Statistical analysis of DNA methylation patterns of tumor suppressor genes for breast cancer

Abstract

Abstract Background Breast cancer is associated with DNA methylation, an epigenetic event in which a methyl group is covalently bonded to a cytosine-guanine (CG) pair. Although previous research has studied methylation patterns of individual tumor suppressor genes (TSGs), there has not been a comprehensive analysis of all available TSGs for breast cancer. The purpose of this study is to conduct the first-ever comprehensive statistical analysis of methylation patterns for all 1,217 TSGs. The authors analyzed publicly available Illumina 450K array data for 53 living (53-Alive) and 32 deceased (32-Dead) breast cancer patients. First, they studied the overall methylation distribution. They then identified differentially methylated (DM) sites between tumors and matched normal tissues in both Alive and Dead samples. They analyzed co-methylation patterns related to these DM sites and reported corresponding TSGs and non-TSGs. Results Below are the key findings of this study. First, tumor tissues had more heterogeneous methylation sites than normal tissues (40% vs. <10%) in both Alive and Dead samples. Second, there were significantly more DM sites in Dead than in Alive samples. Third, co-methylation patterns were investigated by calculating the Spearman correlation coefficients between each DM site and all 391,459 CG sites for both Alive and Dead samples. In normal tissues, some DM sites tended to have strong co-methylation with many other CG sites. In tumor tissues, some of these strong co-methylations were lost and some new co-methylation relationships were developed. These patterns were seen in both Alive and Dead data. Fourth, there were more co-methylation changes between normal and tumor tissues in Dead than in Alive samples. 30 TSGs and 92 non-TSGs were identified as having notable differences between Alive and Dead data. Finally, ESR1, PAX6, ZIC1, TP73, PPP1CA, POU6F2, and TFAP2A were involved in many different co-methylation changes between normal and tumor tissues. These 7 TSGs played a key role as hub genes in different networks. Conclusion Significant differences were identified for various methylation-pattern changes between normal and tumor as well as between Alive and Dead samples. These differences can be used to identify novel TSGs and biomarkers to improve breast cancer study.