Gastrointestinal (GI) cancers are the most frequently diagnosed malignancies and the leading cause of cancer-related deaths worldwide. The asymptotic early stages of the disease lead to most patients being diagnosed at a later stage, with large and genetically/phenotypically heterogeneous tumors. These tumors often contain multiple clones with different driver mutations that render them virtually refractive to current targeted therapies. In the case of gastric cancer (GC), for example, only two targeted therapies are available, and both offer modest benefits to the patients. The consequence of such a natural history is that all targeted therapies are currently administered with classical therapies, either chemotherapy or radiotherapy. This holds true even for new modalities, like immunotherapeutics. If, then, the current paradigm of targeted therapies (targeting driver mutations) is unlikely to be effective in highly heterogenous tumors, we propose to design new targeted therapies that will directly synergize with the classical ones and/or immunotherapy, instead of being merely orthogonal to them. For this synergy to occur, the reason for therapy failure – the development of resistance – needs to be molecularly and functionally delineated.
In our Junior Group at German Cancer Consortium (DKTK), we model the rise of the resistance to therapy in patient-derived organoids, a physiologically relevant culture system that is shown to preserve tumor heterogeneity and can correctly predict patient responses to therapy. This modeling is done across a range of GI entities, including GC and colorectal cancer (CRC), and across a range of current treatment regimens. Omics approaches are used to study genomic, transcriptomic, and proteomic changes along the evolutionary path of resistance acquisition, while functional characterization is achieved via large-scale genetic screens. Our screens utilize a range of Cas9 modalities to mimic different patterns of resistance evolution observed in omics analyses. The main goals of the lab are the identification of pathways that drive resistance to therapy and the rational design of drugs that can resensitize resistant tumors. In collaboration with the clinicians on the campus, we perform validation drug experiments utilizing large organoid biobanks, as well as mouse models.