Urinary Glycopeptide Analysis for the Investigation of Novel Biomarkers

Purpose Urine is a rich source of potential biomarkers, including glycoproteins. Glycoproteomic analysis remains difficult due to the high heterogeneity of glycans. Nevertheless, recent advances in glycoproteomics software solutions facilitate glycopeptide identification and characterization. The ai...

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Published inProteomics. Clinical applications Vol. 13; no. 3; pp. e1800111 - n/a
Main Authors Belczacka, Iwona, Pejchinovski, Martin, Krochmal, Magdalena, Magalhães, Pedro, Frantzi, Maria, Mullen, William, Vlahou, Antonia, Mischak, Harald, Jankowski, Vera
Format Journal Article
LanguageEnglish
Published Germany Wiley Subscription Services, Inc 01.05.2019
Subjects
Adolescent
Adult
Aged
Aged, 80 and over
Aging - urine
Antibiotics
Apolipoproteins
Biomarkers
Biomarkers - urine
Bladder
Cancer
Cholangiocarcinoma
Computer programs
Connectin
Design of experiments
Female
Glycopeptides
Glycopeptides - urine
Glycoproteins
glycosylation
Growth factors
Humans
Insulin
Kidney cancer
Male
Middle Aged
Neoplasms - urine
Pancreatic cancer
Peptides
Polysaccharides
posttranslational modifications
Prostate cancer
protein biomarkers
Proteomics
Renal cell carcinoma
Software
Statistical analysis
Urine
Workflow
Young Adult
glycosylation
glycopeptides
posttranslational modifications
urine
protein biomarkers
Online AccessGet full text
ISSN1862-8346
1862-8354
1862-8354
DOI10.1002/prca.201800111

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Abstract Purpose Urine is a rich source of potential biomarkers, including glycoproteins. Glycoproteomic analysis remains difficult due to the high heterogeneity of glycans. Nevertheless, recent advances in glycoproteomics software solutions facilitate glycopeptide identification and characterization. The aim is to investigate intact glycopeptides in the urinary peptide profiles of normal subjects using a novel PTM‐centric software—Byonic. Experimental design The urinary peptide profiles of 238 normal subjects, previously analyzed using CE–MS and CE–MS/MS and/or LC–MS/MS, are subjected to glycopeptide analysis. Additionally, glycopeptide distribution is assessed in a set of 969 patients with five different cancer types: bladder, prostate and pancreatic cancer, cholangiocarcinoma, and renal cell carcinoma. Results A total of 37 intact O‐glycopeptides and 23 intact N‐glycopeptides are identified in the urinary profiles of 238 normal subjects. Among the most commonly identified O‐glycoproteins are Apolipoprotein C‐III and insulin‐like growth factor II, while titin among the N‐glycoproteins. Further statistical analysis reveals that three O‐glycopeptides and five N‐glycopeptides differed significantly in their abundance among the different cancer types, comparing to normal subjects. Conclusions and clinical relevance Through the established glycoproteomics workflow, intact O‐ and N‐glycopeptides in human urine are identified and characterized, providing novel insights for further exploration of the glycoproteome with respect to specific diseases.
AbstractList PurposeUrine is a rich source of potential biomarkers, including glycoproteins. Glycoproteomic analysis remains difficult due to the high heterogeneity of glycans. Nevertheless, recent advances in glycoproteomics software solutions facilitate glycopeptide identification and characterization. The aim is to investigate intact glycopeptides in the urinary peptide profiles of normal subjects using a novel PTM‐centric software—Byonic.Experimental designThe urinary peptide profiles of 238 normal subjects, previously analyzed using CE–MS and CE–MS/MS and/or LC–MS/MS, are subjected to glycopeptide analysis. Additionally, glycopeptide distribution is assessed in a set of 969 patients with five different cancer types: bladder, prostate and pancreatic cancer, cholangiocarcinoma, and renal cell carcinoma.ResultsA total of 37 intact O‐glycopeptides and 23 intact N‐glycopeptides are identified in the urinary profiles of 238 normal subjects. Among the most commonly identified O‐glycoproteins are Apolipoprotein C‐III and insulin‐like growth factor II, while titin among the N‐glycoproteins. Further statistical analysis reveals that three O‐glycopeptides and five N‐glycopeptides differed significantly in their abundance among the different cancer types, comparing to normal subjects.Conclusions and clinical relevanceThrough the established glycoproteomics workflow, intact O‐ and N‐glycopeptides in human urine are identified and characterized, providing novel insights for further exploration of the glycoproteome with respect to specific diseases.
