Alterations in glycosylation have long been associated with the development and progression ofmany types of chronic and acute diseases. Our group (Mehta) was one of the first to performglycan analysis in serum and perform proteomics on specific glycoforms (glycoproteomics). Usingsuch methods, we identified a number of serum glycoproteins with altered glycosylation inhepatocellular carcinoma, a primary cancer of the liver.However, because of limitations in technology, we were forced to either examine each proteinone at a time or examine pools of proteins without the ability to link a particular glycan to a givenprotein. In some situations, we performed structural glycan analysis on purified proteins whichprovided the best "biomarker" information, but took days to weeks for analysis. Alternatively, wecould forgo true structural information and use lectins to determine if only one specific sugarmoiety was present, and perform analysis in a more rapid manner. But again, this was generallydone only on one protein at a time. In all of these situations, the biomarker potential of theseglycoproteins was diminished because of the technology used.To address this limitation, GlycoPath has recently developed a streamlined antibody capture slidearray approach to directly profile N-linked glycans on captured serum glycoproteins. This processrequires only a few microliters of sample and utilizes simple methods that require no proteinpurification or sugar modifications prior to analysis. This method is referred to as the GlycoTyper.In this method, N-linked glycans are released from antibody captured glycoproteins and aredirectly analyzed by MALDI-TOF mass spectrometry. We hypothesize that this method can beused to identify glycan biomarkers reflective of the changes that occur during the development ofhepatocellular carcinoma. In this Phase I STTR application we anticipate developing areproducible and translatable workflow using MALDI-MS of captured proteins that can accuratelydetect the presence of hepatocellular carcinoma.
Public Health Relevance Statement: Narrative: This application will develop a new platform for glycan analysis and determine its
ability to detect liver cancer.
Project Terms: <α2-Macroglobulin><α2m><α-Fetoproteins><7S Gamma Globulin>
