Identification of a RNA-Seq Based Prognostic Signature with Seven Immune-Related lncRNAs for Lung Adenocarcinoma.

Abstract

BACKGROUND\nLung adenocarcinoma (LUAD) is still a worldwide challenge. Accumulated evidence demonstrates that the superiority of immune-related long noncoding RNAs (lncRNAs) are closely connected with tumorigenesis and prognosis of cancer. However, no detailed studies have been conducted to present a reliable signature for predicting prognosis in LUAD patients from the perspective of tumor immunology. The aim of this study was to con-struct a risk score model based on the signature of the group of seven immune-related lncRNAs to predict the prognosis of patients with LUAD.\n\n\nMETHODS\nWe performed a genome-wide analysis of expression profiles in 522 LUAD patients from The Cancer Genome Atlas (TCGA) project to explore the prognostic ability of immune-related lncRNAs. By using Kaplan-Meier analysis, univariate/multivariate Cox regression, receiver operating characteristic curve (ROC), and principal components analysis (PCA), a risk score model was constructed based on the signature of the group of seven immune-related lncRNAs to predict the prognosis of patients with LUAD.\n\n\nRESULTS\nUsing survival analysis and Cox regression model, we identified a set of seven lncRNAs (LINC00941, FAM83A-AS1, AC026355.1, AC068338.3, AC010980.2, AL365181.2, and AC079949.2) demonstrating an ability to stratify patients into high and low risk groups with significantly different survival outcomes. Moreover, the signature was identified as an independent prognostic factor and significantly associated with the overall survival (OS) of LUAD. The area under curve (AUC) of a ROC curve for the signature of the group of seven immune-related lncRNAs in predicting OS was 0.757. In addition, low-risk and high-risk groups displayed different immune statuses based on PCA.\n\n\nCONCLUSIONS\nThis study suggested a promising seven prognostic immune-related lncRNAs risk scoring system and may provide new information for immunological treatment in LUAD.