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首页> 外文期刊>American Journal of Translational Research >Identification of key miRNA-gene pairs in gastric cancer through integrated analysis of mRNA and miRNA microarray
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Identification of key miRNA-gene pairs in gastric cancer through integrated analysis of mRNA and miRNA microarray

机译:通过MRNA和miRNA微阵列综合分析鉴定胃癌中的关键miRNA-基对

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Nowadays, the current bioinformatic methods have been increasingly applied in the field of oncological research. In this study, we expect a better understanding of the molecular mechanism of gastric cancer from the bioinformatic methods. By systematically addressing the differential expression of microRNAs (miRNAs) and mRNAs between gastric cancer specimens and normal gastric specimens with the application of bioinformatics tools, A total of 206 DEGs and 38 DEMs were identified. The Gene Ontology (GO) analysis of Annotation, Visualization and Integrated Discovery (DAVID) database revealed that the differentially expressed genes (DEGs) were significantly enriched in biological process, molecular function and cellular component, while Kyoto Encyclopedia of Genes and Genomes (KEGG) database showed DEGs were significantly enriched in 8 signal pathways. The miRNA-gene regulatory network was constructed based on 385 miRNA-gene (DEM-DEG) pairs, consisting of 35 miRNAs and 107 target genes. In the regulatory network, the top 5 up-regulated genes were Transmembrane Protease, Serine 11B (TMPRSS11B), regulator of G protein signaling 1 (RGS1), cysteine rich angiogenic inducer 61 (CYR61), inhibin subunit beta A (INHBA), syntrophin gamma 1 (SNTG1), and the top 5 down-regulated genes were tumor necrosis factor receptor superfamily, member 19 (TNFRSF19), pleckstrin homology domain containing B2 (PLEKHB2), Tax1 binding protein 3 (TAX1BP3), presenilin enhancer, gamma-secretase subunit (PSENEN), NME/NM23 nucleoside diphosphate kinase 3 (NME3). Based on the gastric cancer patient database from Kaplan-Meier Plotter tools, we found that 8 of 10 genes with most significant changes in the miRNA-gene regulatory network possessed a prognostic value for survival time of gastric cancer patients. Patients with higher level of RGS1, PLEKHB2, TAX1BP3 and PSENEN in gastric cancer had a longer survival time compared with the patients with lower level of these genes. On the contrary, patients with higher level of INHBA, SNTG1, TNFRSF19 and NME3 were found associated with a shorter survival time. In conclusion, our findings provided several potential targets regarding gastric cancer, which may result in a new strategy to treat gastric cancer from a system rather than a single-gene perspective.
机译:如今,目前的生物信息方法越来越多地应用于肿瘤学研究领域。在这项研究中,我们期望从生物信息方法中更好地了解胃癌的分子机制。通过系统地解决胃癌标本和正常胃标本之间的MicroRNA(miRNA)和MRNA的差异表达,通过应用生物信息学工具,共鉴定了总共206℃和38个DEM。基因本体论(GO)对注释,可视化和集成发现(David)数据库的分析显示,差异表达的基因(DEGS)在生物过程中显着富集,分子功能和细胞组分,而Kyoto基因和基因组(Kegg)数据库显示DEG在8个信号途径中显着富集。基于385 miRNA-基因(DEM-DEG)对构建的miRNA-基因调节网络,由35 miRNA和107个靶基因组成。在监管网络中,前5个上调基因是跨膜蛋白酶,丝氨酸11b(Tmprs11b),G蛋白信号传导的调节剂1(RGS1),半胱氨酸富血管生成诱导剂61(Cyr61),抑制蛋白亚单位βa(Inhba),Syntrophin γ1(SNTG1)和前5个下调基因是肿瘤坏死因子受体超家族,构件19(TNFRSF19),含有B2(PLEKHB2)的Pleckstrin同源结构域,税1结合蛋白3(税1.BP3),PresenIlin Enhancer,γ-分泌酶亚基(脂酮),NME / NM23核苷二磷酸激酶3(NME3)。基于来自Kaplan-Meier绘图仪工具的胃癌患者数据库,我们发现MiRNA-基因调节网络中具有最显着变化的10个基因具有胃癌患者的存活时间的预后值。 RGS1,PlekhB2,毒性患者患者患者患者胃癌中的患者与这些基因较低的患者相比,生存时间更长。相反,发现患有较高水平的InHBA,SNTG1,TNFRSF19和NME3与较短的存活时间相关。总之,我们的研究结果提供了有关胃癌的几种潜在目标,这可能导致从系统而不是单基因的角度来治疗胃癌的新策略。

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