Urine is a rich source of potential biomarkers, including glycoproteins. Glycoproteomic analysis remains difficult due to the high heterogeneity of glycans. Nevertheless, recent advances in glycoproteomics software solutions facilitate glycopeptide identification and characterization. The aim is to investigate intact glycopeptides in the urinary peptide profiles of normal subjects using a novel PTM-centric software-Byonic. The urinary peptide profiles of 238 normal subjects, previously analyzed using CE-MS and CE-MS/MS and/or LC-MS/MS, are subjected to glycopeptide analysis. Additionally, glycopeptide distribution is assessed in a set of 969 patients with five different cancer types: bladder, prostate and pancreatic cancer, cholangiocarcinoma, and renal cell carcinoma. A total of 37 intact O-glycopeptides and 23 intact N-glycopeptides are identified in the urinary profiles of 238 normal subjects. Among the most commonly identified O-glycoproteins are Apolipoprotein C-III and insulin-like growth factor II, while titin among the N-glycoproteins. Further statistical analysis reveals that three O-glycopeptides and five N-glycopeptides differed significantly in their abundance among the different cancer types, comparing to normal subjects. Through the established glycoproteomics workflow, intact O- and N-glycopeptides in human urine are identified and characterized, providing novel insights for further exploration of the glycoproteome with respect to specific diseases.
Urine is a rich source of potential biomarkers, including glycoproteins. Glycoproteomic analysis remains difficult due to the high heterogeneity of glycans. Nevertheless, recent advances in glycoproteomics software solutions facilitate glycopeptide identification and characterization. The aim is to investigate intact glycopeptides in the urinary peptide profiles of normal subjects using a novel PTM-centric software-Byonic.PURPOSEUrine is a rich source of potential biomarkers, including glycoproteins. Glycoproteomic analysis remains difficult due to the high heterogeneity of glycans. Nevertheless, recent advances in glycoproteomics software solutions facilitate glycopeptide identification and characterization. The aim is to investigate intact glycopeptides in the urinary peptide profiles of normal subjects using a novel PTM-centric software-Byonic.The urinary peptide profiles of 238 normal subjects, previously analyzed using CE-MS and CE-MS/MS and/or LC-MS/MS, are subjected to glycopeptide analysis. Additionally, glycopeptide distribution is assessed in a set of 969 patients with five different cancer types: bladder, prostate and pancreatic cancer, cholangiocarcinoma, and renal cell carcinoma.EXPERIMENTAL DESIGNThe urinary peptide profiles of 238 normal subjects, previously analyzed using CE-MS and CE-MS/MS and/or LC-MS/MS, are subjected to glycopeptide analysis. Additionally, glycopeptide distribution is assessed in a set of 969 patients with five different cancer types: bladder, prostate and pancreatic cancer, cholangiocarcinoma, and renal cell carcinoma.A total of 37 intact O-glycopeptides and 23 intact N-glycopeptides are identified in the urinary profiles of 238 normal subjects. Among the most commonly identified O-glycoproteins are Apolipoprotein C-III and insulin-like growth factor II, while titin among the N-glycoproteins. Further statistical analysis reveals that three O-glycopeptides and five N-glycopeptides differed significantly in their abundance among the different cancer types, comparing to normal subjects.RESULTSA total of 37 intact O-glycopeptides and 23 intact N-glycopeptides are identified in the urinary profiles of 238 normal subjects. Among the most commonly identified O-glycoproteins are Apolipoprotein C-III and insulin-like growth factor II, while titin among the N-glycoproteins. Further statistical analysis reveals that three O-glycopeptides and five N-glycopeptides differed significantly in their abundance among the different cancer types, comparing to normal subjects.Through the established glycoproteomics workflow, intact O- and N-glycopeptides in human urine are identified and characterized, providing novel insights for further exploration of the glycoproteome with respect to specific diseases.CONCLUSIONS AND CLINICAL RELEVANCEThrough the established glycoproteomics workflow, intact O- and N-glycopeptides in human urine are identified and characterized, providing novel insights for further exploration of the glycoproteome with respect to specific diseases.
