Genomic approaches in the management and treatment of breast cancer

Abstract

Breast cancer is the most common malignancy afflicting women from Western cultures. It has been estimated that approximately 211 000 women will be diagnosed with breast cancer in 2003 in the United States alone, and each year over 40 000 women will die of this disease. Developments in breast cancer molecular and cellular biology research have brought us closer to understanding the genetic basis of this disease. Unfortunately, this information has not yet been incorporated into the routine diagnosis and treatment of breast cancer in the clinic. Recent advancements in microarray technology hold the promise of further increasing our understanding of the complexity and heterogeneity of this disease, and providing new avenues for the prognostication and prediction of breast cancer outcomes. The most recent application of microarray genomic technologies to studying breast cancer will be the focus of this review. Mortality from breast cancer results from the ability of some tumours to metastasise to distant sites. Selecting patients with micrometastases at diagnosis is crucial for clinicians in deciding who should and who should not receive toxic and expensive adjuvant chemotherapy to eradicate these metastatic cells. Axillary nodal status, the best marker now available, is still an imperfect indicator, since about 25% of node-negative patients do harbour micrometastases and are destined to recur, while up to 25% of node-positive patients will not recur even without adjuvant treatment after many years of follow-up. In spite of extensive studies, expression of most individual genes has not proven powerful enough for routine clinical use to predict accurately distant metastases over the lifetime of an individual patient. However, recent developments in applying microarray technologies to breast tumour samples suggest that these new techniques may provide for the transition of molecular biological discoveries to clinical application, and will generate clinically useful genomic profiles that more accurately predict long-term outcome of individual breast cancer patients. NATURAL HISTORY OF BREAST CANCERBreast cancer is characterised by a very heterogeneous clinical course. A major goal of recent studies is to determine whether RNA microarray expression profiling, or DNA array gene amplification/gene loss patterns, can accurately predict an individual's long-term potential for recurrence from breast cancer, so that appropriate treatment decisions can be made. It is well established that some aspects of breast cancer heterogeneity is related to the different risk factors for diagnosis of this disease, such as race, diet, age, environmental factors, and cumulative exposure to the sex hormone oestrogen. The diversity in clinical course of breast cancer is undoubtedly related to differences in tumour growth rates, tumour invasiveness, metastatic potential, and other complex cellular growth signalling and survival pathways. It has long been held that knowledge of these various biological factors would help individualise patient t...

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