A three-lncRNA signature derived from the Atlas of ncRNA in cancer (TANRIC) database predicts the survival of patients with head and neck squamous cell carcinoma

Objective: Long non-coding RNAs (lncRNAs) have important biological functions and can be used as prognostic biomarkers in cancer. To identify a lncRNA prognostic signature for head and neck squamous cell carcinoma (HNSCC). Method: We analysed RNA-seq data derived from the TANRIC database to identify a lncRNA prognostic signature model using the orthogonal partial least squares discrimination analysis (OPLS-DA) and 1.5-fold expression change criterion methods. The prognosis prediction model based on the lncRNA signatures and clinical parameters were evaluated using the 5-fold cross validation method. Results: A total of 84 out of 3199 lncRNAs were significantly associated with the survival of patients with HNSCC (log-rank test P < 0.01). Using the OPLS-DA and 1.5-fold change selection criterion, 5 lncRNAs (KTN1-AS1, LINC00460, GUSBP11, LINC00923 and RP5-894A10.6) were further selected. The prediction power of each combination of the 5 lncRNAs was evaluated through the receiver operating characteristic (ROC) curve and a three-lncRNA panel (KTN1-AS1, LINC00460 and RP5-894A10.6) achieved the highest prognostic prediction power (AUC 0.68, 95% CI 0.60-0.76, P < 0.0001) in the cohort. The patients were categorized into high- and low-risk groups based on their three-lncRNA profiles. Patients with high-risk scores had worse overall survival than those with low risk scores in the cohort (log-rank test P = 0.0003). Multivariable Cox regression analyses showed that the lncRNA signature and tumour grade were independent prognostic factors for patients with HNSCC. Conclusions: Our findings showed that the three-lncRNA signature might be a novel biomarker for the accurate prognosis prediction of patients with HNSCC. (C) 2016 Elsevier Ltd. All rights reserved.