Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
and JavaScript.
Substantial progress has been made using aromatase inhibitors in early-stage breast cancer. This article highlights results from recent and ongoing trials of aromatase inhibitors as adjuvant therapy and discusses options for integration of these agents with tamoxifen in various subsets of patients and clinical scenarios.
Development of therapies directed to specific molecular abnormalities within cancer cells, as exemplified by human epidermal growth factor receptor 2 (HER2), can be a very rewarding strategy in cancer treatment. The integration of genomic and proteomic approaches into the search for therapeutic targets will be more fruitful than either approach alone and allow further individualization of breast cancer therapy.
As our understanding of cancer evolves, the perceptions and prevailing paradigms that define this disease have also changed. The molecular basis of cancer has helped to influence oncology clinical practice; however, paradigms affect both the focus and design of research and also impact upon patient care. A clear recognition of how these varying perceptions of cancer affect and limit communication among the cancer-related disciplines as well as between these disciplines is needed. Both professionals and the general public should consider cancer as a group of diseases for which cure is related to tumor type, stage and available treatment.
Important changes in the field of epidemiology as a result of genotyping, identification of genetic and gene-environment causes of disease, and proteomics will ultimately influence all aspects of medical practice. The necessity for good study design, and the difference between observation and experiment, is paramount in this regard. This review discusses opportunities for molecular classification of disease that will help tailor treatment to the biologic profile of the patient and disease.
Breast cancer is a multifactorial condition, and changes in cellular biology are affected by a large number of variables known to affect an individual's susceptibility to this malignancy. Current risk prediction models are based on combinations of risk factors and have good predictive but low discriminatory power. Risk estimation might be improved by incorporating additional factors into risk prediction models, which will allow better determination of breast cancer risk and provide new targets for preventive therapies.
