Fibroblast growth factor receptors (FGFRs) are recurrently altered by single nucleotide variants (SNVs) in many human cancers. The prevalence of SNVs in FGFRs depends on the cancer type. In some tumors, such as the urothelial carcinoma, mutations of FGFRs occur at very high frequency (up to 60%). Many characterized mutations occur in the extracellular or transmembrane domains, while fewer known mutations are found in the kinase domain. In this study, we performed a bioinformatics analysis to identify novel putative cancer driver or therapeutically actionable mutations of the kinase domain of FGFRs. To pinpoint those mutations that may be clinically relevant, we exploited the recurrence of alterations on analogous amino acid residues within the kinase domain (PK_Tyr_Ser-Thr) of different kinases as a predictor of functional impact. By exploiting MutationAligner and LowMACA bioinformatics resources, we highlighted novel uncharacterized mutations of FGFRs which recur in other protein kinases. By revealing unanticipated correspondence with known variants, we were able to infer their functional effects, as alterations clustering on similar residues in analogous proteins have a high probability to elicit similar effects. As FGFRs represent an important class of oncogenes and drug targets, our study opens the way for further studies to validate their driver and/or actionable nature and, in the long term, for a more efficacious application of precision oncology.
Keywords: FGFR; Protein domain; Protein kinase; Recurrence; Somatic mutation.
Copyright © 2021. Published by Elsevier B.V.