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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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Detalles Bibliográficos
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
Descripción
Sumario: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.