Triple-negative breast cancer (TNBC) is the most aggressive and fatal sub-type of breast cancer. This study aimed to identify metastasis-associated genes that could serve as biomarkers for TNBC diagnosis and prognosis. RNA-seq data and clinical information on TNBC from the Cancer Genome Atlas were used to conduct analyses. Expression data were used to establish co-expression modules using average linkage hierarchical clustering. We used weighted gene co-expression network analysis to explore the associations between gene sets and clinical features and to identify metastasis-associated candidate biomarkers. The K-M plotter website was used to explore the association between the expression of candidate biomarkers and patient survival. In addition, receiver operating characteristic curve analysis was used to illustrate the diagnostic performance of candidate genes. The pale turquoise module was significantly associated with the occurrence of metastasis. In this module, 64 genes were identified, and its functional enrichment analysis revealed that they were mainly associated with transcriptional misregulation in cancer, microRNAs in cancer, and negative regulation of angiogenesis. Further, 4 genes, IGSF10, RUNX1T1, XIST, and TSHZ2, which were negatively associated with relapse-free survival and have seldom been reported before in TNBC, were selected. In addition, the mRNA expression levels of the 4 candidate genes were significantly lower in TNBC tumor tissues compared with healthy tissues. Based on the K-M plotter, these 4 genes were correlated with poor prognosis of TNBC. The area under the curve of IGSF10, RUNX1T1, TSHZ2, and XIST was 0.918, 0.957, 0.977, and 0.749. These findings provide new insight into TNBC metastasis. IGSF10, RUNX1T1, TSHZ2, and XIST could be used as candidate biomarkers for the diagnosis and prognosis of TNBC metastasis.

三阴性乳腺癌（TNBC）是乳腺癌中最具侵害性和致命性的亚型。这项研究旨在鉴定与转移相关的基因，这些基因可以作为TNBC诊断和预后的生物标记。来自癌症基因组图谱的RNA-seq数据和有关TNBC的临床信息用于进行分析。使用平均链接层次聚类，将表达数据用于建立共表达模块。我们使用加权基因共表达网络分析来探索基因集和临床特征之间的关联，并确定与转移相关的候选生物标志物。KM绘图仪网站用于探索候选生物标记物表达与患者生存之间的关联。此外，接收者操作特征曲线分析被用来说明候选基因的诊断性能。苍白的绿松石组件与转移的发生显着相关。在该模块中，鉴定出64个基因，其功能富集分析表明，它们主要与癌症中的转录失调，癌症中的microRNA和血管生成的负调控有关。此外，有4个基因，选择了IGSF10，RUNX1T1，XIST和TSHZ2，它们与无复发生存呈负相关，并且在TNBC中很少被报道。此外，与健康组织相比，TNBC肿瘤组织中4个候选基因的mRNA表达水平显着降低。根据KM绘图仪，这4个基因与TNBC的不良预后相关。IGSF10，RUNX1T1，TSHZ2和XIST的曲线下面积为0.918、0.957、0.977和0.749。这些发现为TNBC转移提供了新的见解。IGSF10，RUNX1T1，TSHZ2和XIST可用作TNBC转移的诊断和预后的候选生物标志物。