Identification of miRNAs and genes for predicting Barrett's esophagus progressing to esophageal adenocarcinoma using miRNA-mRNA integrated analysis
| Autor: | Li-Hong Luo, Cheng-Jiao Yao, Peimin Feng, Yilin Li, Xiaowu Zhong, Qin Xiong, Fengjiao Xie |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Esophageal Neoplasms
Microarrays Biochemistry CDH1 Breast Tumors Medicine and Health Sciences Gene Regulatory Networks Pathology and laboratory medicine Regulation of gene expression Multidisciplinary Nasopharyngeal Carcinoma biology CTNND1 Medical microbiology Prognosis Nucleic acids Gene Expression Regulation Neoplastic Bioassays and Physiological Analysis Oncology Viruses embryonic structures Disease Progression Medicine DNA microarray Pathogens ITGA6 Research Article Cell Binding Herpesviruses Cell Physiology Science Computational biology Adenocarcinoma Research and Analysis Methods Microbiology Barrett Esophagus microRNA Gastrointestinal Tumors Breast Cancer medicine Genetics Epstein-Barr virus Humans Non-coding RNA Gene Natural antisense transcripts Biology and life sciences Carcinoma Organisms Viral pathogens Cancers and Neoplasms Cell Biology medicine.disease Gene regulation Microbial pathogens body regions MicroRNAs Gastric Cancer Barrett's esophagus biology.protein RNA Gene expression DNA viruses Transcriptome |
| Zdroj: | PLoS ONE, Vol 16, Iss 11, p e0260353 (2021) PLoS ONE |
| ISSN: | 1932-6203 |
| Popis: | Barrett’s esophagus (BE) is defined as any metaplastic columnar epithelium in the distal esophagus, which predisposes to esophageal adenocarcinoma (EAC). Yet, the mechanism through which BE develops to EAC still remain unclear. Moreover, the miRNA-mRNA regulatory network in distinguishing BE from EAC still remains poorly understood. To identify differentially expressed miRNAs (DEMs) and genes (DEGs) between EAC and BE from tissue samples, gene expression microarray datasets GSE13898, GSE26886, GSE1420 and miRNA microarray datasets GSE16456, GSE20099 were downloaded from Gene Expression Omnibus (GEO) database. GEO2R was used to screen the DEMs and DEGs. Pathway and functional enrichment analysis were performed by DAVID database. The protein–protein interaction (PPI) network was constructed by STRING and been visualized by Cytoscape software. Finnal, survival analysis was performed basing TCGA database. A total of 21 DEMs were identified. The enriched functions and pathways analysis inclued Epstein-Barr virus infection, herpesvirus infection and TRP channels. GART, TNFSF11, GTSE1, NEK2, ICAM1, PSMD12, CTNNB1, CDH1, PSEN1, IL1B, CTNND1, JAG1, CDH17, ITCH, CALM1 and ITGA6 were considered as the hub-genes. Hsa-miR-143 and hsa-miR-133b were the highest connectivity target gene. JAG1 was predicted as the largest number of target miRNAs. The expression of hsa-miR-181d, hsa-miR-185, hsa-miR-15b, hsa-miR-214 and hsa-miR-496 was significantly different between normal tissue and EAC. CDH1, GART, GTSE1, NEK2 and hsa-miR-496, hsa-miR-214, hsa-miR-15b were found to be correlated with survival. |
| Databáze: | OpenAIRE |
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