MicroRNAs as effectors of variable human drug metabolism

描述（由申请人提供）：药物基因组学的承诺-为每个人第一次确定正确药物的正确剂量-尚未完全实现，部分原因是 因为我们对药物反应变异性的机制缺乏完整的理解。最近的研究表明，microRNAs（miRs）-转录后调节基因表达的小非编码RNA-可能是药物代谢和处置中个体间差异的重要决定因素。在这里，我们建议使用各种新的方法来识别负责药物代谢酶变异的miR。该申请的重点将是UDP-葡萄糖醛酸转移酶（UGT）1A酶，该酶对消除许多具有狭窄治疗指数的临床重要药物至关重要。重要的是，所有9种UGT 1A酶（在18种总的人UGT中）由共享相同的3 '-非翻译区（UTR）的剪接mRNA编码。虽然我们有证据表明，这些酶的共同调节的转录后机制，几乎没有什么是已知的关于UGT 1A表达的miR的作用。我们的总体假设是，特异性miR通过保守的UGT 1A-3 '-UTR mRNA区域和/或间接通过调节转录因子水平来调节UGT 1A基因表达。为了检验这一假设，提出了以下具体目标。在目标1中，将通过多种独立方法鉴定与UGT 1A葡萄糖醛酸化相关的候选miR，包括生物信息学、功能基因组学筛选和全基因组（miR-转录组）关联研究。我们提出的新的功能基因组学筛选使得能够从所有已知的人miR的合并的慢病毒文库中快速鉴定抑制荧光标记的miR 3 '-UTR报告基因的miR。这种方法应该在我们的领域之外具有广泛的应用，从而能够实现成本有效的快速方法来描述“miR相互作用组”。将评价参比UGT 1A-3 '-UTR等位基因以及与体内胆红素葡萄糖醛酸化降低相关的主要变体（*1b）。还将通过miR转录组学（阵列和Next gen small RNA-seq）鉴定在具有低UGT 1A活性和翻译效率表型的人肝库样品中过表达的miR。在目的2中，我们将通过候选miR在人模型细胞系和原代肝细胞中的过表达（慢miR）和敲低（慢miR）来证实候选miR对UGT 1A葡萄糖醛酸化的功能影响。在目标3中，我们将通过使用UGT 1A-3 'UTR内切酶-报告基因构建体，并通过研究模型细胞系和原代人肝细胞中miR过表达和敲低对特定候选转录因子蛋白（PXR和HNF 1）以及整个蛋白质组的影响（iTRAQ LC-MS/MS方法），确定功能性miR对UGT 1A的调控机制。这项工作最终将导致开发经验证的预测生物标志物（血液中miR相关多态性和/或miR水平），这些生物标志物将被纳入目前正在开发的药物遗传学算法中，以指导低治疗指数药物的给药。

DESCRIPTION (provided by applicant): The promise of pharmacogenomics - identification of the right dose of the right drug the first time for everyone - has yet to be fully realized in part because we lack a complete understanding of the mechanisms underlying drug response variability. Recent studies suggest that microRNAs (miRs) - small noncoding RNAs that regulate gene expression post-transcriptionally - could be an important determinant of interindividual variability in drug metabolism and disposition. Here we propose to use a variety of novel approaches to identify miRs that are responsible for drug metabolizing enzyme variability. The focus of the application will be the UDP- glucuronosyltransferase (UGT) 1A enzymes that are critical to the elimination of many clinically important drugs with a narrow therapeutic index. Importantly, al 9 UGT1A enzymes (out of 18 total human UGTs) are encoded by spliced mRNAs that share an identical 3'-untranslated region (UTR). Although we have evidence that these enzymes are co-regulated by a post-transcriptional mechanism, virtually nothing is known regarding the role of miRs in UGT1A expression. Our overarching hypothesis is that specific miRs regulate UGT1A gene expression through the conserved UGT1A-3'-UTR mRNA region and/or indirectly by modulating regulatory transcription factor levels. To test this hypothesis, th following specific aims are proposed. In Aim 1 candidate miRs associated with UGT1A glucuronidation will be identified by multiple independent approaches, including bioinformatics, functional genomics screen, and whole genome (miR-transcriptome) association studies. The novel functional genomics screen we propose enables rapid identification of miRs that suppress a fluorescent- tagged miR 3'-UTR reporter from a pooled lentivirus library of all known human miRs. This method should have broad application outside of our field enabling a cost-effective rapid approach to describing of the "miR interactome". The reference UGT1A-3'-UTR allele will be evaluated as well as the major variant (*1b) associated with decreased bilirubin glucuronidation in vivo. miRs that are overexpressed in human liver bank samples with a low UGT1A activity and translational efficiency phenotype will also be identified by miR transcriptomics (arrays and Next gen small RNA-seq). In Aim 2 we wil confirm the functional impact of candidate miRs on UGT1A glucuronidation through overexpression (lenti-miRs) and knockdown (lenti- antagomiRs) of candidate miRs in human model cell lines and primary hepatocytes. In Aim 3 we will determine the mechanism of UGT1A regulation by functional miRs through use of UGT1A-3'UTR luciferase-reporter constructs and through studying effects of miR overexpression and knockdown in model cell lines and primary human hepatocytes on specific candidate transcription factor proteins (PXR and HNF1) as well as the entire proteome (iTRAQ LC-MS/MS method). This work will ultimately lead to development of validated predictive biomarkers (miR-associated polymorphisms and/or miR levels in blood) that would be incorporated into the pharmacogenetic algorithms currently being developed to guide dosing of low therapeutic index drugs.