Molecular biology in breast cancer: Intrinsic subtypes and signaling pathways

The last decade has brought a breakthrough in the knowledge of the biology of breast cancer. The technological development, and in particular the high throughput technologies, have allowed researchers to inquire more deeply into the nature of the disease through the comparative study of large numbers of samples. The classification of breast cancer by traditional parameters has been joined by rankings based on gene expression. Among the most popular platforms are MammaPrint (R), Oncotype DX (R) the wound-response model, the rate of two genes model, the genomic grade index and the intrinsic subtype model. The latter one provides the amplest biological information and allows for the classification of breast cancer into six intrinsic subtypes: luminal A, luminal B, HER2-enriched, basal-like, normal breast and claudin-low. These new classifications are not yet fully applicable to clinical practice not only because they have not been standardized, but also because they entail a substantial economic outlay. Nevertheless, they have provided valuable information on tumor biology that has led to a better understanding of the signaling pathways governing the processes of formation, maintenance and expansion of the tumors. Researchers now know more about the HER2, estrogen receptor, IGF1R, PI3K/AKT, mTOR, AMPK and angiogenesis pathways which has allowed for the development of new targeted therapeutics now being tested in ongoing clinical trials. In general, one can say that the last decade has changed the way researchers understand, classify and study breast cancer, and it has reshaped the way doctors diagnose and treat this disease. In addition, it has undoubtedly changed the search for alternative therapies by integrating molecular studies and the selection of study populations based on their molecular markers into clinical trials. The present review summarizes the advances that have allowed researchers to both better classify the disease, as well as explore some of the most important signaling pathways. (C) 2011 Elsevier Ltd. All rights reserved.