乳腺癌预后相关基因的生物信息学筛选与分析

doi:10.11904/j.issn.1002-3070.2023.05.006

摘要/Abstract

摘要： 目的运用生物信息学技术方法,分析影响乳腺癌患者生存的关键基因,为乳腺癌预后评估及靶向治疗提供理论依据。方法通过TCGA数据库筛选出乳腺癌样本与正常乳腺样本间的差异表达基因,进行基因本体论(GO)和京都基因和基因组数据库(KEGG)富集分析。构建蛋白互作网络并筛选出关键基因。运用Kaplan-Meier法寻找可能作为乳腺癌潜在预后生物标志物的基因并进行验证,探究预后相关靶基因与分子分型及分期的相关性。运用Timer数据库分析预后相关靶基因与免疫细胞浸润相关性。结果共筛选出差异表达基因1 285个,其中上调基因318个,下调基因967个(|log₂FC|≥1,P＜0.05)。差异表达基因主要富集于细胞因子-细胞因子受体相互作用、PI3K-Akt信号通路、cAMP信号通路等。蛋白互作网络共筛选出10个关键基因(AURKB、CDC20、CCNA2、NCAPG、BUB1、TOP2A、BUB1B、CCNB1、CDK1、KIF11),其中CCNA2、NCAPG、BUB1在乳腺癌组织中表达水平高于正常组织,其高表达与患者总生存期的不良预后相关(P＜0.05),同时与乳腺癌分子分型及分期存在显著相关性。免疫浸润结果显示,CCNA2、NCAPG、BUB1的表达与B淋巴细胞、CD8⁺T淋巴细胞、中性粒细胞、树突状细胞等免疫细胞的浸润存在显著相关性。结论 CCNA2、NCAPG、BUB1可能是乳腺癌发生发展过程中的关键基因,其高表达与乳腺癌患者预后不良有关,可作为乳腺癌预后的潜在生物标志物。

关键词: 乳腺癌, 预后分析, 生物信息学, 差异表达基因, 生物标志物

Abstract: Objective Bioinformatics techniques were used to analyze the key genes that affect the survival of patients with breast cancer,so as to provide theoretical basis for the prognosis evaluation and targeted therapy of breast cancer. Methods The differentially expressed genes between breast cancer samples and normal breast samples were screened by TCGA database,enriched and analyzed by gene ontology(GO)and Kyoto Encyclopedia of Gene and Genome(KEGG).The protein-protein interaction network was constructed and the key genes were screened.The Kaplan-Meier method was used to find and verify the genes that might be used as potential prognostic biomarkers for breast cancer,and to explore the correlation between prognostic target genes and molecular typing and staging.The Timer database was used to analyze the correlation between prognosis-related target genes and immune cell infiltration. Results A total of 1,285 differentially expressed genes were screened,including 318 up-regulated genes and 967 down-regulated genes(|log₂FC| ≥1,P＜0.05).Differentially expressed genes were mainly enriched in cytokine-cytokine receptor interactions,PI3K-AKT signaling pathway,cAMP signaling pathway,and so on.A total of 10 key genes(AURKB,CDC20,CCNA2,NCAPG,BUB1,TOP2A,BUB1B,CCNB1,CDK1,and KIF11)were screened from the protein interaction network.Among them,the expression of CCNA2,NCAPG and BUB1 in breast cancer tissues were higher than those in normal tissues.Their high expression was associated with the poor prognosis of patient's overall survival(P＜0.05),and was significantly associated with the molecular typing and staging of breast cancer.The results of immune infiltration showed a significant correlation between the expression of CCNA2,NCAPG,BUB1 and the infiltration of immune cells such as B lymphocytes,CD8⁺T lymphocytes,neutrophils,dendritic cells and other immune cells. Conclusion CCNA2,NCAPG and BUB1 may be key genes in the occurrence and development of breast cancer,and their high expression is related to poor prognosis of breast cancer patients,which can be used as potential biomarkers for the prognosis of breast cancer.

Key words: Breast cancer, Prognostic analysis, Bioinformatics, Differentially expressed genes, Biomarker

中图分类号:

R737.9

赵诗璐, 庞达. 乳腺癌预后相关基因的生物信息学筛选与分析[J]. 实用肿瘤学杂志, 2023, 37(5): 422-428.

ZHAO Shilu, PANG Da. Bioinformatics screening and analysis of prognostic genes in breast cancer[J]. Journal of Practical Oncology, 2023, 37(5): 422-428.

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链接本文: http://journal09.magtechjournal.com/Jwk3_syzlxzz/CN/10.11904/j.issn.1002-3070.2023.05.006

http://journal09.magtechjournal.com/Jwk3_syzlxzz/CN/Y2023/V37/I5/422

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