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

项目摘要 我们正在开发一种新的疾病诊断工具，称为指示细胞分析平台(ICAP)，它使用 标准化培养细胞作为生物传感器从血液或脑脊液中检测患者的疾病状态 (脑脊液)样本。在这里，我们建议通过以下方式建立将该分析应用于药物发现的概念证明 开始开发用于阿尔茨海默病(AD)药物选择的ICAP，如下所述。 我们正在开发的诊断AD的ICAP使用标准化的正常人类神经元作为生物传感器。在……里面 在这项测试中，神经元暴露于来自正常和AD患者的血浆(或脑脊液)样本，然后是全球 神经元的不同转录反应被用来定义疾病和正常信号。化验结果 然后根据患者的ICAP签名来诊断新患者。ICAP中的细胞反应反映了 已知的AD病理；我们已发现AD ICAP信号与AD特异性的基因显著重叠 尸检时在患者脑切片中发现的转录特征。因此，ICAP不仅是一个 诊断工具，也是一个独特的AD细胞模型，反映了最初健康的神经元对 病人样本中的疾病信号。 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 治疗早期阿尔茨海默病的候选人。我们将使用一种称为反向基因表达图谱的方法，该方法 通过识别引起细胞基因表达谱的药物来预测疾病的药物治疗 与疾病状态的特征相反。我们的方法有两个具体目标：1)我们将通过计算筛选一个 基因表达谱对各种药物的反应文库，以识别那些与现有药物相反的基因 早期AD的ICAP签名，以及2)我们将通过将药物暴露于神经元来进行实验测试 在ICAP中，并识别那些可以纠正ICAP早期AD签名并(部分)恢复 正常签名。我们的目标是确定使用ICAP进行药物发现的可行性，并确定新的 早期阿尔茨海默病的候选药物将在第二阶段研究的动物模型中进一步表征。 我们的长期目标是将ICAP建立为一个强大的药物选择工具，可以整合到药物中- 测试管道，并确定预防、治愈或减缓阿尔茨海默病进展的新药。就像化验一样 为个别患者生成个人签名，我们预计完全开发的ICAP将具有 能够为精确医学快速评估特定于患者的药物效果(无需生成 患者来源的神经元)。 PreCyte机密

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