Development and validation of a three-long noncoding RNA signature for predicting prognosis of patients with gastric cancer

BACKGROUND: Gastric cancer (GC) is one of the most frequently diagnosed gastrointestinal cancers throughout the world. Novel prognostic biomarkers are required to predict the prognosis of GC. AIM: To identify a multi-long noncoding RNA (lncRNA) prognostic model for GC. METHODS: Transcriptome data and clinical data were downloaded from The Cancer Genome Atlas. COX and least absolute shrinkage and selection operator regression analyses were performed to screen for prognosis associated lncRNAs. Receiver operating characteristic curve and Kaplan-Meier survival analyses were applied to evaluate the effectiveness of the model. RESULTS: The prediction model was established based on the expression of AC007991.4, AC079385.3, and AL109615.2 Based on the model, GC patients were divided into “high risk” and “low risk” groups to compare the differences in survival. The model was re-evaluated with the clinical data of our center. CONCLUSION: The 3-lncRNA combination model is an independent prognostic factor for GC.