Metabolomics-based Identification of Hepatocellular Cancer Biomarkers

描述(申请人提供)：建议的工作重点是发现可靠的生物标志物，用于肝癌的早期检测。肝炎患者特别容易患上肝细胞癌，尽管其发病机制尚不清楚。我们建议使用代谢组学，这是一个新兴的领域，它根据多个小分子代谢物的变化提供关于生物扰动的新信息。核磁共振谱和质谱学的新进展及其与多元统计方法的结合为疾病的早期诊断和后续治疗提供了一条很有前途的途径。目前，还没有高度可靠的代谢物生物标志物被确定为肝癌存在的早期指标。我们的目标是确定可能对疾病早期发病具有诊断作用的关键代谢特征，从而为早期治疗打开可能性，从而降低总体死亡率。使用代谢组学检测肝癌将建立在人类患者血清和组织中关键的小分子代谢物特征，以及使用先进的核磁共振/质谱仪技术的非恶性肝病患者和健康对照的血清样本。已经从适度数量的患者样本中确定了一组来自血清的假定生物标记物候选。来自肿瘤组织和血清的信号的关联将有助于识别血清中的其他关键代谢特征，这些特征可用于非侵入性检测早期肝癌。基于这些代谢标志物的统计模型的验证将在一组盲样上进行。如果成功，这一进展将为医学肿瘤学家提供新的工具和知识，以更有效地护理肝癌患者。该项目将为代谢组学在大量患者身上的早期肝癌诊断的临床应用奠定基础，同时通过基础研究促进对疾病机制的科学认识。然后，这种方法可以很快地转化为临床实践。公共卫生相关性：该项目寻求开发一种新的、非侵入性的早期肝癌检测方法，通过识别血液中指示癌症发病的小分子，特别是对肝炎患者。

DESCRIPTION (provided by applicant): The proposed work focuses on the discovery of reliable biomarkers for the early detection of liver cancer. Patients with hepatitis are particularly susceptible to the development of hepatocellular cancer, although the disease mechanisms are poorly understood. We propose to use metabolomics, an emerging field that provides new information on biological perturbations based on changes in multiple small molecule metabolites. New advances in nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) and their combination with multivariate statistical methods provide a promising approach for early disease diagnosis and for following therapy. Presently, no highly reliable metabolite biomarkers have been identified that are early indicators of the presence of liver cancer. Our aim is to identify key metabolic signatures that may be diagnostic of the early onset of the disease, thus opening up the possibility for earlier therapy, and thereby reducing overall mortality rates. Detection of liver cancer using metabolomics will be based on the establishment of key small molecular weight metabolite signatures in serum and tissue from human patients, as well as serum samples from patients with non-malignant liver disease and healthy controls using advanced NMR/MS techniques. A putative set of biomarker candidates from serum have already been identified from a moderate number of patient samples. Correlation of signals from tumor tissue and serum will help identify additional key metabolic signatures in serum that may be used to detect early liver cancer non-invasively. Validation of a statistical model based on these metabolic markers will be performed on a set of blinded samples. If successful, this advance would provide medical oncologists with the new tools and knowledge to more efficiently care for liver cancer patients. This project will lay the foundation for clinical applications of metabolomics of early liver cancer diagnosis on a large number of patients, while advancing scientific knowledge on disease mechanisms through basic research. This approach could then very quickly be translated into clinical practice. PUBLIC HEALTH RELEVANCE: This project seeks to develop a new and non-invasive method for early liver cancer detection by identifying small molecules in the blood that indicate the onset of cancer, especially for patients with hepatitis.