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High-throughput genetic analysis of breast cancer results in improved classification of breast cancer and can be used to identify prognostic and predictive factors. These prognostic and predictive factors are increasingly useful to guide therapy decisions in individual breast cancer patients.  There is a rapidly increasing body of literature on gene expression signatures associated with prognosis; and on gene expression signatures associated with response to specific systemic treatment, including chemotherapy, hormonal therapy and HER2 targeted therapy. The main prognostic profiles published to date are a 70-gene signature identified by our group in the Netherlands Cancer Institute (Amsterdam, the Netherlands); a 76-gene prognosis profile identified by investigators from Erasmus Medical Centre (Rotterdam, the Netherlands; a 21-gene recurrence score developed by the company Genomic Health (Redwood City, USA); and a genomic-grade signature developed by investigators at the Institut Bordet (Brussels, Belgium).  Breast cancer is a very heterogeneous disease, and prognostic and predictive profiles may differ in breast cancer subtypes. We are therefore currently performing gene expression profiling studies, assessment of DNA copy number changes and miRNA expression profiles in triple-negative breast cancers (n = 96) and HER2-positive breast cancers (n = 140).  Prognostic classifiers can be used to identify patients that will benefit most from adjuvant systemic therapy, but other classifiers will be needed to decide which treatment should be given.  To guide the choice of chemotherapy, hormonal therapy and targeted therapy, neoadjuvant studies are well suited to identify predictive factors for therapy response. For this purpose, we have analysed gene expression profiles in pretreatment biopsies of 191 patients treated with neoadjuvant chemotherapy; and patients with HER2-positive breast cancer treated with the combination of chemotherapy and trastuzumab. Our results and studies from various other groups show that basal-type/triple-negative tumors show a pathological complete remission in 30 to 40% of cases; as compared with <5% in luminal-type tumors. It has been more difficult to identify gene expression profiles associated with response to chemotherapy and response to trastuzumab using supervised classification techniques. Research aimed at the identification of genetic classifiers for responsiveness to specific systemic therapies is expanding rapidly and should lead to clinically useful tests in the coming years.  At present, there are several ongoing randomised clinical trials investigating genetic profiling in guiding adjuvant systemic therapy; and in neoadjuvant systemic therapy. These studies will enable us to better understand differences between genetic sets; and will allow us to develop our preferences based on results obtained in large well-controlled trials.

Genetic profile sets: differences and preferences