Cancer Research
Prof. Dr. Sven Diederichs
Cancer is frequently driven by genetic aberrations like mutations. However, for the vast majority of mutations, their functional relevance for tumorigenesis as well as their impact on therapy response or drug sensitivity is unknown. This excludes a large part of the information available from cancer genome analysis from clinical decision making.
Functional genomics is thus crucial to interpret cancer genome data and to understand the biological impact of each individual mutation. Indeed, precision oncology relies on the characterization of these mutations to clinically match patients with the best available targeted therapies. However, except for the few better studied hotspot mutations, most cancer mutations are variants of unknown significance (VUS) whose impact on activation and drug sensitivity or resistance is widely unknown considerably limiting the number of therapeutic options despite the availability of inhibitors for the corresponding targets. Given the huge number of different mutations found in cancer genomes, high-throughput approaches are essential to characterize relevant numbers of mutations in parallel.
Our research focuses on high-throughput functional and translational genomics at the mutation level. Therefore, we are not only investigating the impact of entire genes on cancer, but the effect of each individual mutation since an individual tumor also harbors only one or multiple individual mutations.
As a prime example, we have selected the Fibroblast Growth Factor Receptor (FGFR) family, since its members FRGFR1, FGFR2, FGFR3 and FGFR4 are often altered in many different tumor entities including lung, bladder, breast or endometrial cancer as well as cholangiocarcinoma and are established drivers of tumorigenesis. Moreover, there are approved FGFR inhibitors available in the clinic. However, for the large number of frequently occurring point mutations in cancer, it is unknown whether they indeed activate the FGFR pathway and which effect they have of drug sensitivity or drug resistance. Thus, we have created a library of every possible mutation in the FGFR family - altogether almost 30000 mutations - and test them for their activation and druggability. The resulting comprehensive catalog allows the selection of tumors for FGFR inhibitor therapy which are likely to respond and offer other therapy options to patients whose tumors are unlikely to respond.
In addition, we discover and characterize non-canonical types of mutations (EMBO Mol Med 2016) like nonstop extension / stop-loss (Nat Cell Biol 2020) or synonymous mutations (Nat Commun 2019) and explore their role in cancer, their functional impact and their molecular mechanisms.
Taken together, we aim to functionally characterize many more cancer-derived mutations to make them informative for therapy selection.
Future projects and goals
In the future, we will expand our FGFR saturation mutational scanning approach to other FGFR inhibitors, then further to other oncogenes and drug targets to aid in clinical decision support.
For the translation of our results into the clinic, we aim to test our drug response prediction from functional screening in a clinical trial to verify and establish the complete map of actionable mutations in the FGFR family across tumor entities.
Prof. Dr. Sven Diederichs
Head of department - partner site Freiburg
University Hospital Freiburg Department of Thoracic Surgery
Division of Cancer Research