Abstract
BackgroundEndometrial carcinoma (EC) is the most common gynecological malignant tumors which poses a serious threat to women health. This study aimed to screen the candidate genes differentially expressed in EC by bioinformatics analysis.MethodsGEO database and GEO2R online tool were applied to screen the differentially expressed genes (DEGs) of EC from the microarray datasets. Protein-protein interaction (PPI) network for the DEGs was constructed to further explore the relationships among these genes and identify hub DEGs. Gene ontology and KEGG enrichment analyses were performed to investigate the biological role of DEGs. Besides, correlation analysis, genetic alteration, expression profile, and survival analysis of these hub DEGs were also investigated to further explore the roles of these hub gene in mechanism of EC tumorigenesis. qRT-PCR analysis was also performed to verify the expression of identified hub DEGs.ResultsA total of 40 DEGs were screened out as the DEGs with 3 upregulated and 37 downregulated in EC. The gene ontology analysis showed that these genes were significantly enriched in cell adhesion, response to estradiol, and growth factor activity, etc. The KEGG pathway analysis showed that DEGs were enriched in focal adhesion, leukocyte transendothelial migration, PI3K-Akt signaling pathway, and ECM-receptor interaction pathway. More importantly, COL1A1, IGF1, COL5A1, CXCL12, PTEN, and SPP1 were identified as the hub genes of EC. The genetic alteration analysis showed that hub genes were mainly altered in mutation and deep deletion. Expression validation by bioinformatic analysis and qRT-PCR also proved the expression of these six hub genes were differentially expressed in EC. Additionally, significantly better overall survival and disease-free survival were observed with six hub genes altered, and survival outcome in high expression of COL1A1, IGF1, and PTEN patients was also significantly better than low expression patients.ConclusionsCOL1A1, IGF1, COL5A1, CXCL12, PTEN, and SPP1 involved in the pathogenesis of EC and might be candidate genes for diagnosis of EC.
Highlights
Endometrial carcinoma (EC) is an epithelial malignant tumor of the endometrium and regarded as the most common cancers in female reproductive system [1]
differentially expressed genes (DEGs) identification Based on the Gene Expression Omnibus (GEO) database and GEO2R online analysis tool, a total of 160 DE mRNAs were detected from GSE115810, of which 13 were upregulated mRNAs and 137 were downregulated; a total of 67 DE mRNAs were detected from GSE36389, of which 15 were upregulated and 52 were downregulated (Fig. 1)
Protein-protein interaction (PPI) network construction and hub genes identification A PPI network of the DEGs was constructed by STRING and visualized by Cytoscape to further explore the relationships among these genes
Summary
Endometrial carcinoma (EC) is an epithelial malignant tumor of the endometrium and regarded as the most common cancers in female reproductive system [1]. Surgical treatment is the main means for EC at present, and appropriate adjuvant therapy is applied according to the pathological and clinical stages of the tumors. About 15– 20% of the tumors still relapse after surgical treatment, and the curative effect of the systematic therapy is limited [6]. Exploring the suitable biomarkers and potential targets for the accurate prediction or diagnosis of EC and to seek the possibilities to improve the therapeutic effect and clinical prognosis of EC patients is urgently needed. Endometrial carcinoma (EC) is the most common gynecological malignant tumors which poses a serious threat to women health. This study aimed to screen the candidate genes differentially expressed in EC by bioinformatics analysis
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