Department of Oncology, The First Hospital of Qinhuangdao, Qinhuangdao, Hebei, China.
Institute of basic medical sciences, Qilu Hospital, Shandong University, Jinan, Shandong, China.
Sci Rep. 2018 Jun 11;8(1):8823. doi: 10.1038/s41598-018-27307-2.
Esophageal squamous cell carcinoma (ESCC) is one of the most common types of cancer and the leading causes of cancer-related mortality worldwide, especially in Eastern Asia. Here, we downloaded the microarray data of lncRNA expression profiles of ESCC patients from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data sets and divided into training, validation and test set. The random survival forest (RSF) algorithm and Cox regression analysis were applied to identify a seven-lncRNA signature. Then the predictive ability of the seven-lncRNA signature was evaluated in the validation and test set using Kaplan-Meier test, time-dependent receiver operating characteristic (ROC) curves and dynamic area under curve (AUC). Stratified analysis and multivariate Cox regression also demonstrated the independence of the signature in prognosis prediction from other clinical factors. Besides, the predict accuracy of lncRNA signature was much better than that of tumor-node-metastasis (TNM) stage in all the three sets. LncRNA combined with TNM displayed better prognostic predict ability than either alone. The role of LINC00173 from the signature in modulating the proliferation and cell cycle of ESCC cells was also observed. These results indicated that this seven-lncRNA signature could be used as an independent prognostic biomarker for prognosis prediction of patients with ESCC.
食管鳞状细胞癌（ESCC）是最常见的癌症类型之一，也是全球癌症相关死亡的主要原因，尤其是在东亚地区。在这里，我们从基因表达综合数据库（GEO）和癌症基因组图谱（TCGA）数据集下载了 ESCC 患者的 lncRNA 表达谱的微阵列数据，并将其分为训练集、验证集和测试集。随机生存森林（RSF）算法和 Cox 回归分析被用于识别七个 lncRNA 特征。然后，通过 Kaplan-Meier 检验、时间依赖性接收者操作特征（ROC）曲线和动态曲线下面积（AUC）在验证集和测试集中评估七个 lncRNA 特征的预测能力。分层分析和多变量 Cox 回归也表明该特征在预后预测中的独立性不受其他临床因素的影响。此外，在所有三组中，lncRNA 特征的预测准确性均明显优于肿瘤-淋巴结-转移（TNM）分期。lncRNA 与 TNM 联合显示出比单独使用任何一种方法更好的预后预测能力。该特征中 LINC00173 的作用也观察到了对 ESCC 细胞增殖和细胞周期的调节。这些结果表明，该七个 lncRNA 特征可作为 ESCC 患者预后预测的独立预后生物标志物。
