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Integrated analysis of long non-coding RNAs and mRNA expression profiles reveals the potential role of lncRNAs in gastric cancer pathogenesis

机译:长时间非编码RNA和mRNA表达谱的综合分析揭示了lncRNA在胃癌发病机理中的潜在作用

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Long non-coding RNAs (lncRNAs) have been shown to play a critical role in cancer biology and are frequently aberrantly expressed. Despite their important role in pathology, little is known mechanistically regarding their role in gastric cancer (GC) pathogenesis. To characterize the role of lncRNAs in GC pathogenesis, 8 paired human GC tissue samples and matched adjacent normal tissue were examined. Large scale expression profiling of lncRNA and mRNA was performed utilizing microarray technology and validated by qPCR. Differentially expressed lncRNAs were subjected to bioinformatic analysis to predict target genes, followed by the integration of differentially expressed mRNA data and GO and network analysis to further characterize potential interactions. In our study, 2,621 lncRNAs and 3,121?mRNAs were identi?ed to be differentially expressed (≥2.0-fold change) in GC samples relative to their matched counterparts. lncRNA target prediction revealed the presence of 221 potential lncRNA-mRNA target pairs for the 75 differentially expressed lncRNAs and 60 differentially expressed genes. KEGG pathway analysis showed that these target genes were significantly enriched in 7 different pathways, of which the p53 signaling pathway was the most signi?cant and has been previously implicated in GC pathogenesis. Construction of a lncRNA-mRNA correlation network revealed 10 differentially expressed lncRNAs potentially regulating the p53 signaling pathway. Overall, this is the first study perform global expression profiling of lncRNAs and mRNAs relating to GC. These results may provide important information for further insights into the pathogenesis of GC and provide potential targets for future therapeutics.
机译:长的非编码RNA(lncRNA)已显示在癌症生物学中起关键作用,并经常异常表达。尽管它们在病理学中具有重要作用,但对其在胃癌(GC)发病机理中的作用机理在机理上知之甚少。为了表征lncRNA在GC发病机理中的作用,检查了8对配对的人GC组织样品和匹配的邻近正常组织。利用微阵列技术进行了lncRNA和mRNA的大规模表达谱分析,并通过qPCR进行了验证。对差异表达的lncRNA进行生物信息学分析以预测靶基因,然后整合差异表达的mRNA数据和GO并进行网络分析以进一步表征潜在的相互作用。在我们的研究中,鉴定出2,621个lncRNA和3,121个mRNA在GC样品中与其匹配的同等物差异表达(变化2.0倍以上)。 lncRNA靶标预测揭示了75个差异表达的lncRNAs和60个差异表达基因中存在221个潜在的lncRNA-mRNA靶标对。 KEGG通路分析表明,这些靶基因在7种不同通路中均显着富集,其中p53信号通路最为重要,并且先前已涉及GC的发病机理。 lncRNA-mRNA相关网络的构建揭示了10个差异表达的lncRNA,它们可能调节p53信号通路。总的来说,这是第一项进行与GC相关的lncRNA和mRNA整体表达谱分析的研究。这些结果可能为进一步深入了解GC的发病机理提供重要信息,并为将来的治疗提供潜在的靶标。

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