Bioinformatics Analysis, ceRNA Network Construction and Prediction of Potential Therapeutic Drug Effects Based on TCGA and CMap Datasets in Endometrial Cancer

Abstract

Background: Uterine Corpus Endometrial Carcinoma (UCEC) ranks second among most common gynecological tumors, and the overall treatment situation is inadequate. In-depth study of tumorigenesis mechanism and the discovery of effective therapeutic drugs are an urgent problem to be solved. Our study mainly focused on the construction of competing endogenous RNA (ceRNA) network and the exploration of potential treatment strategies of UCEC. Methods: 35 normal and 543 endometrial cancer samples had RNA expression profile extracted from The Cancer Genome Atlas (TCGA) GDC data portal. DEGs of LncRNAs (DELncRNAs), DEGs of miRNAs (DEmiRNAs) and DEGs of mRNAs (DEmRNAs) were calculated by R software (version 4.2.1). The function of DEmRNAs was analyzed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Protein-protein interaction (PPI) network and long non-coding RNA (LncRNA)-microRNA (miRNA)-mRNA regulation network were constructed. Further evaluation included venn analysis for vital protein and prediction of potential drugs were based on Connectivity Map (CMap). Lastly, we verified the cyclin B1 (CCNB1) as a potential therapeutic target with wet experiment (western blotting, clonogenic assay and flow cytometry). Results: Our results revealed that 1218 DELncRNAs, 187 DEmiRNAs and 1897 DEmRNAs were identified by comparing UCEC tissue with normal controls. A total of 106 DELncRNAs, 27 DEmiRNAs and 56 DEmRNAs were included to construct a ceRNA network. GO analysis revealed that upregulated mRNAs were involved in nuclear division process. CCNB1 was included in both hub genes of PPI network and ceRNA network, which might be a powerful potential therapeutic target. We predicted 10 potential compounds based on ceRNA network and 49 potential compounds based on DEmRNAs. Aminopurvalanol-a, purvalanol-a and AZD-8055 were candidate compounds most likely to have therapeutic effect. Based on the TCGA database, we successfully constructed a PPI network and ceRNA network. Downregulation of CCNB1 markedly suppressed the proliferation ability and promoted the apoptosis of the UCEC cell lines (p < 0.001). Conclusions: We demonstrated that CCNB1, a gene involved in multiple bioinformatic models, is considered to be a potential therapeutic target for endometrial cancer. Aminopurvalanol-a, purvalanol-a and AZD-8055 are the three most potential therapeutic drugs for UCEC.