解剖学报

解剖学报 ›› 2019, Vol. 50 ›› Issue (3): 310-316.doi: 10.16098/j.issn.0529-1356.2019.03.008

• 肿瘤生物学 • 上一篇    下一篇

膀胱癌基因芯片生物信息分析及功能探讨

秦松林1 周洋2* 胡威1 刘伯龙1 唐正1   

  1. 1.南华大学附属第一医院泌尿男科，湖南 衡阳 421001; 2.江苏大学附属医院泌尿外科，江苏 镇江 212000
  • 收稿日期:2018-06-11 修回日期:2018-08-04 出版日期:2019-06-06 发布日期:2019-06-06
  • 通讯作者: 周洋 E-mail:1010240654@qq.com

Bioinformatics analysis and functional analysis of bladder cancer gene microarray

QIN Song-lin1 ZHOU Yang 2* HU Wei1 LIU Bo-long1 TANG Zheng1   

  1. 1.Department of Urology, the First Affiliated Hospital, University of South China, Hu’nan Hengyang 421001, China; 2.Department of Urology, Affiliated Hospital of Jiangsu University, Jiangsu Zhenjiang 212000, China
  • Received:2018-06-11 Revised:2018-08-04 Online:2019-06-06 Published:2019-06-06
  • Contact: ZHOU Yang E-mail:1010240654@qq.com

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摘要：

目的 从分子水平探讨膀胱癌的发病机制，为临床诊断及预后评估提供新思路。 方法 从基因芯片数据库中下载人膀胱癌的相关基因芯片数据GSE31189（包括52例尿路上皮癌和40例正常膀胱组织），使用Morpheus（software.broadinstitute.org/morpheus/）在线工具分析癌症尿路上皮组织和正常尿路上皮组织的差异表达基因，然后使用生物技术信息基因云（GCBI，https://www.GCBI.com.cn)在线分析系统进行差异表达基因信号通路富集以及差异基因之间相互作用的分析，最后选择差异基因通过细胞计数试剂盒8（CCK-8）、侵袭实验和免疫印迹法初步验证其功能。 结果 按q值进行排序并筛选出差异最大的前20个基因，其中膀胱癌中上调基因18个，下调基因2个。基因分类（GO）分析发现，这些差异基因主要集中在炎症反应、免疫反应，负调控凋亡过程，来自RNA聚合酶Ⅱ启动子的转录负调控等多个生物学功能。信息通路（Pathway）分析结果显示，这些差异基因主要参与癌症中转录失调、代谢途径、核因子（NF）-κB信号通路等生物学过程。基因网络分析发现，CXC趋化因子受体4（CXCR4）、丝裂原活化蛋白激酶10（MAPK10）是这些基因网络的中心环节。初步体外实验表明，基质金属蛋白酶12（MMP-12）下调后，膀胱癌细胞的增殖明显减少，侵袭能力下降，细胞外调节蛋白激酶（ERK）磷酸化水平下降。 结论 通过多重生物信息学分析可以找出膀胱肿瘤中关键基因，CXCR4、MAPK10是膀胱基因网络中的关键环节，MMP-12在膀胱癌细胞中高表达，下调MMP-12可抑制膀胱癌细胞增殖和侵袭，它可能通过ERK途径发挥其生物学功能。

关键词: 膀胱癌, 基因网络, 生物信息学, 在线分析, 人

Abstract:

Objective To explore the pathogenesis of bladder cancer from the molecular level and provide new ideas for clinical diagnosis and prognosis evaluation. Methods Human bladder cancer-associated gene chip data GSE31189, including 52 bladder cancer samples and 40 normal bladder samples, was downloaded from a database of gene chips, and then Morpheus (https://software.broadinstitute.org/morpheus/) online tools were used to analyze cancer urothelial tissue and normal urothelial tissue. Differentially expressed genes were then analyzed online using gene-cloud of biotechnology information(GCBI) (https://www.GCBI.com.cn) for enrichment of differentially expressed gene signaling pathways and differential gene interactions. Finally, differential selection genes were selected for cell counting kit-8(CCK-8), invasion and Western blotting assays. Initially verify its function. Results According to the q value, the top 20 genes with the largest difference were selected. Among them, 18 genes were up-regulated and 2 genes were down-regulated in bladder cancer. Gene ontology（GO）analysis revealed that these differentially expressed genes are mainly involved in many biological functions such as inflammatory responses, immune responses, negative regulation of apoptosis, and transcriptional negative control from the RNA polymerase Ⅱ promoter. Pathway analysis showed that these differentially expressed genes are involved in biological processes such as transcriptional dysregulation, metabolic pathways, and nuclear factor kappa beta（NF-κB）signaling pathways in cancer. Gene network analysis found that CXC chemokine receptor 4 (CXCR4) and mitogenactivated protein kinase 10（MAPK10）are the central links in these gene networks. In vitro experiments showed that matrix metalloproteindase-12(MMP-12）downregulation led to the decreased proliferation and invasion of bladder cancer cells and the phoshorylation level of extracellular regulated protein kinases(ERK）. Conclusion Multiple bioinformatics analysis can identify the key genes in bladder tumors. CXCR4 and MAPK10 are the key links in the bladder gene network. MMP-12 is highly expressed in bladder cancer cells. Downregulation of MMP-12 can inhibit the proliferation and invasion abilities of bladder cancer cells through ERK pathway.

Key words: Bladder cancer, Gene network, Bioinformatics, On-line analysis, Human