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

被引:8
|
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
下载
收藏
页码:2554 / 2564
页数:11
相关论文
共 50 条
  • [31] Identification of key genes in oral squamous cell carcinoma by integrated bioinformatics analysis
    Xu, Jie
    Lu, Shaowen
    Wu, Jianhua
    Yang, Lili
    Ma, Sijia
    Li, Yanli
    Peng, Yi
    BIOLOGIA, 2022, 77 (03) : 907 - 914
  • [32] Identification of key genes and biological pathways in lung adenocarcinoma by integrated bioinformatics analysis
    Zhang, Lin
    Liu, Yuan
    Zhuang, Jian-Guo
    Guo, Jie
    Li, Yan-Tao
    Dong, Yan
    Song, Gang
    WORLD JOURNAL OF CLINICAL CASES, 2023, 11 (23) : 5504 - 5518
  • [33] The Identification of Key Genes and Biological Pathways in Heart Failure by Integrated Bioinformatics Analysis
    Yang, Qianhong
    Bai, Xiaolu
    Li, Xiang
    Hu, Wei
    COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE, 2021, 2021
  • [34] Identification of key genes and pathways in abdominal aortic aneurysm by integrated bioinformatics analysis
    Liu, Yihai
    Wang, Xixi
    Wang, Hongye
    Hu, Tingting
    JOURNAL OF INTERNATIONAL MEDICAL RESEARCH, 2019,
  • [35] 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
  • [36] Identification of key genes and small molecule drugs in osteoarthritis by integrated bioinformatics analysis
    Liu, Zhendong
    Wang, Hongbo
    Cheng, Xingbo
    Zhang, Jiangfen
    Gao, Yanzheng
    BIOCHEMISTRY AND BIOPHYSICS REPORTS, 2023, 34
  • [37] Identification of key genes of papillary thyroid cancer using integrated bioinformatics analysis
    W. Liang
    F. Sun
    Journal of Endocrinological Investigation, 2018, 41 : 1237 - 1245
  • [38] Identification of key genes in oral squamous cell carcinoma by integrated bioinformatics analysis
    Jie Xu
    Shaowen Lu
    Jianhua Wu
    Lili Yang
    Sijia Ma
    Yanli Li
    Yi Peng
    Biologia, 2022, 77 : 907 - 914
  • [39] Identification of key genes of papillary thyroid cancer using integrated bioinformatics analysis
    Liang, W.
    Sun, F.
    JOURNAL OF ENDOCRINOLOGICAL INVESTIGATION, 2018, 41 (10): : 1237 - 1245
  • [40] Identification of key genes for predicting colorectal cancer prognosis by integrated bioinformatics analysis
    Dai, Gong-Peng
    Wang, Li-Ping
    Wen, Yu-Qing
    Ren, Xue-Qun
    Zuo, Shu-Guang
    ONCOLOGY LETTERS, 2020, 19 (01) : 388 - 398