小RNA
基因
生物
比例危险模型
生存分析
子宫内膜癌
微阵列
微阵列分析技术
单变量分析
肿瘤科
信使核糖核酸
基因表达
癌症
生物信息学
癌症研究
内科学
遗传学
医学
多元分析
作者
Ying Dong,Ting Zhang,Xining Li,Feng Yu,Hongwei Yu,Shengwen Shao
出处
期刊:Gynecologic and Obstetric Investigation
[S. Karger AG]
日期:2022-01-01
卷期号:87 (1): 12-21
被引量:1
摘要
Endometrial carcinoma (EC) is one of the leading causes of death from gynecological cancer due to the high recurrence rate. However, the molecular mechanisms of EC progression are not well understood. This study aimed to identify critical genes and miRNAs associated with the progression and prognosis of EC and find the potential mRNA-miRNA regulatory relationship.The mRNA and miRNA data were downloaded from The Cancer Genome Atlas (TCGA) database. Next, differentially expressed genes (DEGs) were identified. Subsequently, prognosis-related genes and miRNAs were identified, followed by co-expression analysis of these mRNAs and miRNAs. Materials, Setting, and Methods: Samples in the mRNA microarray were divided into normal (n = 35), early stage (n = 385), and advanced stage (n = 153). Next, DEGs in normal versus early stage and early stage versus advanced stage were, respectively, identified, followed by Venn analysis to screen overlapping DEGs in 2 comparison groups. Based on the expression level of these DEGs, univariate Cox regression analysis and Kaplan-Meier method were performed to obtain prognosis-related genes. Moreover, genes-related miRNAs were predicted, and miRNA-mRNA co-expressed pairs were identified. Then, survival analysis of co-expressed miRNA was performed. Finally, co-expressed genes of key genes were identified, and then functional enrichment analysis was conducted.After integrating analysis, 326 overlapping (309 upregulated and 17 downregulated) DEGs were obtained. Univariate Cox regression analysis showed that 44 mRNAs and 8 miRNAs were associated with the prognosis of EC. Combined with the co-expressed analysis, only one prognosis-related hsa-miR-326/ELFN2 axis was obtained. In addition, functional enrichment analysis showed that co-expressed genes of ELFN2 were mainly involved in the PI3K-Akt signaling pathway.These findings were obtained via bioinformatics analysis, and thus further experimental studies are urgently demanded to validate our results.One key miRNA-mRNA regulatory pair (hsa-miR-326-ELFN2) was screened. This study provided a bioinformatics basis for the molecular mechanism of EC progression and might contribute to the identification of novel therapeutic targets.
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