Literature DB >> 26600477

Analysis of the gene-protein interaction network in glioma.

C Zhou1, W J Teng2, J Zhuang1, H L Liu3, S F Tang1, X J Cao4, B N Qin4, C C Wang4, C G Sun5.   

Abstract

Glioma is the most aggressive type of brain tumor. Great progress has been achieved in glioma treatment, but the protein-protein interaction networks underlining glioma are poorly understood. We identified the protein-protein interaction network for glioma based on gene expression and predicted biological pathways underlying the molecular complexes in the network. Genes involved in glioma were selected from the Online Mendelian Inheritance in Man (OMIM) database. A literature search was performed using the Agilent Literature Search plugin, and Cytoscape was used to establish a protein-protein interaction network. The molecular complexes in the network were detected using the Clusterviz plugin, and pathway enrichment of molecular complexes was performed using DAVID online. There were 378 glioma genes in the OMIM database. The protein-protein interaction network in glioma contained 1814 nodes, 6471 edges, and 8 molecular complexes. There were 17 pathways (false discovery rate <1), which were related to cytokine-cytokine receptor interaction, Toll-like receptor signaling pathway, chemokine signaling pathway, oocyte meiosis, progesterone-mediated oocyte maturation, transmembrane transport of small molecules, metabolism of amino acids, and notch signaling pathway, among others. Our results provide a bioinformatic foundation for further studies of the mechanisms of glioma.

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Year:  2015        PMID: 26600477     DOI: 10.4238/2015.November.13.3

Source DB:  PubMed          Journal:  Genet Mol Res        ISSN: 1676-5680


  4 in total

1.  Leucine-rich glioma inactivated 3: integrative analyses support its prognostic role in glioma.

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Journal:  Onco Targets Ther       Date:  2017-05-24       Impact factor: 4.147

2.  Long Noncoding RNA MEG3 Suppresses Glioma Cell Proliferation, Migration, and Invasion by Acting as a Competing Endogenous RNA of miR-19a.

Authors:  Nan Qin; Gui-Feng Tong; Li-Wei Sun; Xiao-Lin Xu
Journal:  Oncol Res       Date:  2017-03-08       Impact factor: 5.574

3.  Gene biomarker prediction in glioma by integrating scRNA-seq data and gene regulatory network.

Authors:  Guimin Qin; Longting Du; Yuying Ma; Yu Yin; Liming Wang
Journal:  BMC Med Genomics       Date:  2021-12-04       Impact factor: 3.063

4.  Identification of new progestogen-associated networks in mammalian ovulation using bioinformatics.

Authors:  Fang Yang; Meng Wang; Baoyun Zhang; Wei Xiang; Ke Zhang; Mingxin Chu; Pingqing Wang
Journal:  BMC Syst Biol       Date:  2018-04-03
  4 in total

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