Zhang Lan, Li Pan, Liu Enjie, Xing Chenju, Zhu Di, Zhang Jianying, Wang Weiwei, Jiang Guozhong
Department of Pathology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450052 Henan China.
State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, 450052 Henan China.
Cancer Cell Int. 2020 Aug 10;20:386. doi: 10.1186/s12935-020-01480-9. eCollection 2020.
The aim of this study was to identify prognostic long non-coding RNAs (lncRNAs) and develop a multi-lncRNA signature for suvival prediction in esophageal squamous cell carcinoma (ESCC).
The clinical and gene expression data from Gene Expression Omnibus database (GSE53624, n = 119) were obtianed as training set. A total of 98 paired ESCC tumor and normal tissues were detected by RNA sequencing and used as test set. Another 84 ESCC tissues were used for real-time quantitative PCR(qRT-PCR) and as an independent validation cohort. Survival analysis, Cox regression and Kaplan-Meier analysis were performed.
We screened a prognostic marker of ESCC from the GSE53624 dataset and named it as the five-lncRNA signature including AC007179.1, MORF4L2-AS1, RP11-488I20.9, RP13-30A9.2, RP4-735C1.6, which could classify patients into high- and low-risk groups with significantly different survival(median survival: 1.75 years vs. 4.01 years, log rank < 0.05). Then test dataset and validation dataset confirmed that the five-lncRNA signature can determine the prognosis of ESCC patients. Predictive independence of the prognostic marker was proved by multivariable Cox regression analyses in the three datasets ( < 0.05). In addition, the signature was found to be better than TNM stage in terms of prognosis.
The five-lncRNA signature could be a good prognostic biomarker for ESCC patients and has important clinical value.
本研究旨在鉴定预后长链非编码RNA（lncRNA），并开发一种多lncRNA特征用于预测食管鳞状细胞癌（ESCC）患者的生存情况。
从基因表达综合数据库（GSE53624，n = 119）获取临床和基因表达数据作为训练集。通过RNA测序检测了98对ESCC肿瘤组织和正常组织，并用作测试集。另外84例ESCC组织用于实时定量PCR（qRT-PCR），并作为独立验证队列。进行了生存分析、Cox回归分析和Kaplan-Meier分析。
我们从GSE53624数据集中筛选出一种ESCC的预后标志物，并将其命名为包含AC007179.1、MORF4L2-AS1、RP11-488I20.9、RP13-30A9.2、RP4-735C1.6的五lncRNA特征，该特征可将患者分为高风险和低风险组，其生存情况有显著差异（中位生存期：1.75年对4.01年，对数秩检验<0.05）。然后测试数据集和验证数据集证实了该五lncRNA特征可确定ESCC患者的预后。在三个数据集中通过多变量Cox回归分析证明了该预后标志物的预测独立性（<0.05）。此外，发现该特征在预后方面优于TNM分期。
五lncRNA特征可能是ESCC患者良好的预后生物标志物，具有重要的临床价值。
