摘要
目的探讨颈动脉不稳定斑块发生的分子机制。方法从Array Express数据库下载基因表达谱数据E-MTAB-2055。该数据包含24例颈动脉不稳定斑块和24例稳定斑块组织,从中筛选差异基因,并通过富集分析获取与不稳定斑块有关的生物学过程和通路。同时,通过构建差异表达基因的生物网络来寻找与该疾病高度相关的风险模块,并用荧光定量PCR法检测五对不稳定斑块和斑块旁标本,验证风险模块中部分基因的差异表达。结果不稳定斑块中发生显著性差异表达变化的基因共有439个,其中上调基因为232个,下调基因为207个。涉及到的生物学过程和通路大部分与炎症和免疫应答有关。生物网络和模块分析提示CXCR4、VCL和TYROBP可能在不稳定斑块发生发展过程中发挥着重要作用。荧光定量PCR结果显示CXCR4和TYROBP基因表达情况与芯片数据分析结果一致。结论本研究比较完整地揭示了不稳定斑块差异表达谱特征和所涉及的生物学过程和信号通路,其中TYROBP可能是不稳定斑块发生发展进程中新的致病基因。
Objective To explore the molecular mechanism in the formation of unstable plaques. Methods The cDNA microarray E-MTAB-2055 was downloaded from ArrayExpress database to screen the differentially expressed genes in 24 ruptured plaques against 24 stable plaques. Functional enrichment analysis was conducted to define the biological processes and pathways involved in disease progression. The protein-protein interaction network was constructed to identify the risk modules with close interactions. Five pairs of carotid specimens were used to validate 3 differentially expressed genes of the risk modules by real-time PCR. Results A total of 439 genes showed differential expression in our analysis, including 232 up-regulated and 207 down-regulated genes according to the data filter criteria. Immune-related biological processes and pathways were greatly enriched. The protein-protein interaction network and module analysis suggested that TYROBP, VCL and CXCR4 might play critical roles in the development of unstable plaques, and differential expressions of CXCR4 and TYROBP in carotid plaques were confirmed by real-time PCR. Conclusion Our study shows the differential gene expression profile, potential biological processes and signaling pathways involved in the process of plaque rupture. TYROBP may be a new candidate disease gene in the pathogenesis of unstable plaques.
出处
《南方医科大学学报》
CAS
CSCD
北大核心
2015年第5期738-742,共5页
Journal of Southern Medical University
基金
南方-哈佛"健康医疗云服务"平台关键技术创新
集成与应用(2013J4500040)
关键词
不稳定斑块
动脉粥样硬化
表达谱
差异表达基因
生物信息学
unstable plaque
atherosclerosis
expression profile
differential expressed genes
bioinformatics