Rational drug selection for Alzheimer's disease using Indicator Cell Assay Platform (iCAP)

使用指示细胞检测平台 (iCAP) 合理选择阿尔茨海默病药物

• 批准号: 9347076
• 负责人: Jennifer Joy Smith
• 金额: $ 29.94万
• 依托单位: PRECYTE, INC.
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-15 至 2019-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9347076
• 关键词: Age; Alzheimer' s Disease; Alzheimer' s disease model; Animal Model; Autopsy; Biological Assay; Biosensor; Blood; Blood - brain barrier anatomy; Brain; Cell model; Cells; Cerebrospinal Fluid; Clinical Trials; Cultured Cells; Data; Databases; Development; Diagnosis; Diagnostic; Disease; Drug vehicle; Elements; Environment; Expression Library; FDA approved; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Gene Library; Generations; Genes; Genetic; Genetic Transcription; Goals; Human; Measures; Modeling; Molecular Profiling; Neurons; Pathology; Patients; Pharmaceutical Preparations; Pharmacology; Pharmacotherapy; Phase; Plasma; Safety; Sampling; Signal Transduction; Standardization; System; Testing; Time; base; differential expression; disease diagnosis; drug candidate; drug discovery; drug testing; in vivo; individual patient; innovation; novel; novel therapeutics; phase 2 study; precision medicine; preclinical development; prevent; response; small molecule; tool

Project Summary We are developing a novel tool for disease diagnosis called the indicator cell assay platform (iCAP) that uses standardized cultured cells as biosensors to detect disease status of patients from blood or cerebral spinal fluid (CSF) samples. Here, we propose to establish proof of concept for applying the assay to drug discovery by initiating development of the iCAP for drug selection for Alzheimer’s disease (AD) as described below. The iCAP we are developing for diagnosis of AD uses standardized normal human neurons as biosensors. In the assay, neurons are exposed to plasma (or CSF) samples from normal and AD patients, and then the global differential transcriptional responses of the neurons are used to define disease and normal signatures. The assay is then used to diagnose new patients based on their iCAP signatures. Cellular responses in the iCAP reflect known AD pathology; we have identified significant overlap in genes of the AD iCAP signature with AD-specific transcriptional signatures identified in patient brain sections at autopsy. Therefore, the iCAP is not only a diagnostic tool, but also a unique cellular model of AD reflecting the response of initially healthy neurons to disease signals in the patient samples. Here we propose to use the iCAP as a cellular model of AD to select and evaluate FDA-approved drugs as candidates for treating early-stage AD. We will use an approach called inverse gene expression profiling, which predicts drug treatments for diseases by identifying drugs that elicit cellular gene expression profiles that are inverse to profiles of the disease state. Our approach has 2 specific aims: 1) We will computationally screen a library of gene expression profile responses to various drugs to identify those that are the inverse of existing iCAP signatures for early-stage AD, and 2) We will experimentally test the drugs by exposing them to neurons in the iCAP, and identifying those that can correct the iCAP early-stage AD signature and (partially) restore the normal signature. Our goals are to establish feasibility of using the iCAP for drug discovery, and to identify new drug candidates for early-stage AD that will be further characterized in an animal model in a Phase II study. Our long term goals are to establish the iCAP as a robust tool for drug selection that can be integrated into drug- testing pipelines, and to identify new drugs to prevent, cure or slow the progression of AD. As the assay generates personal signatures for individual patients, we anticipate that the fully developed iCAP will have capability to rapidly assess patient-specific drug effects for precision medicine (without the need for generating patient-derived neurons). PreCyte Confidential

项目摘要 我们正在开发一种新的疾病诊断工具，称为指示细胞检测平台（iCAP）， 标准化培养细胞作为生物传感器，从血液或脑脊液检测患者的疾病状态 (CSF)样品在这里，我们建议通过以下方式建立将该测定应用于药物发现的概念证明： 启动用于阿尔茨海默病（AD）药物选择的iCAP的开发，如下所述。 我们正在开发的用于诊断AD的iCAP使用标准化的正常人类神经元作为生物传感器。在 在该测定中，将神经元暴露于来自正常和AD患者的血浆（或CSF）样品，然后将神经元暴露于来自正常和AD患者的血浆（或CSF）样品的总体浓度。 神经元的不同转录应答用于定义疾病和正常信号。测定 然后用于基于他们的iCAP签名诊断新患者。iCAP中的细胞反应反映了 已知的AD病理学;我们已经确定了AD iCAP特征基因与AD特异性 在尸检时发现了病人大脑切片中的转录特征。因此，iCAP不仅是一个 诊断工具，但也是一个独特的AD细胞模型，反映了最初健康的神经元对 患者样本中的疾病信号。 在这里，我们建议使用iCAP作为AD的细胞模型来选择和评估FDA批准的药物， 用于治疗早期AD的候选物。我们将使用一种称为反向基因表达谱的方法， 预测药物治疗的疾病，通过确定药物，引起细胞基因表达谱， 与疾病状态的分布相反。我们的方法有两个具体目标：1）我们将计算筛选一个 基因表达谱库对各种药物的反应，以确定那些是现有的逆转 早期AD的iCAP特征，以及2）我们将通过将药物暴露于神经元来实验性地测试药物 在iCAP中，并确定那些可以纠正iCAP早期AD特征码并（部分）恢复 正常签名我们的目标是建立使用iCAP进行药物发现的可行性，并确定新的 用于早期AD的候选药物，其将在II期研究的动物模型中进一步表征。 我们的长期目标是将iCAP作为一种强大的药物选择工具，可以整合到药物筛选中。 测试管道，并确定新的药物，以预防，治愈或减缓AD的进展。作为试验 为个体患者生成个人签名，我们预计完全开发的iCAP将具有 能够快速评估患者特异性药物效应，以实现精准医疗（无需生成 患者源性神经元）。 PreCyte机密