Bioinformatical analysis of key genes and pathways of bronchopulmonary dysplasia based on GEO
XIE Xiangjun1, ZHANG Bo1, LYU Ying1, NING Shangwei2, QU Shuqiang1
(1. Department of Pediatrics, the Second Affiliated Hospital of Harbin Medical University, Harbin Heilongjiang 150086; 2. College of Bioinformatics Science and Technology, Harbin Medical University, Harbin Heilongjiang 150081, China)
Abstract：Objective:To explore the key genes and signal pathways of bronchopulmonary dysplasia (BPD) using bioinformatics. Methods: Data sets were screened in the gene expression omnibus (GEO) database, the GEO2R tool was used to screen the differentially expressed genes between BPD and extremely preterm infants without BPD. Functional annotation and pathway analysis were performed using the DAVID database, proteinprotein interaction (PPI) network construction of key DEGs was completed using the STRING online tool. The core genes were screened and visualized by Cytoscape software. Results: A total of 375 genes were up-regulated and 390 genes were downregulated via differential analysis. GO enrichment analysis showed that differentially expressed genes were involved in cellular response to calcium ions responsiveness, transcriptional regulation of RNA polymerase Ⅱ promoter, and heart development. KEGG enrichment analysis showed that differentially expressed genes were concentrated in glucagon signaling pathway and breast cancer signaling pathway. Ten core genes were identified from the constructed PPI network, namely JUN, FOS, SMARCA4, ATF3, EGR1, ERBB2, PPARA, FOSB, NR4A1 and IGF1. Conclusion: JUN, FOS, ATF3 and EGR1 may play an important role in the pathogenesis and development of BPD.
［1］Principi N, Di Pietro GM, Esposito S. Bronchopulmonary dysplasia: clinical aspects and preventive and therapeutic strategies［J］. J Transl Med, 2018, 16(1): 36.
［2］Gortner L, Misselwitz B, Milligan D, et al. Rates of bronchopulmonary dysplasia in very preterm neonates in Europe: results from the MOSAIC cohort［J］.Neonatology, 2011, 99(2): 112-117.
［3］Shahzad T, Radajewski S, Chao CM, et al. Pathogenesis of bronchopulmonary dysplasia: when inflammation meets organ development［J］. Mol Cell Pediatr, 2016, 3(1): 23.
［4］Clough E, Barrett T. The Gene Expression Omnibus Database［J］. Methods Mol Biol, 2016, 1418: 93-110.
［5］Cohen J, Van Marter LJ, Sun Y, et al. Perturbation of gene expression of the chromatin remodeling pathway in premature newborns at risk for bronchopulmonary dysplasia［J］.Genome Biol, 2007, 8(10): R210.
［6］Barrett T, Wilhite SE, Ledoux P, et al. NCBI GEO: archive for functional genomics data sets—update［J］. Nucleic Acids Res, 2013, 41: D991-D995.
［7］Chen C, Chen H, Zhang Y, et al. TBtools:an integrative toolkit developed for Interactive analyses of big biological data［J］. Mol Plant, 2020, 13(8): 1194-1202.
［8］The Gene Ontology Consortium. The Gene Ontology Resource: 20 years and still GOing strong［J］. Nucleic Acids Res, 2019, 47(D1): D330-D338.
［9］Kanehisa M, Furumichi M, Tanabe M, et al. KEGG: new perspectives on genomes, pathways, diseases and drugs［J］. Nucleic Acids Res, 2017, 45(D1): D353-D361.
［10］Szklarczyk D, Franceschini A, Wyder S, et al. STRING v10: proteinprotein interaction networks, integrated over the tree of life［J］. Nucleic Acids Res, 2015, 43: D447-D452.
［11］Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks［J］. Genome Res, 2003, 13(11): 2498-2504.
［12］Jobe AH. Mechanisms of lung injury and bronchopulmonary dysplasia［J］. Am J Perinatol, 2016, 33(11): 1076-1078.
［13］Miyake T, McDermott JC. Nucleolar localization of cJun［J］. FEBS J, 2022, 289(3): 748-765.
［14］周华芳, 杨梅, 王毅, 等.亚急性砷中毒对大鼠脑氧化应激及Fos/Jun蛋白表达影响［J］.中国公共卫生, 2018, 34(11): 1523-1526.
［15］李文斌, 常立文, 祝华平, 等.早产儿支气管肺发育不良不同时期基质金属蛋白酶表达及其调控的研究［J］. 中国实用儿科杂志, 2004, 19(1): 10-12.
［16］Kompass KS, Deslee G, Moore C, et al. Highly conserved transcriptional responses to mechanical ventilation of the lung［J］. Physiol Genomics, 2010, 42(3): 384-396.
［17］Ku HC, Cheng CF. Master regulator activating transcription factor 3 (ATF3) in metabolic homeostasis and cancer［J］. Front Endocrinol (Lausanne), 2020, 11: 556.
［18］Yeo H, Lee JY, Kim J, et al. Transcription factor EGR1 transactivates the MMP1 gene promoter in response to TNFα in HaCaT keratinocytes［J］. BMB Rep, 2020, 53(6): 323-328.
［19］Kramer EL, Deutsch GH, Sartor MA, et al. Perinatal increases in TGFα disrupt the saccular phase of lung morphogenesis and cause remodeling: microarray analysis［J］. Am J Physiol Lung Cell Mol Physiol, 2007, 293(2): L314-L327.
［20］Hillman NH, Kallapur SG, Pillow JJ, et al. Airway injury from initiating ventilation in preterm sheep［J］. Pediatr Res, 2010, 67(1): 60-65.
［21］Godfrey J, Riscal R, Skuli N, et al. Glucagon signaling via supraphysiologic GCGR can reduce cell viability without stimulating gluconeogenic gene expression in liver cancer cells［J］. Cancer Metab, 2022, 10(1): 4.
［22］Peng Y, Lin H, Tian S, et al. Glucagonlike peptide1 receptor activation maintains extracellular matrix integrity by inhibiting the activity of mitogenactivated proteinkinases and activator protein1［J］. Free Radic Biol Med, 2021, 177: 247-259.
［23］Hamvas A, Feng R, Bi Y, et al. Exome sequencing identifies gene variants and networks associated with extreme respiratory outcomes following preterm birth［J］. BMC Genet, 2018, 19(1): 94.
［24］Mo W, Li Y, Chang W, et al. The role of LncRNA H19 in MAPK signaling pathway implicated in the progression of bronchopulmonary dysplasia［J］. Cell Transplant, 2020, 29: 963689720918294.
［25］Yeung YT, Aziz F, GuerreroCastilla A, et al. Signaling pathways in inflammation and antiinflammatory therapies［J］. Curr Pharm Des, 2018, 24(14): 1449-1484.
［26］Sokolova O, Vieth M, Naumann M. Protein kinase C isozymes regulate matrix metalloproteinase1 expression and cell invasion in Helicobacter pylori infection［J］. Gut, 2013, 62(3): 358-367.
