Identification of DGUOK-AS1 as a Prognostic Factor in Breast Cancer by Bioinformatics Analysis

Background: Significant developments have been made in breast cancer diagnosis and treatment, yet the prognosis remains unsatisfactory. Accumulating evidence indicates that long non-coding RNAs (lncRNAs) play pivotal roles in the development and progression of human tumors. However, the regulatory mechanisms and clinical significance of most lncRNAs in breast cancer remain poorly understood. Methods: The lncRNA, miRNA, and mRNA expression profiles were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. A lncRNA-miRNA-mRNA regulatory network was constructed and visualized using Cytoscape. The protein-protein interaction (PPI) network was constructed using the STRING database and hub genes were extracted using the cytoHubba plugin. Gene Ontology and Kyoto Encyclopedia of Gene and Genomes analyses identified the functions and signaling pathways associated with these differentially expressed mRNAs (DEmRNAs). Expression of the key lncRNA and the relationship with prognosis of patients with breast cancer were evaluated. Results: Six differentially expressed lncRNAs (DElncRNAs), 29 differentially expressed miRNAs (DEmiRNAs), and 253 DEmRNAs were selected to construct the regulatory network. A PPI network was established and seven hub genes were identified. A lncRNA-miRNA-hub gene regulatory sub-network was established containing two DElncRNAs, five DEmiRNAs, and seven DEmRNAs. Hub genes were associated with breast cancer onset and progression. The upregulated DGUOK-AS1 was identified as the key lncRNA in breast cancer based on the competing endogenous RNA network. High DGUOK-AS1 expression was associated with adverse prognosis in patients with breast cancer and a prognostic nomogram built on Grade, LN status, and DGUOK-AS1 expression shows significant prognostic value. Conclusions: Our results reveal the significant roles of lncRNA/miRNA/mRNA regulatory networks in breast cancer and identified a novel prognosis predictor and promising therapeutic target for patients with breast cancer.