Predictive biomarkers for personalized medicine in breast cancer

Breast cancer is one of the most frequent malignancies among women worldwide. Based on clinical and molecular features of breast tumors, patients are treated with chemotherapy, hormonal therapy and/or radiotherapy and more recently with immunotherapy or targeted therapy. These different therapeutic options have markedly improved patient outcomes. However, further improvement is needed to fight against resistance to treatment. In the rapidly growing area of research for personalized medicine, predictive biomarkers - which predict patient response to therapy - are essential tools to select the patients who are most likely to benefit from the treatment, with the aim to give the right therapy to the right patient and avoid unnecessary overtreatment. The search for predictive biomarkers is an active field of research that includes genomic, proteomic and/or machine learning approaches. In this review, we describe current strategies and innovative tools to identify, evaluate and validate new biomarkers. We also summarize current predictive biomarkers in breast cancer and discuss companion biomarkers of targeted therapy in the context of precision medicine. •Resistance to treatment remains a major cause of death among breast cancer patients and is a driving force for the development of predictive biomarkers.•Predictive biomarkers allow to identify breast cancer patients who are likely to benefit from a particular therapy, and predict the efficiency of a given treatment as well as tumor resistance.•The search for new predictive biomarkers is critical to the development of personalized medicine for breast cancer patients.•Novel approaches including -omics and artificial intelligence are being considered for the identification of predictive - molecular or imaging - biomarkers with high accuracy.