World Health Organization classification of tumours of the breast 6th edition 2026
Cecily Quinn, Puay Hoon Tan, Kimberly H. Allison, Edi Brogi, Sunil R. Lakhani, Stuart J. Schnitt, Stephen B. Fox, Shabnam Jaffer 等 29 位
St. Vincent's University Hospital Eye & Retina Surgeons Stanford University Memorial Sloan Kettering Cancer Center
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The 6th edition of the WHO Classification of Breast Tumours introduces both major and minor changes based on recent advances in our understanding of breast biology, developments in diagnostic modalities, identification of specific molecular targets and new treatment regimens necessitating modifications to pathology reporting and tumour biomarker categorisation. This review summarises the main changes that strive towards a classification of global relevance. In invasive carcinoma, predictive factors increasingly inform modern breast cancer treatment. The 6th edition provides an update on HER2 reporting categories following the DESTINY-Breast 04 and 06 trials. Terminologies used to classify invasive tumours are clarified, with the term 'variant' now reserved for molecular/genetic alterations. Invasive lobular carcinoma (ILC) with extracellular mucin is recognised as a new diagnostic entity with prognostic implications. The diagnosis of mucinous carcinoma (MC) is reserved for mucin secreting carcinomas with grade 1 or 2 morphology and a favourable biomarker profile. The diagnosis of malignant phyllodes tumours requires only four of the original five adverse histological criteria. Classification of neuroendocrine tumours (NETs) is revised, recognising that the unified model, promoted in the 5th edition, is difficult to apply to the breast. New approaches to the classification of adenomyoepithelioma are discussed but the 5th edition system is broadly retained. A new section on 'Small Diagnostic Samples' outlines the merits of non-operative biopsy diagnosis, the B coding system and the importance of multidisciplinary review. Changes to diagnostic practice and the emerging role of artificial intelligence, with advantages and challenges, are discussed in a new section on 'Digital Pathology'.
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生物医学Breast Lesions and Carcinomas
Breast Cancer Treatment Studies · AI in cancer detection
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