Background: Identification of biomarkers to distinguish between stable and unstable plaque formation would be very useful to predict plaque vulnerability. Methods: We downloaded microarray profiles of gene set enrichment (GSE) accession numbers including GSE71226 and GSE20680 (group A: containing healthy vs stable plaque samples) and GSE62646 and GSE34822 (group B: containing stable vs unstable plaque samples) from Gene expression omnibus (GEO) database. Differentially expressed genes were compared in both data sets of each group. Results: Ten and 12 key genes were screened in groups A and B, respectively. Gene Ontology (GO) enrichment was applied by the plugin “BiNGO” (Biological networks gene ontology tool) of the Cytoscape. The key genes were mostly enriched in the biological process of positive regulation of the cellular process. The protein-protein interaction and co-expression network were analyzed by the STRING (search tool for the retrieval of interacting genes/proteins) and GeneMANIA (gene multiple association network integration algorithm) plugin of Cytoscape, respectively, which showed that Epidermal growth factor (EGF), Heparin-binding EGF like growth factor (HBEGF), and Matrix metalloproteinase 9 (MMP9) were at the core of the network. Further validation of key genes using two datasets showed that Phosphodiesterase 5A (PDE5A) and Protein S (PROS1) were decreased in unstable plaques, while Suppressor of cytokine signaling (SOCS3), HBEGF, and Leukocyte immunoglobulin-like receptor B4 (LILRB4) were increased. Conclusion: The present study used several datasets to identify key genes associated with stable and unstable atherosclerotic plaque.

中文翻译：

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区分稳定和不稳定动脉粥样硬化斑块的关键基因的鉴定：生物信息学和计算分析

背景：识别生物标志物来区分稳定和不稳定的斑块形成对于预测斑块的脆弱性非常有用。方法：我们从基因表达综合库（Gene expression omnibus）下载了基因集富集（GSE）登录号的微阵列图谱，包括 GSE71226 和 GSE20680（A 组：包含健康与稳定斑块样本）以及 GSE62646 和 GSE34822（B 组：包含稳定与不稳定斑块样本）。 GEO）数据库。比较每组两个数据集中的差异表达基因。结果：A组和B组分别筛选出10个和12个关键基因。基因本体（GO）富集是通过 Cytoscape 的插件“BiNGO”（生物网络基因本体工具）应用的。关键基因大多富集于细胞过程正调控的生物过程中。分别通过Cytoscape的STRING（用于检索相互作用基因/蛋白质的搜索工具）和GeneMANIA（基因多重关联网络集成算法）插件对蛋白质-蛋白质相互作用和共表达网络进行分析，结果表明表皮生长因子（ EGF）、肝素结合 EGF 样生长因子 (HBEGF) 和基质金属蛋白酶 9 (MMP9) 是该网络的核心。使用两个数据集对关键基因的进一步验证表明，不稳定斑块中磷酸二酯酶 5A (PDE5A) 和蛋白 S (PROS1) 减少，而细胞因子信号传导抑制因子 (SOCS3)、HBEGF 和白细胞免疫球蛋白样受体 B4 (LILRB4) 增加。结论：本研究使用多个数据集来识别与稳定和不稳定动脉粥样硬化斑块相关的关键基因。