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

Abstract

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

CLC Number:

R737.9

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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URL: http://journal09.magtechjournal.com/Jwk3_syzlxzz/EN/10.11904/j.issn.1002-3070.2023.05.006

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

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Bioinformatics screening and analysis of prognostic genes in breast cancer

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