In silico modeling to predict oncogenicity and potential targetability of novel fgfr variants in pediatric low grade glioma

Abstract Pediatric Low grade gliomas (pLGGs) are largely driven by alterations in the RAS-MAPK pathway. The third most commonly mutated gene in pLGGs is the FGFR1 gene, having alterations including fusions, duplications or missense mutations. Accurate identification of these alterations has become increasingly important as FGFR inhibitors enter the therapeutic space. Here we describe a case of a pLGG patient with an FGFR1 W289_insW290 found through NGS in the tumor at diagnosis, and progression, without additional alterations. This extracellular, third-Ig domain mutation has not been reported. Transcriptional and proteomic profiling of the tumor showed low MAPK and high PIK-AKT pathway activation when compared to other gliomas. Literature review identified disorders of bone formation with similar mutations in the homologous FGFR2 gene. One such mutation, FGFR2 W290G favors inter-receptor disulfide bond formation over the normal intra-receptor disulfide bond. To determine if this insertion is a possible driver mutation in our pLGG case, Alphafold2 protein simulation software was used to make in silico models; quality metrics from both Alphafold2 and VADAR1.8 were used. Structure simulations of the FGFR1 insertion mutant (pLDDT = 81.8) and the mutant FGFR2 W290G (pLDDT = 83.4), were generated and compared to a protein data base, experimentally determined structure of wildtype FGFR1. When monomers of all three structures were aligned using PyMol, the root mean square deviations were < 1.5 indicating the structures are correct or the same. Based on these results we concluded that, like the known FGFR2 mutation, this insertion is predicted to cause hyperactivity by inducing prolonged dimerization due to an aberrant inter-receptor disulfide bond but any structural or functional differences only occur when receptors are dimerized. We are currently generating isogenic cell line models to test this hypothesis and treat these cell lines with inhibitors to determine which treatments might work best for our patient.