Development of a model to predict the prognosis of esophageal carcinoma based on autophagy-related genes

Abstract

Aim: To identify a potential prognostic signature of esophageal carcinoma based on autophagy-related genes (ARGs). Methods: RNA sequencing and clinical data were downloaded from the Cancer Genome Atlas. Significantly different ARGs were identified by Wilcoxon signed-rank test. A prognostic model was established employing Cox regression analysis. The model was evaluated by receiver operating characteristic and Kaplan–Meier curve. Results: A total of 28 significantly different ARGs were identified. Seven ARGs were screened to construct the prognostic model. The efficacy of the model was verified. A nomogram also validated the role of risk score in predicting prognosis. Enrichment analyses showed the possible underlying mechanisms. Conclusion: The seven-ARGs prognostic model was validated to be promising for predicting the prognosis of patients with esophageal carcinoma.