Protein expression profiles and clinicopathologic characteristics associate with gastric cancer survival

Abstract Background: Prognosis remains one of most crucial determinants of gastric cancer (GC) treatment, but current methods do not predict prognosis accurately. Identification of additional biomarkers is urgently required to identify patients at risk of poor prognoses. Methods: Tissue microarray...

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Autores principales:	Li,Wei, Chen,Yan, Sun,Xuan, Yang,Jupeng, Zhang,David Y., Wang,Daguang, Suo,Jian
Lenguaje:	English
Publicado:	Sociedad de Biología de Chile 2019
Materias:	Gastric cancer Protein expression profiling Tissue microarray Immunohistochemistry Pathway
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0716-97602019000100239
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spelling	oai:scielo:S0716-976020190001002392019-10-10Protein expression profiles and clinicopathologic characteristics associate with gastric cancer survivalLi,WeiChen,YanSun,XuanYang,JupengZhang,David Y.Wang,DaguangSuo,Jian Gastric cancer Protein expression profiling Tissue microarray Immunohistochemistry Pathway Abstract Background: Prognosis remains one of most crucial determinants of gastric cancer (GC) treatment, but current methods do not predict prognosis accurately. Identification of additional biomarkers is urgently required to identify patients at risk of poor prognoses. Methods: Tissue microarrays were used to measure expression of nine GC-associated proteins in GC tissue and normal gastric tissue samples. Hierarchical cluster analysis of microarray data and feature selection for factors associated with survival were performed. Based on these data, prognostic scoring models were established to predict clinical outcomes. Finally, ingenuity pathway analysis (IPA) was used to identify a biological GC network. Results: Eight proteins were upregulated in GC tissues versus normal gastric tissues. Hierarchical cluster analysis and feature selection showed that overall survival was worse in cyclin dependent kinase (CDK)2, Akt1, X-linked inhibitor of apoptosis protein (XIAP), Notch4, and phosphorylated (p)-protein kinase C (PKC) α/β2 immunopositive patients than in patients that were immunonegative for these proteins. Risk score models based on these five proteins and clinicopathological characteristics were established to determine prognoses of GC patients. These proteins were found to be involved in cancer related-signaling pathways and upstream regulators were identified. Conclusion: This study identified proteins that can be used as clinical biomarkers and established a risk score model based on these proteins and clinicopathological characteristics to assess GC prognosis.info:eu-repo/semantics/openAccessSociedad de Biología de ChileBiological Research v.52 20192019-01-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0716-97602019000100239en10.1186/s40659-019-0249-0
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	Gastric cancer Protein expression profiling Tissue microarray Immunohistochemistry Pathway
spellingShingle	Gastric cancer Protein expression profiling Tissue microarray Immunohistochemistry Pathway Li,Wei Chen,Yan Sun,Xuan Yang,Jupeng Zhang,David Y. Wang,Daguang Suo,Jian Protein expression profiles and clinicopathologic characteristics associate with gastric cancer survival
description	Abstract Background: Prognosis remains one of most crucial determinants of gastric cancer (GC) treatment, but current methods do not predict prognosis accurately. Identification of additional biomarkers is urgently required to identify patients at risk of poor prognoses. Methods: Tissue microarrays were used to measure expression of nine GC-associated proteins in GC tissue and normal gastric tissue samples. Hierarchical cluster analysis of microarray data and feature selection for factors associated with survival were performed. Based on these data, prognostic scoring models were established to predict clinical outcomes. Finally, ingenuity pathway analysis (IPA) was used to identify a biological GC network. Results: Eight proteins were upregulated in GC tissues versus normal gastric tissues. Hierarchical cluster analysis and feature selection showed that overall survival was worse in cyclin dependent kinase (CDK)2, Akt1, X-linked inhibitor of apoptosis protein (XIAP), Notch4, and phosphorylated (p)-protein kinase C (PKC) α/β2 immunopositive patients than in patients that were immunonegative for these proteins. Risk score models based on these five proteins and clinicopathological characteristics were established to determine prognoses of GC patients. These proteins were found to be involved in cancer related-signaling pathways and upstream regulators were identified. Conclusion: This study identified proteins that can be used as clinical biomarkers and established a risk score model based on these proteins and clinicopathological characteristics to assess GC prognosis.
author	Li,Wei Chen,Yan Sun,Xuan Yang,Jupeng Zhang,David Y. Wang,Daguang Suo,Jian
author_facet	Li,Wei Chen,Yan Sun,Xuan Yang,Jupeng Zhang,David Y. Wang,Daguang Suo,Jian
author_sort	Li,Wei
title	Protein expression profiles and clinicopathologic characteristics associate with gastric cancer survival
title_short	Protein expression profiles and clinicopathologic characteristics associate with gastric cancer survival
title_full	Protein expression profiles and clinicopathologic characteristics associate with gastric cancer survival
title_fullStr	Protein expression profiles and clinicopathologic characteristics associate with gastric cancer survival
title_full_unstemmed	Protein expression profiles and clinicopathologic characteristics associate with gastric cancer survival
title_sort	protein expression profiles and clinicopathologic characteristics associate with gastric cancer survival
publisher	Sociedad de Biología de Chile
publishDate	2019
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0716-97602019000100239
work_keys_str_mv	AT liwei proteinexpressionprofilesandclinicopathologiccharacteristicsassociatewithgastriccancersurvival AT chenyan proteinexpressionprofilesandclinicopathologiccharacteristicsassociatewithgastriccancersurvival AT sunxuan proteinexpressionprofilesandclinicopathologiccharacteristicsassociatewithgastriccancersurvival AT yangjupeng proteinexpressionprofilesandclinicopathologiccharacteristicsassociatewithgastriccancersurvival AT zhangdavidy proteinexpressionprofilesandclinicopathologiccharacteristicsassociatewithgastriccancersurvival AT wangdaguang proteinexpressionprofilesandclinicopathologiccharacteristicsassociatewithgastriccancersurvival AT suojian proteinexpressionprofilesandclinicopathologiccharacteristicsassociatewithgastriccancersurvival
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Protein expression profiles and clinicopathologic characteristics associate with gastric cancer survival

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