基于TCGA数据挖掘筛选肺鳞癌预后相关lncRNA分子标签

doi:10.3969/j.issn.1004-616x.2018.06.010

癌变·畸变·突变 ›› 2018, Vol. 30 ›› Issue (6): 468-472,478.doi: 10.3969/j.issn.1004-616x.2018.06.010

基于TCGA数据挖掘筛选肺鳞癌预后相关lncRNA分子标签

刘颖¹, 王可¹, 何杨婷¹, 肖金荣¹, 王唤卓¹, 李旸凯², 魏晟¹

1. 华中科技大学同济医学院公共卫生学院流行病与卫生统计学系环境与健康教育部重点实验室, 湖北武汉 430030;
2. 华中科技大学同济医学院附属同济医院胸外科, 湖北武汉 430030

收稿日期:2018-07-24 修回日期:2018-10-12 出版日期:2018-11-30 发布日期:2018-11-30
通讯作者: 魏晟,E-mail:weisheng@mails.tjmu.edu.cn E-mail:weisheng@mails.tjmu.edu.cn
作者简介:刘颖,E-mail:liuyingtj0222@163.com。
基金资助:
国家自然科学基金资助项目（NFSC81773520，NFSC81703552）

Prognosis-associated lncRNA signature in lung squamous cell carcinomas based on TCGA database

LIU Ying¹, WANG Ke¹, HE Yangting¹, XIAO Jinrong¹, WANG Huanzhuo¹, LI Yangkai², WEI Sheng¹

1. Key Laboratory of Ministry of Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030;
2. Department of Thoracic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China

Received:2018-07-24 Revised:2018-10-12 Online:2018-11-30 Published:2018-11-30

摘要/Abstract

摘要： 目的：通过对TCGA数据库的挖掘，筛选与肺鳞癌预后相关的lncRNA。方法：提取TCGA数据库中肺鳞癌患者临床数据以及肺鳞癌和癌旁组织中的lncRNA表达数据，采用LASSO Cox回归筛选肺鳞癌预后相关的lncRNA，并构建lncRNA分子标签。采用Cox模型研究该分子标签的表达水平对肺鳞癌患者预后的影响。结果：首先筛选出322个在癌和癌旁组织中差异表达的lncRNA。经LASSO Cox回归分析从中筛选出6个与肺鳞癌预后相关的lncRNA，分别为KTN1-AS1、FAM83A-AS1、AF131217.1、RP11-108M12.3、CTD-2555C10.3和AC068831.16。根据这6个lncRNA构建的分子标签表达水平中位数-0.09将肺鳞癌病人分为高表达组和低表达组，高表达组病人死亡风险是低表达组的2.14倍（HR=2.14，95%CI：1.50~3.04，P < 0.01）。预测模型的Harrell's C统计量为0.69（95%CI：0.64~0.75）。结论：通过对TCGA数据库的挖掘，发现KTN1-AS1、FAM83A-AS1、AF131217.1、RP11-108M12.3、CTD-2555C10.3和AC068831.16对肺鳞癌的预后有影响，且构建的lncRNA分子标签表达水平与肺鳞癌病人的预后有显著性关联。

关键词: 肺鳞癌, lncRNA分子标签, TCGA数据库, 预后, 预测模型

Abstract: OBJECTIVE: Using TCGA data mining to explore lncRNAs signature with prognosis of lung squamous cell carcinomas. METHODS: Both the clinical and the RNAseq data of lung squamous cell carcinoma patients were extracted from TCGA transcriptome database. Association between lncRNAs and prognosis of lung squamous cell carcinoma were mined using LASSO Cox regression. Then,the lncRNA signature was constructed based on the coefficient of LASSO Cox regression model. The impact of the lncRNA signature expression level on prognosis of the patients were evaluated uisng Cox regression. RESULTS: 322 differentially expressed lncRNAs were screened out in tumor and adjacent tissues. A signature was constructed by LASSO Cox regression which included six lncRNAs as KTN1-AS1,FAM83A-AS1,AF131217.1,RP11-108M12.3,CTD-2555C10.3 and AC068831.16. When the patients were divided into high and low expression groups (based on the median of signature),the risk of death was 2.14 times higher in the high expression group patients than that in low expression group (HR=2.14,95%CI 1.50-3.04) (P < 0.01). When some clinical characteristics were added into the prediction model,the Harrell's C statistic of the prediction model was elevated to 0.69 (95%CI 0.64-0.75). CONCLUSION: The IncRNA signatures:KTN1-AS1,FAM83A-AS1,AF131217.1,RP11-108M12.3,CTD-2555C10.3 and AC068831.16 were associated with prognosis of lung squamous cell carcinoma based on the TCGA database analysis. Furthermore,expression levels of the lncRNA signature was predictive of the prognosis.

Key words: lung squamous cell carcinoma, lncRNA signature, TCGA database, prognosis, prediction model

中图分类号:

R734.2

刘颖, 王可, 何杨婷, 肖金荣, 王唤卓, 李旸凯, 魏晟. 基于TCGA数据挖掘筛选肺鳞癌预后相关lncRNA分子标签[J]. 癌变·畸变·突变, 2018, 30(6): 468-472,478.

LIU Ying, WANG Ke, HE Yangting, XIAO Jinrong, WANG Huanzhuo, LI Yangkai, WEI Sheng. Prognosis-associated lncRNA signature in lung squamous cell carcinomas based on TCGA database[J]. Carcinogenesis, Teratogenesis & Mutagenesis, 2018, 30(6): 468-472,478.

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基于TCGA数据挖掘筛选肺鳞癌预后相关lncRNA分子标签

Prognosis-associated lncRNA signature in lung squamous cell carcinomas based on TCGA database

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