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Oncol Lett. 2019 Sep;18(3):2464-2476. doi: 10.3892/ol.2019.10550. Epub 2019 Jun 28.

Identification of key genes and pathways between type I and type II endometrial cancer using bioinformatics analysis.

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Department of Gynecology and Obstetrics, Tianjin Medical University General Hospital, Tianjin 300052, P.R. China.


Endometrial carcinoma (EC) is a common malignant neoplasm of the female reproductive tract. The malignant degree of type II EC is much greater than that of type I EC, usually presenting with a high recurrence rate and a poor prognosis. Therefore, the present study aimed to examine the principal genes associated with the degree of differentiation in type I and type II EC and reveal their potential mechanisms. Differentially expressed genes (DEGs) were selected from the gene expression profiles derived from The Cancer Genome Atlas. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. In the present study, the KEGG pathway enrichment analysis revealed that 5,962 upregulated DEGs were significantly enriched in the 'p53 signaling pathway' and involved in 'lysine degradation'. In addition, 3,709 downregulated DEGs were enriched in 'pathways in cancer', as well as 'tight junction regulation', the 'cell cycle' and the 'Wnt signaling pathway'. The 13 top hub genes MAPK1, PHLPP1, ESR1, MDM2, CDKN2A, CDKN1A, AURKA, BCL2L1, POLQ, PIK3R3, RHOQ, EIF4E and LATS2 were identified via the protein-protein interaction network. Furthermore, the OncoPrint algorithm from cBioPortal declared that 25% of EC cases carried genetic alterations. The altered DEGs (MAPK1, MDM2, AURKA, EIF4E and LATS2) may be involved in tumor differentiation and may be valuable diagnostic biomarkers. In conclusion, a number of principal genes were identified in the present study that may be determinants of poorly differentiated type II EC carcinogenesis, which may contribute to future research into potential molecular mechanisms. In addition, these genes may help identify candidate biomarkers and novel therapeutic targets for type II EC.


bioinformatics method; biomarkers; core genes; endometrial carcinoma; survival; therapeutic targets

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