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Exploring the molecular pathogenesis and biomarkers of high risk oral premalignant lesions on the basis of long noncoding RNA expression profiling by serial analysis of gene expression

机译:通过长期的非编码RNA表达谱分析和基因表达序列分析探索高风险口腔癌前病变的分子发病机制和生物标志物

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摘要

Oral premalignant lesions (OPLs) have malignant transformation potential, with no reliable markers available. This study aimed to assess molecular events to identify biomarkers that can reflect high-risk lesions as predictive factors to tailor clinical decision for patients on the basis of long noncoding RNAs (lncRNA) expression profiling by serial analysis of gene expression. The and datasets were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and lncRNAs were identified using the LIMMA package in R language. The genes targeted by lncRNAs were predicted among screened DEGs using Pearson’s correlation. Gene ontology function and Kyoto Encyclopedia of Genes and Genomes pathway analyses were carried out for genes targeted by lncRNAs using the Database for Annotation, Visualization, and Integrated Discovery online tool. A total of 674 DEGs and differentially expressed lncRNAs were screened. Thirty-two interactions of 10 lncRNAs and 524 target genes were predicted. The lncRNA NEAT1 was among the top 10 lncRNAs. The coregulated target genes RP4-684O24, RP11-283I3, and RP11-350G8 were significantly enriched in the immune response and mannosyl-oligosaccharide mannosidase activity. The target genes coregulated by LINC00665 and MIR378D2 were significantly enriched in the ubiquitin-dependent protein catabolic process, ubiquitin-protein ligase activity, and neurotrophin signaling. The lncRNA NEAT1 may play an important role in high-risk lesions. The novel lncRNAs and DEGs identified in OPLs may mediate the immune response and neurotrophin signaling and show ubiquitin ligase activity. These results improve our understanding of the molecular pathogenesis of OPLs and identify some potential targets for early diagnosis of high risk OPLs.
机译:口腔恶变前病变(OPL)具有恶变的潜力,没有可靠的标记物。这项研究旨在评估分子事件,以识别可以反映高危病变的生物标志物,作为通过对基因表达进行序列分析的长非编码RNA(lncRNA)表达谱来调整患者临床决策的预测因素。和数据集是从Gene Expression Omnibus数据库下载的。使用LI语言的LIMMA软件包识别了差异表达的基因(DEG)和lncRNA。使用皮尔逊相关性,在筛选出的DEG中预测了lncRNA靶向的基因。使用注释,可视化和集成发现数据库在线工具对lncRNA靶向的基因进行了基因本体功能和《京都议定书》的《基因与基因组百科全书》。总共筛选了674个DEG和差异表达的lncRNA。预测了10个lncRNA与524个靶基因的三十二种相互作用。 lncRNA NEAT1在前10个lncRNA中。具有核心功能的靶基因RP4-684O24,RP11-283I3和RP11-350G8的免疫反应和甘露糖寡糖甘露糖苷酶活性显着丰富。由LINC00665和MIR378D2整合的靶基因在泛素依赖性蛋白分解代谢过程,泛素蛋白连接酶活性和神经营养蛋白信号转导中显着富集。 lncRNA NEAT1可能在高危病变中起重要作用。在OPL中鉴定出的新型lncRNA和DEG可能介导免疫应答和神经营养蛋白信号传导,并显示泛素连接酶活性。这些结果增进了我们对OPL分子发病机理的了解,并确定了一些早期诊断高危OPL的潜在目标。

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