Ye Gengchen, Feng Shuyue, Yang Yufei, Cao Zhengzhi, Zhang Beilei, Wang Fu
School of Basic Medical Sciences, Xi'an Jiaotong University, Xi'an 710061, China.
Department of Obstetrics and Gynecology, Tangdu Hospital, Air Force Medical University, Xi'an, China.
J Oncol. 2022 Mar 10;2022:5120342. doi: 10.1155/2022/5120342. eCollection 2022.
The rate of ovarian cancer (OC) is one of the highest in women's reproductive systems. An improperly expressed microRNA (miRNA) has been discovered to have a vital role in the pathophysiology of OC. However, more research into OC's miRNA-message RNA (mRNA) gene interaction network is required.
Firstly, the microarray data sets GSE25405 and GSE119055 from the GEO (Gene Expression Omnibus) database were downloaded and then analyzed with the GEO2R tool aiming at identifying DEMs (differential expressed miRNAs) between ovarian malignant tissue and ovarian normal tissue. The whole consistently changed miRNAs were then screened out to be candidate DEMs. For estimating underlying upstream transcription factors, FunRich was employed. miRNet was utilized to determine putative DEMs' downstream target genes. The R program was then used to do the GO annotation as well as the analysis of KEGG pathway enrichment for target genes. The PPI (protein-protein interaction), as well as the DEM-hub gene networks, were created by the Cytoscape software and STRING database. Finally, we chose the GSE74448 dataset to test the precision of hub gene expressions.
We have screened out six (five upregulated and one downregulated) DEMs. The majority of upregulated and downregulated DEMs are likely regulated by SP1 (specificity protein 1). SP4 (s protein 4), POU2F1 (POU class 2 homeobox 1), MEF2A (myocyte-specific enhancer factor 2A), ARID3A (AT-rich interaction domain 3A), and EGR1 (early growth response 1) can regulate upregulated and downregulated DEMs. We have found 807 target genes (656 upregulated and 151 downregulated DEM), being generally enriched in focal adhesion and proteoglycans in cancer, gastric cancer, hepatocellular carcinoma, as well as breast cancer. The majority of hub genes are projected to be controlled by hsa-miR-429, hsa-miR-140-5p, hsa-miR-199a-5p, and hsa-miR-199a-3p after the DEM-hub gene network was built. VEGFA (vascular endothelial growth factor A), EZH2 (enhancer of zeste 2 polycomb repressive complex 2 subunit), and HIF1A (hypoxia inducible factor 1 subunit alpha) expressions are consistent with the GSE74448 dataset in the first 18 hub genes.
We have built an underlying miRNA-mRNA interacting network in OC, giving us unparalleled insight into the disease's diagnosis and treatment.
卵巢癌（OC）发病率是女性生殖系统中最高的之一。已发现一种表达异常的微小RNA（miRNA）在OC的病理生理学中起关键作用。然而，仍需要对OC的miRNA-信使RNA（mRNA）基因相互作用网络进行更多研究。
首先，从基因表达综合数据库（GEO）下载数据集GSE25405和GSE119055，然后使用GEO2R工具进行分析，旨在识别卵巢恶性组织与卵巢正常组织之间的差异表达miRNA（DEM）。然后筛选出全部一致变化的miRNA作为候选DEM。为估计潜在的上游转录因子，使用了FunRich软件。利用miRNet确定推定DEM的下游靶基因。然后使用R程序对靶基因进行基因本体（GO）注释以及京都基因与基因组百科全书（KEGG）通路富集分析。通过Cytoscape软件和STRING数据库构建蛋白质-蛋白质相互作用（PPI）网络以及DEM-枢纽基因网络。最后，我们选择GSE74448数据集来测试枢纽基因表达的准确性。
我们筛选出6个DEM（5个上调和1个下调）。大多数上调和下调的DEM可能受特异性蛋白1（SP1）调控。SP4（s蛋白4）、POU2F1（POU类2同源盒1）、MEF2A（肌细胞特异性增强因子2A）、ARID3A（富含AT相互作用结构域3A）和早期生长反应1（EGR1）可调控上调和下调的DEM。我们发现了807个靶基因（656个上调和151个下调的DEM），这些基因通常富集于癌症、胃癌、肝细胞癌以及乳腺癌中的粘着斑和蛋白聚糖。构建DEM-枢纽基因网络后，大多数枢纽基因预计受hsa-miR-429、hsa-miR-140-5p、hsa-miR-199a-5p和hsa-miR-199a-3p调控。在前18个枢纽基因中，血管内皮生长因子A（VEGFA）、zeste基因增强子同源物2（EZH2）和缺氧诱导因子1α亚基（HIF1A）的表达与GSE74448数据集一致。
我们构建了OC中潜在的miRNA-mRNA相互作用网络，为该疾病的诊断和治疗提供了前所未有的见解。
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