Department of Stomatology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China.
School of Basic Medical Sciences, Hebei Medical University, Shijiazhuang, China.
J Comput Biol. 2020 Jan;27(1):40-54. doi: 10.1089/cmb.2019.0211. Epub 2019 Aug 19.
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.
本研究旨在通过生物信息学分析，从分子水平探讨口腔鳞状细胞癌（OSCC）的关键基因、微小 RNA（miRNA）和发病机制，为药物靶点的筛选提供理论依据。从基因表达综合数据库（GEO）中获取 OSCC 数据。通过 GEO2R 分析鉴定差异表达基因（DEGs）。接下来，通过 Search Tool for the Retrieval of Interacting Gene 构建 DEGs 的蛋白质-蛋白质相互作用（PPI）网络，并通过 Cytoscape 可视化，然后通过 Cytoscape 筛选出枢纽基因。通过数据库 for Annotation、Visualization and Integrated Discovery 进行基因本体（GO）分析和京都基因与基因组百科全书（KEGG）分析。通过 TargetScan 筛选可能调节枢纽基因的 miRNA，并对 miRNA 进行 GO 和 KEGG 分析。通过 Kaplan-Meier plotter 进行 DEGs 的生存分析。最后，通过比较毒理学基因组数据库分析基因产物与肿瘤之间的关系。共鉴定出 121 个差异基因。获得 135 个 GO 术语和 56 条通路，主要与 PI3K-Akt 信号通路、FoxO 信号通路、Wnt 信号通路、细胞周期、p53 信号通路、细胞衰老等通路有关；通过 PPI 网络中的模块分析，鉴定出 10 个枢纽基因。最后，对 10 个枢纽基因进行生存分析，结果显示 MMP1、MMP3 和 C-X-C 基序趋化因子配体（CXCL）1 低表达，CXCL9 和 CXCL10 高表达，OSCC 患者 5 年总生存率显著降低。本研究分析了 OSCC 的差异基因，有助于我们系统地了解 OSCC 发生发展的致病机制。MMP1、MMP3、CXCL1、CXCL9 和 CXCL10 基因可能作为潜在的治疗靶点，提高 OSCC 的诊断水平，并作为 OSCC 的免疫治疗标志物。
