PROJECT SUMMARY – PROJECT 1 (AIM 4): Multi-scale modeling of adaptive drug resistance in BRAF- mutant melanoma. The overall goal of Project 1 is to develop an integrated, quantitative understanding of adaptive drug resistance to targeted BRAF and MEK kinase inhibitors in melanoma, with comparative studies performed in BRAF mutant thyroid and colorectal cancers. One of the primary challenges in understanding adaptive drug resistance is the sheer diversity of proposed mechanisms, ranging from reactivation of MAPK signaling, to engagement of parallel PI3K/mTOR/AKT signaling cascades and altered receptor trafficking. Individual published studies focus on subsets of these phenomena, often in different cell lines, and it remains unclear whether differences in emphasis reflect differences in the underlying biology, methodology (single cell RNASeq v. proteomics for example) or time scale (hours vs. weeks). One possibility is that the phenomenological diversity masks the operation of a common mechanism, in which feedback pathways, receptor trafficking, and parallel signaling cascades all play a role. However, because a single patient can harbor melanomas each with a different set of resistance mutations, the observed diversity is likely to be meaningful. The other extreme is that every tumor finds a unique way to become drug resistant, and that we will discover few if any underlying principles. We believe that the most likely explanation lies midway between these extremes: adaptation involves a handful of biochemically distinct mechanisms that can have a variety of presentations depending on cell type, microenvironment, assay method and time scale. We will test this hypothesis by studying adaptive resistance with detailed kinetic modeling and single cell data in a few BRAF-mutant cell lines combined with more phenomenological modeling in a wider range of cell types. Aim 4.1 will use single-cell data and ODE networks to study homeostasis in immediate-early BRAF/MEK/ERK (MAPK) signaling in four cell lines to elucidate the role played by negative feedback loops involving phosphatases and adaptor proteins. Aim 4.2 will examine the phenomenon of de-differentiation and the generation of slowly cycling drug-insensitive cells likely to contribute to residual disease. Aim 4.3 will use similar in-depth methods to study changes in ADAM protease activity and receptor shedding that cause sustained autocrine and paracrine signaling and increased MAPK activity. Aim 4.4 will look at the time evolution of adaptation based on preliminary evidence showing that, in a single cell line, adaptations can involve MAPK feedback in the short term (1-2 days) and de-differentiation and changes in receptor biology on a longer term (days to weeks). Aim 4.5 will use multi-omic analysis across a panel of 20 BRAF mutant cells lines to establish the extent of variability in mechanisms analyzed in Aims 4.1 to 4.4. Statistical and machine learning approaches will identify the changes in intracellular and autocrine/endocrine signaling most consequential for phenotype.