DNA Methylation Identifies Epigenetic Subtypes of Triple-Negative Breast Cancers With Distinct Clinicopathologic and...

Triple-negative breast cancers (TNBC) include diverse carcinomas with heterogeneous clinical behavior. DNA methylation is a useful tool in classifying a variety of cancers. In this study, we analyzed TNBC using DNA methylation profiling and compared the results to those of mutational analysis. DNA methylation profiling (Infinium MethylationEPIC array, Illumina) and 50-gene panel-targeted DNA sequencing were performed in 44 treatment-naïve TNBC. We identified 3 distinct DNA methylation clusters with specific clinicopathologic and molecular features. Cluster 1 (phosphoinositide 3-kinase/protein kinase B-enriched cluster; n = 9) patients were significantly older (mean age, 71 years; P = .008) with tumors that were more likely to exhibit apocrine differentiation (78%; P < .001), a lower grade (44% were grade 2), a lower proliferation index (median Ki-67, 15%; P = .002), and lower tumor-infiltrating lymphocyte fractions (median, 15%; P = .0142). Tumors carried recurrent PIK3CA and AKT1 mutations and a higher percentage of low HER-2 expression (89%; P = .033). Cluster 3 (chromosomal instability cluster; n = 28) patients were significantly younger (median age, 57 years). Tumors were of higher grade (grade 3, 93%), had a higher proliferation index (median Ki-67, 75%), and were with a high fraction of tumor-infiltrating lymphocytes (median, 30%). Ninety-one percent of the germline BRCA1/2 mutation carriers were in cluster 3, and these tumors showed the highest level of copy number alterations. Cluster 2 represented cases with intermediate clinicopathologic characteristics and no specific molecular profile (no specific molecular profile cluster; n = 7). There were no differences in relation to stage, recurrence, and survival. In conclusion, DNA methylation profiling is a promising tool to classify patients with TNBC into biologically relevant groups, which may result in better disease characterization and reveal potential targets for emerging therapies.