Guan Guo-Fang, Zheng Ying, Wen Lian-Ji, Zhang De-Jun, Yu Duo-Jiao, Lu Yan-Qing, Zhao Yan, Zhang Hui
Department of Otolaryngology, Head and Neck Surgery, The Second Hospital of Jilin University, Changchun, Jilin 130041, P.R. China.
Department of Otolaryngology, Head and Neck Surgery, Tumor Hospital of Jilin Province, Changchun, Jilin 130012, P.R. China.
Mol Med Rep. 2015 Aug;12(2):2457-64. doi: 10.3892/mmr.2015.3701. Epub 2015 Apr 29.
The present study aimed to identify key genes and relevant microRNAs (miRNAs) involved in laryngeal squamous cell carcinoma (LSCC). The gene expression profiles of LSCC tissue samples were analyzed with various bioinformatics tools. A gene expression data set (GSE51985), including ten laryngeal squamous cell carcinoma (LSCC) tissue samples and ten adjacent non-neoplastic tissue samples, was downloaded from the Gene Expression Omnibus. Differential analysis was performed using software package limma of R. Functional enrichment analysis was applied to the differentially expressed genes (DEGs) using the Database for Annotation, Visualization and Integrated Discovery. Protein-protein interaction (PPI) networks were constructed for the protein products using information from the Search Tool for the Retrieval of Interacting Genes/Proteins. Module analysis was performed using ClusterONE (a software plugin from Cytoscape). MicroRNAs (miRNAs) regulating the DEGs were predicted using WebGestalt. A total of 461 DEGs were identified in LSCC, 297 of which were upregulated and 164 of which were downregulated. Cell cycle, proteasome and DNA replication were significantly over-represented in the upregulated genes, while the ribosome was significantly over-represented in the downregulated genes. Two PPI networks were constructed for the up- and downregulated genes. One module from the upregulated gene network was associated with protein kinase. Numerous miRNAs associated with LSCC were predicted, including miRNA (miR)-25, miR-32, miR-92 and miR-29. In conclusion, numerous key genes and pathways involved in LSCC were revealed, which may aid the advancement of current knowledge regarding the pathogenesis of LSCC. In addition, relevant miRNAs were also identified, which may represent potential biomarkers for use in the diagnosis or treatment of the disease.
本研究旨在鉴定喉鳞状细胞癌（LSCC）中涉及的关键基因和相关微小RNA（miRNA）。使用各种生物信息学工具分析了LSCC组织样本的基因表达谱。从基因表达综合数据库下载了一个基因表达数据集（GSE51985），其中包括10个喉鳞状细胞癌（LSCC）组织样本和10个相邻的非肿瘤组织样本。使用R语言的limma软件包进行差异分析。使用注释、可视化和综合发现数据库对差异表达基因（DEG）进行功能富集分析。利用相互作用基因/蛋白质检索工具的信息为蛋白质产物构建蛋白质-蛋白质相互作用（PPI）网络。使用ClusterONE（Cytoscape的一个软件插件）进行模块分析。使用WebGestalt预测调控DEG的微小RNA（miRNA）。在LSCC中总共鉴定出461个DEG，其中297个上调，164个下调。细胞周期、蛋白酶体和DNA复制在上调基因中显著富集，而核糖体在下调基因中显著富集。为上调和下调基因构建了两个PPI网络。上调基因网络中的一个模块与蛋白激酶相关。预测了许多与LSCC相关的miRNA，包括miRNA（miR）-25、miR-32、miR-92和miR-29。总之，揭示了许多参与LSCC的关键基因和途径，这可能有助于增进目前对LSCC发病机制的了解。此外，还鉴定出了相关的miRNA，它们可能代表用于该疾病诊断或治疗的潜在生物标志物。
