摘要
目的:分析高危前列腺癌(high-risk prostate cancer)患者前列腺癌组织基因表达芯片数据的生物学网络调控及关键蛋白,为高危前列腺癌的诊断及治疗提供新的理论依据。方法:从基因芯片公共数据库(Gene Expression Omnibus,GEO)中下载来自于丹麦一个人群队列(正常前列腺14例,前列腺癌36例)的前列腺组织基因芯片数据,利用基因云,基因大数据分析(Gene-Cloud of Biotechnology Informs,GCBI)实验平台、GenClip2.0、Sytoscape 3.5.1等软件,筛选差异表达基因,探讨差异基因的蛋白交互作用网络和生物学通路,从转录组角度阐述高危前列腺癌发展的分子机制。结果:与正常前列腺组相比,高危前列腺癌组共有4 828个(8.83%)差异表达基因;主要涉及细胞黏附、细胞运动、细胞发育等功能。SOCS3、VEGFA、TOP2A和FGFR2基因为蛋白网络核心节点,均与高危前列腺癌的发生具有密切关系。结论:SOCS3、VEGFA、TOP2A和FGFR2基因为蛋白网络核心节点,在高危前列腺癌组中差异表达,其功能主要涉及P450细胞色素通路、β信号通路、血小板通路、细胞连接组织通路、ECM受体通路等9条通路。
Objective:To analyze the biological regulation and key proteins of prostate tissue gene expression gene data in high-risk prostate cancer patients,to provide a new theoretical basis for prostate cancer diagnosis and treatment.Methods:Microarray gene chip data of prostate tissue were downloaded from Gene Expression Omnibus(GEO) public database including normal prostate tissue(14 cases) and high-risk prostate cancer(36 cases),the differential expression genes were imported into the analysis software Gene-Cloud of Biotechnology Informs(GCBI) experimental platform,GenClip2.0 and Sytoscape 3.5.1.Exploring expression of protein interaction network,biological pathway,and the molecular mechanism of the development of high-risk prostate cancer from the perspective of transcriptions.Results:Compared with the control group,there were 4 828(8.83%) differentially expressed genes between the two groups.The difference gene was mainly associated with cell adhesion,cell motility and cell development.SOCS3,VEGFA,TOP2A and FGFR2 genes are the key nodes of the protein-protein interaction network,and have a closed relationship with high-risk prostate cancer development.Conclusion:SOCS3,VEGFA,TOP2A and FGFR2 genes are the core nodes of protein network in prostate tissue of high-risk prostate cancer patients.The function mainly includes P450 cytochrome pathway,beta signaling pathway,platelet pathway,cell connective tissue pathway,ECM receptor pathway and other pathways.
作者
郭亚收
徐晓峰
李楠
孙娜
段丽芳
Guo Yashou;Xu Xiaofeng;Li Nan;Sun Na;Duan Lifang(Department of Urology,Xianyang Central Hospital,Shaanxi Xianyang 712000,China;Department of Epidemiology and Health Statistics,School of Public Health,Shaanxi University of Chinese Medicine,Shaanxi Xianyang 712046,China)
出处
《现代肿瘤医学》
CAS
2019年第8期1281-1284,共4页
Journal of Modern Oncology
基金
国家自然科学基金青年项目(编号:81603420)
咸阳市科学技术研究攻关项目(编号:2017k02-85)
关键词
前列腺癌
基因表达
计算生物学
prostate cancer
gene expression
computational biology
