Triple-negative breast cancer (TNBC) represents 10–20 % of all breast cancer (BC) cases and is characterized by poor prognosis. Given the urgent need to improve prognostication and develop specific therapies for TNBC, the identification of new molecular targets is of great importance. MicroRNA (miRNA) has been reported as a valuable and novel molecular target in the progression of TNBC. However, the expression and function of miRNAs in different tumors are heterogeneous. Herein, we first analyzed miRNA data from The Cancer Genome Atlas (TCGA) and surprisedly found that overexpressed miRNAs were associated with poor survival in all breast cancer patients, but the overexpressed miRNAs were associated with better survival in TNBC patients. Based on the heterogeneity of miRNA expression in TNBC, we conducted further analysis using univariate Cox proportional hazard regression models and identified 17 miRNAs with prognostic potential. Subsequently, a multivariate Cox model was employed to create a 3-miRNA prognostic model for predicting overall survival in TNBC patients. The diagnostic model exhibited an area under the curve (AUC) of 0.727, and multivariable Cox regression indicated that each covariate was associated with survival. These data indicate that this model is relatively accurate and robust for risk assessment, which have a certain value for clinical application. In order to explore the network behind the overexpressed miRNAs in TNBC, we established a novel network consisting of lncRNAs, miRNAs, and mRNAs through complete transcriptome data from matched samples in the TCGA database. In this network, IRS-1 appeared to be the top hub gene. Experimental results demonstrated that miR-15b-5p and miR-148a-3p effectively target IRS-1 in vitro, shedding light on the intricate regulatory mechanisms in TNBC mediated by the heterogeneous miRNAs. Besides, miR-148a-3p significantly inhibited cell migration and viability. Overall, this study may add valuable insights into the molecular landscape of TNBC based on miRNAs and have the potential to contribute to the development of targeted therapies and improved prognostic strategies of TNBC.

三阴性乳腺癌 (TNBC) 占所有乳腺癌 (BC) 病例的 10-20%，其特点是预后不良。鉴于迫切需要改善 TNBC 的预后并开发特异性疗法，识别新的分子靶点非常重要。据报道，MicroRNA (miRNA) 是 TNBC 进展中有价值的新型分子靶标。然而，不同肿瘤中miRNA的表达和功能存在差异。在此，我们首先分析了来自癌症基因组图谱（TCGA）的 miRNA 数据，并惊讶地发现过度表达的 miRNA 与所有乳腺癌患者的较差生存率相关，但过度表达的 miRNA 与 TNBC 患者的更好的生存率相关。基于TNBC中miRNA表达的异质性，我们使用单变量Cox比例风险回归模型进行了进一步分析，并鉴定了17个具有预后潜力的miRNA。随后，采用多变量 Cox 模型创建 3-miRNA 预后模型，用于预测 TNBC 患者的总生存期。诊断模型的曲线下面积 (AUC) 为 0.727，多变量 Cox 回归表明每个协变量都与生存相关。这些数据表明该模型对于风险评估相对准确且稳健，具有一定的临床应用价值。为了探索TNBC中过度表达的miRNA背后的网络，我们通过TCGA数据库中匹配样本的完整转录组数据建立了一个由lncRNA、miRNA和mRNA组成的新型网络。在这个网络中，IRS-1 似乎是顶部的枢纽基因。实验结果表明，miR-15b-5p 和 miR-148a-3p 在体外有效靶向 IRS-1，揭示了异质 miRNA 介导的 TNBC 中复杂的调控机制。此外，miR-148a-3p 显着抑制细胞迁移和活力。总体而言，这项研究可能为基于 miRNA 的 TNBC 分子格局提供有价值的见解，并有可能为靶向治疗的开发和改善 TNBC 的预后策略做出贡献。