Abstract: |
Breast cancer is a complex disease and comprises a panoply of entities, each with different biology, prognosis, and response to therapy. The implementation of high-throughput molecular methods has allowed the systematic characterization of the genomic landscape of breast cancer, having a profound effect on our understanding of the disease. Microarray-based gene expression studies have played a pivotal role in unraveling the heterogeneity of breast cancer and have led to the implementation of a molecular classification with prognostic implications and to the development of prognostic signatures. First-generation prognostic signatures, based on the expression of proliferation-related genes, have recently been incorporated in the staging of estrogen receptor-positive breast cancer patients and are key to guide therapeutic decisions in this population. The advent of massively parallel sequencing has allowed the identification of driver genes and actionable mutations in breast cancer, which is crucial to the refinement of the taxonomy of this disease and the guidance of therapy. The vast tumor heterogeneity of breast cancer, however, poses major diagnostic and therapeutic challenges. Novel methodologies, such as liquid biopsies, are being implemented and will undoubtedly allow a more accurate dissection of the evolving genomic landscapes of breast cancers and new opportunities for disease monitoring. It is anticipated that these strategies will soon be incorporated in the diagnostic armamentarium of pathologists for the optimal selection of systemic therapies for breast cancer patients. © Springer International Publishing AG, part of Springer Nature 2019. |