Seeking for endometrial carcinoma-related genes and their bioinformatics analysis  

作　　者：Yicheng Su Jieqing Zhang 

机构地区：[1]Department of Gynecologic Oncology, the Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021,China

出　　处：《广西医科大学学报》2017年第7期961-966,共6页Journal of Guangxi Medical University

基　　金：supported by the National Natural Science Foundation of China(No. 81160318);the Natural Science Foundation of Guangxi Province of China(No.2013GXNSFAA01 9219)

摘　　要：Objective:Screening and excavating genes and biological information related to endometrial carcinoma(EC),to provide novel means for clinical diagnosis and treatment.Methods:The gene chip data of EC was obtained from the Gene Expression Omnibus(GEO)database,we integrated gene discrepantly expressive gene analysis,enrichment of genic function and pathway analysis,protein-protein interaction(PPI)network and literature mining to predict genes and pathways of EC.Results:Functional enrichment analysis identified 976differential expression genes were participated in cell cycle regulation,proliferation,biosynthesis,protein phosphorylation and fission biological process,etc.We found eight significantly up-regulated pathways in the microarray datasets,including the MAPK signaling pathway and mTOR pathway,and six down-regulated pathways,including the P53signaling pathway and cell cycle.Gene protein related interaction network analysis was further performed,and we found twelve distinct genes,including the PCNA and CCND1,these genes were located in key position of EC related network,which may be related to the pathogenesis and progression of EC.Furthermore,there was a high correlation between PCNA and CCND1with EC by consulting the related literature and data,however,the functional mechanism was uncleared.Conclusion:The pathogenesis and progression of EC may involve in several different pathways and genes,the genes PCNA,CCND1and MAPK signaling pathway may be valuable.Objective： Screening and excavating genes and biological information related to endometrial carcinoma （EC）, to provide novel means for clinical diagnosis and treatment. Methods：The gene chip data of EC was obtained from the Gene Expression Omnibus （GEO） database, we integrated gene discrepantly expressive gene analysis, enrichment of genic function and pathway analysis, protein-protein interaction （PPI） network and literature mining to predict genes and pathways of EC. Results： Functional enrichment analysis i- dentified 976 differential expression genes were participated in cell cycle regulation, proliferation, biosynthesis, protein phosphorylation and fission biological process, etc. We found eight significantly up-regulated pathways in the microarray datasets, including the MAPK signaling pathway and mTOR pathway, and six down-regulated pathways, including the P53 signaling pathway and cell cycle. Gene protein related in- teraction network analysis was further performed, and we found twelve distinct genes, including the PCNA and CC- ND1, these genes were located in key position of EC related network, which may be related to the pathogenesis and pro- gression of EC. Furthermore, there was a high correlation between PCNA and CCND1 with EC by consulting the related literature and data, however, the functional mechanism was uncleared. Conclusion： The pathogenesis and progression of EC may involve in several different pathways and genes, the genes PCNA, CCND1 and MAPK signaling pathway may be valuable.

关 键 词：endometrial carcinoma gene chip GEO bioin-formatics analysis 

分 类 号：R735.7[医药卫生—肿瘤]