摘要
目的探索促红细胞生成素产生型人肝细胞受体A5(erythropoietin-producing hepatocellular receptor A5,EPHA5)在肺腺癌中的表达。方法通过网络数据库获得EPHA5在不同肿瘤中的变异情况,构建EPHA5蛋白互作网络图,分析EPHA5在肺腺癌中的预后情况。收集肺腺癌患者的手术标本及临床资料,采用免疫组织化学方法检测EPHA5的表达情况,分析肺腺癌中EPHA5表达与患者临床特征的相关性。结果EPHA5在肺腺癌中的突变频率最高,以错义突变为主。除EPH家族的配体之外,EPHA5与RhoA、ADAM10蛋白密切相关。EPHA5的高表达与肺腺癌患者的总生存时间和首次进展时间相关。EPHA5在肺腺癌组织中表达上调,与患者淋巴结转移、分化程度、TNM分期显著相关。结论EPHA5在肺腺癌组织中高表达,可以作为预测肺腺癌预后的一个因素。
Objective To investigate the expression of erythropoietin-producing hepatocellular receptor A5(EPHA5)in lung adenocarcinoma.Methods The variation of EPHA5 in different tumors was obtained through the network database,and the EPHA5 protein interaction network diagram was constructed to analyze the prognosis of EPHA5 in lung adenocarcinoma.The surgical specimens and clinical data of patients with lung adenocarcinoma were collected.The expression of EPHA5 was detected by immunohistochemistry,and the correlation between EPHA5 expression in lung adenocarcinoma and clinical characteristics of patients was analyzed.Results EPHA5 has the highest mutation frequency in lung adenocarcinoma,mainly missense mutations.In addition to the ligands of EPH family,EPHA5 was closely related to RhoA and ADAM10 proteins.High expression of EPHA5 was associated with overall survival and time to first progression in patients with lung adenocarcinoma.EPHA5 expression was up-regulated in lung adenocarcinoma tissues,which was significantly correlated with lymph node metastasis,differentiation degree and TNM stage.Conclusion EPHA5 is highly expressed in lung adenocarcinoma tissues,which can be used as a prognostic factor for lung adenocarcinoma.
作者
李杰
王兰
LI Jie;WANG Lan(Department of Respiratory and Critical Care Medicine,Jiangyin Clinical Medical College of Jiangsu University/Jiangyin People′s Hospital,Jiangsu Province,Jiangyin 214400,China)
出处
《河北医科大学学报》
CAS
2024年第2期215-220,共6页
Journal of Hebei Medical University
基金
国家自然科学基金(82000012)
江苏大学2021年度临床医学科技发展基金(JLY2021075)
中华国际医学交流基金会项目(Z-2014-08-2209)。
关键词
肺腺癌
免疫组织化学
数据挖掘
lung adenocarcinoma
immunohistochemistry
data mining
