Analysis of methylation profiling data of hyperplasia and primary and metastatic endometrial cancers. (October 2017)

• Record Type: Journal Article
• Authors: Wu, Xihai; Miao, Jilan; Jiang, Jingyan; Liu, Fangmei
• Is Part Of: European journal of obstetrics, gynecology, and reproductive biology. Volume 217(2017)
• Page Start: 161
• Page End: 166
• Publication Date: 2017-10
• Subjects: Differentially methylated genes -- Endometrial cancer -- Hyperplasia -- Metastasis -- Protein-protein interaction; Obstetrics -- Periodicals; Gynecology -- Periodicals; Reproductive health -- Periodicals; Gynecology -- Periodicals; Obstetrics -- Periodicals; Reproduction -- Periodicals; Obstétrique -- Périodiques; Gynécologie -- Périodiques; Reproduction -- Périodiques; Verloskunde; Gynaecologie; Voortplanting (biologie); Gynecology; Obstetrics; Reproduction; Electronic journals; Periodicals; Electronic journals; 618.05
• DOI: 10.1016/j.ejogrb.2017.08.036
• Languages: English
• ISSNs: 0301-2115

Abstract

Abstract: Objective: Endometrial cancer is a prevalent cancer, and its metastasis causes low survival rate. This study aims to utilize DNA methylation data to investigate the mechanism of the development and metastasis of endometrial cancer. Study design: Methylation profiling data were down-loaded from Gene Expression Omnibus, including 8 hyperplasias, 33 primary and 53 metastatic endometrial cancers. COHCAP package and annotation files were utilized to identify differentially methylated genes (DMGs) and CpG islands between the three different endometrial diseases. STRING database and Cytoscape were used to analyze and visualize protein–protein interactions (PPIs) between DMGs. CytoNCA plugin was utilized to identify key nodes in PPI network. Results: A total of 610, 1076, and 501 DMGs were identified between primary endometrial cancer and hyperplasia, metastatic endometrial cancer and hyperplasia, as well as metastatic and primary endometrial cancers, respectively. For the three DMG sets, 53 common hypermethylated DMGs (e.g. PAX6 and INSR) and 6 common hypomethylated DMGs (e.g. PRDM8, KLHL14, and DUSP6) were found. For primary-hyperplasia DMG set and metastasis-hyperplasia DMG set, 527 common DMGs were found. For these common DMGs, a PPI network involving 692 PPIs was constructed. For DMGs between metastatic and primary endometrial cancers, a PPI network involving 673 PPIs was established, with PAX6 and INSR in the top 20 DMGs in both networks. PRDM8, KLHL14, and DUSP6 had hypomethylated CpG islands. Conclusion: DMGs comparison, PPI network analysis, and analysis of differentially methylated CpG islands indicated that PAX6, INSR, PRDM8, KLHL14, and DUSP6 might participate in the development and metastasis of endometrial cancer.