Purpose Urine is a rich source of potential biomarkers, including glycoproteins. Glycoproteomic analysis remains difficult due to the high heterogeneity of glycans. Nevertheless, recent advances in glycoproteomics software solutions facilitate glycopeptide identification and characterization. The aim is to investigate intact glycopeptides in the urinary peptide profiles of normal subjects using a novel PTM‐centric software—Byonic. Experimental design The urinary peptide profiles of 238 normal subjects, previously analyzed using CE–MS and CE–MS/MS and/or LC–MS/MS, are subjected to glycopeptide analysis. Additionally, glycopeptide distribution is assessed in a set of 969 patients with five different cancer types: bladder, prostate and pancreatic cancer, cholangiocarcinoma, and renal cell carcinoma. Results A total of 37 intact O‐glycopeptides and 23 intact N‐glycopeptides are identified in the urinary profiles of 238 normal subjects. Among the most commonly identified O‐glycoproteins are Apolipoprotein C‐III and insulin‐like growth factor II, while titin among the N‐glycoproteins. Further statistical analysis reveals that three O‐glycopeptides and five N‐glycopeptides differed significantly in their abundance among the different cancer types, comparing to normal subjects. Conclusions and clinical relevance Through the established glycoproteomics workflow, intact O‐ and N‐glycopeptides in human urine are identified and characterized, providing novel insights for further exploration of the glycoproteome with respect to specific diseases.
Author Frantzi, Maria
Krochmal, Magdalena
Magalhães, Pedro
Mullen, William
Pejchinovski, Martin
Mischak, Harald
Vlahou, Antonia
Jankowski, Vera
Belczacka, Iwona
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  surname: Jankowski
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  email: vjankowski@ukaachen.de
  organization: Institute for Molecular Cardiovascular Research (IMCAR)
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Keywords glycosylation
glycopeptides
posttranslational modifications
urine
protein biomarkers
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Snippet Purpose Urine is a rich source of potential biomarkers, including glycoproteins. Glycoproteomic analysis remains difficult due to the high heterogeneity of...
Urine is a rich source of potential biomarkers, including glycoproteins. Glycoproteomic analysis remains difficult due to the high heterogeneity of glycans....
PurposeUrine is a rich source of potential biomarkers, including glycoproteins. Glycoproteomic analysis remains difficult due to the high heterogeneity of...
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SubjectTerms Adolescent
Adult
Aged
Aged, 80 and over
Aging - urine
Antibiotics
Apolipoproteins
Biomarkers
Biomarkers - urine
Bladder
Cancer
Cholangiocarcinoma
Computer programs
Connectin
Design of experiments
Female
Glycopeptides
Glycopeptides - urine
Glycoproteins
glycosylation
Growth factors
Humans
Insulin
Kidney cancer
Male
Middle Aged
Neoplasms - urine
Pancreatic cancer
Peptides
Polysaccharides
posttranslational modifications
Prostate cancer
protein biomarkers
Proteomics
Renal cell carcinoma
Software
Statistical analysis
Urine
Workflow
Young Adult
Title Urinary Glycopeptide Analysis for the Investigation of Novel Biomarkers
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fprca.201800111
https://www.ncbi.nlm.nih.gov/pubmed/30334612
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https://www.proquest.com/docview/2122577598
Volume 13
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