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Expression profile of cytokines in gastric cancer patients using proteomic antibody microarray

Gastric cancer (GC) is often a deadly disease due to the late diagnosis and chemoresistance that characterizes many cases of this disease. The aim of this study was to explore a panel of candidate cytokines as diagnostic and predictive biomarkers for GC. Sixteen tissue samples of GC and adjacent non...

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Autores principales: Quan, Xiaoqiang, Ding, Yi, Feng, Ruo, Zhu, Xiaoyan, Zhang, Qinxian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5755243/
https://www.ncbi.nlm.nih.gov/pubmed/29344174
http://dx.doi.org/10.3892/ol.2017.7104
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author Quan, Xiaoqiang
Ding, Yi
Feng, Ruo
Zhu, Xiaoyan
Zhang, Qinxian
author_facet Quan, Xiaoqiang
Ding, Yi
Feng, Ruo
Zhu, Xiaoyan
Zhang, Qinxian
author_sort Quan, Xiaoqiang
collection PubMed
description Gastric cancer (GC) is often a deadly disease due to the late diagnosis and chemoresistance that characterizes many cases of this disease. The aim of this study was to explore a panel of candidate cytokines as diagnostic and predictive biomarkers for GC. Sixteen tissue samples of GC and adjacent noncancerous mucosa were selected from GC patients (n=8) for antibody microarray analysis. Proteomic chip-based analysis was performed to simultaneously identify 507 cytokines using a cytokine antibody array in the gastric tissues to screen for differential proteins related in cases of GC. Fold changes of protein expression >2.0 or <0.5 were considered significant. The proteins that showed significant differences in levels between the cancerous and non-cancerous samples were analyzed using bioinformatics analysis. One hundred and five cytokines that were significantly different (p<0.05) between GC tissues and normal gastric mucosa were identified. Gene Ontology (GO) enrichment analysis showed that these differentially expressed proteins are involved in many biological and immunological processes, mainly in response to stress, chloroplast thylakoid membrane, vacuole, photosynthesis, aspartic-type endopeptidase activity and flavin adenine dinucleotide binding. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that these proteins mainly were involved in the process of cytokine-cytokine receptor interaction, transforming growth factor-β (TGF-β) signaling pathway, pathways in cancer, tumor necrosis factor (TNF) signaling pathway, and mitogen-activated protein kinase (MAPK) signaling pathway. These findings suggest that the differentially expressed proteins could be associated with GC in patients. Further study of these cytokines may provide a promising approach for diagnosis, classification and prognosis of GC.
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spelling pubmed-57552432018-01-17 Expression profile of cytokines in gastric cancer patients using proteomic antibody microarray Quan, Xiaoqiang Ding, Yi Feng, Ruo Zhu, Xiaoyan Zhang, Qinxian Oncol Lett Articles Gastric cancer (GC) is often a deadly disease due to the late diagnosis and chemoresistance that characterizes many cases of this disease. The aim of this study was to explore a panel of candidate cytokines as diagnostic and predictive biomarkers for GC. Sixteen tissue samples of GC and adjacent noncancerous mucosa were selected from GC patients (n=8) for antibody microarray analysis. Proteomic chip-based analysis was performed to simultaneously identify 507 cytokines using a cytokine antibody array in the gastric tissues to screen for differential proteins related in cases of GC. Fold changes of protein expression >2.0 or <0.5 were considered significant. The proteins that showed significant differences in levels between the cancerous and non-cancerous samples were analyzed using bioinformatics analysis. One hundred and five cytokines that were significantly different (p<0.05) between GC tissues and normal gastric mucosa were identified. Gene Ontology (GO) enrichment analysis showed that these differentially expressed proteins are involved in many biological and immunological processes, mainly in response to stress, chloroplast thylakoid membrane, vacuole, photosynthesis, aspartic-type endopeptidase activity and flavin adenine dinucleotide binding. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that these proteins mainly were involved in the process of cytokine-cytokine receptor interaction, transforming growth factor-β (TGF-β) signaling pathway, pathways in cancer, tumor necrosis factor (TNF) signaling pathway, and mitogen-activated protein kinase (MAPK) signaling pathway. These findings suggest that the differentially expressed proteins could be associated with GC in patients. Further study of these cytokines may provide a promising approach for diagnosis, classification and prognosis of GC. D.A. Spandidos 2017-12 2017-09-29 /pmc/articles/PMC5755243/ /pubmed/29344174 http://dx.doi.org/10.3892/ol.2017.7104 Text en Copyright: © Quan et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Quan, Xiaoqiang
Ding, Yi
Feng, Ruo
Zhu, Xiaoyan
Zhang, Qinxian
Expression profile of cytokines in gastric cancer patients using proteomic antibody microarray
title Expression profile of cytokines in gastric cancer patients using proteomic antibody microarray
title_full Expression profile of cytokines in gastric cancer patients using proteomic antibody microarray
title_fullStr Expression profile of cytokines in gastric cancer patients using proteomic antibody microarray
title_full_unstemmed Expression profile of cytokines in gastric cancer patients using proteomic antibody microarray
title_short Expression profile of cytokines in gastric cancer patients using proteomic antibody microarray
title_sort expression profile of cytokines in gastric cancer patients using proteomic antibody microarray
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5755243/
https://www.ncbi.nlm.nih.gov/pubmed/29344174
http://dx.doi.org/10.3892/ol.2017.7104
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