Lv Xuemei, He Miao, Zhao Yanyun, Zhang Liwen, Zhu Wenjing, Jiang Longyang, Yan Yuanyuan, Fan Yue, Zhao Hongliang, Zhou Shuqi, Ma Heyao, Sun Yezhi, Li Xiang, Xu Hong, Wei Minjie
1Department of Pharmacology, School of Pharmacy, China Medical University, No. 77 Puhe Road, Shenyang North New Area, Shenyang, 110122 Liaoning Province People's Republic of China.
Liaoning Key Laboratory of Molecular Targeted Anti-tumour Drug Development and Evaluation, Shenyang, China.
Cancer Cell Int. 2019 Jun 28;19:172. doi: 10.1186/s12935-019-0884-0. eCollection 2019.
Triple negative breast cancer (TNBC) is a specific subtype of breast cancer with a poor prognosis due to its aggressive biological behaviour and lack of therapeutic targets. We aimed to explore some novel genes and pathways related to TNBC prognosis through bioinformatics methods as well as potential initiation and progression mechanisms.
Breast cancer mRNA data were obtained from The Cancer Genome Atlas database (TCGA). Differential expression analysis of cancer and adjacent cancer, as well as, triple negative breast cancer and non-triple negative breast cancer were performed using R software. The key genes related to the pathogenesis were identified by functional and pathway enrichment analysis and protein-protein interaction network analysis. Based on univariate and multivariate Cox proportional hazards model analyses, a gene signature was established to predict overall survival. Receiver operating characteristic curve was used to evaluate the prognostic performance of our model.
Based on mRNA expression profiling of breast cancer patients from the TCGA database, 755 differentially expressed overlapping mRNAs were detected between TNBC/non-TNBC samples and normal tissue. We found eight hub genes associated with the cell cycle pathway highly expressed in TNBC. Additionally, a novel six-gene (, , , , and ) signature from the 755 differentially expressed mRNAs was constructed and significantly associated with prognosis as an independent prognostic signature. TNBC patients with high-risk scores based on the expression of the 6-mRNAs had significantly shorter survival times compared to patients with low-risk scores (< 0.0001).
The eight hub genes we identified might be tightly correlated with TNBC pathogenesis. The 6-mRNA signature established might act as an independent biomarker with a potentially good performance in predicting overall survival.
三阴性乳腺癌（TNBC）是乳腺癌的一种特殊亚型，因其侵袭性生物学行为和缺乏治疗靶点，预后较差。我们旨在通过生物信息学方法探索一些与TNBC预后相关的新基因和通路，以及潜在的起始和进展机制。
从癌症基因组图谱数据库（TCGA）获取乳腺癌mRNA数据。使用R软件对癌组织与癌旁组织，以及三阴性乳腺癌与非三阴性乳腺癌进行差异表达分析。通过功能和通路富集分析以及蛋白质-蛋白质相互作用网络分析确定与发病机制相关的关键基因。基于单变量和多变量Cox比例风险模型分析，建立基因特征以预测总生存期。采用受试者工作特征曲线评估我们模型的预后性能。
基于TCGA数据库中乳腺癌患者的mRNA表达谱，在TNBC/非TNBC样本与正常组织之间检测到755个差异表达的重叠mRNA。我们发现8个与细胞周期通路相关的枢纽基因在TNBC中高表达。此外，从755个差异表达的mRNA中构建了一个新的六基因（、、、、和）特征，并作为独立的预后特征与预后显著相关。基于6-mRNA表达的高危评分的TNBC患者与低危评分患者相比，生存时间显著缩短（<0.0001）。
我们鉴定的8个枢纽基因可能与TNBC发病机制密切相关。建立的6-mRNA特征可能作为一种独立的生物标志物，在预测总生存期方面具有潜在的良好性能。
