腫瘍バイオマーカー探索のためのグライコプロテオーム解析法

抄録

Discovery of cancer biomarker is a major objective of clinical proteomics; molecular biomarkers allow for detection of early-stage cancer, for classification of tumors, and for monitoring their progression, regression following treatment and/or recurrence. Glycoproteins are one of the ideal candidates for biomarkers because most secretory and cell surface proteins are glycosylated, and their glycan structures frequently and drastically change during tumorigenesis as well as normal cell differentiation. In addition, the core proteins are often expressed as cell specific. In fact, most cancer-related biomarkers available to date, such as prostate specific antigen, carcinoembryonic antigen, and alpha-fetoprotein, are glycoproteins. Thus far, we developed LC/MS-based glycoproteomic analysis method, termed IGOT (isotope-coded glycosylation site-specific tagging), and applied it for large-scale profiling of N-glycosylated proteins of C.elegans and mouse tissues; about 1,450 sites on 829 proteins and 4,500 sites on 2,300 proteins were determined, respectively. Using the large dataset of N-glycoproteins, we constructed a glycoprotein database, JCGGDB, and the partial data will become available soon at the Japan Consortium for Glycobiology and Glycoscience. Recently, to apply the IGOT procedure for biomarker discovery, we incorporated a step of differential stable isotope tagging for quantitative analysis. The isotope tags could be incorporated into the core peptide portion by both enzymatic and chemical methods. In this presentation, the methods of quantitative glycoproteomics and its application will be introduced.