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

PLOS ONE RESEARCH ARTICLE Identification of miRNAs and genes for predicting Barrett’s esophagus progressing to esophageal adenocarcinoma using miRNAmRNA integrated analysis Chengjiao Yao ID1,2☯, Yilin Li1,3☯, Lihong Luo1☯, Qin Xiong1, Xiaowu Zhong3,4*, Fengjiao Xie1, Peimin Feng1* a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 1 Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China, 2 Department of Geriatrics of the Affiliated Hospital, North Sichuan Medical College, Nanchong, Sichuan, China, 3 Department of Laboratory Medicine, North Sichuan Medical College, Nanchong, Sichuan, China, 4 Department of Clinical Laboratory, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China ☯ These authors contributed equally to this work. * (PF); (XZ) Abstract OPEN ACCESS Citation: Yao C, Li Y, Luo L, Xiong Q, Zhong X, Xie F, et al. (2021) Identification of miRNAs and genes for predicting Barrett’s esophagus progressing to esophageal adenocarcinoma using miRNA-mRNA integrated analysis. PLoS ONE 16(11): e0260353. https://doi.org/10.1371/journal.pone.0260353 Editor: Eduardo Andrés-León, Institute of Parasitology and Biomedicine, SPAIN Received: May 1, 2021 Accepted: November 8, 2021 Published: November 24, 2021 Copyright: © 2021 Yao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability 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). 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. Funding: This work support by Special fund for cooperative scientific research of Nanchong City (19XHZ0153). PLOS ONE | https://doi.org/10.1371/journal.pone.0260353 November 24, 2021 1 / 22 PLOS ONE Competing interests: The authors have declared that no competing interests exist. Abbreviations: BE, Barrett’s esophagus; BP, biological process; CC, cellular component; CDH1, cadherin 1; DAVID, database for annotation, visualization and integrated discovery; DEGs, differentially expressed genes; DEMs, differentially expressed miRNAs; EAC, esophageal adenocarcinoma; EC, esophageal carcinoma; FDR, false discovery rate; GART, phosphoribosylglycinamide formyltransferase; GEO, gene expression omnibus; GO, gene ontology; GTSE1, G2 and S-phase expressed 1; KEGG, Kyoto Encyclopedia of Genes and Genomes; MF, molecular function; NEK2, NIMA related kinase 2; OS, overall survival; PPI, protein–protein interactions; STRING, search tool for the retrieval of interacting genes/proteins. Key biomarker for esophageal adenocarcinoma 1. Introduction Esophageal carcinoma (EC) is the eighth most common cancer in the world. A total of 17650 new cases and 16080 deaths have been reported in 2019 [1]. The mortality rate is significantly higher in males than in females, and the overall five-year survival rate is only 19% [1]. EC is usually classified into esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). There are several accepted hypotheses concerning which cells give rise to EAC in adults. The most plausible one is that EAC develops according to the following process: normal esophageal epithelium ! hyperplasia of proper esophageal gland ! dentate line Migration ! Barrett’s esophagus (BE) ! EAC [2]. From the conversional process, BE is the only recognized precursor of EAC. Patients with BE are almost 30–120 times more likely to develop EAC [3]. However, the mechanism through which BE develops to EAC and relevant driving factors still remain unclear. Therefore, the identification of key molecular biomarkers for predicting BE, implementing the strategy of clinical risk stratification, and focusing on the higher risk patient may be critical in preventing EAC. Over recent years, a number of studies examined specific patterns of gene transcript levels in EAC. So far, many significant genes have been associated with the pathogenesis of EAC. For example, a tumor suppressor gene TP53 is one of the first genes that was examined in Barrett’s-associated neoplasms. Studies have found that patients with loss of TP53 are almost 16 times more likely to develop EAC compared to those with normal expression of TP53 [4]. Moreover, a decreased expression of p14ARF has been suggested as a biomarker for disease progression, from normal epithelium to non-dysplastic BE and even to EAC [4]. MMP1 gene, which participates in numerous inflammatory processes of cancer, has shown to be up-regulated in EAC and BE samples [5]. COL1A1 has shown to be a potential biomarker for distinguishing EAC from BE [3]. MicroRNAs (miRNAs) are a group of small non-coding RNA molecules that contain approxinately 18 to 25 nucleotides. It has been described that miRMAs participate in a series of biological processes as a post-transcriptional regulators. Aberrant expression of miRNAs has been associated with the development of BE. For instance, miR-215, which acts as a tumor suppressor by promoting apoptosis, is low in the normal squamous epithelium and high in BE [6]. In BE, miR-196a which targets KRT5 and S (...truncated)