UPLC‐MS/MS based diagnostics for epithelial ovarian cancer using fully sialylated C4‐binding protein

Abstract

Serum levels of fully sialylated C4-binding protein (FS-C4BP) are remarkably elevated in patients with epithelial ovarian cancer (EOC) and can be used as a marker to distinguish ovarian clear cell carcinoma from endometrioma. This study aimed to develop a stable, robust and reliable liquid chromatography-hybrid mass spectrometry (UPLC-MS/MS) based diagnostic method that would generalize FS-C4BP as a clinical EOC biomarker. Glycopeptides derived from 20 μL of trypsin-digested serum glycoprotein were analyzed via UPLC equipped with an electrospray ionization time-of-flight mass spectrometer. This UPLC-MS/MS-based diagnostic method was optimized for FS-C4BP and validated using sera from 119 patients with EOC and 127 women without cancer. A1958 (C4BP peptide with two fully sialylated biantennary glycans) was selected as a marker of FS-C4BP because its level in serum was highest among FS-C4BP family members.Preparation and UPLC-MS/MS were optimized for A1958, and performance and robustness were significantly improved relative to our previous method. An area under the curve analysis of the FS-C4BP index receiver operating characteristic curve revealed that the ratio between A1958 and A1813 (C4BP peptide with two partially sialylated biantennary glycans) reached 85%.A combination of the FS-C4BP index and carbohydrate antigen-125 levels further enhanced the sensitivity and specificity. peptide with a fully sialylated and fucosylated triantennary glycan and fully sialylated biantennary glycan, exhibited superior sensitivity and specificity as an EOC marker. However, a complicated lectin-based enrichment process is needed to detect A2160, which is present in serum at quite low levels. This prolonged preparation process led not only to a -----------------------------------------------------------------------This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Fucosylated C4b‑binding protein α‑chain, a novel serum biomarker that predicts lymph node metastasis in pancreatic ductal adenocarcinoma

“…Previously, the serum level of fully-sialylated C4BPA was reported to be upregulated in patients with clear-cell ovarian cancer. However, the utility of the serum level of fully-sialylated C4BPA for cancer diagnosis has been limited due to the absence of a high-throughput method for measurement ( 10 ).…”

“…Previously, the serum level of fully-sialylated C4BPA was reported to be upregulated in patients with clear-cell ovarian cancer. However, the utility of the serum level of fully-sialylated C4BPA for cancer diagnosis has been limited due to the absence of a high-throughput method for measurement (10). Cancer progression encompasses major alterations in molecular glycosylation, such as incomplete synthesis of O-glycan structures, increased expression of branched N-glycans, expression of terminal sialylated glycans, and altered fucosylation.…”

“…Thus, glycoproteins are potential serum diagnostic biomarkers for cancer. Previous studies have reported that the fully-sialylated C4BPA levels are upregulated in the serum of patients with ovarian cancer ( 10 ). However, there are no studies on the importance of serum fucosylated (Fuc-) C4BPA in patients with cancer.…”

Comprehensive Serum Glycopeptide Spectra Analysis Combined with Artificial Intelligence (CSGSA-AI) to Diagnose Early-Stage Ovarian Cancer

“…To establish a reliable and robust blood test for early-stage EOC detection, we developed a glycopeptide profiling technology using mass spectrometry, which detects aberrant serum sugar chains in patient sera [14]. In our previous studies, we have shown that C4-binding protein with fully sialylated sugar chains is specifically increased in the sera of EOC patients [15][16][17]. Based on this, we developed a comprehensive serum glycopeptide spectra analysis (CSGSA) technology by combining glycopeptide profiling with orthogonal partial least squares discriminant analysis (OPLS-DA) [18].…”