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bioRxiv · 10.1101/2024.09.08.611557

Quantitative site-specific glycoproteomics by ZenoTOF reveals glyco-signatures for breast cancer diagnosis

Yang, Y.·Zhao, D.·Luo, J.·Lin, L.·Lin, Y.·Shan, B.·Chen, H.·Qiao, L.
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Abstract

Intact glycopeptide characterization by mass spectrometry has proven a versatile tool for site-specific glycoproteomics analysis and biomarker screening. Here, we present a method using the ZenoTOF instrument with optimized fragmentation for intact glycopeptide identification and demonstrate its ability to analyze large-cohort glycoproteomes. From 124 clinical serum samples of breast cancer, non-cancerous diseases, and non-disease controls, a total of 6901 unique site-specific glycans on 807 gly-cosites of proteins were detected. Much more differences of glycoproteome were observed in breast diseases than the proteome. By employing machine learning, 15 site-specific glycans were determined as potential glyco-signatures in detecting breast cancer. The results demonstrate that our method provides a powerful tool in glycoproteomic analyses for biomarker discovery studies.

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Yang, Y., Zhao, D., Luo, J., Lin, L., Lin, Y., Shan, B., Chen, H., Qiao, L.. 2024-09-09. Quantitative site-specific glycoproteomics by ZenoTOF reveals glyco-signatures for breast cancer diagnosis. https://doi.org/10.1101/2024.09.08.611557

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