Many studies have attempted pan-cancer analyses in order to identify recurrent coding mutations, but few have explored non-coding space, and often the results do not extend to breast cancer. While some breast cancer specific studies have identified significantly mutated promoters, they have often failed to incorporate transcriptome data to assess the impact and relevance of mutations on gene expression within tumors (Nik-Zainal et al. 2016, Rheinbay et al. 2017). In order to address this issue, we have compiled a data set consisting of 458 breast cancer tumor/normal pairs. Mutations have been identified with whole genome, exome, or custom capture sequencing and expression with transcriptome sequencing or microarray. The custom (regulome) capture reagent covers regions assembled from regulatory databases, 5’ untranslated regions, 500 bases upstream and downstream of transcription start sites, and 50,000 bases upstream and downstream of 178 genes that have been implicated as being important in breast cancer (Lesurf et al. 2016). While this custom capture region is similar in size to an exome, it has advantages over WGS and exome sequencing. It provides deep sequence coverage of regulatory regions, including GC-rich promoter regions, where WGS often produces insufficient coverage. After extensive filtering, our preliminary analysis revealed significant mutation clustering within the noncoding space of RMRP, WDR74, as noted in previous studies, as well as ∼50 other genes not previously reported. The significance of these mutations, based on recurrence, transcriptome changes, and molecular subtype relationships will be presented.