Abstract
Mutations can be important biomarkers that influence the selection of specific cancer treatments. We recently combined mathematical modeling of RAS signaling network biochemistry with experimental cancer cell biology to determine why KRAS G13D is a biomarker for sensitivity to epidermal growth factor receptor (EGFR)-targeted therapies. The critical mechanistic difference between KRAS G13D and the other most common KRAS mutants is impaired binding to tumor suppressor Neurofibromin (NF1). Here, we hypothesize that impaired binding to NF1 is a "biophysical biomarker" that defines other RAS mutations that retain therapeutic sensitivity to EGFR inhibition. Both computational and experimental investigations support our hypothesis. By screening RAS mutations for this biophysical characteristic, we identify 10 additional RAS mutations that appear to be biomarkers for sensitivity to EGFR inhibition. Altogether, this work suggests that personalized medicine may benefit from migrating from gene-based and allele-based biomarker strategies to biomarkers based on biophysically defined subsets of mutations.