Prognostic significance of autophagy-related genes within esophageal carcinoma

• Published in: BMC cancer Vol. 20; no. 1; p. 797
• Main Authors: Chen, Chongxiang, Chen, Siliang, Cao, Huijiao, Wang, Jiaojiao, Wen, Tianmeng, Hu, Xiaochun, Li, Huan
• Format: Journal Article
• Language: English
• Published: England BioMed Central 24.08.2020; BMC
• Subjects: Autophagy; Autophagy - genetics; Biomarkers, Tumor - genetics; Cancer therapies; Carcinoma - diagnosis; Carcinoma - genetics; Carcinoma - mortality; Carcinoma - pathology; Datasets as Topic; Esophageal cancer; Esophageal carcinoma; Esophageal Neoplasms - diagnosis; Esophageal Neoplasms - genetics; Esophageal Neoplasms - mortality; Esophageal Neoplasms - pathology; Esophagus; Esophagus - pathology; Feasibility Studies; Female; Gender; Gene expression; Gene Expression Profiling; Genomes; Homeostasis; Humans; Kaplan-Meier Estimate; Male; Medical prognosis; Neoplasm Staging; Oligonucleotide Array Sequence Analysis; Online data bases; Patients; Phagocytosis; Principal components analysis; Prognosis; Prognostic; Regression analysis; Risk Assessment - methods; ROC Curve; Survival Rate; Esophageal carcinoma; Autophagy; Prognostic
• ISSN: 1471-2407; 1471-2407
• DOI: 10.1186/s12885-020-07303-4

Several works suggest the importance of autophagy during esophageal carcinoma development. The aim of the study is to construct a scoring system according to the expression profiles of major autophagy-related genes (ARGs) among esophageal carcinoma cases. The Cancer Genome Atlas was employed to obtain the esophageal carcinoma data. Thereafter, the online database Oncolnc ( http://www.oncolnc.org/ ) was employed to verify the accuracy of our results. According to our results, the included ARGs were related to overall survival (OS). We detected the expression patterns of ARG within esophageal carcinoma and normal esophageal tissues. In addition, we identified the autophagy related gene set, including 14 genes displaying remarkable significance in predicting the esophageal carcinoma prognosis. The cox regression results showed that, 7 ARGs (including TBK1, ATG5, HSP90AB1, VAMP7, DNAJB1, GABARAPL2, and MAP2K7) were screened to calculate the ARGs scores. Typically, patients with higher ARGs scores were associated with poorer OS. Moreover, the receiver operating characteristic (ROC) curve analysis suggested that, ARGs accurately distinguished the healthy people from esophageal carcinoma patients, with the area under curve (AUC) value of > 0.6. A scoring system is constructed in this study based on the main ARGs, which accurately predicts the outcomes for esophageal carcinoma.