓鼠的 SARS-CoV-2 疾病结果减少：病理评估中的定量图像分析。

• 发表时间: 2022-07
• 影响因子: 2.4
• 作者: Piedra;Robinson, Sally R;Tostanoski, Lisa H;Dayao, Denise A E;Chandrashekar, Abishek;Bauer, Katherine;Wrijil, Linda;Ducat, Sarah;Hayes, Tammy;Yu, Jingyou;Bondzie, Esther A;McMahan, Katherine;Sellers, Daniel;Giffin, Victoria;Hope
• 通讯作者: Hope