Literature DB >> 30379973

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

Jiang-Hui Zeng1, Xu-Zhi Liang2, Hui-Hua Lan3, Xu Zhu1, Xiu-Yun Liang1.   

Abstract

BACKGROUND: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSION: In summary, this study based on common target genes provides an innovative perspective for exploring the molecular mechanism of miR-375 in human tumors.

Entities:  

Mesh:

Substances:

Year:  2018        PMID: 30379973      PMCID: PMC6209324          DOI: 10.1371/journal.pone.0206689

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  68 in total

1.  MicroRNA genes are transcribed by RNA polymerase II.

Authors:  Yoontae Lee; Minju Kim; Jinju Han; Kyu-Hyun Yeom; Sanghyuk Lee; Sung Hee Baek; V Narry Kim
Journal:  EMBO J       Date:  2004-09-16       Impact factor: 11.598

2.  Prediction of both conserved and nonconserved microRNA targets in animals.

Authors:  Xiaowei Wang; Issam M El Naqa
Journal:  Bioinformatics       Date:  2007-11-29       Impact factor: 6.937

3.  Interactive exploration of RNA22 microRNA target predictions.

Authors:  Phillipe Loher; Isidore Rigoutsos
Journal:  Bioinformatics       Date:  2012-10-16       Impact factor: 6.937

4.  Statistics Commentary Series: Commentary No. 24: Box Plots.

Authors:  David L Streiner
Journal:  J Clin Psychopharmacol       Date:  2018-02       Impact factor: 3.153

5.  Vasorin, a transforming growth factor beta-binding protein expressed in vascular smooth muscle cells, modulates the arterial response to injury in vivo.

Authors:  Yuichi Ikeda; Yasushi Imai; Hidetoshi Kumagai; Tetsuya Nosaka; Yoshihiro Morikawa; Tomoko Hisaoka; Ichiro Manabe; Koji Maemura; Takashi Nakaoka; Takeshi Imamura; Kohei Miyazono; Issei Komuro; Ryozo Nagai; Toshio Kitamura
Journal:  Proc Natl Acad Sci U S A       Date:  2004-07-09       Impact factor: 11.205

6.  Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers.

Authors:  George Adrian Calin; Cinzia Sevignani; Calin Dan Dumitru; Terry Hyslop; Evan Noch; Sai Yendamuri; Masayoshi Shimizu; Sashi Rattan; Florencia Bullrich; Massimo Negrini; Carlo M Croce
Journal:  Proc Natl Acad Sci U S A       Date:  2004-02-18       Impact factor: 11.205

7.  Evidence of a novel gene HERPUD1 in polypoidal choroidal vasculopathy.

Authors:  Enzhong Jin; Yujing Bai; Lvzhen Huang; Min Zhao; Chunfang Zhang; Mingwei Zhao; Xiaoxin Li
Journal:  Int J Clin Exp Pathol       Date:  2015-11-01

8.  Robust rank aggregation for gene list integration and meta-analysis.

Authors:  Raivo Kolde; Sven Laur; Priit Adler; Jaak Vilo
Journal:  Bioinformatics       Date:  2012-01-12       Impact factor: 6.937

9.  miR-375 suppresses IGF1R expression and contributes to inhibition of cell progression in laryngeal squamous cell carcinoma.

Authors:  Jie Luo; Jianhui Wu; Zenghong Li; Hao Qin; Bin Wang; Thian-Sze Wong; Weiqiang Yang; Qing-Ling Fu; Wenbin Lei
Journal:  Biomed Res Int       Date:  2014-08-12       Impact factor: 3.411

10.  MiR-9-3p augments apoptosis induced by H2O2 through down regulation of Herpud1 in glioma.

Authors:  Ling Yang; Yongping Mu; Hongwei Cui; Yabing Liang; Xiulan Su
Journal:  PLoS One       Date:  2017-04-21       Impact factor: 3.240

View more
  1 in total

1.  Identifying anal and cervical tumorigenesis-associated methylation signaling with machine learning methods.

Authors:  Fangfang Jian; FeiMing Huang; Yu-Hang Zhang; Tao Huang; Yu-Dong Cai
Journal:  Front Oncol       Date:  2022-09-29       Impact factor: 5.738

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.