The Molecular Basis of Hepatitis C Clinical Resistance to Interferon Therapy

描述（由申请人提供）：本申请的长期目标是更好地了解病毒与宿主的相互作用，这种相互作用决定了为什么只有约50%的慢性HCV感染患者对干扰素和利巴韦林（目前的标准治疗）联合治疗有反应。这一目标很重要，因为在可预见的未来，即使在小分子抑制剂时代，干扰素治疗仍将是HCV治疗的关键支柱。了解干扰素治疗也将导致更好地了解病毒的先天免疫逃避机制。大型临床试验表明，感染不同HCV基因型的患者需要显著不同的治疗时间，并实现显著不同的持续病毒学应答率。我们的假设是(a)病毒基因组中的元素促成了这些对干扰素治疗的可变反应；因此(b)，我们的研究设计结合了HCV全长基因组的进化分析、基因型特异性临床结果数据和HCV蛋白结构信息，以确定病毒内导致对干扰素反应不足的关键因素。我们的初步数据包括HCV的系统基因组分析，显示HCV基因型年龄与临床对干扰素的反应相关。利用这种关系，我们已经生成了一个与临床对干扰素反应相关的病毒突变的计算机数据库。利用同源性模型，我们已经确定了HCV NS5A基因中这些突变的亚群，这些突变以基因型特异性的方式改变了HCV的生物物理性质。该应用程序的具体目的是：(1)基于进化、临床结果和HCV蛋白结构信息，使用定点诱变技术创建HCV突变体体外文库；2)分析这些HCV突变体对干扰素的敏感性。公共卫生相关性：全世界有超过1.7亿人慢性感染丙型肝炎病毒（HCV）。在美国，丙型肝炎病毒是导致肝癌的最常见原因。这项研究的目的是更好地了解谁将对目前的治疗有反应，并利用这些信息设计下一代抗丙型肝炎病毒药物。

DESCRIPTION (provided by applicant): The long term objective of this application is to better understand the viral-host interactions that determine why only ~50 percent of patients chronically-infected with HCV respond to combination therapy with interferon and ribavirin, the current standard of care. This objective is important because interferon therapy will remain the critical backbone of HCV therapy for the foreseeable future, even in the era of small molecule inhibitors. Understanding interferon therapy will also result in a better understanding of viral innate immune evasion mechanisms. Large clinical trials have revealed that patients infected with the various HCV genotypes require significantly different durations of therapy and achieve substantially different sustained virologic response rates. Our hypothesis is that (a) elements within the viral genome contribute to these variable responses to interferon therapy; and thus (b), our research design combines evolutionary analysis of full-length HCV genomes, genotype-specific clinical outcome data, and HCV protein structural information, to identify the key elements within the virus that contribute to inadequate response to interferon. Our preliminary data includes a phylogenomic analysis of HCV that reveals that HCV genotype age correlates with clinical response to interferon. Using this relationship, we have generated an in-silico database of viral mutations that correlate with clinical response to interferon. Using homology modeling, we have identified subsets of these mutations within the NS5A gene of HCV that alter its biophysical nature in a genotype-specific manner. The SPECIFIC AIMS of this application are to (1) use site-directed mutagenesis to create an in-vitro library of HCV mutants, based on evolutionary, clinical outcome, and HCV protein structural information; 2) to characterize the interferon sensitivity of these HCV mutants. PUBLIC HEALTH RELEVANCE: Over 170 million people worldwide are chronically infected with hepatitis C virus (HCV). In the US, HCV is the most common cause of liver cancer. The goal of this research is to better understand who will respond to current treatment and to use this information to design the next generation of anti-HCV drugs.