Quantitative\nSite-Specific Glycoproteomics Reveals\nGlyco-Signatures for Breast Cancer Diagnosis

Intact glycopeptide characterization by mass spectrometry\nhas proven\nto be a versatile tool for site-specific glycoproteomics analysis\nand biomarker screening. Here, we present a method using a new model\nof a Q-TOF instrument equipped with a Zeno trap for intact glycopeptide\nidentification and demonstrate its ability to analyze large-cohort\nglycoproteomes. From 124 clinical serum samples of breast cancer,\nnoncancerous diseases, and nondisease controls, a total of 6901 unique\nsite-specific glycans on 807 glycosites of proteins were detected.\nMuch more differences of glycoproteome were observed in breast diseases\nthan the proteome. By employing machine learning, 15 site-specific\nglycans were determined as potential glyco-signatures in detecting\nbreast cancer. The results demonstrate that our method provides a\npowerful tool in glycoproteomic studies.