Comprehensive analysis of novel three-long noncoding RNA signatures as a diagnostic and prognostic biomarkers of human triple-negative breast cancer
Comprehensive analysis of novel three-long noncoding RNA signatures as a diagnostic and prognostic biomarkers of human triple-negative breast cancer
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DOI：
10.1002/jcb.27584
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发表时间：
2019-03-01
影响因子：
4
通讯作者：
Liu, Ning
中科院分区：
文献类型：
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作者：
Fan, Chun-Ni;Ma, Lei;Liu, Ning
目前，传统的预后预测因子（肿瘤大小、淋巴结状态、孕激素受体 [PR]、雌激素受体 [ER] 或人表皮生长因子受体 2 [HER2]）不足以精确预测三阴性乳腺癌 (TNBC) 的生存率。据观察，长非编码 RNA (lncRNA) 在癌症（包括 TNBC）中发挥关键功能。然而，基于序列数据系统追踪基于表达的 lncRNA 生物标志物以预测 TNBC 的预后尚未得到研究。为了确定是否存在可以区分 TNBC 与邻近正常组织或 nTNBC 的生物标志物，我们对癌症基因组图谱数据库中 1097 个 BC 样本的 lncRNA 表达谱和临床数据进行了全面分析。在正常和TNBC样本中总共提取了1510个差异表达的lncRNA。同样，在 nTNBC 和 TNBC 样本之间检测到 672 个差异表达的 lncRNA。受试者工作特征曲线分析表明，三个上调的lncRNA（AC091043.1、AP000924.1和FOXCUT）可能对预测训练和验证集中TNBC的存在具有很强的诊断价值（曲线下面积（AUC>0.85）。Kaplan-Meier分析表明，其他三个lncRNA（AC010343.3、AL354793.1和FGF10-AS1）与 TNBC 患者的预后相关（P < 0.05），我们使用三种与总生存期 (OS) 相关的 lncRNA 建立了三变量 Cox 回归分析，表明三 lncRNA 标记是独立于其他临床变量的预后因素 (P < 0.01)，可用于预测 TNBC 患者的 OS，可用于将患者分为高风险或低风险亚组。为TNBC的临床诊断和预后评估提供有效的特征。
Currently, traditional predictors of prognosis (tumor size, nodal status, progesterone receptor [PR], estrogen receptor [ER], or human epidermal growth factor receptor-2 [HER2]) are insufficient for precise survival prediction for triple-negative breast cancer (TNBC). Long noncoding RNAs (lncRNAs) have been observed to exert critical functions in cancer, including in TNBC. Nevertheless, systematically tracking expression-based lncRNA biomarkers based on the sequence data for the prediction of prognosis in TNBC has not yet been investigated. To ascertain whether biomarkers exist that can distinguish TNBC from adjacent normal tissue or nTNBC, we implemented a comprehensive analysis of lncRNA expression profiles and clinical data of 1097 BC samples from The Cancer Genome Atlas database. A total of 1510 differentially expressed lncRNAs in normal and TNBC samples were extracted. Similarly, 672 differentially expressed lncRNAs between nTNBC and TNBC samples were detected. The receiver operating characteristic curve analysis indicated that three upregulated lncRNAs (AC091043.1, AP000924.1, and FOXCUT) may be of strong diagnostic value for predicting the existence of TNBC in the training and validation sets (area under the curve (AUC > 0.85). Kaplan-Meier analysis demonstrated that the other three lncRNAs (AC010343.3, AL354793.1, and FGF10-AS1) were associated with the prognosis of TNBC patients (P < 0.05). We used the three overall survival (OS)-related lncRNAs to establish a three-lncRNA signature. Multivariate Cox regression analysis suggested that the three-lncRNA signature was a prognostic factor independent of other clinical variables (P < 0.01) for predicting OS in TNBC patients that could be utilized to classify patients into high- or low-risk subgroups. Our results might provide efficient signatures for clinical diagnosis and prognostic evaluation of TNBC.