Li Gao1, Li-Jie Zhang1, Sheng-Hua Li2, Li-Li Wei1, Bin Luo2, Rong-Quan He3, Shuang Xia4. 1. Department of Human Anatomy, Guangxi Medical University, 22 Shuangyong Road, Nanning, Guangxi, Zhuang Autonomous Region, 530021, China. 2. Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi, Zhuang Autonomous Region, 530021, China. 3. Department of Biochemistry, Guangxi Medical University, 22 Shuangyong Road, Nanning, Guangxi, Zhuang Autonomous Region, 530021, China. Electronic address: herongquan@gxmu.edu.cn. 4. Department of Human Anatomy, Guangxi Medical University, 22 Shuangyong Road, Nanning, Guangxi, Zhuang Autonomous Region, 530021, China. Electronic address: xiassxia@163.com.
Abstract
BACKGROUND: MiR-452-5p has been reported to be down-regulated in prostate cancer, affecting the development of this type of cancer. However, the molecular mechanism of miR-452-5p in prostate cancer remains unclear. Therefore, we investigated the network of target genes of miR-452-5p in prostate cancer using bioinformatics analyses. MATERIALS AND METHODS: We first analyzed the expression profiles and prognostic value of miR-452-5p in prostate cancer tissues from a public database. Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), PANTHER pathway analyses, and a disease ontology (DG) analysis were performed to find the molecular functions of the target genes from GSE datasets and miRWalk. Finally, we validated hub genes from the protein-protein interaction (PPI) networks of the target genes in the Human Protein Atlas (HPA) database and Gene Expression Profiling Interactive Analysis (GEPIA). Narrowing down the optimal target genes was conducted by seeking the common parts of up-regulated genes from GEPIA, down-regulated genes from GSE datasets, and predicted genes in miRWalk. RESULTS: Based on mining of GEO and ArrayExpress microarray chips and miRNA-Seq data in the TCGA database, which includes 1007 prostate cancer samples and 387 non-cancer samples, miR-452-5p is shown to be down-regulated in prostate cancer. GO, KEGG, and PANTHER pathway analyses suggested that the target genes might participate in important biological processes, such as transforming growth factor beta signaling and the positive regulation of brown fat cell differentiation and mesenchymal cell differentiation, as well as the Ras signaling pathway and pathways regulating the pluripotency of stem cells and arrhythmogenic right ventricular cardiomyopathy (ARVC). Nine genes-GABBR, PNISR, NTSR1, DOCK1, EREG, SFRP1, PTGS2, LEF1, and BMP2-were defined as hub genes in the PPI network. Three genes-FAM174B, SLC30A4, and SLIT1-were jointly shared by GEPIA, the GSE datasets, and miRWalk. CONCLUSIONS: Down-regulated miR-452-5p might play an essential role in the tumorigenesis of prostate cancer.
BACKGROUND:MiR-452-5p has been reported to be down-regulated in prostate cancer, affecting the development of this type of cancer. However, the molecular mechanism of miR-452-5p in prostate cancer remains unclear. Therefore, we investigated the network of target genes of miR-452-5p in prostate cancer using bioinformatics analyses. MATERIALS AND METHODS: We first analyzed the expression profiles and prognostic value of miR-452-5p in prostate cancer tissues from a public database. Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), PANTHER pathway analyses, and a disease ontology (DG) analysis were performed to find the molecular functions of the target genes from GSE datasets and miRWalk. Finally, we validated hub genes from the protein-protein interaction (PPI) networks of the target genes in the Human Protein Atlas (HPA) database and Gene Expression Profiling Interactive Analysis (GEPIA). Narrowing down the optimal target genes was conducted by seeking the common parts of up-regulated genes from GEPIA, down-regulated genes from GSE datasets, and predicted genes in miRWalk. RESULTS: Based on mining of GEO and ArrayExpress microarray chips and miRNA-Seq data in the TCGA database, which includes 1007 prostate cancer samples and 387 non-cancer samples, miR-452-5p is shown to be down-regulated in prostate cancer. GO, KEGG, and PANTHER pathway analyses suggested that the target genes might participate in important biological processes, such as transforming growth factor beta signaling and the positive regulation of brown fat cell differentiation and mesenchymal cell differentiation, as well as the Ras signaling pathway and pathways regulating the pluripotency of stem cells and arrhythmogenic right ventricular cardiomyopathy (ARVC). Nine genes-GABBR, PNISR, NTSR1, DOCK1, EREG, SFRP1, PTGS2, LEF1, and BMP2-were defined as hub genes in the PPI network. Three genes-FAM174B, SLC30A4, and SLIT1-were jointly shared by GEPIA, the GSE datasets, and miRWalk. CONCLUSIONS: Down-regulated miR-452-5p might play an essential role in the tumorigenesis of prostate cancer.
Authors: Nelson T Gross; Jianmin Wang; Michael V Fiandalo; Eduardo Cortes Gomez; Anica Watts; Alejandro S Godoy; Gary J Smith; Yue Wu Journal: PLoS One Date: 2020-06-25 Impact factor: 3.240