Identification of key genes in endometrioid endometrial adenocarcinoma via TCGA database

利用TCGA数据库鉴定子宫内膜样腺癌的关键基因

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Abstract

BACKGROUND: Understanding the molecular mechanisms is important in development and therapy of endometrioid endometrial adenocarcinoma. OBJECTIVE: To identify key genes in endometrioid endometrial adenocarcinoma. METHODS: The data of mRNA, miRNA and DNA methylation were downloaded from The Cancer Genome Atlas (TCGA) database and differential analysis was performed. Then, bioinformatic analysis was used to explore the regulatory mechanisms of miRNA and DNA methylation on gene expression. The regulatory network between differentially expressed miRNAs and target genes was established. Finally, the quantitative RT-PCR was applied to validate the bioinformatics results. RESULTS: We obtained biological omics data of 381 patients with endometrioid endometrial adenocarcinoma from TCGA data portal. After data processing, up to 2068 DEGs and 69 differentially expressed miRNAs were identified. Prediction and correlation analysis revealed that 175 DEGs that were not only the target genes but also negatively correlated with the screened differentially expressed miRNAs. After the integrated analysis of differentially methylated CpG islands and DEGs, 16 related genes were obtained. The quantitative RT-PCR results were roughly consistent with the bioinformatics analysis. CONCLUSIONS: The altered DEGs (ZEB1, ZEB2, TIMP2, TCF4, CYP1B1, PITX1, PITX2, ZNF154 and TSPYL5) may be involved in tumor differentiation of endometrioid endometrial adenocarcinoma and could be used as potential therapeutic targets for the disease.

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