Biomarker identification and trans-regulatory network analyses in esophageal adenocarcinoma and Barrett's esophagus

作     者：Jing Lv Lei Guo Ji-Han Wang Yu-Zhu Yan Jun Zhang Yang-Yang Wang Yan Yu Yun-Fei Huang He-Ping Zhao 

作者机构：Department of Clinical LaboratoryHonghui Hospital Xi’an Jiaotong University Department of Spinal Surgery Honghui Hospital Xi’an Jiaotong University Department of Gastroenterology Second Affiliated Hospital of Xi’an Jiaotong University The Tenth Research Institute of Telecommunications Technology 

出 版 物：《World Journal of Gastroenterology》 (世界胃肠病学杂志（英文版）)

年 卷 期：2019年第25卷第2期

页      面：233-244页

核心收录：

学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学] 

主　　题：Esophageal adenocarcinoma Differentially expressed genes Barrett’s esophagus Transcription factors Microarray 

摘      要：BACKGROUND Esophageal adenocarcinoma(EAC) is an aggressive disease with high mortality and an overall 5-year survival rate of less than 20%. Barrett s esophagus(BE) is the only known precursor of EAC, and patients with BE have a persistent and excessive risk of EAC over time. Individuals with BE are up to 30-125 times more likely to develop EAC than the general population. Thus, early detection of EAC and BE could significantly improve the 5-year survival rate of EAC. Due to the limitations of endoscopic surveillance and the lack of clinical risk stratification strategies, molecular biomarkers should be considered and thoroughly *** To explore the transcriptome changes in the progression from normal esophagus(NE) to BE and *** Two datasets from the Gene Expression Omnibus(GEO) in NCBI Database(https://***/geo/) were retrieved and used as a training and a test dataset separately, since NE, BE, and EAC samples were included and the sample sizes were adequate. This study identified differentially expressed genes(DEGs) using the R/Bioconductor project and constructed trans-regulatory networks based on the Transcriptional Regulatory Element Database and Cytoscape software. Enrichment of Kyoto Encyclopedia of Genes and Genomes(KEGG) and Gene Ontology(GO) terms was identified using the Database for Annotation, Visualization, and Integrated Discovery(DAVID) Bioinformatics Resources. The diagnostic potential of certain DEGs was assessed in both *** In the GSE1420 dataset, the number of up-regulated DEGs was larger than that of down-regulated DEGs when comparing EAC vs NE and BE vs NE. Among these DEGs, five differentially expressed transcription factors(DETFs) displayed the same trend in expression across all the comparison groups. Of these five DETFs,E2 F3, FOXA2, and HOXB7 were up-regulated, while PAX9 and TFAP2 C were down-regulated. Additionally, the majority of the DEGs in trans-regulatory networks were up-regulated. Th