Identification of a novel gene expression signature associated with overall survival in patients with lung adenocarcinoma: A comprehensive analysis based on TCGA and GEO databases

Abstract

Objectives

Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Understanding the molecular mechanisms underlying tumor progression is of clinical significance. This study aimed to identify novel molecular markers associated with LUAD prognosis.

Materials and Methods

RNA sequencing data from the Cancer Genome Atlas (TCGA) database of LUAD tumors and paired normal tissues, and microarray data from the Gene Expression Omnibus (GEO) database were obtained. In the TCGA dataset, differentially expressed (DE) genes were identified by comparing gene expression between early-stage tumors and normal tissue, as well as between advanced-stage and early-stage tumors. A risk score was developed using a weighted linear combination of individual dysregulated protein-coding genes that was associated with overall survival (OS). The prognostic value of the risk score was evaluated using Kaplan-Meier and multivariate Cox analysis. The gene signature was further validated using independent datasets from GEO.

Results

Among the 68 identified DE genes, 19 were individually associated with OS in univariate analyses. A risk score was constructed for each patient based on the coefficients in multivariate Cox model and normalized expression levels of these 19 genes. LUAD patients with a low risk score had a significantly better survival than those with a high risk score (log-rank P < 0.0001). After adjusting for age, sex, clinical stage, smoking history, and treatments, the patients with a low risk score had a 81 % decreased risk for death, compared to those with a high risk score (hazard ratio 0.19, 95 % confidence interval 0.097−0.36). The significant association of the risk score with OS in LUAD patients was further validated in three independent GEO datasets.

Conclusion

A novel 19-gene prognostic signature based on gene expression was identified in LUAD patients. The findings further improve the understanding of LUAD prognostication and have the potential to facilitate risk-stratified disease management.