Development of efficient on-bead protein elution process coupled to ultra-high performance liquid chromatography-tandem mass spectrometry to determine immunoglobulin G subclass and glycosylation for discovery of bio-signatures in pancreatic disease.

J Chromatogr A

Department of Biochemistry and Molecular Cell Biology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan; School of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei, Taiwan; Graduate Institute of Medical Sciences, College of Medicine, Taipei Medical University, Taipei, Taiwan; Master Program for Clinical Pharmacogenomics and Pharmacoproteomics, School of Pharmacy, Taipei Medical University, Taipei, Taiwan; International Ph.D. Program for Cell Therapy and Regeneration Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan; Pulmonary Research Center, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan. Electronic address:

Published: June 2020

Type 1 autoimmune pancreatitis (AIP) is a kind of IgG4-related disease in which higher IgG4 and total IgG levels have been found in patient serum. Due to the similar imaging features and laboratory parameters between AIP and pancreatic ductal adenocarcinoma (PDAC), a differential diagnosis is still challenging. Since IgG profiles can be potential bio-signatures for disease, we developed and validated a method which coupled on-bead enzymatic protein elution process to an efficient UHPLC-MS/MS method to determine IgG subclass and glycosylation. A stable-isotope labeled IgG was incorporated as internal standard to achieve accurate quantification. For calibration curves, the correlation coefficients for total IgG and the four IgG subclasses were higher than 0.995. Intraday (n = 5) and interday (n = 3) precisions of the peak area ratios of LLOQ, low, medium, and high QC samples were all less than 6.6% relative standard deviation (% RSD), and the accuracies were between 93.5 and 114.9%. Calibration curves, precision, and accuracy were also evaluated for 26 IgG glycopeptides. The method was applied to samples from healthy controls and patients with AIP and PDAC. Distinct IgG patterns were discovered among the groups, and 7 glycopeptides showed high potential in differentiating AIP and PDAC. The results demonstrated that the developed method is suitable for multi-feature analysis of human IgG, and the discovered IgG profiles can be used as bio-signatures for AIP and PDAC.

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http://dx.doi.org/10.1016/j.chroma.2020.461039DOI Listing

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