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      Breast Cancer Molecular Stratification: From Intrinsic Subtypes to Integrative Clusters.

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          Abstract

          Breast carcinomas can be stratified into different entities based on clinical behavior, histologic features, and/or by biological properties. A classification of breast cancer should be based on underlying biology, which we know must be determined by the somatic genomic landscape of mutations. Moreover, because the latest generations of anticancer agents are founded on biological mechanisms, a detailed molecular stratification is a requirement for appropriate clinical management. Such stratification, based on genomic drivers, will be important for selecting patients for clinical trials. It will also facilitate the discovery of novel drivers, the study of tumor evolution, and the identification of mechanisms of treatment resistance. Assays for risk stratification have focused mainly on response prediction to existing treatment regimens. Molecular stratification based on gene expression profiling revealed that breast cancers could be classified in so-called intrinsic subtypes (luminal A and B, HER2-enriched, basal-like, and normal-like), which mostly corresponded to hormone receptor and HER2 status, and further stratified luminal tumors based on proliferation. The realization that a significant proportion of the gene expression landscape is determined by the somatic copy number alterations that drive expression in cis led to the newer classification of breast cancers into integrative clusters. This stratification of breast cancers into integrative clusters reveals prototypical patterns of single-nucleotide variants and is associated with distinct clinical courses and response to therapy.

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          Author and article information

          Journal
          Am. J. Pathol.
          The American journal of pathology
          Elsevier BV
          1525-2191
          0002-9440
          Oct 2017
          : 187
          : 10
          Affiliations
          [1 ] Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway; Department of Pathology, Oslo University Hospital Radiumhospitalet, Oslo, Norway.
          [2 ] Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway; Department of Computer Science, University of Oslo, Oslo, Norway.
          [3 ] Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway; Department of Medicine, University of Oslo, Oslo, Norway.
          [4 ] Department of Oncology, Cancer Research UK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom. Electronic address: carlos.caldas@cruk.cam.ac.uk.
          Article
          S0002-9440(17)30134-7
          10.1016/j.ajpath.2017.04.022
          28733194
          cbdfc16e-e475-4ce5-862a-eef5e1e19428
          History

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