基于生物信息学挖掘乳腺癌关键代谢基因及生存预后分析

Bioinformatics-based Analysis of Key Metabolic Genes of Breast Cancer and Survival Prognosis

目的:通过生物信息学方法分析乳腺癌的关键代谢基因并进行生存预后分析。方法:通过癌症基因组图谱(the cancer genome atlas,TCGA)数据库获取乳腺癌转录组数据,利用GSEA数据库查找相关代谢基因,匹配TCGA数据库相关基因,明确最终代谢基因;利用Lasso模型构建,得出生存预后分析结果。结果:得到了3个与乳腺癌相关的代谢基因,分别为POLR2K、NMNAT2、SUCLA2。生存分析结果显示高风险组和低风险组最长生存时间均为24年,年龄、状态、肿瘤分期这3个因素可作为单因素的独立预后。结论:POLR2K基因是最为明显的高表达基因,且初步显示该基因与乳腺癌的发生、发展及预后存在一定相关性,但需要通过实验验证来确认。

Objective:To analyze the key metabolic genes of breast cancer based on bioinformatics approach and survival prognosis.Methods:Breast cancer transcriptome data was gained from TCGA database,the related metabolic genes were searched utilizing GSEA database to match the related genes in TCGA database and confirm the final metabolic gene;the results of survival prognosis was obtained using Lasso models construction.Results:Three metabolic genes related to breast cancer were yielded,containing POLR2K,NMNAT2 and SUCLA2.The results of survival analysis displayed that the longest survival time of high risk group and low risk group was 24 years,age,state and the phasing of tumor could be taken as the single-factor independent prognosis.Conclusion:Obviously,POLR2K is the highly expressed gene,which is correlated with the occurrence,the development and prognosis of breast cancer in the primary study,but it needs to be confirmed through experiments.