Yudi Mao1,2, Qihong Zhao3, Shi Yin2, Xiping Ding1,2, Hua Wang4. 1. Department of Gastroenterology, Affiliated Provincial Hospital of Anhui Medical University, Hefei, China. 2. Department of Geriatrics, Affiliated Provincial Hospital of Anhui Medical University, Hefei, China. 3. Department of Food and Nutrition Hygiene, School of Public Health, Anhui Medical University, Hefei, China. 4. Department of Oncology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.
Abstract
AIM: The aim of this study was to analyze the gene expression profile and biological processes enriched in gastric cancer. METHODS: We collected five human advanced gastric cancer tissues by gastroscopy and five peritumor normal tissues as controls and examined the gene expression changes by microarray. KEGG Orthology Based Annotation System annotation was used to identify pathways and biological processes regulated by the deregulated genes. Protein-protein interaction network analysis identified protein complex and functional modules. We also selected 14 genes for further verification by real-time quantitative Polymerase Chain Reaction (PCR). RESULTS: Human gene expression profile analysis showed that 2028 deregulated genes were detected in gastric cancer compared with the control group (at least a 2.0-fold change and P < 0.05), among which there were 689 upregulated and 1339 downregulated genes. Interestingly, we identified some important genes, such as CXCL17, OTX1 and CCDC125, which have not previously been reported in gastric cancer. Real-time quantitative PCR results verified that CXCL8, OTX1, CEBPB, FOSL1, FOXS1, ARFRP1 and IRF9 were upregulated in gastric cancer and CCDC125, PPP1R36, SOX2, JUN and MIA2 were downregulated. Moreover, bioinformatics analysis demonstrated that the biological processes of inflammatory response, angiogenesis, cell migration and pathways of chemokine signaling pathway, TNF signaling pathway were enriched. We also selected the top 30 significant Gene Ontology terms and select pathways for a brief summary. CONCLUSION: We performed a global analysis of the mRNA landscape in gastric cancer. Our results may stimulate a deeper understanding of the disease, and lead to the development of potential therapies and the identification of novel biomarkers.
AIM: The aim of this study was to analyze the gene expression profile and biological processes enriched in gastric cancer. METHODS: We collected five human advanced gastric cancer tissues by gastroscopy and five peritumor normal tissues as controls and examined the gene expression changes by microarray. KEGG Orthology Based Annotation System annotation was used to identify pathways and biological processes regulated by the deregulated genes. Protein-protein interaction network analysis identified protein complex and functional modules. We also selected 14 genes for further verification by real-time quantitative Polymerase Chain Reaction (PCR). RESULTS:Human gene expression profile analysis showed that 2028 deregulated genes were detected in gastric cancer compared with the control group (at least a 2.0-fold change and P < 0.05), among which there were 689 upregulated and 1339 downregulated genes. Interestingly, we identified some important genes, such as CXCL17, OTX1 and CCDC125, which have not previously been reported in gastric cancer. Real-time quantitative PCR results verified that CXCL8, OTX1, CEBPB, FOSL1, FOXS1, ARFRP1 and IRF9 were upregulated in gastric cancer and CCDC125, PPP1R36, SOX2, JUN and MIA2 were downregulated. Moreover, bioinformatics analysis demonstrated that the biological processes of inflammatory response, angiogenesis, cell migration and pathways of chemokine signaling pathway, TNF signaling pathway were enriched. We also selected the top 30 significant Gene Ontology terms and select pathways for a brief summary. CONCLUSION: We performed a global analysis of the mRNA landscape in gastric cancer. Our results may stimulate a deeper understanding of the disease, and lead to the development of potential therapies and the identification of novel biomarkers.