Identification of a 4-lncRNA Signature Predicting Prognosis of Patients with Non-Small Cell Lung Cancer: a Multicenter Study in China

Abstract Background: Previous findings have indicated that the tumor, nodes, and metastases (TNM) staging system is sub-optimal in terms of predicting survival outcomes in patients with non-small lung carcinoma (NSCLC).Thus, the aims to identify a long non-coding RNA (lncRNA) signature for predicting survival in patients with NSCLC and to provide additional prognostic information in combination with the TNM system.Methods: Patients with NSCLC were recruited from a hospital and divided into a discovery cohort (n=194) and validation cohort (n=172), and detected using a custom lncRNA microarray. Lung tissues obtained from patients at a different hospital (n = 73, independent validation cohort) were examined via qRT-PCR. Differentially expressed lncRNAs were determined with the Significance Analysis of Microarrays program and used to identify those associated with survival in the discovery cohort. These prognostic lncRNAs were employed to construct a prognostic signature with a risk-score method. Then, the utility of the prognostic signature was confirmed using the validation cohort and the independent cohort. Results: In the discovery cohort, we identified 305 lncRNAs that were differentially expressed between the NSCLC tissues and matched, adjacent normal lung tissues, of which 15 are associated with survival; a 4-lncRNA prognostic signature was identified from the 15 survival lncRNAs, which was significantly correlated with survivals of NSCLC patients. This signature was further validated in the validation cohort and independent cohort. Moreover, multivariate Cox analysis demonstrates that the 4-LncRNA signature is an independent survival predictor. Then we established a new risk-score model by combining 4-lncRNA signature and TNM stage. The receiver operating characteristics (ROC) curve indicates that the prognostic value of the combined model is significantly higher than that of the TNM stage alone, in all the cohorts. Conclusions: In this study, we identified a 4-lncRNA signature that can potentially serve as a powerful prognosis biomarker and can provide additional survival information to the traditional TNM staging system.