High accuracy differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma by immunoglobulin G glycosylation

Hsi Chang Shih, Ming Chu Chang, Chein Hung Chen, I. Lin Tsai, San Yuan Wang, Ya Po Kuo, Chung Hsuan Chen, Yu Ting Chang

Research output: Contribution to journalArticle

Abstract

Background: Misdiagnosis of autoimmune pancreatitis (AIP) as pancreatic cancer (PDAC) or vice versa can cause dismal patents' outcomes. Changes in IgG glycosylation are associated with cancers and autoimmune diseases. This study investigated the IgG glycosylation profiles as diagnostic and prognostic biomarkers in PDAC and AIP. Methods: Serum IgG-glycosylation profiles from 86 AIP patients, 115 PDAC patients, and 57 controls were analyzed using liquid chromatography-electrospray ionization mass spectrometry. Classification and regression tree (CART) analysis was applied to build a decision tree for discriminating PDAC from AIP. The result was validated in an independent cohort. Results: Compared with AIP patients and controls, PDAC patients had significantly higher agalactosylation, lower fucosylation, and sialylation of IgG1, a higher agalactosylation ratio of IgG1 and a higher agalactosylation ratio of IgG2. AIP patients had significantly higher fucosylation of IgG1 and a higher sialylation ratio of IgG subclasses 1, 2 and 4. Using the CART analysis of agalactosylation and sialylation ratios in the IgG to discriminate AIP from PDAC, the diagnostic accuracy of the glycan markers was 93.8% with 94.6% sensitivity and 92.9% specificity. There were no statistically significant difference of IgG-glycosylation profiles between diffuse type and focal type AIP. Conclusions: AIP and PDAC patients have distinct IgG-glycosylation profilings. IgG-glycosylation could different PDAC from AIP with high accuracy.

Original languageEnglish
JournalClinical Proteomics
Volume16
Issue number1
DOIs
Publication statusPublished - Jan 3 2019

Fingerprint

Glycosylation
Pancreatitis
Adenocarcinoma
Immunoglobulin G
Regression Analysis
Electrospray ionization
Decision Trees
Patents
Electrospray Ionization Mass Spectrometry
Liquid chromatography
Biomarkers
Decision trees
Diagnostic Errors
Pancreatic Neoplasms
Liquid Chromatography
Autoimmune Diseases
Mass spectrometry
Polysaccharides

Keywords

  • Autoimmune pancreatitis (AIP)
  • Glycosylation
  • Immunoglobulin G (IgG)
  • Pancreatic cancer

ASJC Scopus subject areas

  • Molecular Medicine
  • Molecular Biology
  • Clinical Biochemistry

Cite this

High accuracy differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma by immunoglobulin G glycosylation. / Shih, Hsi Chang; Chang, Ming Chu; Chen, Chein Hung; Tsai, I. Lin; Wang, San Yuan; Kuo, Ya Po; Chen, Chung Hsuan; Chang, Yu Ting.

In: Clinical Proteomics, Vol. 16, No. 1, 03.01.2019.

Research output: Contribution to journalArticle

Shih, Hsi Chang ; Chang, Ming Chu ; Chen, Chein Hung ; Tsai, I. Lin ; Wang, San Yuan ; Kuo, Ya Po ; Chen, Chung Hsuan ; Chang, Yu Ting. / High accuracy differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma by immunoglobulin G glycosylation. In: Clinical Proteomics. 2019 ; Vol. 16, No. 1.
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abstract = "Background: Misdiagnosis of autoimmune pancreatitis (AIP) as pancreatic cancer (PDAC) or vice versa can cause dismal patents' outcomes. Changes in IgG glycosylation are associated with cancers and autoimmune diseases. This study investigated the IgG glycosylation profiles as diagnostic and prognostic biomarkers in PDAC and AIP. Methods: Serum IgG-glycosylation profiles from 86 AIP patients, 115 PDAC patients, and 57 controls were analyzed using liquid chromatography-electrospray ionization mass spectrometry. Classification and regression tree (CART) analysis was applied to build a decision tree for discriminating PDAC from AIP. The result was validated in an independent cohort. Results: Compared with AIP patients and controls, PDAC patients had significantly higher agalactosylation, lower fucosylation, and sialylation of IgG1, a higher agalactosylation ratio of IgG1 and a higher agalactosylation ratio of IgG2. AIP patients had significantly higher fucosylation of IgG1 and a higher sialylation ratio of IgG subclasses 1, 2 and 4. Using the CART analysis of agalactosylation and sialylation ratios in the IgG to discriminate AIP from PDAC, the diagnostic accuracy of the glycan markers was 93.8{\%} with 94.6{\%} sensitivity and 92.9{\%} specificity. There were no statistically significant difference of IgG-glycosylation profiles between diffuse type and focal type AIP. Conclusions: AIP and PDAC patients have distinct IgG-glycosylation profilings. IgG-glycosylation could different PDAC from AIP with high accuracy.",
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AU - Chang, Ming Chu

