Signaling Networks in Cancer
We are developing and applying functional genomic screening technologies with the goal to identify novel strategies to treat cancer
The complexity and heterogeneity of cancer poses an enormous challenge for the identification and selection of effective cancer therapies. Genomic alterations identified in human cancers commonly affect components of signaling networks thereby contributing to cancerous phenotypes. As a result, components of these signaling networks represent potential targets for cancer therapy. However, the complex structure of these networks, the extensive crosstalk between pathways and unanticipated feedback control pose a major challenge in the selection of the right targets in individual patients. In addition, the use of pathway inhibitors in a clinical setting is frequently characterized by dramatic but short-lived responses. Phenomena like adaptation and emerge of resistance still represent major hurdles in the further application and success of these drugs.
Our research over the last decade has evolved around the characterization of cancer specific signaling networks with the goal to identify critical components and understand the complex dynamic circuitry of signaling pathways in the context of targeted inhibition. This insight is not only valuable to identify novel targets but also for identification of biomarkers to stratify patients, and to enable the identification of more effective combination therapies.
To achieve these goals, we apply functional genomic technologies (RNA interference, CRISPR, CRISPRi and CRISPRa) combined with large scale screening including small molecule screening that together create an iterative process of characterization, identification and validation of potential targets or combinations thereof.
Currently, the lab has a strong focus on the development of screening technologies not based on cell survival and proliferation but on more complex cellular phenotypes. We are developing cellular sensors, using CRISPR-CAS9 genome editing, that can report the level of diverse cellular processes including mismatch repair, stress pathways or early apoptotic signaling.
Our research increases our understanding of drug response in cancer and creates exiting new strategies for future more effective anti-cancer therapies.