Construction of miRNA-mRNA-TF Regulatory Network for Diagnosis of Gastric Cancer.
Construction of miRNA-mRNA-TF Regulatory Network for Diagnosis of Gastric Cancer.
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胃癌诊断中miRNA-mRNA-TF调控网络的构建
DOI：
10.1155/2021/9121478
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发表时间：
2021
影响因子：
--
通讯作者：
Chen Y
中科院分区：
文献类型：
--
作者：
Fu Z;Xu Y;Chen Y;Lv H;Chen G;Chen Y
胃癌（GC）作为全球范围内的流行性癌症，2020年全球新发病例超过100万例，估计死亡76.9万例，在全球发病率和死亡率中分别排名第五和第四。在哺乳动物中，miRNA和转录因子（TF）在基因表达调控中起部分作用。采用GEO 2 R软件对GEO数据库中的mRNA表达谱和miRNA表达谱进行筛选，寻找差异表达基因（DEG）和差异表达miRNA（DEM）。然后，大卫注释了DEG的功能，以了解在生物过程中发挥的功能。分别用mipathDB V2. 0和CHEA 3对miRNA的潜在靶基因和mRNA的关键转录因子进行预测，并进行基因列表比较，寻找关键转录因子和DEM共同调控的重叠基因。最后，利用获得的miRNAs、TF和重叠基因构建miRNA-mRNA-TF调控网络，并通过RT-qPCR进行验证。从mRNA（GSE 26899、GSE 29998、GSE 51575和GSE 13911）和miRNA（GSE 93415）的表达谱中分别鉴定出76个上调的DEG、199个下调的DEG和3个上调的miRNA（miR-199 a-3 p/miR-199 b-3 p、miR-125 b-5 p和miR-199 a-5 p）。通过数据库预测和基因列表比较发现，在199个下调的DEG中，分别有61、71和69个基因是miR-199 a-3 p/miR-199 b-3 p、miR-125 b-5 p和miR-199 a-5 p的潜在靶基因。以199个下调的DEGs作为关键转录因子预测的基因列表，结果显示RFX 6的预测效果最好。miR-199 a-3 p/miR-199 b-3 p、miR-125 b-5 p和miR-199 a-5 p的潜在靶重叠基因分别为4个基因（SH 3GL 2、ATP 4 B、CTSE和SORBS 2）、7个基因（SLC 7A 8、RNASE 4、ESRRG、PGC、MUC 6、Fam 3B和FMO 5）和6个基因（CHGA、PDK 4、TMPRSS 2、CLIC 6、GPX 3和PSCA）。最后，基于上述17个mRNA、3个miRNA和1个TF构建了一个miRNA-mRNA-TF调控网络，并通过RT-qPCR和western blot验证了RFX 6在胃癌组织中的表达下调。这些鉴定的miRNAs、mRNAs和TF对进一步探讨GC的调控机制具有一定的参考价值。
Gastric cancer (GC), as an epidemic cancer worldwide, has more than 1 million new cases and an estimated 769,000 deaths worldwide in 2020, ranking fifth and fourth in global morbidity and mortality. In mammals, both miRNAs and transcription factors (TFs) play a partial role in gene expression regulation. The mRNA expression profile and miRNA expression profile of GEO database were screened by GEO2R for differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs). Then, DAVID annotated the functions of DEGs to understand the functions played in biological processes. The prediction of potential target genes of miRNA and key TFs of mRNA was performed by mipathDB V2.0 and CHEA3, respectively, and the gene list comparison was performed to look for overlapping genes coregulated by key TFs and DEMs. Finally, the obtained miRNAs, TF, and overlapping genes were used to construct the miRNA-mRNA-TF regulatory network, which was verified by RT-qPCR. 76 upregulated DEGs, 199 downregulated DEGs, and 3 upregulated miRNAs (miR-199a-3p/miR-199b-3p, miR-125b-5p, and miR-199a-5p) were identified from the expression profiles of mRNA (GSE26899, GSE29998, GSE51575, and GSE13911) and miRNA (GSE93415), respectively. Through database prediction and gene list comparison, it was found that among the 199 downregulated DEGs, 61, 71, and 69 genes were the potential targets of miR-199a-3p/miR-199b-3p, miR-125b-5p, and miR-199a-5p, respectively. 199 downregulated DEGs were used as the gene list for the prediction of key TFs, and the results showed that RFX6 ranked the highest. The potential target overlap genes of miR-199a-3p/miR-199b-3p, miR-125b-5p, and miR-199a-5p were 4 genes (SH3GL2, ATP4B, CTSE, and SORBS2), 7 genes (SLC7A8, RNASE4, ESRRG, PGC, MUC6, Fam3B, and FMO5), and 6 genes (CHGA, PDK4, TMPRSS2, CLIC6, GPX3, and PSCA), respectively. Finally, we constructed a miRNA-mRNA-TF regulatory network based on the above 17 mRNAs, 3 miRNAs, and 1 TF and verified by RT-qPCR and western blot results that the expression of RFX6 was downregulated in GC tissues. These identified miRNAs, mRNAs, and TF have a certain reference value for further exploration of the regulatory mechanism of GC.
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DOI：
10.3390/molecules23061479
发表时间：
2018-06-19
期刊：
Molecules (Basel, Switzerland)
影响因子：
--
作者：
Lambert M;Jambon S;Depauw S;David-Cordonnier MH
通讯作者：
David-Cordonnier MH
DOI：
10.1126/science.1162327
发表时间：
2009-06-26
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Badis G;Berger MF;Philippakis AA;Talukder S;Gehrke AR;Jaeger SA;Chan ET;Metzler G;Vedenko A;Chen X;Kuznetsov H;Wang CF;Coburn D;Newburger DE;Morris Q;Hughes TR;Bulyk ML
通讯作者：
Bulyk ML
影响因子：
16.6
作者：
Kang MH;Choi H;Oshima M;Cheong JH;Kim S;Lee JH;Park YS;Choi HS;Kweon MN;Pack CG;Lee JS;Mills GB;Myung SJ;Park YY
通讯作者：
Park YY
影响因子：
3.4
作者：
Khattab, Abdul-Zaher M.;Nasif, Wesam A.;Lotfy, Mahmoud
通讯作者：
Lotfy, Mahmoud
影响因子：
3.8
作者：
Camacho-Moll, Maria E.;Macdonald, Joni;Mitchell, Rod T.
通讯作者：
Mitchell, Rod T.