Title: LC-MS based metabolomics for disease biomarker discovery and confirmation
Abstract: Complex diseases such as cancer, diabetes and obesity arise from an interaction of genetic and environmental factors. Their (early) diagnosis is very difficult, especially based on only singular biomarker. The move toward a biomarker group is a tendency, especially in the translational medicine applications.
Metabolomics is a technique based on analyzing as many endogenetic metabolites as possible. It has shown a great potential in finding biomarker group. At this moment NMR and MS-based methods are used to analyze the metabolome, unfortunately, because of the complexity, until now no a single method can analyze the total metabolome. To resolve this problem, in our group an integrated platform has been developed, it mainly consists of one-dimensional and multi-dimensional GC-MS and LC-MS. RP-UHPLC and HILIC are online or off-line combined to separate hydrophilic and hydrophobic metabolites producing the complementary metabolite information. Applications of an ultra-high capacity small molecule chip (UHC-chip)-MS in the metabolomics are also explored. In the meantime, a comprehensive identification method of the metabolites was suggested.
As the examples, we shall report our newest work on the metabolic biomarker discovery of ovarian cancer and prediabetes by using non-target metabolomics analysis to ‘fish’ the differential metabolites and target LC-MRM MS analysis to confirm the found biomarker group.
Publication Year: 2011
Publication Date: 2011-06-19
Language: en
Type: article
Access and Citation
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot