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The Identification and Characterization of Novel N-glycan-based Biomarkers in Gastric Cancer

BACKGROUND AND AIMS: To identify and validate N-glycan biomarkers in gastric cancer (GC) and to elucidate their underlying molecular mechanism of action. METHODS: In total, 347 individuals, including patients with GC (gastric cancer) or atrophic gastritis and healthy controls, were randomly divided...

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Autores principales: Liu, Long, Yan, Bing, Huang, Junlong, Gu, Qunhao, Wang, Lina, Fang, Meng, Jiao, Jianpeng, Yue, Xiaoqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3798316/
https://www.ncbi.nlm.nih.gov/pubmed/24147084
http://dx.doi.org/10.1371/journal.pone.0077821
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author Liu, Long
Yan, Bing
Huang, Junlong
Gu, Qunhao
Wang, Lina
Fang, Meng
Jiao, Jianpeng
Yue, Xiaoqiang
author_facet Liu, Long
Yan, Bing
Huang, Junlong
Gu, Qunhao
Wang, Lina
Fang, Meng
Jiao, Jianpeng
Yue, Xiaoqiang
author_sort Liu, Long
collection PubMed
description BACKGROUND AND AIMS: To identify and validate N-glycan biomarkers in gastric cancer (GC) and to elucidate their underlying molecular mechanism of action. METHODS: In total, 347 individuals, including patients with GC (gastric cancer) or atrophic gastritis and healthy controls, were randomly divided into a training group (n=287) and a retrospective validation group (n=60). Serum N-glycan profiling was achieved with DNA sequencer-assisted/fluorophore-assisted carbohydrate electrophoresis (DSA-FACE). Two diagnostic models were constructed based on the N-glycan profiles using logistic stepwise regression. The diagnostic performance of each model was assessed in retrospective, prospective (n=60), and follow-up (n=40) cohorts. Lectin blotting was performed to determine total core-fucosylation, and the expression of genes involved in core-fucosylation in GC was analyzed by reverse transcriptase-polymerase chain reaction. RESULTS: We identified at least 9 N-glycan structures (peaks) and the levels of core fucose residues and fucosyltransferase were significantly decreased in GC. Two diagnostic models, designated GCglycoA and GCglycoB, were constructed to differentiate GC from control and atrophic gastritis. The areas under the receiver operating characteristic (ROC) curves (AUC) for both GCglycoA and GCglycoB were higher than those for CEA, CA19-9, CA125 and CA72-4. Compared with CEA, CA19-9, CA125 and CA72-4, the sensitivity of GCglycoA increased 29.66%, 37.28%, 56.78% and 61.86%, respectively, and the accuracy increased 10.62%, 16.82%, 25.67% and 28.76%, respectively. For GCglycoB, the sensitivity increased 27.97%, 35.59%, 55.09% and 60.17% and the accuracy increased 21.26%, 24.64%, 31.40% and 34.30% compared with CEA, CA19-9, CA125 and CA72-4, respectively. After curative surgery, the core fucosylated peak (peak 3) and the total core fucosylated N-glycans (sumfuc) were reversed. CONCLUSIONS: The results indicated that the diagnostic models based on N-glycan markers are valuable and noninvasive alternatives for identifying GC. We concluded that decreased core-fucosylation in both tissue and serum from GC patients may result from the decreased expression of fucosyltransferase.
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spelling pubmed-37983162013-10-21 The Identification and Characterization of Novel N-glycan-based Biomarkers in Gastric Cancer Liu, Long Yan, Bing Huang, Junlong Gu, Qunhao Wang, Lina Fang, Meng Jiao, Jianpeng Yue, Xiaoqiang PLoS One Research Article BACKGROUND AND AIMS: To identify and validate N-glycan biomarkers in gastric cancer (GC) and to elucidate their underlying molecular mechanism of action. METHODS: In total, 347 individuals, including patients with GC (gastric cancer) or atrophic gastritis and healthy controls, were randomly divided into a training group (n=287) and a retrospective validation group (n=60). Serum N-glycan profiling was achieved with DNA sequencer-assisted/fluorophore-assisted carbohydrate electrophoresis (DSA-FACE). Two diagnostic models were constructed based on the N-glycan profiles using logistic stepwise regression. The diagnostic performance of each model was assessed in retrospective, prospective (n=60), and follow-up (n=40) cohorts. Lectin blotting was performed to determine total core-fucosylation, and the expression of genes involved in core-fucosylation in GC was analyzed by reverse transcriptase-polymerase chain reaction. RESULTS: We identified at least 9 N-glycan structures (peaks) and the levels of core fucose residues and fucosyltransferase were significantly decreased in GC. Two diagnostic models, designated GCglycoA and GCglycoB, were constructed to differentiate GC from control and atrophic gastritis. The areas under the receiver operating characteristic (ROC) curves (AUC) for both GCglycoA and GCglycoB were higher than those for CEA, CA19-9, CA125 and CA72-4. Compared with CEA, CA19-9, CA125 and CA72-4, the sensitivity of GCglycoA increased 29.66%, 37.28%, 56.78% and 61.86%, respectively, and the accuracy increased 10.62%, 16.82%, 25.67% and 28.76%, respectively. For GCglycoB, the sensitivity increased 27.97%, 35.59%, 55.09% and 60.17% and the accuracy increased 21.26%, 24.64%, 31.40% and 34.30% compared with CEA, CA19-9, CA125 and CA72-4, respectively. After curative surgery, the core fucosylated peak (peak 3) and the total core fucosylated N-glycans (sumfuc) were reversed. CONCLUSIONS: The results indicated that the diagnostic models based on N-glycan markers are valuable and noninvasive alternatives for identifying GC. We concluded that decreased core-fucosylation in both tissue and serum from GC patients may result from the decreased expression of fucosyltransferase. Public Library of Science 2013-10-17 /pmc/articles/PMC3798316/ /pubmed/24147084 http://dx.doi.org/10.1371/journal.pone.0077821 Text en © 2013 Liu et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Liu, Long
Yan, Bing
Huang, Junlong
Gu, Qunhao
Wang, Lina
Fang, Meng
Jiao, Jianpeng
Yue, Xiaoqiang
The Identification and Characterization of Novel N-glycan-based Biomarkers in Gastric Cancer
title The Identification and Characterization of Novel N-glycan-based Biomarkers in Gastric Cancer
title_full The Identification and Characterization of Novel N-glycan-based Biomarkers in Gastric Cancer
title_fullStr The Identification and Characterization of Novel N-glycan-based Biomarkers in Gastric Cancer
title_full_unstemmed The Identification and Characterization of Novel N-glycan-based Biomarkers in Gastric Cancer
title_short The Identification and Characterization of Novel N-glycan-based Biomarkers in Gastric Cancer
title_sort identification and characterization of novel n-glycan-based biomarkers in gastric cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3798316/
https://www.ncbi.nlm.nih.gov/pubmed/24147084
http://dx.doi.org/10.1371/journal.pone.0077821
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