In Vitro Gene Expression Model Predicting Drug Induced Liver Disease

描述(申请人提供)：磷脂沉积症(PLD)或脂代谢紊乱是许多药物引起的肝病的一个因素。药物诱导的、剂量依赖的一组基因表达的改变，无论是直接的因果关系，都可以提供功能表型效应的分子特征(S)(例如，不良代谢)。明确的诊断是基于电子显微镜，但高通量的方法已发表评估基于基因表达和荧光脂类染色。大多数系统使用细胞系，尽管有些系统使用次优培养的原代肝细胞，但没有一个系统提供用于定量构效关系的精确剂量反应数据。众所周知，细胞系缺乏在原代肝细胞和肝脏中发现的代谢途径。在这个第一阶段的SBIR计划中，我们将一种新的基因表达测量方法-qNPA-与优化培养(三明治培养)的人类原代肝细胞相结合，将其与Hep-G2系统进行比较，并通过从以前报告中提取的一大组(~63)参考化合物来描述所有与PLDsis相关的(~86)个基因。我们将评估之前用于基因表达(24小时)、尼罗红(48小时)和电子显微镜(72小时)的基因表达，以便对结果进行直接比较。我们将对所有化合物的所有基因进行剂量响应测量，验证该分析可以提供对QSAR有用的EC50数据。最后，将选择一组集中的基因作为PLDsis的特征，并将评估初级肝细胞与Hep-G2以及基于qNPA的基因表达与尼罗红的益处。如果成功，我们将提交第二阶段申请，将该模型扩展到包括miRNA和额外的、可能更具选择性的基因，并包括识别其他肝病的基因签名。公共卫生相关性：磷脂沉积症(PLD)或脂代谢紊乱是许多药物引起的肝病的一个因素。在这一阶段的SBIR计划中，我们建议将基因表达方法-定量核酸酶保护分析(QNPA)与三明治培养的原代肝细胞相结合，为在药物发现过程中早期识别PLD提供一个灵敏的体外模型。QNPA的精密度高于聚合酶链式反应。原代肝细胞具有完整的肝细胞代谢和药物转运机制，而Hep-G2等细胞系则不具备，因此，我们的模型应该是一个更完善和更具相关性的细胞系统。我们将验证覆盖其他评估PLDsis方法所用时间点的其他时间点的额外基因，以证明提供精确的剂量反应数据和EC50值的能力，药物化学家可以使用这些数据来“设计”化学系列的PLDsis易感性。我们的目标是生成所需的数据，以确定使用qNPA基因表达/原代肝细胞模型与使用其他方法相比有什么优势。在第二阶段，我们将改进该模型，并将其扩展到其他肝脏疾病、大鼠初级肝细胞系统以及使用循环血细胞的体内生物标记系统。

DESCRIPTION (provided by applicant): Phospholipidosis (PLDosis) or lipid metabolism disorders are a factor in many drug induced liver diseases. Drug induced, dose-dependent, alterations in the expression of sets of genes, whether direct cause or effect, can provide a molecular signature of the functional phenotypic effect(s) (e.g. adverse metabolism). Definitive identification of PLDosis is based on electron microscopy, but high throughput methods to assess PLDosis have been published based on gene expression and fluorescent lipids staining. Most systems use cell lines, though some have used sub-optimally cultured primary hepatocytes, but none provides precise dose response data used for QSAR. It is known that cell lines lack metabolic pathways found in primary hepatocytes and the liver. In this Phase I SBIR program, we combine a novel method for measuring gene expression-qNPA--with optimally cultured (sandwich-cultured) human primary hepatocytes, compare this to a Hep-G2 system, and profile all the (~86) genes that have been linked to PLDosis across a large set (~63) of reference compounds taken from previous reports. We will evaluate gene expression across the time points used previously for gene expression (24hr) Nile Red (48 hr) and electron microscopy (72 hr) so that a direct comparison of results can be made. We will perform dose response measurements for all the genes for all the compounds, validating that the assay can provide EC50 data useful for QSAR. Finally, a focused set of genes will be selected as a PLDosis signature, and the benefit of primary hepatocytes vs HEp-G2 and of qNPA-based gene expression versus Nile Red will be evaluated. If successful, we will submit a Phase II application to expand the model to include miRNA and additional, potentially more selective genes, and to include identification of gene signatures for other liver diseases. PUBLIC HEALTH RELEVANCE: Phospholipidosis (PLDosis) or lipid metabolism disorders are a factor in many drug induced liver diseases. In this Phase I SBIR program, we propose to combine a gene expression method, the quantitative Nuclease Protection Assay (qNPA) with sandwich-cultured primary hepatocytes to provide a sensitive in vitro model for identifying PLDosis early in the drug discovery process. qNPA provides a level of precision superior to that of PCR. Primary hepatocytes have all the mechanisms of liver cell metabolism and drug transport intact, while cell lines such as Hep-G2 do not; therefore, our model should be a greatly improved and more relevant cell system. We will validate additional genes across time points that cover the time points used by other methods of assessing PLDosis to demonstrate the ability to provide precise dose response data and EC50 values that can be used by medicinal chemists to "design out" the PLDosis liability of chemical series. Our goal is to generate the data required to determine what the advantages of using the qNPA gene expression/primary hepatocyte model are compared to using other methods. In Phase II we will improve the model and extend it to other liver diseases, to a rat primary hepatocyte system, and to an in vivo biomarker system using circulating blood cells.