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 i s 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.
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.
| Bowers, Jeremiah; Hughes, Emma; Skill, Nicholas et al. (2014) Detection of hepatocellular carcinoma in hepatitis C patients: biomarker discovery by LC-MS. J Chromatogr B Analyt Technol Biomed Life Sci 966:154-62 |
| Baniasadi, Hamid; Gowda, G A Nagana; Gu, Haiwei et al. (2013) Targeted metabolic profiling of hepatocellular carcinoma and hepatitis C using LC-MS/MS. Electrophoresis 34:2910-7 |
