Open AccessIdentification of a multidimensional transcriptome prognostic signature for lung adenocarcinoma
Author(s) -
Ye Jing,
Liu Hui,
Xu ZhiLi,
Zheng Ling,
Liu RongYu
Publication year - 2019
Publication title -
journal of clinical laboratory analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.536
H-Index - 50
eISSN - 1098-2825
pISSN - 0887-8013
DOI - 10.1002/jcla.22990
Subject(s) - proportional hazards model , transcriptome , adenocarcinoma , receiver operating characteristic , oncology , survival analysis , log rank test , lung cancer , coding (social sciences) , medicine , computational biology , biology , bioinformatics , gene , cancer , gene expression , statistics , genetics , mathematics
Background Lung adenocarcinoma (LUAD) is one of the leading contributors to cancer‐related deaths worldwide. The objective of the current study is to identify a multidimensional transcriptome prognostic signature by combining protein‐coding gene (PCG) with long non‐coding RNA (lncRNA) for patients with LUAD. Methods We obtained LUAD PCG and lncRNA expression profile data from three datasets in the Gene Expression Omnibus database and conducted survival analyzes for these individuals. Results We established a predictive model comprising the three PCGs (NHLRC2, PLIN5, GNAI3), and one lncRNA ( AC087521.1 ). This model segregated patients with LUAD into low‐ and high‐risk groups based on significant differences in survival in the training dataset (GSE31210, n = 226, log‐rank test P < .001). Risk stratification of the model was subsequently validated in other two test datasets (GSE37745, n = 106, log‐rank test P < .001; GSE30219, n = 85, log‐rank test P = .006). Time‐dependent receiver operating characteristic (timeROC) curve analysis demonstrated that the model correlated strongly with disease progression and outperformed pathological stage in terms of prognostic ability. Cox proportional hazards regression analysis revealed that the signature could serve as an independent predictor of clinical outcomes in patients with LUAD. Conclusions We describe a novel multidimensional transcriptome signature that can predict survival probabilities in patients with LUAD.