Estimated sensitivity profiles of lung cancer specific uncommon BRAF mutants towards experimental and clinically approved kinase inhibitors.

Current experimental and clinical data are inadequate to conclusively predict the oncogenicity of uncommon BRAF mutants and their sensitivity towards kinase inhibitors. Therefore, the present study aims at estimating sensitivity profiles of uncommon lung cancer specific BRAF mutations towards clinically approved as well as experimental therapeutics based on computationally derived direct binding energies. Based on the data derived from cBioportal, BRAF mutants displayed significant mutual exclusivity with KRAS and EGFR mutants indicating them as potential drivers in lung cancer. Predicted sensitivity of BRAF-V600E conformed to published experimental and clinical data thus validating the usefulness of computational approach. The BRAF-V600K displayed higher sensitivity to most inhibitors as compared to that of the BRAF-V600E. All the uncommon mutants displayed higher sensitivity than both the wild type and BRAF-V600E towards PLX 8394 and LSN3074753. While V600K, G469R and N581S displayed favorable sensitivity profiles to most inhibitors, V600L/M, G466A/E/V and G469A/V displayed resistance profiles to a variable degree. Notably, molecular dynamic (MD) simulation revealed that increased number of interactions caused enhanced sensitivity of G469R and N581S towards sorafenib. RAF kinase inhibitors were further classified into two groups as per their selectivity (Group I: BRAF-V600E-selective and Group II: CRAF-selective) based on which potential mutation-wise combinations of RAF kinase inhibitors were proposed to overcome resistance. Based on computational inhibitor sensitivity profiles, appropriate treatment strategies may be devised to prevent or overcome secondary drug resistance in lung cancer patients with uncommon mutations.