Division of Radiooncology / Radiobiology

The division of RadioOncology/ RadioBiology works on the translational aspect of integrating radiobiological findings into clinical patient outcome parameters and clinical studies. To follow the translational concept "from bench-to-bedside" in both directions, we are also working on reverse translation bringing clinical findings back to the lab bench in order to unravel the biological mechanisms behind radiotherapy and combined radiotherapy treatments. Both directions of the translational chain require the efforts of a multidisciplinary team of clinician scientists, bioinformaticians, biologists, and biostatisticians and their close interactions. Our research ranges from basic biology over biostatistics and pre-clinical trials to medical informatics, including image processing, and assistance and support of clinical studies.

In close collaboration with our partners here at the DKFZ, the clinic and site-overarching with the German Cancer Consortium (DKTK), our current projects include:

• Elucidation of molecular mechanisms of radioresistance in tumor models with special emphasis on the hypoxic micromilieu in tumors and the investigation of inter- and intratumoral heterogeneity on single cell level
• Biomarker validation and drug screens in preclinical set-ups of 3D in vitro cultures and mouse models
• Clinical study design, management and monitoring

The knowledge generated (not only) with our research will be translated into the conception of clinical trials for personalized treatments. Future clinical trials and anti-tumor therapies won´t rely on a single treatment modality but rather on combinatorial therapies customized to the patient’s individual known clinical and biological profile. New insight into the molecular biological mechanisms of radioresistance and tumor heterogeneity will help to establish intracellular signaling pathways involved in therapy failure and thereby elucidate potential drugable targets in combination with radiotherapy. Patients' individual imaging parameters will be used to compare and integrate them with the corresponding clinical and biological information in order to further stratify each patient for the most effective and least aggressive therapy.