The biological functions of target genes in pan-cancers and cell lines were predicted by miR-375 microarray data from GEO database and bioinformatics

• Published in: PloS one Vol. 13; no. 10; p. e0206689
• Main Authors: Zeng, Jiang-Hui, Liang, Xu-Zhi, Lan, Hui-Hua, Zhu, Xu, Liang, Xiu-Yun
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 31.10.2018; Public Library of Science (PLoS)
• Subjects: Amino acids; Annotations; Apoptosis; Bioinformatics; Biological activity; Biology and life sciences; Biotechnology; Cancer; Carcinoma; Cell growth; Cell Line, Tumor; Cervical cancer; Computational Biology; Computer programs; Data acquisition; Databases, Genetic; DNA microarrays; Encyclopedias; Gene expression; Gene Expression Profiling; Gene Expression Regulation, Neoplastic; Genes; Genomes; Head & neck cancer; Humans; Laboratories; Medicine and Health Sciences; Metabolism; Metastasis; Methionine; MicroRNAs; MicroRNAs - genetics; miRNA; Non-coding RNA; Pathogenesis; Predictions; Protein interaction; Proteins; Research and Analysis Methods; Ribonucleic acid; RNA; Software; Squamous cell carcinoma; Tumor cell lines; Tumorigenesis; Tumors; China
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0206689

MicroRNA is endogenous non-coding small RNA that negative regulate and control gene expression, and increasing evidence links microRNA to oncogenesis and the pathogenesis of cancer. The goal of this study was to explore the potential molecular mechanism of miR-375 in various cancers. MiR-375 overexpression in different tumor cell lines was probed with microarray data from Gene Expression Omnibus (GEO). The common target genes of miR-375 were obtained by Robust Rank Aggregation (RRA), and identified by miRWalk2.0 software for target gene prediction. Additionally, we directed in silico analysis including Protein-Protein Interactions (PPI) analysis, gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways annotations to provide a summary of the function of miR-375 in various carcinomas. Eventually, data was obtained from The Cancer Genome Atlas (TCGA) were utilized for a validation in 7 cancers. The nine miR-375 related chips were acquired by the GEO data. The 5 down regulated genes came from 9 available microarray datasets, which overlapped with the potential target genes predicted by miRWalk2.0 software. The target genes were intensely enriched in amino acid biosynthetic and metabolic process from biological process (GO) and Cysteine and methionine metabolism (KEGG analysis). In view of these approaches, VASN, MAT2B, HERPUD1, TPAPPC6B and TAT are probably the most important miR-375 targets. In addition, miR-375 was negatively correlated with MAT2B, which was verified in 5 tumors of TCGA. In summary, this study based on common target genes provides an innovative perspective for exploring the molecular mechanism of miR-375 in human tumors.