摘要
目的:通过数据挖掘分析肝细胞癌中KIF2C基因的表达并探讨其临床意义。方法:使用Oncomine和GEPIA数据库分析KIF2C在肝细胞癌组织中的表达情况;通过GEPIA数据库进行KIF2C的表达程度与病理分级及肝细胞癌生存期的相关性分析;最后利用STRING数据库分析与KIF2C相互作用的蛋白。结果:通过Oncomine和GEPIA数据库分析显示,在mRNA水平上,KIF2C在肝细胞癌中显著高表达(P=0.000),表达水平与其预后为负相关(P=0.000),且肝癌病理分级越高,KIF2C表达水平越高。通过STRING数据库分析显示与KIF2C相关的蛋白有PLK1、AURKB、CENPA等。结论:通过对肿瘤基因数据库进行挖掘发现,KIF2C在肝细胞癌组织中明显高表达且与患者预后相关,为肝细胞癌的致病机制研究和抗肿瘤靶向治疗提供了理论支持。
Objective:To investigate the expression and clinical significance of the KIF2 C gene in hepatocellular carcinoma by data mining.Methods:Oncomine and GEPIA databases were used to analyze the expression of the KIF2 C gene in hepatocellular carcinoma.GEPIA database was used to investigate the correlation of KIF2 C expression with pathological classification and survival time.STRING database was used to determine the proteins interacting with KIF2 C.Results:The analysis using Oncomine and GEPIA databases showed high mRNA expression of KIF2 C in hepatocellular carcinoma tissue(P=0.000),and its expression level was negatively correlated with the prognosis of hepatocellular carcinoma(P=0.000);the expression level of KIF2 C increased with the increase in pathological classification.The analysis using STRING database showed that PLK1,AURKB,and CENPA proteins were associated with KIF2 C.Conclusion:Tumor gene database mining shows that KIF2 C is highly expressed in hepatocellular carcinoma tissue and is associated with patient prognosis,which provides a theoretical basis for research on the pathogenesis of hepatocellular carcinoma and anti-tumor targeted therapy.
作者
张越美
赵洪波
朱亚玲
蒋保三
王刚
何春艳
Zhang Yuemei;Zhao Hongbo;Zhu Yaling;Jiang Baosan;Wang Gang;He Chunyan(Research Group of Molecular and Genetic Epidemiology,Huaqiac University School of Medicine;Institute of Molecular Clinical Medicine,Kunming Medical University and Key Laboratory of Stem Cell and Regenerative Medicine of Yunnan Province)
出处
《重庆医科大学学报》
CAS
CSCD
北大核心
2019年第11期1454-1457,共4页
Journal of Chongqing Medical University
基金
福建省第四批创业创新人才引进计划资助项目（编号：Z16X0079）
