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. 2016 Jul;12(1):157-166.
doi: 10.3892/ol.2016.4608. Epub 2016 May 18.

Integration and bioinformatics analysis of DNA-methylated genes associated with drug resistance in ovarian cancer

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Integration and bioinformatics analysis of DNA-methylated genes associated with drug resistance in ovarian cancer

Bingbing Yan et al. Oncol Lett. 2016 Jul.

Abstract

The main obstacle to the successful treatment of ovarian cancer is the development of drug resistance to combined chemotherapy. Among all the factors associated with drug resistance, DNA methylation apparently plays a critical role. In this study, we performed an integrative analysis of the 26 DNA-methylated genes associated with drug resistance in ovarian cancer, and the genes were further evaluated by comprehensive bioinformatics analysis including gene/protein interaction, biological process enrichment and annotation. The results from the protein interaction analyses revealed that at least 20 of these 26 methylated genes are present in the protein interaction network, indicating that they interact with each other, have a correlation in function, and may participate as a whole in the regulation of ovarian cancer drug resistance. There is a direct interaction between the phosphatase and tensin homolog (PTEN) gene and at least half of the other genes, indicating that PTEN may possess core regulatory functions among these genes. Biological process enrichment and annotation demonstrated that most of these methylated genes were significantly associated with apoptosis, which is possibly an essential way for these genes to be involved in the regulation of multidrug resistance in ovarian cancer. In addition, a comprehensive analysis of clinical factors revealed that the methylation level of genes that are associated with the regulation of drug resistance in ovarian cancer was significantly correlated with the prognosis of ovarian cancer. Overall, this study preliminarily explains the potential correlation between the genes with DNA methylation and drug resistance in ovarian cancer. This finding has significance for our understanding of the regulation of resistant ovarian cancer by methylated genes, the treatment of ovarian cancer, and improvement of the prognosis of ovarian cancer.

Keywords: DNA methylation; bioinformatics; drug resistance; ovarian cancer.

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Figures

Figure 1.
Figure 1.
Unilateral interaction analysis of 26 ovarian cancer drug resistance-related genes with DNA methylation using STRING software. The line between two proteins represents the interaction between the two proteins. Different colours represent the different types of interactions, indicated by ‘interaction type’.

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