基于数据挖掘分析极光激酶A在食管癌中的表达及意义

目的：探讨极光激酶A（AURKA）在食管癌组织中的表达与功能，并分析其对患者生存预后的影响。方法：基于GEPIA及Oncomine数据库检索AURKA在食管癌组织与正常组织中的表达差异；通过STRING网络在线数据库构建有关AURKA的蛋白相互作用（PPI）网络，并将数据导入Cytoscape软件后采用CytoHubba分析插件筛选出核心基因；在GEPIA数据库中，基于TCGA和GTEx数据集分析AURKA与核心基因表达的相关性；采用DAVID网络分析工具对核心基因进行GO功能注释和KEGG通路富集分析；基于R2基因分析可视化平台分析AURKA的表达与食管癌患者生存预后的关系。结果：GEPIA、Oncomine数据库分析显示，AURKA在食管癌组织中的表达较正常组织明显升高（P < 0.05），但与患者肿瘤分期无关（P > 0.05）；AURKA与CDC20（r=0.78）、PLK1（r=0.83）等核心基因的表达呈显著正相关，其生物学功能主要富集于细胞分化、DNA损伤检测点、细胞增殖、负性调控细胞凋亡等；参与细胞周期调控、细胞衰老、P53以及FoxO等信号通路的调节；AURKA高表达组与低表达组患者相比预后较差，差异具有统计学意义（P < 0.05），且核心基因CCNB1、BUB1B、NEK2高表达组患者的生存率也显著低于低表达组（P均 < 0.05）。结论：AURKA在食管癌组织中表达升高，且高表达组患者预后不良；AURKA与CCNB1、NEK2等核心基因共同参与了肿瘤发生相关的功能与通路，AURKA有望成为食管癌患者早期诊断、治疗及判断预后的候选分子靶标。

Data mining to investigate expression and significance of aurora kinase A in esophageal carcinoma

OBJECTIVE: To explore the expression and function of aurora kinase A (AURKA) in esophageal cancer (ESCA) and its prognostic value in patients. METHODS: Differences of AURKA expression in ESCA tissues and normal esophagus tissues were analyzed using GEPIA and Oncomine databases. A protein-protein interaction (PPI) network about AURKA was constructed based on STRING online database and hub genes were screened with cytoHubba application of cytoscape. Correlation expressions between AURKA and hub genes were analyzed using TCGA and GTEx datasets. GO function and KEGG pathway enrichment analyses were carried out using DAVID online database. The R2 platform was used to study the association of AURKA expression and overall survival (OS) of ESCA patients. RESULTS: Expression of AURKA in ESCA tissues was significantly higher than that in normal tissues (P < 0.05),but it was unrelated to disease stages (P > 0.05). AURKA was positively correlated with CDC20 (r=0.78),PLK1 (r=0.83) and other hub genes,and their functions were mainly enriched in cell differentiation,DNA damage detection points,cell proliferation,and negative regulation of cell apoptosis. These were involved in the regulation of cell cycle,cell senescence,P53 and FoxO signaling pathways. The AURKA high expressed group was significantly associated with poor prognosis (P < 0.05),similarly the high expressions of CCNB1,BUB1B and NEK2 were significantly associated with low survival rates (all P < 0.05). CONCLUSION: AURKA was up-regulated in ESCA significantly and associated with poor prognosis based on the Oncomine and GEPIA database analyses. It was also involved in tumor-related functions and pathways together with CCNB1,NEK2 and other hub genes. Therefore,it can be used as a biomarker for early diagnosis,treatment and prognosis of patients with ESCA.