Leveraging Systematic Functional Analysis to Benchmark an Framework Distinguishes Driver from Passenger MEK Mutants in Cancer.

Despite significant advances in cancer precision medicine, a significant hurdle to its broader adoption remains the multitude of variants of unknown significance identified by clinical tumor sequencing and the lack of biologically validated methods to distinguish between functional and benign variants. Here we used functional data on and mutations generated in real-time within a co-clinical trial framework to benchmark the predictive value of a three-part methodology. Our computational approach to variant classification incorporated hotspot analysis, three-dimensional molecular dynamics simulation, and sequence paralogy.