Abstract: Methods and systems are presented herein for creating and using cell type-specific, quantitative network models of signaling in cells, such as melanoma, to predict cellular response to untested combinational perturbations. The methods involve performing a set of perturbation experiments with cells of a particular type to produce phosphoproteomic and/or phenotypic profiles for the cells; automatically extracting prior pathway information from one or more known databases to build a qualitative prior model; building a signaling pathway model from (i) the phosphoproteomic and/or phenotypic profiles produced from the perturbation experiments and (ii) the qualitative prior model from the known database(s); and performing in silico perturbations using the signaling pathway model to predict responses to a set of perturbation conditions not yet experimentally tested, and identifying one or more candidate drug combinations from the predicted responses.

Abstract: Presented herein are methods of treating cancer, for example, RAFi-resistant melanoma, using a combination of a bromodomain inhibitor such as JQ1, together with either a MEK inhibitor (e.g., MEKi) or a BRAF inhibitor (e.g., RAFi). These combinations were identified from candidate combinations produced by a cell type-specific, quantitative network model of signaling in cells (e.g., melanoma) to predict cellular response to untested combinatorial perturbations.