Investigating age-induced differentially expressed genes and potential molecular mechanisms in osteosarcoma based on integrated bioinformatics analysis

被引:12
|
作者
Wang, Jian-Sheng [1 ]
Duan, Ming-Yue [2 ]
Zhong, Yong-Sheng [3 ]
Li, Xue-Dong [4 ]
Du, Shi-Xin [4 ]
Xie, Peng [4 ]
Zheng, Gui-Zhou [4 ]
Han, Jing-Ming [1 ]
机构
[1] Shenzhen Childrens Hosp, Dept Orthoped, Ward 2, 7019 Yitian Rd, Shenzhen 518038, Guangdong, Peoples R China
[2] Xian Childrens Hosp, Shanxi Inst Pediat Dis, Xian 710043, Shanxi, Peoples R China
[3] Shantou Univ, Med Coll, Affiliated Hosp 1, Dept Neurosurg, Shantou 515041, Guangdong, Peoples R China
[4] Shenzhen Univ, Hlth Sci Ctr, Affiliated Hosp 3, Dept Orthoped, Shenzhen 518000, Guangdong, Peoples R China
关键词
osteosarcoma; age; Gene Expression Omnibus data; integrated bioinformatics; regulatory network; SUPPRESSES TUMOR-GROWTH; PROGNOSTIC-FACTORS; POTASSIUM CHANNELS; DOWN-REGULATION; EXTREMITY; PROMOTES; SURVIVAL; MIR-21;
D O I
10.3892/mmr.2019.9912
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Osteosarcoma (OS) is the most common primary bone malignancy. It predominantly occurs in adolescents, but can develop at any age. The age at diagnosis is a prognostic factor of OS, but the molecular basis of this remains unknown. The current study aimed to identify age-induced differentially expressed genes (DEGs) and potential molecular mechanisms that contribute to the different outcomes of patients with OS. Microarray data (GSE39058 and GSE39040) obtained from the Gene Expression Omnibus database and used to analyze age-induced DEGs to reveal molecular mechanism of OS among different age groups (<20 and >20 years old). Differentially expressed mRNAs (DEMs) were divided into up and downregulated DEMs (according to the expression fold change), then Gene Ontology function enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed. Furthermore, the interactions among proteins encoded by DEMs were integrated with prediction for microRNA-mRNA interactions to construct a regulatory network. The key subnetwork was extracted and Kaplan-Meier survival analysis for a key microRNA was performed. DEMs within the subnetwork were predominantly involved in ubiquitin protein ligase binding', response to growth factor', regulation of type I interferon production', response to decreased oxygen levels', voltage-gated potassium channel complex', synapse part', regulation of stem cell proliferation'. In summary, integrated bioinformatics was applied to analyze the potential molecular mechanisms leading to different outcomes of patients with OS among different age groups. The hub genes within the key subnetwork may have crucial roles in the different outcomes associated with age and require further analysis.
引用
收藏
页码:2729 / 2739
页数:11
相关论文
共 24 条
  • [21] Identification of Potential Key Genes Associated With the Pathogenesis and Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis
    Liu, Xinkui
    Wu, Jiarui
    Zhang, Dan
    Bing, Zhitong
    Tian, Jinhui
    Ni, Mengwei
    Zhang, Xiaomeng
    Meng, Ziqi
    Liu, Shuyu
    FRONTIERS IN GENETICS, 2018, 9
  • [22] Identification of a 3-gene signature based on differentially expressed invasion genes related to cancer molecular subtypes to predict the prognosis of osteosarcoma patients
    Wan, Yue
    Qu, Ning
    Yang, Yang
    Ma, Jing
    Li, Zhe
    Zhang, Zhenyu
    BIOENGINEERED, 2021, 12 (01) : 5916 - 5931
  • [23] Exploration of estrogen receptor-associated hub genes and potential molecular mechanisms in non-smoking females with lung adenocarcinoma using integrated bioinformatics analysis
    Wang, Hao
    Zhang, Zhihong
    Xu, Ke
    Wei, Song
    Li, Lailing
    Wang, Lijun
    ONCOLOGY LETTERS, 2019, 18 (05) : 4605 - 4612
  • [24] CENPA is one of the potential key genes associated with the proliferation and prognosis of ovarian cancer based on integrated bioinformatics analysis and regulated by MYBL2
    Han, Jing
    Xie, Rongkai
    Yang, Ying
    Chen, Diangang
    Liu, Li
    Wu, Jiayang
    Li, Sufen
    TRANSLATIONAL CANCER RESEARCH, 2021, 10 (09) : 4076 - 4086