Wang Jia-Hong, Ma Wenjing, Hu Zheng-Li, Gao Zhaobing, Long Yi-Tao, Li Tiehai, Ying Yi-Lun
Molecular Sensing and Imaging Center, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China.
State Key Laboratory of Chemical Biology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, P. R. China.
Research (Wash D C). 2025 Sep 4;8:0850. doi: 10.34133/research.0850. eCollection 2025.
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.
O-糖肽在多种人类癌症中高度表达,在癌症进展和转移中起关键作用,使其成为早期诊断的有前景的生物标志物。然而,聚糖固有的复杂性和异质性对多种糖肽的同时精确分析构成了重大挑战。在此,我们开发了一种低温纳米孔技术,能够同时区分4种具有不同糖型的截短O-糖肽。该方法能够直接从混合物中鉴定和相对定量O-糖肽,鉴别准确率达到92.9%。这种通用策略有望用于糖肽生物标志物的无标记分析,在癌症诊断中具有潜在应用价值。