Background: Lung squamous cell carcinoma (LUSC) is malignant disease with poor therapeutic response and unfavourable prognosis.
Objective: This study aims to develop a long non-coding RNA (lncRNA) signature for survival prediction in patients with LUSC.
Methods: We obtained lncRNA expression profiles of 493 LUSC cases from The Cancer Genome Atlas, and randomly divided the samples into a training set (n= 296) and a testing set (n= 197). Univariate Cox regression and random survival forest algorithm were performed to select optimum survival-related lncRNAs.
Results: A lncRNA-focused risk score model was then constructed for prognosis prediction in the training set and further validated in the testing set and the entire set. Finally, bioinformatics analysis was carried out to explore the potential signaling pathways associated with the prognostic lncRNAs. A set of 9 lncRNAs were found to be strongly correlated with overall survival of LUSC patients. These 9 lncRNAs were integrated into a prognostic signature, which could separate patients into high- and low-risk groups with significantly different survival times in the training set (median: 30.5 vs. 80.5 months, log-rank P< 0.001). This signature was also confirmed in the testing set and the entire set. Besides, the prognostic value of the 9-lncRNA signature was independent of clinical features and maintained stable in stratified analyses. Functional enrichment study suggested that the 9 lncRNAs may be mainly involved in metabolism-related pathways, phosphatidylinositol signaling system, p53 signaling pathway, and notch signaling pathway.
Conclusions: Our study demonstrated the potential clinical implication of the 9-lncRNA signature for survival prediction of LUSC patients.
Keywords: Biomarker; long non-coding RNA; lung squamous cell carcinoma; prognosis.