通过综合生物信息学分析鉴定三阴性乳腺癌中的枢纽基因
Identification of hub genes in triple-negative breast cancer by integrated bioinformatics analysis.
作者信息
Wei Li-Min, Li Xin-Yang, Wang Zi-Ming, Wang Yu-Kun, Yao Ge, Fan Jia-Hao, Wang Xin-Shuai
机构信息
Department of Cancer Institute, The First Affiliated Hospital and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China.
出版信息
Gland Surg. 2021 Feb;10(2):799-806. doi: 10.21037/gs-21-17.
BACKGROUND
Triple negative breast cancer (TNBC) is usually aggressive and accompanied by a poor prognosis. The molecular biological mechanism of TNBC pathogenesis is still unclear, and requires more detailed research. The aim of this study was to screen and verify potential biomarkers of TNBC, and provide new clues for the treatment and diagnosis of TNBC.
METHODS
In this work, GSE76250 was downloaded from the Gene Expression Omnibus (GEO) database and included 165 TNBC samples and 33 paired normal breast tissues. The R software and its related software package were used for data processing and analysis. Compared with normal tissues, genes with a false discovery rate (FDR) <0.01 and log fold change (logFC) ≥1 or ≤-1 were identified as differentially expressed genes (DEGs) by limma package. Survival prognoses were analyzed by Kaplan-Meier plotter database.
RESULTS
In total, 160 up-regulated and 180 down-regulated genes were identified. The biological mechanism of enrichment analysis presented that DEGs were significantly enriched in chromosome segregation, extracellular matrix, and extracellular matrix structural constituent, among others. A total of 8 hub genes ( and ) were identified by the protein-protein interaction network (PPIN) and Cytoscape software. Survival prognosis of these hub genes showed that they were negatively correlated with overall survival.
CONCLUSIONS
The 8 hub genes and pathways that were identified might be involved in tumorigenesis and become new candidate biomarkers for TNBC treatment.
背景
三阴性乳腺癌（TNBC）通常侵袭性强且预后较差。TNBC发病的分子生物学机制仍不清楚，需要更详细的研究。本研究的目的是筛选和验证TNBC的潜在生物标志物，并为TNBC的治疗和诊断提供新线索。
方法
在本研究中，从基因表达综合数据库（GEO）下载GSE76250数据集，其中包括165例TNBC样本和33对配对的正常乳腺组织。使用R软件及其相关软件包进行数据处理和分析。通过limma软件包，将错误发现率（FDR）<0.01且log2倍变化（logFC）≥1或≤-1的基因鉴定为与正常组织相比的差异表达基因（DEGs）。通过Kaplan-Meier绘图数据库分析生存预后。
结果
共鉴定出160个上调基因和180个下调基因。富集分析的生物学机制表明，DEGs在染色体分离、细胞外基质和细胞外基质结构成分等方面显著富集。通过蛋白质-蛋白质相互作用网络（PPIN）和Cytoscape软件共鉴定出8个枢纽基因（和）。这些枢纽基因的生存预后表明它们与总生存期呈负相关。
结论
鉴定出的8个枢纽基因和通路可能参与肿瘤发生，并成为TNBC治疗的新候选生物标志物。
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