基于数据挖掘分析极光激酶A在食管癌中的表达及意义

doi:10.3969/j.issn.1004-616x.2020.03.012

Abstract

Abstract: 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.

Key words: esophagus cancer, data mining, aurora kinase A, prognosis

CLC Number:

R735.1

YANG Li, ZHANG Mengxian, ZHANG Wei, XIONG Yingyou, CHEN Shiyong, FANG Chengxiang. Data mining to investigate expression and significance of aurora kinase A in esophageal carcinoma[J]. Carcinogenesis, Teratogenesis & Mutagenesis, 2020, 32(3): 221-228.

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

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