AU - Chen, Chein Hung

AU - Tsai, I. Lin

AU - Wang, San Yuan

AU - Kuo, Ya Po

AU - Chen, Chung Hsuan

AU - Chang, Yu Ting

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N2 - Background: Misdiagnosis of autoimmune pancreatitis (AIP) as pancreatic cancer (PDAC) or vice versa can cause dismal patents' outcomes. Changes in IgG glycosylation are associated with cancers and autoimmune diseases. This study investigated the IgG glycosylation profiles as diagnostic and prognostic biomarkers in PDAC and AIP. Methods: Serum IgG-glycosylation profiles from 86 AIP patients, 115 PDAC patients, and 57 controls were analyzed using liquid chromatography-electrospray ionization mass spectrometry. Classification and regression tree (CART) analysis was applied to build a decision tree for discriminating PDAC from AIP. The result was validated in an independent cohort. Results: Compared with AIP patients and controls, PDAC patients had significantly higher agalactosylation, lower fucosylation, and sialylation of IgG1, a higher agalactosylation ratio of IgG1 and a higher agalactosylation ratio of IgG2. AIP patients had significantly higher fucosylation of IgG1 and a higher sialylation ratio of IgG subclasses 1, 2 and 4. Using the CART analysis of agalactosylation and sialylation ratios in the IgG to discriminate AIP from PDAC, the diagnostic accuracy of the glycan markers was 93.8% with 94.6% sensitivity and 92.9% specificity. There were no statistically significant difference of IgG-glycosylation profiles between diffuse type and focal type AIP. Conclusions: AIP and PDAC patients have distinct IgG-glycosylation profilings. IgG-glycosylation could different PDAC from AIP with high accuracy.

AB - Background: Misdiagnosis of autoimmune pancreatitis (AIP) as pancreatic cancer (PDAC) or vice versa can cause dismal patents' outcomes. Changes in IgG glycosylation are associated with cancers and autoimmune diseases. This study investigated the IgG glycosylation profiles as diagnostic and prognostic biomarkers in PDAC and AIP. Methods: Serum IgG-glycosylation profiles from 86 AIP patients, 115 PDAC patients, and 57 controls were analyzed using liquid chromatography-electrospray ionization mass spectrometry. Classification and regression tree (CART) analysis was applied to build a decision tree for discriminating PDAC from AIP. The result was validated in an independent cohort. Results: Compared with AIP patients and controls, PDAC patients had significantly higher agalactosylation, lower fucosylation, and sialylation of IgG1, a higher agalactosylation ratio of IgG1 and a higher agalactosylation ratio of IgG2. AIP patients had significantly higher fucosylation of IgG1 and a higher sialylation ratio of IgG subclasses 1, 2 and 4. Using the CART analysis of agalactosylation and sialylation ratios in the IgG to discriminate AIP from PDAC, the diagnostic accuracy of the glycan markers was 93.8% with 94.6% sensitivity and 92.9% specificity. There were no statistically significant difference of IgG-glycosylation profiles between diffuse type and focal type AIP. Conclusions: AIP and PDAC patients have distinct IgG-glycosylation profilings. IgG-glycosylation could different PDAC from AIP with high accuracy.

KW - Autoimmune pancreatitis (AIP)

KW - Glycosylation

KW - Immunoglobulin G (IgG)

KW - Pancreatic cancer

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