Genome-wide DNA methylation profiling reveals distinct epigenetic landscapes and novel biomarkers in estrogen receptor-positive and -negative breast cancers

BACKGROUND: Breast cancer is a molecularly heterogeneous disease driven partly by subtype-specific DNA methylation patterns with diagnostic and prognostic potential. We aimed to construct a comprehensive methylation dataset to identify novel differentially methylated regions, define the global methylation patterns distinguishing breast carcinomas from normal tissue, and characterize differences between estrogen receptor (ER)-positive and ER-negative tumors. METHODS: We curated a large-scale methylation dataset by processing raw data from HumanMethylation450 and EPIC array platforms (GEO accessions GPL13534, GPL21145) from GEO and GDC. The cohort included solid tissue samples from untreated breast cancer patients and healthy cases. Data preprocessing, BMIQ normalization, and quality control were performed using minfi and wateRmelon in R. Probes were annotated into functional gene regions (TSS1500, TSS200, 5'UTR, first exon, gene body and 3'UTR). Differential methylation analysis (∆beta > 0.2) between normal, ER+, and ER- groups was conducted using Kruskal-Wallis and Mann-Whitney tests with Bonferroni correction. Biomarker potential was evaluated using receiver operating characteristic (ROC) analysis with 5-fold cross-validation (cvAUC). Gene Ontology (GO) enrichment was performed with clusterProfiler. RESULTS: Based on HM450K and EPIC arrays, tumors exhibited significant, location-specific methylation shifts versus normal tissue, with distinct ER-positive and ER-negative patterns. ER-positive tumors showed pervasive promoter hypermethylation (455 hyper-, and 43 hypomethylated gene regions; Δbeta>0.2, p<0.05), enriched for pattern specification (HM450K: 4.7 fold enrichment (FE), p<0.001; EPIC: 9.3 FE, p<0.05) and appetite regulation (HM450K: 17.2, p<0.001; EPIC: 34.3 FE, p<0.001). ER-negative tumors (354 hyper-, and 23 hypomethylated gene regions shared by platforms with Δbeta>0.2, p<0.05), and were enriched for homophilic cell adhesion (EPIC: 16.2 FE, p<0.001) and olfactory receptor genes (EPIC: FE 12.2, p>0.001). Both platforms consistently identified high-confidence, differentially methylated regions, such as hypermethylation in the NEURL2 gene body in ER-positive (cvAUC: 0.99 HM450K, 0.99 EPIC; Δbeta HM450K: 0.43, EPIC: 0.3) and the NKAPL 5'UTR in ER-negative tumors (cvAUC: 0.99 HM450K, 0.99 EPIC; Δbeta HM450K: 0.47, EPIC: 0.44). CONCLUSIONS: This study mapped the methylomes of ER+ and ER- breast cancers, identifying subtype-specific patterns of epigenetic dysregulation. The dataset and interactive visualization tools are available at epigenplot.com.