The Cancer Genome Atlas Network conducted a comprehensive analysis of primary breast cancers using multiple genomic and molecular techniques, including DNA copy number arrays, DNA methylation, exome sequencing, mRNA expression, microRNA sequencing, and reverse-phase protein arrays. This integrated approach revealed four main breast cancer classes, each with significant molecular heterogeneity. Key findings include the identification of three genes (TP53, PIK3CA, GATA3) with high mutation rates across all breast cancers, and the enrichment of specific mutations in GATA3, PIK3CA, and MAP3K1 in the luminal A subtype. Two novel protein-expression-defined subgroups were identified, and specific signaling pathways were associated with each molecular subtype. Basal-like breast tumors showed molecular similarities with high-grade serous ovarian tumors, suggesting a related etiology and similar therapeutic opportunities. Breast cancer is a heterogeneous disease categorized into three therapeutic groups: ER-positive, HER2-enriched, and triple-negative. The study identified 510 tumors with 30,626 somatic mutations, including 6,486 silent, 19,045 missense, 1,437 nonsense, and 2,302 insertions/deletions. Many significantly mutated genes were identified, including TBX3, RUNX1, CBFB, AFF2, PIK3R1, PTPN22, PTPRD, NF1, SF3B1, and CCND3. These mutations were associated with specific mRNA expression subtypes, with luminal A and B tumors showing more diverse and recurrent mutations than basal-like and HER2-enriched subtypes. DNA methylation analysis identified five distinct methylation groups, with group 3 showing a hypermethylated phenotype and being enriched for luminal B mRNA subtypes. DNA copy number analysis identified focal amplifications and deletions, with characteristic losses in basal-like cancers and gains in luminal tumors. Reverse-phase protein arrays identified 171 cancer-related proteins and phosphopeptides, revealing seven subtypes, with high concordance with mRNA subtypes. Multiplatform analysis identified four major subtypes, with basal-like cancers showing the most distinct multiplatform signature. The study also identified potential therapeutic targets, including PIK3CA inhibitors, AKT1 inhibitors, and PARP inhibitors for BRCA1/BRCA2 mutations. The findings suggest that many clinically observable plasticity and heterogeneity occur within, not across, the four major breast cancer subtypes. The study highlights the importance of integrating multiple data types to understand the molecular architecture of breast cancer and identify potential therapeutic targets.The Cancer Genome Atlas Network conducted a comprehensive analysis of primary breast cancers using multiple genomic and molecular techniques, including DNA copy number arrays, DNA methylation, exome sequencing, mRNA expression, microRNA sequencing, and reverse-phase protein arrays. This integrated approach revealed four main breast cancer classes, each with significant molecular heterogeneity. Key findings include the identification of three genes (TP53, PIK3CA, GATA3) with high mutation rates across all breast cancers, and the enrichment of specific mutations in GATA3, PIK3CA, and MAP3K1 in the luminal A subtype. Two novel protein-expression-defined subgroups were identified, and specific signaling pathways were associated with each molecular subtype. Basal-like breast tumors showed molecular similarities with high-grade serous ovarian tumors, suggesting a related etiology and similar therapeutic opportunities. Breast cancer is a heterogeneous disease categorized into three therapeutic groups: ER-positive, HER2-enriched, and triple-negative. The study identified 510 tumors with 30,626 somatic mutations, including 6,486 silent, 19,045 missense, 1,437 nonsense, and 2,302 insertions/deletions. Many significantly mutated genes were identified, including TBX3, RUNX1, CBFB, AFF2, PIK3R1, PTPN22, PTPRD, NF1, SF3B1, and CCND3. These mutations were associated with specific mRNA expression subtypes, with luminal A and B tumors showing more diverse and recurrent mutations than basal-like and HER2-enriched subtypes. DNA methylation analysis identified five distinct methylation groups, with group 3 showing a hypermethylated phenotype and being enriched for luminal B mRNA subtypes. DNA copy number analysis identified focal amplifications and deletions, with characteristic losses in basal-like cancers and gains in luminal tumors. Reverse-phase protein arrays identified 171 cancer-related proteins and phosphopeptides, revealing seven subtypes, with high concordance with mRNA subtypes. Multiplatform analysis identified four major subtypes, with basal-like cancers showing the most distinct multiplatform signature. The study also identified potential therapeutic targets, including PIK3CA inhibitors, AKT1 inhibitors, and PARP inhibitors for BRCA1/BRCA2 mutations. The findings suggest that many clinically observable plasticity and heterogeneity occur within, not across, the four major breast cancer subtypes. The study highlights the importance of integrating multiple data types to understand the molecular architecture of breast cancer and identify potential therapeutic targets.