OncoTargets and Therapy (Dec 2020)
Identifying an Eight-Gene Signature to Optimize Overall Survival Prediction of Esophageal Adenocarcinoma Using Bioinformatics Analysis of ceRNA Network
Abstract
Yuanyong Wang,1,* Naixin Liang,2,* Zhiqiang Xue,1 Xinying Xue3,4 1Department of Thoracic Surgery, Chinese PLA General Hospital, Beijing, People’s Republic of China; 2Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, People’s Republic of China; 3Department of Respiratory Disease, Beijing Shijitan Hospital, Capital Medical University, Beijing, People’s Republic of China; 4Department of Respiratory Disease, School of Clinical Medicine, Weifang Medical University, Weifang, Shandong, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xinying XueDepartment of Respiratory Disease, Beijing Shijitan Hospital, Capital Medical University, Beijing, People’s Republic of ChinaEmail [email protected] XueDepartment of Thoracic Surgery, Chinese PLA General Hospital, Beijing, People’s Republic of ChinaEmail [email protected] and Aims: Esophageal adenocarcinoma (EAC) patients usually have a poor prognosis without early diagnosis. In this study, we aimed to identify a novel signature to improve the prediction of overall survival (OS) in EAC.Methods: Eighty-one and 68 samples from The Cancer Genome Atlas (TCGA) and GSE19417 dataset were included for discovery and survival validation, respectively. In the TCGA cohort, a total of 1,811 DEmRNAs, 1,096 DElncRNAs, and 31 DEmiRNAs were identified between EAC and normal esophagus tissues. A mRNA–miRNA–lncRNA ceRNA network of EAC was established, which consisted of 94 DEmRNAs, 13 DEmiRNAs, and 46 DElncRNAs.Results: In this study, we identified eight genes (UBE2B, LAMP2, B3GNT2, TAF9B, EFNA1, PHF8, PIGA, and NEURL1) which were related to survival in EAC. The independent external microarray data from the Gene Expression Omnibus (GEO) was used to validate these candidate genes. The prognostic ability of the signature was also validated in EAC patients in our hospital. Patients assigned to the high-risk group had a poor overall survival rate compared with the low-risk.Conclusion: The current study provides novel insights into the mRNA-related ceRNA network in EAC and the eight mRNA biomarkers may be independent prognostic signatures in predicting the survival of EAC patients.Keywords: esophageal adenocarcinoma, signature, competing endogenous RNA, overall survival, TCGA
