ArticleBMC urology2021
Exploring microRNA target genes and identifying hub genes in bladder cancer based on bioinformatic analysis.
Article in BMC urology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Comprehensive analysis of single-cell and bulk transcriptomes reveals key B-cell genes and immune microenvironment regulation in bladder cancer.Frontiers in immunology · 2025Article
- From bioinformatics to clinical applications: a novel prognostic model of cuproptosis-related genes based on single-cell RNA sequencing data in hepatocellular carcinoma.BMC immunology · 2024Article
- Identification and verification of anoikis-related gene markers to predict the prognosis of patients with bladder cancer and assist in the diagnosis and treatment of bladder cancer.Translational cancer research · 2024Article
- Tropomyosin 2 exerts anti-tumor effects in lung adenocarcinoma and is a novel prognostic biomarker.Histology and histopathology · 2023Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBladder cancer (BC) is the second most frequent malignancy of the urinary system. The aim of this study was to identify key microRNAs (miRNAs) and hub genes associated with BC as well as analyse their targeted relationships.
methodsAccording to the microRNA dataset GSE112264 and gene microarray dataset GSE52519, differentially expressed microRNAs (DEMs) and differentially expressed genes (DEGs) were obtained using the R limma software package. The FunRich software database was used to predict the miRNA-targeted genes. The overlapping common genes (OCGs) between miRNA-targeted genes and DEGs were screened to construct the PPI network. Then, gene ontology (GO) analysis was performed through the "cluster Profiler" and "org.Hs.eg.db" R packages. The differential expression analysis and hierarchical clustering of these hub genes were analysed through the GEPIA and UCSC Cancer Genomics Browser databases, respectively. KEGG pathway enrichment analyses of hub genes were performed through gene set enrichment analysis (GSEA).
resultsA total of 12 DEMs and 10 hub genes were identified. Differential expression analysis of the hub genes using the GEPIA database was consistent with the results for the UCSC Cancer Genomics Browser database. The results indicated that these hub genes were oncogenes, but VCL, TPM2, and TPM1 were tumour suppressor genes. The GSEA also showed that hub genes were most enriched in those pathways that were closely associated with tumour proliferation and apoptosis.
conclusionsIn this study, we built a miRNA-mRNA regulatory targeted network, which explores an understanding of the pathogenesis of cancer development and provides key evidence for novel targeted treatments for BC.
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