Analysis of Racial Disparities in HCC by Systems Metabolomics

 描述（由申请人提供）：肝细胞癌（HCC）在美国是一个严重的健康问题。与欧洲裔美国人（EA）相比，非裔美国人（AA）的HCC发病率更高，并且与诊断时更晚期的肿瘤分期和更低的生存率相关。据报道，甲胎蛋白（AFP）用于诊断患有丙型肝炎病毒（HCV）感染的非裔美国人中的HCC的敏感性低于所有其他种族群体的患者的总和。我们先前通过使用液相色谱-质谱（LC-MS）和气相色谱-质谱（GC-MS）对HCC病例和肝硬化患者的血清进行代谢组学分析，对种族差异进行了初步调查。通过LC/GC-MS数据的分层分析，我们确定了区分HCC病例与AA和EA中的动脉粥样硬化对照的不同候选者。该应用建立在这些有希望的初步结果的基础上，以发现和验证种族特异性代谢物作为HCC的生物标志物。这将通过对HCC病例和代表AA和EA的肝硬化患者的肝组织和血清中的代谢物进行靶向分析来实现。将通过统计学和基于网络的方法选择以种族特异性方式区分HCC病例与HCC对照的Metabolism。然后，将这些代谢物与其他候选生物标志物（基因，聚糖和蛋白质）相结合的系统导向方法将用于选择HCC中受干扰的关键信号通路。在通过来自HCC病例、肝硬化患者和健康受试者的独立样本验证候选物之后，我们将通过体外和体内实验阐明其功能作用。成功完成本 研究将使我们能够确定HCC生物标志物和干扰途径，这些生物标志物和干扰途径是种族特异性的，也是AA和EA共有的。这些发现不仅有助于更好地理解HCC的种族差异，而且有助于通过种族特异性生物标志物改善HCC的诊断。

 DESCRIPTION (provided by applicant): Hepatocellular carcinoma (HCC) is a significant health problem in the United States. Compared to European Americans (EA), the incidence of HCC is higher in African Americans (AA) and is associated with more advanced tumor stage at diagnosis and lower survival rates. It has been reported that the sensitivity of α- fetoprotein (AFP) for the diagnosis of HCC in African Americans with hepatitis C virus (HCV) infection is lower than that of patients of all other racial groups combined. We previously performed preliminary investigation into racial disparities through metabolomics profiling of sera from HCC cases and patients with liver cirrhosis by using both liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS). Through stratified analysis of the LC/GC-MS data, we identified different candidates that distinguish HCC cases from the cirrhotic controls among AA and EA. This application builds on these promising preliminary results to find and validate race-specific metabolites as biomarkers for HCC. This will be accomplished by targeted analysis of metabolites in liver tissues and sera from HCC cases and patients with liver cirrhosis representing AA and EA. Metabolites that differentiate HCC cases from cirrhotic controls in a race-specific manner will be selected by statistical and network-based methods. Then, a systems-oriented approach that combines these metabolites with other candidate biomarkers (genes, glycans, and proteins) will be utilized for the selection of key signaling pathways perturbed in HCC. Following validation of the candidates via independent samples from HCC cases, patients with liver cirrhosis, and healthy subjects, we will elucidate their functional roles through both in vitro and in vivo experiments. Successful completion of this research will enable us to identify HCC biomarkers and perturbed pathways that are race-specific as well as those that are shared by AA and EA. These findings will contribute not only to a greater understanding of racial disparities in HCC but also to improving diagnosis of HCC through race-specific biomarkers.