A ten-long non-coding RNA signature for predicting prognosis of patients with cervical cancer

PURPOSE: The aim of the present study was to construct a novel long non-coding RNA (lncRNA) signature to predict the prognosis of patients with cervical cancer (CC). MATERIALS AND METHODS: We downloaded lncRNA expression profiles and clinical characteristics from The Cancer Genome Atlas database and randomly divided them into a training dataset (n=200) and a testing dataset (n=87). Using a Cox-based iterative sure independence screening procedure combined with a resampling technique, a lncRNA signature was calculated from prognostic lncRNAs in the training dataset and was independently verified in the testing and the entire datasets. In addition, multivariate Cox regression and further stratified analyses were performed, taking into consideration the lncRNA signature as well as other clinical characteristics. Finally, we predicted the underlying functional effects of the prognostic lncRNAs by using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. RESULTS: We constructed a promising ten-lncRNA signature that was significantly associated with the prognosis of CC on the basis of a risk score formula. The risk score was used to classify patients into high-risk and low-risk groups with different overall survival in the training dataset, and was confirmed in the testing and entire datasets. Compared with the clinical factors, the ten-lncRNA signature was found to be an independent prognostic indicator and displayed robust prognostic performance. A functional analysis indicated that these ten lncRNAs were enriched in immune response, cell adhesion molecules and nuclear factor kappa B signaling. CONCLUSION: Our results demonstrated that this ten-lncRNA signature may serve as a prognostic biomarker for patients with CC.