Abstract
O-glycopeptides are highly expressed in various human cancers and play a key role in cancer progression and metastasis, making them promising biomarkers for early diagnostics. However, the inherent complexity and heterogeneity of glycans pose a major challenge for the simultaneous and precise analysis of multiple glycopeptides. Here, we developed a low-temperature nanopore technique capable of simultaneously discriminating 4 truncated O-glycopeptides with varied glycoforms. This method enables the direct identification and relative quantification of O-glycopeptides from a mixture, achieving a discrimination accuracy of 92.9%. This general strategy holds promise for the label-free analysis of glycopeptide biomarkers, with potential applications in cancer diagnostics.