Simin He1, Jingcheng Shi1, Jie Mao1, Xi Luo1, Wen Liu1, Rong Liu2, Fang Yang3. 1. Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Shangmayuanling 238, Kaifu District, Changsha, Hunan 410078, People's Republic of China. 2. Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, People's Republic of China. 3. Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Shangmayuanling 238, Kaifu District, Changsha, Hunan 410078, People's Republic of China. Electronic address: yangfang2010@csu.edu.cn.
Abstract
BACKGROUND: MiR-375, as a member of miRNA family, plays essential roles in prostate cancer (PC). We purpose to explore the expression and possible molecular mechanism of the miR-375 in PC using database analysis. METHODS: First, Student's t-test, overall and subgroup meta-analyses with 20 eligible datasets in the Gene Expression Omnibus (GEO) database were performed to explore the expression of miR-375 in PC. Then the results of meta-analyses were verified in The Cancer Genome Atlas (TCGA) database by Student's t-test and Paired t-test. The candidate genes of miR-375 were predicted by four platforms. Protein-protein interaction (PPI) networks, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to investigate the potential molecular mechanism of miR-375 in PC. RESULTS: The overall meta-analysis showed the expression of miR-375 was significantly up-regulated in PC groups compared with non-cancerous group (SMD; 0.71; 95% CI: 0.38-1.04). In addition, the meta-analyses by subgroup showed the expression of miR-375 in PC tissues was higher than that in healthy prostate tissues and adjacent non-cancerous tissues. The results of TCGA database verified the expression of miR-375 in PC tissues was obviously higher than that in adjacent non-cancerous tissues. Moreover, GO and KEGG analysis revealed that the latent target genes were mainly involved in protein binding function and ubiquitin mediated proteolysis. PPI analysis identified JAK2, EHMT1 and QKI as the hub genes (highly connected genes with high degree in PPI). CONCLUSIONS: MiR-375 was up-regulated in PC tissues. Meanwhile, miR-375 may play an important role in aggressive PC by targeting its potential target genes.
BACKGROUND:MiR-375, as a member of miRNA family, plays essential roles in prostate cancer (PC). We purpose to explore the expression and possible molecular mechanism of the miR-375 in PC using database analysis. METHODS: First, Student's t-test, overall and subgroup meta-analyses with 20 eligible datasets in the Gene Expression Omnibus (GEO) database were performed to explore the expression of miR-375 in PC. Then the results of meta-analyses were verified in The Cancer Genome Atlas (TCGA) database by Student's t-test and Paired t-test. The candidate genes of miR-375 were predicted by four platforms. Protein-protein interaction (PPI) networks, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to investigate the potential molecular mechanism of miR-375 in PC. RESULTS: The overall meta-analysis showed the expression of miR-375 was significantly up-regulated in PC groups compared with non-cancerous group (SMD; 0.71; 95% CI: 0.38-1.04). In addition, the meta-analyses by subgroup showed the expression of miR-375 in PC tissues was higher than that in healthy prostate tissues and adjacent non-cancerous tissues. The results of TCGA database verified the expression of miR-375 in PC tissues was obviously higher than that in adjacent non-cancerous tissues. Moreover, GO and KEGG analysis revealed that the latent target genes were mainly involved in protein binding function and ubiquitin mediated proteolysis. PPI analysis identified JAK2, EHMT1 and QKI as the hub genes (highly connected genes with high degree in PPI). CONCLUSIONS:MiR-375 was up-regulated in PC tissues. Meanwhile, miR-375 may play an important role in aggressive PC by targeting its potential target genes.
Authors: Jacob Fredsøe; Anne K I Rasmussen; Peter Mouritzen; Marianne T Bjerre; Peter Østergren; Mikkel Fode; Michael Borre; Karina D Sørensen Journal: Diagnostics (Basel) Date: 2020-03-28