Research Programs & Groups
Dedicated research programs have been established for Tumor Immunology, Epigenetics, Genetics and Genomics, Oncogenic Signaling and Imaging and Technology Development to streamline and facilitate the translation of scientific discoveries into clinical application. In these programs, scientists and physicians from around 50 research groups and clinical departments from the UZH, USZ, Children's Hospital, Balgrist University Hospital and ETH work closely together aiming to develop novel therapeutic and diagnostic procedures and to ultimately improve cancer patient care.
There is clear evidence from patients and preclinical cancer models that the immune system can control the development of malignancies, a process termed tumor immune surveillance. However, anti-tumor immune responses are frequently subverted by tumors. Recent evidence suggests that the immune system not only fails to eliminate established tumors and their metastases but it actually creates a niche enabling a pre-malignant lesion to develop into a tumor which has ”learned” to evade immune surveillance. Despite these challenges the concept of utilizing and manipulating the immune system to control or eliminate tumors is a promising therapeutic option. Over the past ten years, advances have been made in anti-cancer strategies, including the use of immunotherapies. However, insufficient attention has been paid to the development of multimodal approaches combining the inhibition of key tumor signaling pathways and immunotherapy. The aim is to improve our understanding of the interactions between tumor and the immune system by joint projects involving clinical and basic researchers as well as the biobanks. Ultimately, this will lead to design of new therapeutic strategies focusing on combined regimens and personalized approaches.
Maries van den Broek
The intercellular signals and intracellular signal transduction pathways that control the development of all multicellular organisms are frequently mutated and deregulated in human cancers and as such contribute to growth and invasion. Thus, research on simple animal model organisms, such as C. elegans (roundworm) or D. melanogaster (fruit fly), significantly contributes to the understanding of genetic and biochemical events leading to cancer formation. By bringing together researchers studying oncogenic signaling pathways during normal animal development with clinical researcher studying the same pathways in human tumor cells, we generate many synergies from which both clinical and basic research will benefit. A long-term outcome of this research is that we will better understand the compensatory effects underlying cancer drug resistance of tumor cells and be able to predict the outcome of specific pharmacological interventions at the molecular level. Obtaining this knowledge is an essential requirement for the development of personalized cancer therapies.
We have witnessed tremendous technological progress in various fields such as computer science, robotics, sensor development, big data analysis and artificial intelligence. Many of these developments have been transferred into medicine and have contributed to a substantial improvement in diagnosis and treatment of various cancers. We aim at developing novel medical imaging methodologies such as innovative MRI sequences, targeted PET tracers for PET imaging and in particular quantitative radiomics analysis with the goal of more accurate and deep cancer characterization. In addition, wearable sensors have become broadly available and promise a comprehensive and observed independent patient characterization. Furthermore, molecular high-throughput methodologies (e.g. next-generation sequencing, epigenomics, proteomics, metabolomics and imaging) are indispensable for molecular diagnostics, patient stratification and monitoring of diseases. To integrate and exploit these enormous amounts of heterogeneous high-throughput and clinical data state-of-the the-art bioinformatics and informatics technologies are pivotal. All OMICS approaches benefit from the technological progress with substantially increased sample throughput and simultaneously reduced costs. We aim to systematically integrated these biomarkers into multi-systems decision making algorithms, treatment planning and response assessment. Ultimately, this will lead to novel personalized therapeutic strategies.