Integrative Analysis of DNA Methylation and Gene Expression to Determine Specific Diagnostic Biomarkers and Prognostic Biomarkers of Breast Cancer - Zhang, Ming; Wang, Yilin; Wang, Yan; Jiang, Longyang; Li, Xueping; Gao, Hua; Wei, Minjie; Zhao, Lin (Frontiers in Cell and Developmental Biology, 2020)
Background DNA methylation is a frequent early event in the development of tumor, including breast cancer (BRCA), so it is particularly suitable as a tumor biomarker. Although previous studies have reported a cluster of aberrant promoter methylation changes in BRCA, but neither of these research groups considered whether other cancer types could have similar methylation alterations. Here we aimed to identify specific DNA methylation signature to function as diagnostic and prognostic markers for BRCA patients. Methods Differential methylation sites were identified using the Cancer Genome Atlas (TCGA) BRCA data set. We screened for BRCA-differential methylation by comparing methylation profiles of BRCA patients, normal breast samples and normal blood samples. These differential methylated sites were compared to nine main cancer patient samples to identify BRCA specific methylated sites. A BayesNet model was built to distinguish BRCA patients from normal controls. The performance of the model was evaluated using two Gene Expression Omnibus (GEO) independent data sets. In addition, we also carried out the Cox regression analysis to find DNA methylation markers significantly related to the overall survival (OS) rate of BRCA patients, and verified them in the validation cohort. Results We identified 7 differentially methylated sites (DMSs) as potential specific diagnostic biomarkers for BRCA patients. The combination of 7 DMSs achieved ~ 94% sensitivity in predicting BRCA, ~ 95% specificity in excluding normal breast, and ~ 88% specificity in excluding other cancers. The 7 DMSs were mainly correlated with cell cycle. We also identified 6 methylation sites that can effectively distinguished the OS of BRCA patients and had a accurately predicted for survival (training cohort: likelihood ratio = 70.25, p = 3.633×10-13, area under the curve (AUC) = 0.784; validation cohort: AUC = 0.734). Stratification analysis by age, clinical stage, Tumor types, and chemotherapy retained statistical significance. Conclusion In summary, our study demonstrated the role of methylation profiles in the diagnosis and prognosis of BRCA. This signature is superior to currently published methylation markers for diagnosis and prognosis for BRCA patients. It might be able to serve as a promising biomarker for early diagnosis and prognosis of BRCA.