基于数据挖掘分析ABAT基因在肝细胞癌中的表达及意义

目的 利用数据库分析基因ABAT在肝细胞癌中的表达以及意义。方法 利用Oncomine数据库及GEPIA分析ABAT在肝细胞癌组织中的表达情况;利用GEPIA做ABATmRNA与肝细胞癌患者生存期以及与病理分期程度的相关性分析;经MethHC数据库分析ABAT基因启动子区甲基化水平;String数据库分析与ABAT蛋白相互作用的蛋白网络;通过TheHumanProteinAtlas分析ABAT蛋白在肝细胞癌组织中的表达情况以及ABAT在蛋白水平上对患者预后的影响。结果 mRNA水平上,ABAT在肝细胞癌组织中较正常肝组织显著低表达,其mRNA水平低者预后较差(log-rank,P=0.0021),ABATmRNA水平越低者病理分期恶性程度越高(P=0.00234)。ABAT蛋白在肝细胞癌组织中也较正常肝组织表达降低,蛋白表达水平低的患者预后较差(log-rank,P=2.14×10-3)。肝细胞癌中ABAT基因启动子区甲基化水平较正常肝组织显著升高(P<0.005)。与ABAT相互作用的蛋白有ALDH1A3、ALDH9A1、ALDH3A2、GAD1、GAD2等,可能参与细胞凋亡、氧化还原及神经递质分泌等细胞功能。结论 通过肿瘤基因数据库信息挖掘发现,无论在mRNA水平或是蛋白水平上,ABAT在肝细胞癌组织中呈低表达,且与患者生存期有关。目前采用数据库挖掘分析数据可为临床上肝细胞癌的诊断以及预后评估提供参考,将为后续的肿瘤研究提供重要的理论依据。

Expression and significance of the ABAT gene in hepatocellular carcinoma: An analysis based on data mining

ObjectiveTo investigate the expression and significance of the ABAT gene in hepatocellular carcinoma (HCC) using related databases. MethodsThe Oncomine database and GEPIA were used to analyze the expression of ABAT in HCC tissue. GEPIA was used to investigate the correlation of ABAT mRNA with the survival time and pathological stage of HCC patients. The MethHC database was used to analyze the methylation level of ABAT promoter region. The String database was used to analyze the network of proteins interacting with ABAT protein. The Human Protein Atlas was used to analyze the expression of ABAT protein in HCC tissue and the influence of the protein expression of ABAT on prognosis. ResultsThe mRNA expression of ABAT in HCC tissue was significantly lower than that in normal liver tissue;patients with lower mRNA expression tended to have a poorer prognosis (log-rank, P =0.002 1) and a higher degree of malignancy ( P =0.002 34). The protein expression of ABAT in HCC tissue was significantly lower than that in normal liver tissue, and patients with lower protein expression tended to have a poorer prognosis (log-rank, P =2.14×10 -3 ). The methylation level of ABAT promoter region in HCC tissue was significantly higher than that in normal liver tissue ( P <0.005). The proteins interacting with ABAT included ALDH1A3, ALDH9A1, ALDH3A2, GAD1, and GAD2, which might be involved in cell functions such as cell apoptosis, redox, and neurotransmitter secretion. ConclusionData mining of tumor gene databases shows that there are low levels of mRNA and protein expression of ABAT in HCC tissue, which is associated with patient’s survival time. At present, database mining can provide a reference for the diagnosis and prognosis evaluation of HCC and a theoretical basis for tumor research in the future.