Cancer is the major cause of disease-related mortality and cancer incidence rates continue to increase. Based on demographic data it is expected that they will continue to do so until 2040, in parallel with ageing of the population. However, more effective treatment regimens have gradually lowered the chance of dying from cancer by ~10% over the past decade. To further improve cancer survival rates research on the causes of cancer, its prevention, and on new and better forms of treatment are essential.
The goal of Translational Cancer Research is to apply the knowledge obtained with basic research to the design of novel treatment modalities and novel tools for diagnosis. Vice versa, it is equally important to use clinical data to formulate scientific research questions.
Novel tumor culture protocols and sophisticated mouse models have greatly improved the quality of translational research. The clinical impact of studies using these platforms will, in all likelihood, be considerably higher than those based on traditional cell culture models. The novel model systems are also increasingly being used for studying basic aspects of tumor biology, metastasis, tumor recurrence following therapy, and therapy resistance. In addition, the rapid development of ‘omics’ technologies that document changes in tumor DNA, RNA, proteins and metabolites allow for an in-depth analysis of the tumors and the genetic background of individual patients. The large datasets that are generated with these techniques requires implementation of Bioinformatics in the research structure. Ultimately these developments should lead to true personalized cancer therapy.
Translational Research can only be successfully done in situations where clinicians and biomedical researchers collaborate closely. The PhD programme Clinical and Translational Oncology strives to optimize such collaboration and most PhD students in the program will work in such an environment.