FGFR2 fusion protein-driven mouse models of intrahepatic cholangiocarcinoma unveil a necessary role for Erk signalling

Abstract

Background and aimsAbout 15% of intrahepatic cholangiocarcinoma (iCCA) express fibroblast growth factor receptor 2 (FGFR2) fusion proteins (FFs), most often in concert with mutationally inactivated TP53, CDKN2A or BAP1. FFs span residues 1-768 of FGFR2 fused to sequences encoded by any of a long list (>60) of partner genes, a configuration sufficient to ignite oncogenic FF activation. In line, FGFR-specific tyrosine kinase inhibitors (F-TKI) were shown to provide clinical benefit in FF+ iCCA, although responses were partial and/or limited by resistance mechanisms, including the FF V565F gatekeeper mutation. Herein we present an FF-driven murine iCCA model and exploit its potential for pre-clinical studies on FF therapeutic targeting. MethodsFour iCCA FFs carrying different fusion sequences were expressed in Tp53-/- mouse liver organoids. Tumorigenic properties of genetically modified liver organoids were assessed by intrahepatic/subcutaneous transplantation in immuno-deficient mice. Cellular models derived from neoplastic lesions were exploited for pre-clinical studies. ResultsTumors diagnosed as CCA were obtained upon transplantation of FF-expressing liver organoids. The penetrance of this tumorigenic phenotype was influenced by FF identity. Tumor organoids and 2D cell lines derived from CCA lesions were addicted to FF signaling via Ras-Erk, regardless of FF identity or presence of V565F mutation. Double blockade of FF-Ras-Erk pathway by concomitant pharmacological inhibition of FFs and Mek1/2 provided greater therapeutic efficacy than single agent F-TKI in vitro and in vivo. ConclusionsFF-driven iCCA pathogenesis was successfully modelled in murine Tp53-/- background. This model revealed biological heterogeneity among structurally different FFs. Double blockade of FF-Erk signaling deserves consideration for improving precision-based approaches against human FF+ iCCA. Abbreviations used in this paper: ANOVA, analysis of variance; Bap1, BRCA1-Associated-Protein 1; Cdkn2a, cyclin-dependent kinase inhibitor 2A; Cftr, cystic fibrosis transmembrane conductance regulator; Ck19, cytokeratin 19; Cyp3A, cytochrome P450, family 3, subfamily A; EGF, Epidermal growth factor; EGFR, Epidermal growth factor receptor; EpCAM, epithelial cell adhesion molecule; Erk, extracellular signal-regulated kinase; FGFR2, fibroblast growth factor receptor 2; FRS2, fibroblast growth factor receptor substrate 2; GRB2, growth factor receptor-bound 2; GSEA, gene set enrichment analysis; GSVA, gene set variation analysis; H&E, hematoxylin and eosin; HepPar1, hepatocyte Paraffin 1; Hnf4-7, hepatocyte nuclear factor 4 alpha; Hprt, hypoxanthine-guanine phosphoribosyl transferase; LGR5, leucine-rich repeat-containing G-protein coupled receptor 5; NTRK, neurotrophic Tyrosine Kinase; Parp, Poly (ADP-ribose) polymerase; RECIST, response evaluation criteria in solid tumors; SHP2, Src homology phosphatase 2; Ttr, transthyretin.