目的：通过生物信息学方法分析与三阴性乳腺癌发生发展有关的关键miRNA。方法：从GEO数据库中找到三阴性乳腺癌miRNA数据集GSE121657，利用GEO2R鉴定差异表达的miRNA，通过starBase数据库预测出差异表达的miRNA所对应的靶基因，并对靶基因进行GO基因功能富集分析以及KEGG信号通路分析，最后建立编码蛋白互作网络并且从中筛查出关键的miRNA。结果：筛选出61个差异表达的miRNA，获得与之相对应的165个靶基因，这些靶基因主要涉及到细胞的定位、细胞周期、细胞分裂、细胞凋亡等生物学过程，参与PI3K-Akt、多巴胺能突触、Hippo、MAPK等信号通路的调控，找到关键性的调控因子hsa-miR-141-3p。结论：生物信息学分析提示hsa-miR-141-3p可能是三阴性乳腺癌重要的调控因子。 Objective: The key miRNA in triple negative breast cancer (TNBC) was analyzed by bioinformatics analysis. Method: The Gene Expression Omnibus (GEO) dataset (GSE121657) was chosen and ex-plored to identify differentially expressed miRNAs using GEO2R, and the target genes matching for the miRNAs were predicted by starBase. Enrichment analysis of Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) was performed by the DAVID online tool. The networks between miRNAs and hub genes were constructed by Cytoscape software. Results: 61 differentially expressed microRNAs were screened and 165 corresponding target genes were obtained. These target genes mainly involved in biological processes such as cell location, cell cycle, cell division, cell apoptosis, etc., and mainly participated in PI3K-Akt, dopaminergic synapse, Hippo, and MAPK sig-naling pathways. The key regulatory factors hsa-mir-141-3p have been screened by the signal pathway, insulin pathway and MAPK pathway. Conclusion: Bioinformatics analysis suggested miR-NA hsa-mir-141-3p may is a good classifier of TNBC and might play key roles in the progression of TNBC.