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Identification of Microrna-Mrna Regulatory Networks and Pathways Related to Retinoblastoma Across Human and Mouse

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Identification of Microrna-Mrna Regulatory Networks and Pathways Related to Retinoblastoma Across Human and Mouse Int J Ophthalmol, Vol. 13, No. 4, Apr.18, 2020 www.ijo.cn Tel: 8629-82245172 8629-82210956 Email: [email protected] ·Basic Research· Identification of microRNA-mRNA regulatory networks and pathways related to retinoblastoma across human and mouse Rui Tian, He Zou, Lu-Fei Wang, Mei-Jiao Song, Lu Liu, Hui Zhang Department of Ophthalmology, the Second Hospital of Jilin INTRODUCTION University, Changchun 130000, Jilin Province, China etinoblastoma (RB) is a rare malignant retina tumor Correspondence to: Hui Zhang. Department of Ophthalmology, R in children. It initiates during foetal stage and is often the Second Hospital of Jilin University, No.218 Ziqiang Street, delay-diagnosed after birth or during the first few years Nan Guan District, Changchun 130000, Jilin Province, China. after birth. The common signs of RB includes leukocoria, [email protected] strabismus, glaucoma and inflammation[1-2]. The prognosis and Received: 2019-07-20 Accepted: 2020-02-19 survival of RB has been improved due to the improvement in diagnosis methods and treatment strategies, including Abstract chemotherapy regiments, magnetic resonance imaging and ● AIM: To explore the mRNA and pathways related to surgical therapy[1-3]. However, the etiology of RB is still now retinoblastoma (RB) genesis and development. clear till now. ● METHODS: Microarray datasets GSE29683 (human) The pathogenesis of RB involves RB tumor suppressor and GSE29685 (mouse) were downloaded from NCBI GEO gene biallelic mutation or inactivation and attendant loss of database. Homologous genes between the two species function of RB protein[1]. It is believed that the molecular were identified using WGCNA, followed by protein-protein features of a disease reflect its origin features and provide interaction (PPI) network construction and gene enrichment clues for treatment. With the development and application analysis. Disease-related miRNAs and pathways were of bioinformatics technology, more and more molecular retrieved from miR2Disease database and Comparative features have been identified to be involved in RB genesis and Toxicogenomics Database (CTD), respectively. development. For instance, the knockdown/loss of p107, p130, ● RESULTS: A total of 352 homologous genes were p53, Cdkn2a and PTEN genes[4-7], and amplifications of Mdm2 identified. Two pathways including “cell cycle” and “pathway and Mycn[8-9] benefit to RB development in mouse. in cancer” in CTD and enrichment analysis were identified Animal models of cancer, especially mouse models, have and seven miRNAs (including hsa-miR-373, hsa-miR-34a, hsa- attracted researchers’ attention long before in cancer miR-129, hsa-miR-494, hsa-miR-503, hsa-let-7 and hsa- field due to the high homologous and identity of human miR-518c) were associated with RB. miRNAs modulate “cell and mouse genome[10-11]. There are plenty and increasing cycle” and “pathway in cancer” pathways via regulating 13 evidences showing the crucial roles of employing mouse genes (including CCND1, CDC25C, E2F2, CDKN2D and TGFB2). model in identifying key features related to human diseases ● CONCLUSION: These results suggest that these and cancers, including RB[10-13]. Researches focusing on the miRNAs play crucial roles in RB genesis through “cell cycle” similarity in molecular features of diseases between human and “pathway in cancer” pathways by regulating their and mouse confer the fast development in disease prognosis targets including CCND1, CDC25C, E2F2 and CDKN2D. and treatment[11]. McEvoy et al[11] identified p53 pathway was ● KEYWORDS: Kyoto Encyclopedia of Genes and suppressed in human RB cells and mouse RB model. It has Genomes pathway; microRNA; retinoblastoma; weighted been widely identified that RB gene is crucial for chromosomal gene co-expression network analysis rearrangement and deletion[14]. RB gene has been identified to DOI:10.18240/ijo.2020.04.02 be a direct target of various miRNAs[15-16]. The dysregulation of microRNAs (miRNAs), including miRNA 17-92 cluster, Citation: Tian R, Zou H, Wang LF, Song MJ, Liu L, Zhang H. hsa-miR-34a, hsa-miR-373 and hsa-miR-518c are reported to Identification of microRNA-mRNA regulatory networks and be related with RB development[17-19]. However, the identity pathways related to retinoblastoma across human and mouse. Int J of miRNA-mRNA regulations between human and mouse RB Ophthalmol 2020;13(4):535-544 had not been reported till now. 535 miRNA and mRNA in retinoblastoma This study was performed to identify the co-expressed miRNA- DAVID (Database for Annotation, Visualization, and Integrated mRNA regulatory networks and developmental programs