Identification of key genes and microRNAs involved in kidney Wilms tumor by integrated bioinformatics analysis

被引:9
|
作者
Zhang, Lei [1 ]
Gao, Xian [2 ]
Zhou, Xiang [1 ]
Qin, Zhiqiang [1 ]
Wang, Yi [1 ]
Li, Ran [1 ]
Tang, Min [1 ]
Wang, Wei [1 ]
Zhang, Wei [1 ]
机构
[1] Nanjing Med Univ, Affiliated Hosp 1, Dept Urol, 300 Guangzhou Rd, Nanjing 210029, Jiangsu, Peoples R China
[2] Nanjing Med Univ, Affiliated Hosp 1, Dept Oncol, Nanjing 210029, Jiangsu, Peoples R China
关键词
Wilms tumor; differentially expressed genes; microRNA; bioinformatics; PROTEIN-INTERACTION NETWORKS; CELL-PROLIFERATION; BLADDER-CANCER; MUTATIONS; EXPRESSION; INVASION; FEATURES; OVEREXPRESSION; ASSOCIATION; CONTRIBUTES;
D O I
10.3892/etm.2019.7870
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
Wilms tumor (WT) is one of the most common types of pediatric solid tumors; however, its molecular mechanisms remain unclear. The present study aimed to identify key genes and microRNAs (miRNAs), and to predict the underlying molecular mechanisms of WT using integrated bioinformatics analysis. Original gene expression profiles were downloaded from the Gene Expression Omnibus (GEO; accession, GSE66405) and The Cancer Genome Atlas (TCGA) databases. Similarly, miRNA expression patterns were downloaded from GEO (accession, GSE57370) and TCGA. R version 3.5.0 software was used to identify differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) using the limma and edgeR packages. Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology analyses were performed to examine the biological functions of the DEGs. Additionally, a protein-protein interaction (PPI) network was constructed to screen hub gene modules using Cytoscape software. By predicting target genes of the DEMs and integrating them with DEGs, the present study constructed a miRNA-mRNA regulatory network to predict the possible molecular mechanism of WT. Expression of hub genes was validated using the Oncomine database. A total of 613 genes and 29 miRNAs were identified to be differentially expressed in WT. By constructing a PPI network and screening hub gene modules, 5 upregulated genes, including BUB1 mitotic checkpoint serine/threonine kinase, BUB1B mitotic checkpoint serine/threonine kinase B, cell division cycle protein 45, cyclin B2 and pituitary tumor-transforming 1. These genes were identified to be associated with the cell cycle pathway, which suggested that these genes may serve important roles in WT. In addition, a miRNA-mRNA regulatory network was constructed and comprised 16 DEMs and 19 DEGs. In conclusion, key genes, miRNAs and the mRNA-miRNA regulatory network identified in the present study may improve understanding of the underlying molecular mechanisms in the occurrence and development of WT, and may aid the identification of potential biomarkers and therapeutic targets.
引用
收藏
页码:2554 / 2564
页数:11
相关论文
共 50 条
  • [1] Bioinformatics analysis and identification of genes and pathways involved in patients with Wilms tumor
    Li, Yufeng
    Tang, Haizhou
    Huang, Zhenwen
    Qin, Huaxing
    Cen, Qin
    Meng, Fei
    Huang, Liang
    Lin, Lifang
    Pu, Jian
    Yang, Di
    TRANSLATIONAL CANCER RESEARCH, 2022, 11 (08) : 2843 - 2857
  • [2] Identification of a 12-Gene Signature and Hub Genes Involved in Kidney Wilms Tumor via Integrated Bioinformatics Analysis
    Huang, Guoping
    Mao, Jianhua
    FRONTIERS IN ONCOLOGY, 2022, 12
  • [3] Identification of key microRNAs and genes in preeclampsia by bioinformatics analysis
    Luo, Shouling
    Cao, Nannan
    Tang, Yao
    Gu, Weirong
    PLOS ONE, 2017, 12 (06):
  • [4] Identification of key genes and microRNAs for multiple sclerosis using bioinformatics analysis
    Xu, Zhong-bo
    Feng, Xin
    Zhu, Wei-na
    Qiu, Ming-liang
    MEDICINE, 2021, 100 (48)
  • [5] Identification of Key Endometrial MicroRNAs and Their Target Genes Associated With Pathogenesis of Recurrent Implantation Failure by Integrated Bioinformatics Analysis
    Shang, Jin
    Cheng, Yan-Fei
    Li, Min
    Wang, Hui
    Zhang, Jin-Ning
    Guo, Xin-Meng
    Cao, Dan-dan
    Yao, Yuan-Qing
    FRONTIERS IN GENETICS, 2022, 13
  • [6] Identification and interaction analysis of key genes and microRNAs in hepatocellular carcinoma by bioinformatics analysis
    Mou, Tong
    Zhu, Di
    Wei, Xufu
    Li, Tingting
    Zheng, Daofeng
    Pu, Junliang
    Guo, Zhen
    Wu, Zhongjun
    WORLD JOURNAL OF SURGICAL ONCOLOGY, 2017, 15
  • [7] Identification of key genes involved in the pathogenesis of cutaneous melanoma using bioinformatics analysis
    Chen, Jianqin
    Sun, Wen
    Mo, Nian
    Chen, Xiangjun
    Yang, Lihong
    Tu, Shaozhong
    Zhang, Siwen
    Liu, Jing
    JOURNAL OF INTERNATIONAL MEDICAL RESEARCH, 2020, 48 (01)
  • [8] Integrated bioinformatics analysis of key genes involved in progress of colon cancer
    Yang, Haojie
    Wu, Jiong
    Zhang, Jingjing
    Yang, Zhigang
    Jin, Wei
    Li, Ying
    Jin, Lei
    Yin, Lu
    Liu, Hua
    Wang, Zhenyi
    MOLECULAR GENETICS & GENOMIC MEDICINE, 2019, 7 (04):
  • [9] Identification of key carcinogenic genes in Wilms' tumor
    He, Shaohua
    Yang, Liu
    Xiao, Zhixiang
    Tang, Kunbin
    Xu, Di
    GENES & GENETIC SYSTEMS, 2021, 96 (03) : 139 - 147
  • [10] Identification of Key Genes and Related Drugs of Adrenocortical Carcinoma by Integrated Bioinformatics Analysis
    Wei, Jian-bin
    Zeng, Xiao-chun
    Ji, Kui-rong
    Zhang, Ling-yi
    Chen, Xiao-min
    HORMONE AND METABOLIC RESEARCH, 2024, 56 (08) : 593 - 603