Currently, decision-making for
breast cancer treatment in the clinical setting is mainly based on clinical data, histomorphological features of the
tumor tissue and a few
cancer biomarkers such as
steroid hormone receptor status (
estrogen and
progesterone receptors) and
oncoprotein HER2 status. Although various therapeutic options were introduced into the clinic in recent decades, with the objective of improving surgery,
radiotherapy, biochemotherapy and
chemotherapy, varying response of individual patients to certain types of
therapy and
therapy resistance is still a challenge in
breast cancer care. Therefore, since
breast cancer treatment should be based on individual features of the patient and her
tumor, tailored
therapy should be an option by integrating
cancer biomarkers to define patients at risk and to reliably predict their course of the disease and/or response to
cancer therapy. Recently, candidate-marker approaches and genome-wide transcriptomic and epigenetic screening of different
breast cancer tissues and bodily fluids resulted in new promising
biomarker panels, allowing
breast cancer prognosis, prediction of
therapy response and monitoring of
therapy efficacy. These
biomarkers are now subject of validation in prospective clinical trials.