Targeted therapy, molecular imaging and biomarkers in cancer treatment: Getting more personalized

In recent years, great progress has been made in the development of targeted therapy against cancer. However, it is also more recognized that these treatments are often only successful in a subgroup of patients. One of the current challenges in oncology lies in identifying these patients and thereby avoiding treating patients with non-effective treatments and thus avoid side-effects of these drugs and reduce costs. This way, cancer medicine will become more and more personalized: a specific therapy for a specific tumor in a specific patient, with as little side-effects as possible. In this thesis, different ways of selecting patients are studied. Using PET scans with different radioactive labeled markers might be useful to predict whether a patient will benefit from a certain treatment. Furthermore, we studied whether biomarkers measured in blood samples can be used to predict side-effects in patients.