BackgroundBreast cancer is one of the most common endocrine cancers among females worldwide. Distant metastasis of breast cancer is causing an increasing number of breast cancer-related deaths. However, the potential mechanisms of metastasis and candidate biomarkers remain to be further explored.ResultsThe gene expression profiles of GSE102484 were downloaded from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was used to screen for the most potent gene modules associated with the metastatic risk of breast cancer, and a total of 12 modules were identified based on the analysis. In the most significant module (R2 = 0.68), 21 network hub genes (MM > 0.90) were retained for further analyses. Next, protein-protein interaction (PPI) networks were used to further explore the biomarkers with the most interactions in gene modules. According to the PPI networks, five hub genes (TPX2, KIF2C, CDCA8, BUB1B, and CCNA2) were identified as key genes associated with breast cancer progression. Furthermore, the prognostic value and differential expression of these genes were validated based on data from The Cancer Genome Atlas (TCGA) and Kaplan-Meier (KM) Plotter. Receiver operating characteristic (ROC) curve analysis revealed that the mRNA expression levels of these five hub genes showed excellent diagnostic value for breast cancer and adjacent tissues. Moreover, these five hub genes were significantly associated with worse distant metastasis-free survival (DMFS) in the patient cohort based on KM Plotter.ConclusionFive hub genes (TPX2, KIF2C, CDCA8, BUB1B, and CCNA2) associated with the risk of distant metastasis were extracted for further research, which might be used as biomarkers to predict distant metastasis of breast cancer.

中文翻译：

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鉴定五个中心基因作为计算机模拟乳腺癌转移的监测生物标志物


背景乳腺癌是全世界女性中最常见的内分泌癌症之一。乳腺癌的远处转移正在导致越来越多的乳腺癌相关死亡。然而，潜在的转移机制和候选生物标志物仍有待进一步探索。结果GSE102484的基因表达谱从基因表达综合数据库（GEO）下载。使用加权基因共表达网络分析（WGCNA）筛选与乳腺癌转移风险相关的最有效的基因模块，并根据分析总共鉴定出12个模块。在最重要的模块（R2 = 0.68）中，保留了 21 个网络枢纽基因（MM > 0.90）用于进一步分析。接下来，利用蛋白质-蛋白质相互作用（PPI）网络进一步探索基因模块中相互作用最多的生物标志物。根据 PPI 网络，五个中心基因（TPX2、KIF2C、CDCA8、BUB1B 和 CCNA2）被确定为与乳腺癌进展相关的关键基因。此外，这些基因的预后价值和差异表达根据癌症基因组图谱 (TCGA) 和 Kaplan-Meier (KM) 绘图仪的数据进行了验证。受试者工作特征（ROC）曲线分析显示，这5个枢纽基因的mRNA表达水平对乳腺癌及癌旁组织显示出优异的诊断价值。此外，根据 KM Plotter，这 5 个中心基因与患者队列中较差的无远处转移生存期 (DMFS) 显着相关。 结论 5 个中心基因（TPX2、KIF2C、CDCA8、BUB1B 和 CCNA2）与远处转移风险相关提取用于进一步研究，可能用作预测乳腺癌远处转移的生物标志物。