Discovery; v6.8; https://david.ncifcrf.gov/) was used. in RB between human and mouse. The GSE29683 and The Gene Ontology (GO) biological processes and Kyoto GSE29685 datasets were downloaded and homologous genes Encyclopedia of Genes and Genomes (KEGG) pathways with between human and mouse RB models were identified and the P<0.05 and/or false discovery rate (FDR) <0.05 were analyzed using bioinformatics analyses. Our study would defined as significant terms. provide new insights into the molecular features in the genesis Protein-Protein Interaction Network Interactions between of RB. the products of homologous genes between human and MATERIALS AND METHODS mouse were identified using Search Tool for the Retrieval of Microarray Data and Processing Microarray dataset Interacting Genes (STRING, v10.0; http://string-db.org/)[28] GSE29686 (including GSE29683 and GSE29685) were with the default setting parameters (reliability threshold 0.4). downloaded from the NCBI GEO database (https://www. The protein-protein interaction (PPI) network of homologous ncbi.nlm.nih.gov/). GSE29683 and GSE29685 is based genes were visualized using Cytoscape software (v3.6.1; http:// on the GPL 570 platform (HG-U133_Plus_2; Affymetrix www.cytoscape.org/)[29]. Human Genome U133 Plus 2.0 Array) and the GPL1261 Identification and Analysis of RB-Related miRNAs The platform (Mouse430_2; Affymetrix Mouse Genome 430 2.0 miR2Disease database (http://www.mir2disease.org/) includes Array), respectively. CEL files were processed using the R various disease-related miRNAs and the detail information of Oligo software package (v3.4.1; http://www.bioconductor. them (inclusing sources, disease, exaiminations and references)[30]. org/packages/release/bioc/html/oligo.html)[20]. GSE29683 is miRNAs related to RB were identified from miR2Disease comprised of 62 RNA samples derived from 55 human RB database with the searching term “retinoblastoma”. specimens, 3 passaged xenografts and 4 human RB cell lines Construction of miRNA-mRNA and RB-Related Pathway (Y79, Weri1, Rb-355, and Rb-13). GSE29685 consisted of 132 Regulatory Network The targets of miRNAs were predicted primary RB tumor samples from mouse models (SCID mice in starBase Version 2.0 database (http://starbase.sysu.edu. with p107- and p130-knockout, Chx10-Cre, p53Lox/Lox, RbLox/Lox, cn/)[31], and targetScan, picTar, RNA22, PITA and miRanda. MDMXTg, and p130Lox/Lox)[11]. The miRNA-mRNA pairs were visualized using Cytoscape. Annotations of Homologous Genes Across Species The Comparative Toxicogenomics Database (CTD, 2017 update; homologous genes between human and mouse were converted http://ctd.mdibl.org/) was interviewed to identify RB-related using the online database mining tool Biomart (v2.3.6; https:// KEGG pathways. The searching keyword was “retinoblastoma”. bioconductor.org/packages/release/bioc/html/biomaRt.html)[21-22]. The key KEGG pathways and genes related to RB were used Weighted Gene Co-Expression Network Analysis for Cross- to construct RB-related miRNA-mRNA-pathway network. Species Genes Weighted gene co-expression network analysis RESULTS (WGCNA) is a bioinformatics algorithm for the identification Identification of Homologous Genes Between Human of co-expressed network related to disease clinic traits[23-25]. and Mouse Figure 1A, 1B shows the data processing for Different WGCNA modules in GSE29683 and GSE29685 GSE29683 and GSE29685, respectively. After normalizing, subset were identified using WGCNA package (v1.61; https:// 13 680 homologous coding genes between human and mouse cran.r-project.org/web/packages/WGCNA/index.html)[26]. were identified using Biomart tool. Correlation analysis Cross-species comparisons of modules with high topological showed that the 13 680 homologous genes were highly overlaps (TOs) were performed using fisher’s precise test with correlated (cor=0.73 and P<1e-200) and connected (cor=0.31 and P<1e-200; Figure 1C), suggesting the viability of enrichment algorithm[27] as follows: , comparative analysis using GSE29683 and GSE29685. where N notes total gene number from human samples, M Identification of WGCNA Modules Associated with RB indicates gene counts in each WGCNA module of human, Genesis The 13 680 homologous genes were then used for K notes gene number in each WGCNA module of mouse, P WGCNA analysis. Figure 2 shows the correlation coefficient value of fisher’s precise test is based on the mini number of square (r2) of eigengenes=0.9 and the mean connectivity=1 genes from human (x). TOs with P value <0.05 and fold >1 when the soft threshold power is 10. Accordingly, r2=0.9 were defined as significant. The homologous genes between and soft threshold power=10 were set as the criteria for the modules with significant TOs were selected as candidate genes identification of WGCNA modules. associated with RB. Following with the aforementioned criteria combined with Enrichment Analysis To investigate the biological
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