Oncogenic mutations in the serine/threonine kinase B-RAF are found in 50–70% of malignant melanomas1. Pre-clinical studies have demonstrated that the B-RAFV600E mutation predicts a dependency on the mitogen activated protein kinase (MAPK) signaling cascade in melanoma1–5—an observation that has been validated by the success of RAF and MEK inhibitors in clinical trials6–8. However, clinical responses to targeted anticancer therapeutics are frequently confounded by de novo or acquired resistance9–11. Identification of resistance mechanisms in a manner that elucidates alternative ‘druggable’ targets may inform effective long-term treatment strategies12. Here, we expressed ~600 kinase and kinase-related open reading frames (ORFs) in parallel to functionally interrogate resistance to a selective RAF kinase inhibitor. We identified MAP3K8 (COT/TPL2) as a MAPK pathway agonist that drives resistance to RAF inhibition in B-RAFV600E cell lines. COT activates ERK primarily through MEK-dependent mechanisms that do not require RAF signaling. Moreover, COT expression is associated with de novo resistance in B-RAFV600E cultured cell lines and acquired resistance in melanoma cells and tissue obtained from relapsing patients following treatment with MEK or RAF inhibition. We further identify combinatorial MAPK pathway inhibition or targeting of COT kinase activity as possible therapeutic strategies for reducing MAPK pathway activation in this setting. Together, these results provide new insights into resistance mechanisms involving the MAPK pathway and articulate an integrative approach through which high-throughput functional screens may inform the development of novel therapeutic strategies.

Systematic efforts are underway to decipher the genetic changes associated with tumor initiation and progression. However, widespread clinical application of this information is hampered by an inability to identify critical genetic events across the spectrum of human tumors with adequate sensitivity and scalability. Here, we have adapted high-throughput genotyping to query 238 known oncogene mutations across 1,000 human tumor samples. This approach established robust mutation distributions spanning 17 cancer types. Of 17 oncogenes analyzed, we found 14 to be mutated at least once, and 298 (30%) samples carried at least one mutation. Moreover, we identified previously unrecognized oncogene mutations in several tumor types and observed an unexpectedly high number of co-occurring mutations. These results offer a new dimension in tumor genetics, where mutations involving multiple cancer genes may be interrogated simultaneously and in 'real time' to guide cancer classification and rational therapeutic intervention.

A detailed understanding of the mechanisms by which tumors acquire resistance to targeted anticancer agents should speed the development of treatment strategies with lasting clinical efficacy. RAF inhibition in BRAF-mutant melanoma exemplifies the promise and challenge of many targeted drugs; although response rates are high, resistance invariably develops. Here, we articulate overarching principles of resistance to kinase inhibitors, as well as a translational approach to characterize resistance in the clinical setting through tumor mutation profiling. As a proof of principle, we performed targeted, massively parallel sequencing of 138 cancer genes in a tumor obtained from a patient with melanoma who developed resistance to PLX4032 after an initial dramatic response. The resulting profile identified an activating mutation at codon 121 in the downstream kinase MEK1 that was absent in the corresponding pretreatment tumor. The MEK1 C121S mutation was shown to increase kinase activity and confer robust resistance to both RAF and MEK inhibition in vitro. Thus, MEK1 C121S or functionally similar mutations are predicted to confer resistance to combined MEK/RAF inhibition. These results provide an instructive framework for assessing mechanisms of acquired resistance to kinase inhibition and illustrate the use of emerging technologies in a manner that may accelerate personalized cancer medicine.