Identification of miRNAs and genes for predicting Barrett's esophagus progressing to esophageal adenocarcinoma using miRNA-mRNA integrated analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34818353", "kind": "science-record", "revision": 5, "content_hash": "sha256:40529c7a50609ad98c02a0ca2517e1311b0bbb8c3d5928b6a244194820a9ff9a", "created_at": "2026-11-01T17:36:31Z", "updated_at": "2026-11-01T22:47:56Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of miRNAs and genes for predicting Barrett's esophagus progressing to esophageal adenocarcinoma using miRNA-mRNA integrated analysis.", "doi": "10.1371/journal.pone.0260353", "pmid": "34818353", "authors": ["Chengjiao Yao", "Yilin Li", "Lihong Luo", "Qin Xiong", "Xiaowu Zhong", "Fengjiao Xie", "Peimin Feng"], "journal": "PloS one", "year": 2021, "abstract": "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.", "claims": [{"id": "claim-method", "statement": "Results from the Kaplan-Meier method [23] and the log-rank test showed that CDH1, GART, GTSE1, NEK2 and hsa-miR-496, hsa-miR-214, hsa-miR-15b were correlated to overall survival (OS) in EAC patients (Fig 9 and Table 4).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34818353", "locator": "sections[15] \"3.6. Survival analysis of miRNA/mRNA in EAC\" paragraph 2", "quote": "Results from the Kaplan-Meier method [23] and the log-rank test showed that CDH1, GART, GTSE1, NEK2 and hsa-miR-496, hsa-miR-214, hsa-miR-15b were correlated to overall survival (OS) in EAC patients (Fig 9 and Table 4)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All files are available from the NCBI GEO database (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi). The accession numbers: GSE16454, GSE20099, GSE13898, GSE26886, GSE1420 (the accession numbers can also be found in the \"Microarray data collection\" section of this article).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34818353", "locator": "sections[20] \"Data Availability\" paragraph 2", "quote": "All files are available from the NCBI GEO database (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi). 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