Identification of a multidimensional transcriptome prognostic signature for lung adenocarcinoma

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 w...

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Bibliographic Details
Published in:Journal of clinical laboratory analysis 2019-11, Vol.33 (9), p.e22990-n/a
Main Authors: Ye, Jing, Liu, Hui, Xu, Zhi‐Li, Zheng, Ling, Liu, Rong‐Yu
Format: Article
Language:English
Subjects:
Adenocarcinoma of Lung - genetics
Adenocarcinoma of Lung - pathology
Databases, Genetic
Female
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Humans
long non‐coding RNA
lung adenocarcinoma
Male
Middle Aged
Multivariate Analysis
Neoplasm Staging
Open Reading Frames - genetics
Prognosis
prognostic
Proportional Hazards Models
protein‐coding gene
Risk Factors
RNA, Long Noncoding - genetics
RNA, Long Noncoding - metabolism
ROC Curve
signature
Survival Analysis
Transcriptome - genetics
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Summary: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 
ISSN:0887-8013
1098-2825
DOI:10.1002/jcla.22990