Breast cancer is no longer thought of as a single disease, but rather as collection of subtypes characterized by molecular signatures. The use of gene array analysis has provided insights into the dominant driver pathways that effect individual tumors and translate into clinical manifestations of the disease, response to treatment and overall clinical outcome. Breast cancer represents a heterogeneous group of diseases with various clinical presentations, responses to treatment, and outcomes. Several clinical factors affect prognosis, such as tumor size, nodal involvement, nuclear grade, histologic type, molecular markers, and surgical margins. Even taking these factors into account, there remains great variation in the behavior of breast cancer. The limitations of the prognostic value of these variables have underscored the rational for developing gene expression profiling of tumor tissue to try to further classify individual tumors to provide more reliable information regarding response to prognosis and treatment. Perou et al. (2000) proposed that the phenotypical diversity of breast tumors could also be associated with diverse gene expression patterns. To evaluate this, Perou et al. used cDNA microarrays to analyze genetic profiles and grouped genes based on their similar patterns of expression. Subsequently, Sorlie et al. (2001, 2003) demonstrated breast tumors can be divided into four distinct molecular subtypes: (i) luminal A, (ii) luminal B, (iii) HER2-type, and (iv) basallike. Investigations of these subtypes in women with breast cancer have given insight into the heterogeneous biology and outcomes in patients with early-stage and locally advanced disease. These subtypes have subsequently been found to correlate with prognosis, response to systemic therapy, and locoregional recurrence.
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging