Sui Jing, Xu Si-Yi, Han Jiali, Yang Song-Ru, Li Cheng-Yun, Yin Li-Hong, Pu Yue-Pu, Liang Ge-Yu
Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, P.R. China.
Department of Epidemiology, Richard M. Fairbanks School of Public Health, Melvin and Bren Simon Cancer Center, Indiana University, Indianapolis, IN, USA.
Oncotarget. 2017 Jul 27;8(39):65997-66018. doi: 10.18632/oncotarget.19627. eCollection 2017 Sep 12.
Accumulating evidence shows the important role of long non-coding RNAs (lncRNAs) in competing endogenous RNA (ceRNA) networks for predicting survival in tumor patients. However, prognostic biomarkers for lung squamous cell carcinoma (LUSC) are still lacking. The objective of this study is to identify a lncRNA signature for evaluation of overall survival (OS) in 474 LUSC patients from The Cancer Genome Atlas (TCGA) database. A total of 474 RNA sequencing profiles in LUSC patients with clinical data were obtained, providing a large sample of RNA sequencing data, and 83 LUSC-specific lncRNAs, 26 miRNAs, and 85 mRNAs were identified to construct the ceRNA network (fold change>2, P<0.05). Among these above 83 LUSC-specific lncRNAs, 22 were assessed as closely related to OS in LUSC patients using a univariate Cox proportional regression model. Meanwhile, two (FMO6P and PRR26) of the above 22 OS-related lncRNAs were identified using a multivariate Cox regression model to construct a risk score as an independent indicator of the prognostic value of the lncRNA signature in LUSC patients. LUSC patients with low-risk scores were more positively correlated with OS (P<0.001). The present study provides a deeper understanding of the lncRNA-related ceRNA network in LUSC and suggests that the two-lncRNA signature could serve as an independent biomarker for prognosis of LUSC.
越来越多的证据表明，长链非编码RNA（lncRNA）在竞争性内源性RNA（ceRNA）网络中对于预测肿瘤患者的生存具有重要作用。然而，肺鳞状细胞癌（LUSC）的预后生物标志物仍然缺乏。本研究的目的是从癌症基因组图谱（TCGA）数据库中识别出一种lncRNA特征，用于评估474例LUSC患者的总生存期（OS）。共获得了474例具有临床数据的LUSC患者的RNA测序谱，提供了大量的RNA测序数据样本，并鉴定出83种LUSC特异性lncRNA、26种miRNA和85种mRNA以构建ceRNA网络（倍数变化>2，P<0.05）。在上述83种LUSC特异性lncRNA中，使用单变量Cox比例回归模型评估了22种与LUSC患者的OS密切相关。同时，使用多变量Cox回归模型从上述22种与OS相关的lncRNA中鉴定出两种（FMO6P和PRR26），构建风险评分作为lncRNA特征在LUSC患者中预后价值的独立指标。低风险评分的LUSC患者与OS的正相关性更强（P<0.001）。本研究提供了对LUSC中lncRNA相关ceRNA网络的更深入理解，并表明双lncRNA特征可作为LUSC预后的独立生物标志物。
