Diagnostic potential of site-specific serotransferrin N-glycosylation in discriminating different liver diseases

Abstract

BackgroundAltered glycosylation modulates the structure and function of disease-related proteins. The associations between serotransferrin (STF) N-glycosylation and liver diseases (LDs) have been revealed. However, how intact N-glycopeptides vary among different types of liver diseases remains unclear. MethodsIntact STF N-glycopeptides from patients with chronic liver disease (CLD, n = 92), primary liver cancer (PLC, n = 123), metastatic liver cancer (MLC, n = 57), and healthy controls (HCs, n = 59) were determined using high-resolution mass spectrometry. ResultsSignificant changes were displayed in STF glycosylation among 4 groups. The LD screening model, including Asn432 G1S/G2S, Asn432 G2S/G2S2, and Asn630 G2NS2/G2FNS2, was constructed to differentiate LDs from HCs, with a AUC of 0.92. The liver cancer (LC) diagnostic model, a combination of Asn432 G1-N/G1S-N, Asn432 G1/G2, Asn432 G2FS/G2FS2, and Asn630 G1S-N /G1S, showed good performance in discriminating LC from CLD (AUC = 0.93). Moreover, AFP-negative LC patients (93 %) were successfully predicted by the LC diagnostic model. Furthermore, the MLC triage model, composed of Asn432 G1/G2, Asn432 G3F/G3FS, Asn630 G2/G2S, Asn630 G2S2/G2NS2, and Asn630 G3FS/G3FS2, yielded an AUC of 0.98 between PLC and MLC. ConclusionsSTF N-glycosylation is a potential biomarker for the accurate classification of different LDs.