Identification of Key Candidate Genes and Pathways in Endometrial Cancer by Integrated Bioinformatical Analysis

Document Type: Methodological papers

Authors

1 Department of Gynecological Ward, The Third Affiliated Hospital ,Jinzhou Medical University, Jinzhou, China.

2 Liaoning Provincial Key Laboratory of Follicle Development and Reproductive Health (Office of Science and Technology) , Jinzhou, China.

3 Department of Gynecological Ward, The First Affiliated Hospital ,Jinzhou Medical University, Jinzhou, China.

4 Department of Gynecological Ward,Dongzhimen Hospital of Traditional Chinese Medicine,Beijing University of Chinese Medicine ,Beijing,China.

Abstract

Endometrial Cancer is the most common female genital tract malignancy, its pathogenesis is complex, not yet
fully described. To identify key genes of Endometrial Cancer we downloaded the gene chip GSE17025 from the Gene
Expression Omnibus database. Differentially expressed genes (DEGs) were identified through the GEO2R analysis
tool. Functional and pathway enrichment analysis were performed for DEGs using DAVID database. The network of
protein–protein-interaction (PPI) was established by STRING website and visualized by Cytoscape. Then, functional
and pathway enrichment analysis of DEGS were performed by DAVID database. A total of 1000 significant differences
genes were obtained, contain 362 up-regulated genes and 638 down-regulated genes. PCDH10, SLC6A2, OGN,
SFRP4, TRH, ANGPTL, FOSB are down-regulated genes. The gene of IGH, CCL20, ELF5, LTF, ASPM expression
level in tumor patients are up-regulated. Biological function of enrichment include metabolism of xenobiotics by
cytochrome P450, MAPK signaling pathway, Serotonergic synapse, Protein digestion and absorption, IL-17 signaling
pathway, Chemokine signaling pathway, HIF-1 signaling pathway, p53 signaling pathway. All in all, the current study
to determine endometrial differentially expressed genes and biological function, comprehensive analysis of intrauterine
membrane carcinoma pathogenesis mechanism, and might be used as molecular targets and diagnostic biomarkers for
the treatment of endometrial cancer.

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