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Updated: Nov 27, 2025
Development of Compendium for Esophageal Squamous Cell Carcinoma
Published on: April 12, 2024
TTK, CDC25A, and ESPL1 as Prognostic Biomarkers for Endometrial Cancer
Qiannan Yang1, Bojun Yu1, Jing Sun1
1Department of Gynaecology, Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai /201204, China.
Objective:
Endometrial cancer (EC) is one of the most common malignant gynaecological tumours worldwide. This study was aimed at identifying EC prognostic genes and investigating the molecular mechanisms of these genes in EC.
Methods:
Two mRNA datasets of EC were downloaded from the Gene Expression Omnibus (GEO). The GEO2R tool and Draw Venn Diagram were used to identify differentially expressed genes (DEGs) between normal endometrial tissues and EC tissues. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Next, the protein-protein interactions (PPIs) of these DEGs were determined by the Search Tool for the Retrieval of Interacting Genes (STRING) tool and Cytoscape with Molecular Complex Detection (MCODE). Furthermore, Kaplan-Meier survival analysis was performed by UALCAN to verify genes associated with significantly poor prognosis. Next, Gene Expression Profiling Interactive Analysis (GEPIA) was used to verify the expression levels of these selected genes. Additionally, a reanalysis of the KEGG pathways was performed to understand the potential biological functions of selected genes. Finally, the associations between these genes and clinical features were analysed based on TCGA cancer genomic datasets for EC.
Results:
In EC tissues, compared with normal endometrial tissues, 147 of 249 DEGs were upregulated and 102 were downregulated. A total of 64 upregulated genes were assembled into a PPI network. Next, 14 genes were found to be both associated with significantly poor prognosis and highly expressed in EC tissues. Reanalysis of the KEGG pathways found that three of these genes were enriched in the cell cycle pathway. TTK, CDC25A, and ESPL1 showed higher expression in cancers with late stage and higher tumour grade.
Conclusion:
In summary, through integrated bioinformatics approaches, we found three significant prognostic genes of EC, which might be potential therapeutic targets for EC patients.
