Expression of microRNA-99a-3p in Prostate Cancer Based on Bioinformatics Data and Meta-Analysis of a Literature Review of 965 Cases

• Published in: Medical science monitor 2018-07, Vol.24, p.4807-4822
• Main Authors: Yan, Hai-Biao, Zhang, Yu, Cen, Jie-Mei, Wang, Xiao, Gan, Bin-Liang, Huang, Jia-Cheng, Li, Jia-Yi, Song, Qian-Hui, Li, Sheng-Hua, Chen, Gang
• Format: Article
• Language: English
• Subjects: Computational Biology; Gene Expression Profiling; Gene Expression Regulation, Neoplastic; Gene Ontology; Gene Regulatory Networks; Genome, Human; Humans; Male; Meta-Analysis; MicroRNAs - genetics; MicroRNAs - metabolism; Middle Aged; Prostatic Neoplasms - genetics; Prostatic Neoplasms - pathology; Protein Interaction Maps - genetics; Reproducibility of Results
• ISSN: 1643-3750; 1234-1010; 1643-3750
• DOI: 10.12659/MSM.908057

BACKGROUND microRNAs (miRNAs) have a role as biomarkers in human cancer. The aim of this study was to use bioinformatics data, and review of cases identified from the literature, to investigate the role of microRNA-99a-3p (miR-99a-3p) in prostate cancer, including the identification of its target genes and signaling pathways. MATERIAL AND METHODS Meta-analysis from a literature review included 965 cases of prostate cancer. Bioinformatics databases interrogated for miR-99a-3p in prostate cancer included The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and ArrayExpress. Twelve computational predictive algorithms were developed to integrate miR-99a-3p target gene prediction data. Bioinformatics analysis data from Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) network analysis were used investigate the possible pathways and target genes for miR-99a-3p in prostate cancer. RESULTS TCGA data showed that miR-99a was down-regulated in prostate cancer when compared with normal prostate tissue. Receiver-operating characteristic (ROC) curve area under the curve (AUC) for miR-99a-3p was 0.660 (95% CI, 0.587-0.732) or a moderate level of discriminations. Pathway analysis showed that miR-99a-3p was associated with the Wnt and vascular endothelial growth factor (VEGF) signaling pathways. The PPP3CA and HYOU1 genes, selected from the PPI network, were highly expressed in prostate cancer tissue compared with normal prostate tissue, and negatively correlated with the expression of miR-99a-3p. CONCLUSIONS In prostate cancer, miR-99a-3p expression was associated with the Wnt and VEGF signaling pathways, which might inhibit the expression of PPP3CA or HYOU1.