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Breast cancer (BC) comprises a diverse spectrum of diseases featuring distinct presentation, morphological, biological, and clinical phenotypes. BC behaviour and response to therapy also vary widely. Current evidence indicates that traditional prognostic and predictive classification systems are insufficient to reflect the biological and clinical heterogeneity of BC. Advancements in high-throughput molecular techniques and bioinformatics have contributed to the improved understanding of BC biology, refinement of molecular taxonomies and