The Co-mutational Spectrum Determines the Therapeutic Response in Murine FGFR2 Fusion-Driven Cholangiocarcinoma

Background and Aims Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver cancer and a highly lethal malignancy. Chemotherapeutic options are limited, but a considerable subset of patients harbors genetic lesions for which targeted agents exist. Fibroblast growth factor receptor 2 (FGFR2) fusions belong to the most frequent and therapeutically relevant alterations in ICC, and the first FGFR inhibitor was recently approved for the treatment of patients with progressed, fusion-positive ICC. Response rates of up to 35% indicate that FGFR-targeted therapies are beneficial in many but not all patients. Thus far, no established biomarkers exist that predict resistance or response to FGFR-targeted therapies in patients with ICC. Approach and Results In this study, we use an autochthonous murine model of ICC to demonstrate that FGFR2 fusions are potent drivers of malignant transformation. Furthermore, we provide preclinical evidence that the co-mutational spectrum acts not only as an accelerator of tumor development, but also modifies the response to targeted FGFR inhibitors. Using pharmacologic approaches and RNA-interference technology, we delineate that Kirsten rat sarcoma oncogene (KRAS)-activated mitogen-activated protein kinase signaling causes primary resistance to FGFR inhibitors in FGFR2 fusion-positive ICC. The translational relevance is supported by the observation that a subset of human FGFR2 fusion patients exhibits transcriptome profiles reminiscent of KRAS mutant ICC. Moreover, we demonstrate that combination therapy has the potential to overcome primary resistance and to sensitize tumors to FGFR inhibition. Conclusions Our work highlights the importance of the co-mutational spectrum as a significant modifier of response in tumors that harbor potent oncogenic drivers. A better understanding of the genetic underpinnings of resistance will be pivotal to improve biomarker-guided patient selection and to design clinically relevant combination strategies.