Genome-wide analysis of aberrant gene expression and methylation profiles reveals susceptibility genes and underlying mechanism of cervical cancer. (December 2016)

• Record Type: Journal Article
• Authors: Lin, Hongmei; Ma, Yifei; Wei, Yongqing; Shang, Hui
• Is Part Of: European journal of obstetrics, gynecology, and reproductive biology. Volume 207(2016:Dec.)
• Page Start: 147
• Page End: 152
• Publication Date: 2016-12
• Subjects: Cervical cancer -- Differentially expressed genes -- Methylation sites -- Functions enrichment -- Risk biomarkers; 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.2016.10.017
• Languages: English
• ISSNs: 0301-2115

Abstract

Abstract: Background: This study aimed to explore the molecular mechanism of cervical cancer (CC) by integrated bioinformatic analyses of gene expression and methylation profiles. Methods: The gene expression and methylation microarrays in CC samples and normal controls were respectively downloaded from the GEO database. After screening the differentially expressed genes (DEGs) with Limma package and the CC-related methylation sites with CpGassoc package in R language, DEGs with CC-related methylation sites were identified from the intersection of the above two groups of results with 50 kb upstream and downstream of a gene as the gene region. Then GO enrichment was performed by GenCLIP2.0 software. Sequentially, analysis of metabolic sub-pathways with pathogenic risk was predicted by iSubpathwayMiner package in R language. Results: A total of 1357 DEGs including 721 up-regulated and 636 down-regulated, as well as 666 CC-related methylation sites were screened out. After being analyzed, 26 DEGs with 35 CC-related methylation sites were identified. EDN3 and EDNRB were significantly involved in a function cluster in GO terms of vein smooth muscle contraction, vascular smooth muscle contraction and phasic smooth muscle contraction. LHX2 and PAX6 were significantly involved in a function cluster in GO terms of telencephalon regionalization and forebrain regionalization. ACOX3, CYP39A1 and DPYS were significantly enriched in 25 sub-pathways of 6 major pathways. Conclusions: EDN3 and EDNRB might play important roles in the molecular mechanism of CC, and LHX2, ACOX3, CYP39A1 and DPYS might be susceptibility genes and potential risk markers in CC.