Zhou Xiao-Li, Wu Jun-Hua, Wang Xin-Juan, Guo Fu-Jun
Department of Stomatology, The First Affiliated Hospital of Henan University of Science and Technology, Luoyang, Henan 471003, P.R. China.
Department of Prosthodontics, School of Stomatology, Tongji University, Shanghai 200072, P.R. China.
Mol Med Rep. 2015 Jul;12(1):885-94. doi: 10.3892/mmr.2015.3467. Epub 2015 Mar 11.
Tongue squamous cell carcinoma (TSCC) is a rare and aggressive type of cancer, which is associated with a poor prognosis. Identification of patients at high risk of TSCC tumorigenesis may provide information for the early detection of metastases, and for potential treatment strategies. MicroRNA (miRNA; miR) and mRNA expression profiling of TSCC tissue samples and normal control tissue samples were obtained from three Gene Expression Omnibus (GEO) data series. Bioinformatics analyses, including the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes were used to identify genes and pathways specifically associated with miRNA-associated TSCC oncology. A total of 25 miRNAs and 769 mRNAs were differentially expressed in the two groups assessed, and all the differentially expressed miRNA and mRNA target interactions were analyzed. The miRNA target genes were predominantly associated with 38 GO terms and 13 pathways. Of the genes differentially expressed between the two groups, and confirmed in another GEO series, miRNA-494, miRNA-96, miRNA-183, runt-related transcription factor 1, programmed cell death protein 4 and membrane-associated guanylate kinase were the most significantly altered, and may be central in the regulation of TSCC. Bioinformatics may be used to analyze large quantities of data in microarrays through rigorous experimental planning, statistical analysis and the collection of complete data on TSCC. In the present study, a novel differential miRNA-mRNA expression network was constructed, and further investigation may provide novel targets for the diagnosis of TSCC.
舌鳞状细胞癌（TSCC）是一种罕见且侵袭性强的癌症类型，其预后较差。识别TSCC发生肿瘤的高危患者可为转移的早期检测及潜在治疗策略提供信息。从三个基因表达综合数据库（GEO）数据系列中获取TSCC组织样本和正常对照组织样本的微小RNA（miRNA；miR）和mRNA表达谱。运用包括基因本体论（GO）和京都基因与基因组百科全书在内的生物信息学分析来识别与miRNA相关的TSCC肿瘤学特异性相关的基因和通路。在评估的两组中共有25个miRNA和769个mRNA差异表达，并对所有差异表达的miRNA与mRNA的靶标相互作用进行了分析。miRNA靶基因主要与38个GO术语和13条通路相关。在两组之间差异表达且在另一个GEO系列中得到证实的基因中，miRNA-494、miRNA-96、miRNA-183、 runt相关转录因子1、程序性细胞死亡蛋白4和膜相关鸟苷酸激酶的变化最为显著，可能在TSCC的调控中起核心作用。通过严谨的实验设计、统计分析以及收集完整的TSCC数据，生物信息学可用于分析微阵列中的大量数据。在本研究中，构建了一个新的差异miRNA-mRNA表达网络，进一步研究可能为TSCC的诊断提供新的靶点。
