To address this hypothesis, we built and compared multiple machine learning models from a publicly available RPPA dataset for 26 BRAF-V600E pan-cancer cell lines and identified protein signatures predictive of sensitivity to the FDA-approved BRAF inhibitor vemurafenib. The gene discussed is BRAF; the disease is cancer.