基于数据挖掘分析KIF2C在肝细胞癌的表达及临床意义

Expression and clinical significance of KIF2C gene in hepatocellular carcinoma：An analysis based on data mining

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。

Abstract:

Objective：To investigate the expression and clinical significance of the KIF2C gene in hepatocellular carcinoma by data mining. Methods：Oncomine and GEPIA databases were used to analyze the expression of the KIF2C gene in hepatocellular carcinoma. GEPIA database was used to investigate the correlation of KIF2C expression with pathological classification and survival time. STRING database was used to determine the proteins interacting with KIF2C. Results：The analysis using Oncomine and GEPIA databases showed high mRNA expression of KIF2C in hepatocellular carcinoma tissue（P=0.000），and its expression level was nega－tively correlated with the prognosis of hepatocellular carcinoma（P=0.000）；the expression level of KIF2C increased with the increase in pathological classification. The analysis using STRING database showed that PLK1，AURKB，and CENPA proteins were associated with KIF2C. Conclusion：Tumor gene database mining shows that KIF2C 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.