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Comprehensive molecular portraits of human breast tumours

Why this mattered

This paper mattered because it made breast cancer classification decisively molecular rather than primarily anatomical or histopathological. Earlier expression-profiling work had already proposed intrinsic subtypes, but TCGA showed that those subtypes were not just transcriptomic patterns: they were coherent, multi-layer biological states visible across copy number, methylation, mutation, mRNA, microRNA, and protein data. That integration made it harder to treat “breast cancer” as one disease with variable behavior, and instead framed luminal A, luminal B, HER2-enriched, and basal-like tumors as major biological classes shaped by distinct genetic and epigenetic programs.

The study also clarified why precision oncology in breast cancer would not be a simple hunt for one common driver mutation. Across all breast cancers, only TP53, PIK3CA, and GATA3 exceeded 10% mutation frequency, while many alterations were subtype-enriched. That finding pushed the field toward subtype-specific biology, pathway-level interpretation, and integrated biomarkers rather than mutation lists alone. It helped make possible later work in targeted therapy selection, PI3K-pathway stratification, HER2 signaling refinement, immune and microenvironmental profiling, and multi-omic tumor atlases across cancer types.

Its comparison of basal-like breast cancers with high-grade serous ovarian cancers was especially paradigm-shifting: it suggested that therapeutic opportunities might follow molecular resemblance across organs, not only tissue of origin. That idea became central to later pan-cancer analyses and basket-style therapeutic thinking. In retrospect, the paper stands as one of TCGA’s defining demonstrations that large-scale, integrated molecular portraits could reorganize cancer taxonomy and provide a durable map for both biological discovery and clinical trial design.

Abstract

We analysed primary breast cancers by genomic DNA copy number arrays, DNA methylation, exome sequencing, messenger RNA arrays, microRNA sequencing and reverse-phase protein arrays. Our ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity. Somatic mutations in only three genes (TP53, PIK3CA and GATA3) occurred at >10% incidence across all breast cancers; however, there were numerous subtype-associated and novel gene mutations including the enrichment of specific mutations in GATA3, PIK3CA and MAP3K1 with the luminal A subtype. We identified two novel protein-expression-defined subgroups, possibly produced by stromal/microenvironmental elements, and integrated analyses identified specific signalling pathways dominant in each molecular subtype including a HER2/phosphorylated HER2/EGFR/phosphorylated EGFR signature within the HER2-enriched expression subtype. Comparison of basal-like breast tumours with high-grade serous ovarian tumours showed many molecular commonalities, indicating a related aetiology and similar therapeutic opportunities. The biological finding of the four main breast cancer subtypes caused by different subsets of genetic and epigenetic abnormalities raises the hypothesis that much of the clinically observable plasticity and heterogeneity occurs within, and not across, these major biological subtypes of breast cancer. The Cancer Genome Atlas Network describe their multifaceted analyses of primary breast cancers, shedding light on breast cancer heterogeneity; although only three genes (TP53, PIK3CA and GATA3) are mutated at a frequency greater than 10% across all breast cancers, numerous subtype-associated and novel mutations were identified. This Article from the Cancer Genome Atlas consortium describes a multifaceted analysis of primary breast cancers in 825 people. Exome sequencing, copy number variation, DNA methylation, messenger RNA arrays, microRNA sequencing and proteomic analyses were performed and integrated to shed light on breast-cancer heterogeneity. Just three genes — TP53, PIK3CA and GATA3 — are mutated at greater than 10% frequency across all breast cancers. Many subtype-associated and novel mutations were identified, as well as two breast-cancer subgroups with specific signalling-pathway signatures. The analyses also suggest that much of the clinically observable plasticity and heterogeneity occurs within, and not across, the major subtypes of breast cancer.

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