SUMMARY BRAFV600E drives tumors by dysregulating ERK signaling. In these tumors, we show that high levels of ERK-dependent negative feedback potently suppress ligand-dependent mitogenic signaling and Ras function. BRAFV600E activation is Ras-independent and it signals as a RAF-inhibitor sensitive monomer. RAF inhibitors potently inhibit RAF monomers and ERK signaling, causing relief of ERK-dependent feedback, reactivation of ligand-dependent signal transduction, increased Ras-GTP and generation of RAF inhibitor-resistant RAF dimers. This results in a rebound in ERK activity and culminates in a new steady state, wherein ERK signaling is elevated compared to its initial nadir after RAF inhibition. In this state, ERK signaling is RAF inhibitor resistant, and MEK inhibitor sensitive, and combined inhibition results in enhancement of ERK-pathway inhibition and antitumor activity.

Recent studies have identified somatic ESR1 mutations in patients with metastatic breast cancer (MBC) and found some of them to promote estrogen-independent activation of the receptor. The degree to which all recurrent mutants can drive estrogen-independent activities and reduced sensitivity to ER antagonists like fulvestrant is not established. In this report, we characterize the spectrum of ESR1 mutations from over 900 patients. ESR1 mutations were detected in 10%, with D538G being the most frequent (36%), followed by Y537S (14%). Several novel, activating mutations were also detected (e.g. L469V, V422del, Y537D). While many mutations lead to constitutive activity and reduced sensitivity to ER antagonists, only select mutants such as Y537S caused a magnitude of change associated with fulvestrant resistance in vivo. Correspondingly, tumors driven by Y537S, but not D5358G, E380Q or S463P were less effectively inhibited by fulvestrant than more potent and bioavailable antagonists including AZD9496. These data point to a need for antagonists with optimal pharmacokinetic properties to realize clinical efficacy against certain ESR1 mutants.

Precision medicines exert selective pressure on tumor cells that leads to the preferential growth of resistant subpopulations, necessitating the development of next generation therapies to treat the evolving cancer. The PIK3CA/AKT/mTOR pathway is one of the most commonly activated pathways in human cancers1, which has led to the development of small molecule inhibitors that target various nodes in the pathway. Among these agents, first generation mTOR inhibitors (rapalogs) have caused responses in so-called “N-of-1” cases and second generation mTOR kinase inhibitors (TORKi) are currently in clinical trials2–4. We sought to delineate the likely resistance mechanisms to existing mTOR inhibitors as a guide for next generation therapies. The mechanism of resistance to the TORKi was unusual in that intrinsic kinase activity of mTOR was increased, rather than a direct active site mutation interfering with drug binding. Indeed, the identical drug resistant mutations have been also identified in drug-naïve patients4, suggesting that tumors with activating mTOR mutations will be intrinsically resistant to second generation mTOR inhibitors. Here, we report the development of a new class of mTOR inhibitors which overcomes resistance to existing first and second generation inhibitors. The third generation mTOR inhibitor exploits the unique juxtaposition of two drug binding pockets to create a bivalent interaction that allows inhibition of these resistant mutants.

Recent genome-wide chromosome conformation capture assays such as Hi-C and HiChIP have vastly expanded the resolution and throughput with which we can study 3D genomic architecture and function. Here, we present HiC-DC+, a software tool for Hi-C/HiChIP interaction calling and differential analysis using an efficient implementation of the HiC-DC statistical framework. HiC-DC+ integrates with popular preprocessing and visualization tools and includes topologically associating domain (TAD) and A/B compartment callers. We found that HiC-DC+ can more accurately identify enhancer-promoter interactions in H3K27ac HiChIP, as validated by CRISPRi-FlowFISH experiments, compared to existing methods. Differential HiC-DC+ analyses of published HiChIP and Hi-C data sets in settings of cellular differentiation and cohesin perturbation systematically and quantitatively recovers biological findings, including enhancer hubs, TAD aggregation, and the relationship between promoter-enhancer loop dynamics and gene expression changes. HiC-DC+ therefore provides a principled statistical analysis tool to empower genome-wide studies of 3D chromatin architecture and function.