Identification of Key Biomarkers and Potential Molecular Mechanisms in Oral Squamous Cell Carcinoma by Bioinformatics Analysis

被引:19
|
作者
Yang, Bao [1 ]
Dong, Keqin [2 ]
Guo, Peiyuan [2 ]
Guo, Peng [3 ]
Jie, Guo [1 ]
Zhang, Guanhua [1 ]
Li, Tianke [1 ]
机构
[1] Hebei Med Univ, Dept Stomatol, Hosp 4, 12 Hlth Rd, Shijiazhuang 050011, Hebei, Peoples R China
[2] Hebei Med Univ, Sch Basic Med Sci, Shijiazhuang, Hebei, Peoples R China
[3] Hebei Med Univ, Dept Orthoped, Hosp 4, Shijiazhuang, Hebei, Peoples R China
关键词
bioinformatics; differentially expressed gene; oral squamous cell carcinoma; CANCER-ASSOCIATED FIBROBLASTS; TUMOR-ASSOCIATED MACROPHAGES; MATRIX-METALLOPROTEINASE; SIGNALING PATHWAY; CXCL10; PROGRESSION; INHIBITION; ACTIVATION; EXPRESSION; RELEVANCE;
D O I
10.1089/cmb.2019.0211
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The aim of this study was to explore the key genes, microRNA (miRNA), and the pathogenesis of oral squamous cell carcinoma (OSCC) at the molecular level through the analysis of bioinformatics, which could provide a theoretical basis for the screening of drug targets. Data of OSCC were obtained from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified via GEO2R analysis. Next, protein-protein interaction (PPI) network of DEGs was constructed through Search Tool for the Retrieval of Interacting Gene and visualized via Cytoscape, whereas the hub genes were screened out with Cytoscape. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed by Database for Annotation, Visualization and Integrated Discovery. The miRNA, which might regulate hub genes, were screened out with TargetScan and GO and KEGG analysis of miRNA was performed by DNA Intelligent Analysis-miRPath. Survival analyses of DEGs were conducted via the Kaplan-Meier plotter. Finally, the relationships between gene products and tumors were analyzed by Comparative Toxicogenomics Database. A total of 121 differential genes were identified. One hundred thirty-five GO terms and 56 pathways were obtained, which were mainly related to PI3K-Akt signals pathway, FoxO signaling pathway, Wnt signaling pathway, cell cycle, p53 signaling pathway, cellular senescence, and other pathways; 10 genes were identified as hub genes through modules analyses in the PPI network. Finally, a survival analysis of 10 hub genes was conducted, which showed that the low expression of matrix metalloproteinase (MMP)1, MMP3, and C-X-C motif chemokine ligand (CXCL)1 and the high expression of CXCL9 and CXCL10 resulted in a significantly poor 5-year overall survival rate in patients with OSCC. In this study, the DEGs of OSCC was analyzed, which assists us in a systematic understanding of the pathogenicity underlying occurrence and development of OSCC. The MMP1, MMP3, CXCL1, CXCL9, and CXCL10 genes might be used as potential targets to improve diagnosis and as immunotherapy biomarkers for OSCC.
引用
收藏
页码:40 / 54
页数:15
相关论文
共 50 条
  • [41] Identification of seven miRNAs as potential biomarkers for oral lichen planus and oral squamous cell carcinoma - A pilot study
    Shi, Wen
    Feng, Zhendong
    Zhao, Chuanke
    Lv, Guanting
    Shan, Xiaofeng
    Hu, Hong
    Zhou, Demin
    Cai, Zhigang
    ORAL ONCOLOGY, 2013, 49 : S4 - S5
  • [42] Identification of potential therapeutic target genes, key miRNAs and mechanisms in oral lichen planus by bioinformatics analysis
    Gong, Cuihua
    Sun, Shangtong
    Liu, Bing
    Wang, Jing
    Chen, Xiaodong
    ARCHIVES OF ORAL BIOLOGY, 2017, 78 : 122 - 128
  • [43] Identification of potential biomarkers for papillary thyroid carcinoma by comprehensive bioinformatics analysis
    Min Liao
    Zhen Wang
    Jiawei Yao
    Hengte Xing
    Yarong Hao
    Bo Qiu
    Molecular and Cellular Biochemistry, 2023, 478 : 2111 - 2123
  • [44] Identification of key genes for esophageal squamous cell carcinoma via integrated bioinformatics analysis and experimental confirmation
    Hu, Jia
    Li, Rongzhen
    Miao, Huikai
    Wen, Zhesheng
    JOURNAL OF THORACIC DISEASE, 2020, 12 (06) : 3188 - +
  • [45] Identification of potential biomarkers for progression and prognosis of renal clear cell carcinoma by comprehensive bioinformatics analysis
    Dong, Haonan
    He, Zexi
    Wang, Haifeng
    Ding, Mingxia
    Huang, Yinglong
    Li, Haihao
    Shi, Hongjin
    Mao, Lan
    Hu, Chongzhi
    Wang, Jiansong
    TECHNOLOGY AND HEALTH CARE, 2024, 32 (02) : 897 - 914
  • [46] Identification of potential biomarkers for papillary thyroid carcinoma by comprehensive bioinformatics analysis
    Liao, Min
    Wang, Zhen
    Yao, Jiawei
    Xing, Hengte
    Hao, Yarong
    Qiu, Bo
    MOLECULAR AND CELLULAR BIOCHEMISTRY, 2023, 478 (09) : 2111 - 2123
  • [47] Identification of potential key genes and key pathways related to clear cell renal cell carcinoma through bioinformatics analysis
    Zhai, Wenxin
    Lu, Haijiao
    Dong, Shenghua
    Fang, Jing
    Yu, Zhuang
    ACTA BIOCHIMICA ET BIOPHYSICA SINICA, 2020, 52 (08) : 853 - 863
  • [48] The Screening and Identification of Key Biomarkers in Adrenocortical Carcinoma: Evidence from a Bioinformatics Analysis
    Yan, Xin
    Liang, Chunfeng
    Liang, Xinghuan
    Li, Li
    Huang, Zhenxing
    Yang, Haiyan
    Qin, Yingfen
    Lu, Decheng
    Ma, Yan
    Luo, Zuojie
    JOURNAL OF BIOMATERIALS AND TISSUE ENGINEERING, 2022, 12 (03) : 523 - 532
  • [49] Screening and identification of key biomarkers in bladder carcinoma: Evidence from bioinformatics analysis
    Yan, Meiqin
    Jing, Xuan
    Liu, Yina
    Cui, Xiangrong
    ONCOLOGY LETTERS, 2018, 16 (03) : 3092 - 3100
  • [50] Identification of microbial biomarkers to predict recurrence of oral squamous cell carcinoma
    Lyu, Wei-Ni
    Lin, Mei-Chun
    Lou, Pei-Jen
    Lai, Liang-Chuan
    Tsai, Mong-Hsun
    CANCER RESEARCH, 2023, 83 (07)