基于机械学习分析KIF11在肺腺癌中的表达及生物学意义

To Analyze the Expression and Biological Significance of KIF11 in Lung Adenocarcinoma Based on Mechanistic Learning

目的:分析探讨驱动蛋白-11在肺腺癌中的表达及生物学意义。方法:应用癌症基因图谱(The Cancer Genome Atlas, TCGA)公共数据库挖掘分析KIF11在正常肺组织与肺腺癌组织中的表达情况,免疫组化检测临床肺腺癌标本检测驱动蛋白-11的表达及临床病理关系,利用Kaplan-Meier Plotter数据库分析驱动蛋白-11与肺腺癌患者生存预后关系。结论:TCGA数据库分析显示驱动蛋白-11在肺腺癌组织中表达明细高于正常肺组织,Kaplan-Meier Plotter分析显示高表达的肺腺癌组的预后较差,免疫组化分析显示驱动蛋白-11在肺腺癌患者中表达明显增强;结论:驱动蛋白-11在肺腺癌中高表达,且与肺腺癌的进展和预后相关,可作为肺腺癌靶向治疗的潜在靶点。

Objective: To analyze the expression and biological significance of kinesin-11 in lung adenocarci-noma. Methods: The Cancer Genome Atlas (TCGA) public database was used to mine and analyze the expression of KIF11 in normal lung tissues and lung adenocarcinoma tissues, immunohistochemis-try was used to detect the expression and clinicopathological relationship between kinesin-11 in clinical lung adenocarcinoma samples, and the relationship between kinesin-11 and the survival prognosis of lung adenocarcinoma patients was analyzed by Kaplan-Meier Plotter database. Result: TCGA database analysis showed that the expression of kinesin-11 in lung adenocarcinoma tissues was higher than that in normal lung tissues, Kaplan-Meier Plotter analysis showed that the progno-sis of the highly expressed lung adenocarcinoma group was poor, and immunohistochemical analy-sis showed that the expression of kinesin-11 in lung adenocarcinoma patients was significantly en-hanced. Conclusion: Kinesin-11 is highly expressed in lung adenocarcinoma and is related to the progression and prognosis of lung adenocarcinoma, which can be used as a potential target for tar-geted therapy of lung adenocarcinoma.