Current concepts in oncology research aim to individualize cancer treatment which relies on the availability of robust prognostic biomarkers and patient specific drugable targets. A top-down approach, i.e. to test biological hypotheses based on prognostic and therapy predictive signals derived from clinical real-world, followed by functional evidence, seems promising. My research focuses on the pharmacogenomics of breast cancer with particular emphasis on estrogen receptor (ER) signaling, a key to endocrine treatment intervention. This includes i) tamoxifen therapy outcome stratification based on the patients’ metabolic capacity, e.g. due to polymorphic enzymes, and other pharmacokinetic/dynamic determinants and their retrospective validation in large patient cohorts ii) genome-wide search of novel endocrine and chemotherapy predictive markers, iii) molecular profiling of breast tumor cell models, iv) mechanisms of ER signaling, and iv) translational studies to implement diagnostic markers from bench to bed-side.