Long-chain noncoding ribonucleic acids affect the survival and prognosis of patients with esophageal adenocarcinoma through the autophagy pathway: construction of a prognostic model.

Objective Autophagy-related long-chain noncoding ribonucleic acids play a vital role in the development of esophageal adenocarcinoma. This study aimed to construct a prognostic model of autophagy-related long-chain noncoding ribonucleic acids and identify potential therapeutical targets for esophageal adenocarcinoma. Methods We downloaded 261 long-chain noncoding RNA transcript samples and clinical data of 87 esophageal adenocarcinoma patients from the Cancer Genome Atlas and 307 autophagy-related genes from www.autophagy.com. We performed Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analyses and Gene Set Enrichment Analysis to determine risk characteristics and bioinformatics functions of signal transduction pathways. Univariate and multivariate Cox regression analyses were used to determine the correlation between autophagy-related long-chain noncoding ribonucleic acids and independent risk factors. The receiver operating characteristic analysis was used to evaluate the feasibility of the prognostic model. Finally, we performed survival analysis, risk analysis and independent prognostic analysis to verify the prognostic model of esophageal adenocarcinoma. Results We identified 22 autophagic long-chain noncoding ribonucleic acids that were highly correlated with the overall survival of esophageal adenocarcinoma patients. The areas under the receiver operating characteristic curve (0.941) and the calibration curve were significantly similar. Moreover, univariate and multivariate Cox regression analyses indicated that autophagy-related long-chain noncoding ribonucleic acids were independent predictors of esophageal adenocarcinoma. Conclusion We found that autophagy-related long-chain noncoding ribonucleic acids might affect tumor development and prognosis in esophageal adenocarcinoma patients. The findings indicate that the prognostic model of esophageal adenocarcinoma has potential therapeutic applications in patients with esophageal adenocarcinoma.