Literature DB >> 26782416

Selecting key genes associated with osteosarcoma based on a differential expression network.

Y B Wang1, N Jia1, C M Xu2, L Zhao1, Y Zhao1, X Wang1, T H Jia3.   

Abstract

Despite recent advances in osteosarcoma diagnosis and therapy, much remains unclear about the molecular mechanisms involved in the disorder, and the discovery of novel drug-targeted genes is essential. We explored the potential molecular mechanisms and target genes involved in the development and progression of osteosarcoma. First, we identified the differentially expressed genes in osteosarcoma patients and matching normal controls. We then constructed a differential expression network based on differential and non-differential interactions. Pathway-enrichment analysis was performed based on the nodes contained in the main differential expression network. Centrality analysis was used to select hub genes that may play vital roles in the progression of human osteosarcoma. Our research revealed a total of 176 differentially expressed genes including 82 upregulated and 94 downregulated genes. A differential expression network was constructed that included 992 gene pairs (1043 nodes). Pathway-enrichment analysis indicated that the nodes in the differential expression network were mainly enriched in several pathways such as those involved in cancer, cell cycle, ubiquitin-mediated proteolysis, DNA replication, ribosomes, T-cell receptor signaling, spliceosomes, neurotrophin signaling, oxidative phosphorylation, and tight junctions. Six hub genes (APP, UBC, CAND1, RPA, YWHAG, and NEDD8) were discovered; of these, two genes (UBC and RPA) were also found to be disease genes. Our study predicted that UBC and RPA had potential as target genes for the diagnosis and treatment of osteosarcoma.

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Year:  2015        PMID: 26782416     DOI: 10.4238/2015.December.21.44

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


  4 in total

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2.  Suppression of 14-3-3γ-mediated surface expression of ANO1 inhibits cancer progression of glioblastoma cells.

Authors:  Young-Sun Lee; Jae Kwang Lee; Yeonju Bae; Bok-Soon Lee; Eunju Kim; Chang-Hoon Cho; Kanghyun Ryoo; Jiyun Yoo; Chul-Ho Kim; Gwan-Su Yi; Seok-Geun Lee; C Justin Lee; Sang Soo Kang; Eun Mi Hwang; Jae-Yong Park
Journal:  Sci Rep       Date:  2016-05-23       Impact factor: 4.379

3.  Identification of key gene modules for human osteosarcoma by co-expression analysis.

Authors:  Jing Zhang; Qing Lan; Jiasheng Lin
Journal:  World J Surg Oncol       Date:  2018-05-02       Impact factor: 2.754

4.  Weighted gene co-expression network analysis revealed key biomarkers associated with the diagnosis of hypertrophic cardiomyopathy.

Authors:  Xin Li; Chenxin Wang; Xiaoqing Zhang; Jiali Liu; Yu Wang; Chunpu Li; Dongmei Guo
Journal:  Hereditas       Date:  2020-10-24       Impact factor: 3.271

  4 in total

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