DNA Methylation Based Molecular Subtypes Predict Prognosis in Breast Cancer Patients

• Published in: Cancer control Vol. 28; p. 1073274820988519
• Main Authors: Wu, Zeng-Hong, Tang, Yun, Zhou, Yan
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01.01.2021; Sage Publications Ltd; SAGE Publishing
• Subjects: Adult; Biomarkers, Tumor - genetics; Breast cancer; Breast Neoplasms - classification; Breast Neoplasms - genetics; Breast Neoplasms - mortality; Cluster Analysis; CpG islands; Deoxyribonucleic acid; DNA; DNA Methylation; Epigenesis, Genetic; Epigenetics; Female; Gene expression; Gene Expression Regulation, Neoplastic; Genomes; Humans; Male; Medical prognosis; Patients; Prognosis; Survival Analysis; Tumorigenesis; DNA methylation; breast cancer; prognosis; TCGA
• ISSN: 1073-2748; 1526-2359; 1526-2359; 1073-2748
• DOI: 10.1177/1073274820988519

Background: Epigenetic changes are tightly linked to tumorigenesis development and malignant transformation’ However, DNA methylation occurs earlier and is constant during tumorigenesis. It plays an important role in controlling gene expression in cancer cells. Methods: In this study, we determining the prognostic value of molecular subtypes based on DNA methylation status in breast cancer samples obtained from The Cancer Genome Atlas database (TCGA). Results: Seven clusters and 204 corresponding promoter genes were identified based on consensus clustering using 166 CpG sites that significantly influenced survival outcomes. The overall survival (OS) analysis showed a significant prognostic difference among the 7 groups (p<0.05). Finally, a prognostic model was used to estimate the results of patients on the testing set based on the classification findings of a training dataset DNA methylation subgroups. Conclusions: The model was found to be important in the identification of novel biomarkers and could be of help to patients with different breast cancer subtypes when predicting prognosis, clinical diagnosis and management.