Genomic and epigenomic <i>BRCA</i> alterations predict adaptive resistance and response to platinum-based therapy in patients with triple-negative breast and ovarian carcinomas.

Abstract

Triple-negative breast cancer (TNBC) and ovarian carcinomas (OvCas) with <i>BRCA1</i> promoter methylation (<i>BRCA1</i>meth) respond more poorly to alkylating agents compared to those bearing mutations in <i>BRCA1</i> and <i>BRCA2</i> (<i>BRCA</i>mut). This is a conundrum given the biologically equivalent homologous recombination deficiency (HRD) induced by these genetic and epigenetic <i>BRCA</i> perturbations. We dissected this problem through detailed genomic analyses of TNBC and OvCa cohorts and experimentation with patient-derived xenografts and genetically engineered cell lines. We found that despite identical downstream genomic mutational signatures associated with <i>BRCA1</i>meth and <i>BRCA</i>mut states, <i>BRCA1</i>meth uniformly associates with poor outcomes. Exposure of <i>BRCA1</i>meth TNBCs to platinum chemotherapy, either as clinical treatment of a patient or as experimental in vivo exposure of preclinical patient derived xenografts, resulted in allelic loss of <i>BRCA1</i> methylation and increased <i>BRCA1</i> expression and platinum resistance. These data suggest that, unlike <i>BRCA</i>mut cancers, where <i>BRCA</i> loss is a genetically "fixed" deficiency state, <i>BRCA1</i>meth cancers are highly adaptive to genotoxin exposure and, through reversal of promoter methylation, recover <i>BRCA1</i> expression and become resistant to therapy. We further found a specific augmented immune transcriptional signal associated with enhanced response to platinum chemotherapy but only in patients with BRCA-proficient cancers. We showed how integrating both this cancer immune signature and the presence of <i>BRCA</i> mutations results in more accurate predictions of patient response when compared to either HRD status or <i>BRCA</i> status alone. This underscores the importance of defining <i>BRCA</i> heterogeneity in optimizing the predictive precision of assigning response probabilities in TNBC and OvCa.