Summary Although RAF kinases are critical for controlling cell growth, their mechanism of activation is incompletely understood. Recently, dimerization was shown to be important for activation. Here we show that the dimer is functionally asymmetric with one kinase functioning as an activator to stimulate activity of the partner, receiver kinase. The activator kinase did not require kinase activity, but did require N-terminal phosphorylation that functioned allosterically to induce cis-autophosphorylation of the receiver kinase. Based on modeling of the hydrophobic spine assembly, we also engineered a constitutively active mutant that was independent of Ras, dimerization, and activation loop phosphorylation. Since N-terminal phosphorylation of BRAF is constitutive, BRAF initially functions to activate CRAF. N-terminal phosphorylation of CRAF was dependent on MEK suggesting a feedback mechanism and explaining a key difference between BRAF and CRAF. Our work illuminates distinct steps in RAF activation that function to assemble the active conformation of the RAF kinase.

Next-generation sequencing (NGS) can identify novel cancer targets. However, interpreting the molecular findings and accessing drugs/clinical trials is challenging. Furthermore, many tumors show resistance to monotherapies. To implement a precision strategy, we initiated a multidisciplinary (basic/translational/clinical investigators, bioinformaticians, geneticists, and physicians from multiple specialties) molecular tumor board (MTB), which included a project manager to facilitate obtaining clinical-grade biomarkers (blood/tissue NGS, specific immunohistochemistry/RNA expression including for immune-biomarkers, per physician discretion) and medication-acquisition specialists/clinical trial coordinators/navigators to assist with medication access. The MTB comprehensively reviewed patient characteristics to develop N-of-One treatments implemented by the treating physician’s direction under the auspices of a master protocol. Overall, 265/429 therapy-evaluable patients (62%) were matched to ≥1 recommended drug. Eighty-six patients (20%) matched to all drugs recommended by MTB, including combinatorial approaches, while 38% received physician’s choice regimen, generally with unmatched approach/low degree of matching. Our results show that patients who receive MTB-recommended regimens (versus physician choice) have significantly longer progression-free (PFS) and overall survival (OS), and are better matched to therapy. High (≥50%) versus low (<50%) Matching Score therapy (roughly reflecting therapy matched to ≥50% versus <50% of alterations) independently correlates with longer PFS (hazard ratio [HR], 0.63; 95% confidence interval [CI], 0.50–0.80; P < 0.001) and OS (HR, 0.67; 95% CI, 0.50–0.90; P = 0.007) and higher stable disease ≥6 months/partial/complete remission rate (52.1% versus 30.4% P < 0.001) (all multivariate). In conclusion, patients who receive MTB-based therapy are better matched to their genomic alterations, and the degree of matching is an independent predictor of improved oncologic outcomes including survival.

To investigate the unregulated Ras activation associated with cancer, we developed and validated a mathematical model of Ras signaling. The model-based predictions and associated experiments help explain why only one of two classes of activating Ras point mutations with in vitro transformation potential is commonly found in cancers. Model-based analysis of these mutants uncovered a systems-level process that contributes to total Ras activation in cells. This predicted behavior was supported by experimental observations. We also used the model to identify a strategy in which a drug could cause stronger inhibition on the cancerous Ras network than on the wild-type network. This system-level analysis of the oncogenic Ras network provides new insights and potential therapeutic strategies.

Cancer treatment decisions are increasingly guided by which specific genes are mutated within each patient’s tumor. For example, agents inhibiting the epidermal growth factor receptor (EGFR) benefit many colorectal cancer (CRC) patients, with the general exception of those whose tumor includes a KRAS mutation. However, among the various KRAS mutations, that which encodes the G13D mutant protein (KRASG13D) behaves differently; for unknown reasons, KRASG13D CRC patients benefit from the EGFR-blocking antibody cetuximab. Controversy surrounds this observation, because it contradicts the well-established mechanisms of EGFR signaling with regard to RAS mutations. Here, we identified a systems-level, mechanistic explanation for why KRASG13D cancers respond to EGFR inhibition. A computational model of RAS signaling revealed that the biophysical differences between the three most common KRAS mutants were sufficient to generate different sensitivities to EGFR inhibition. Integrated computation with experimentation then revealed a nonintuitive, mutant-specific dependency of wild-type RAS activation by EGFR that is determined by the interaction strength between KRAS and the tumor suppressor neurofibromin (NF1). KRAS mutants that strongly interacted with and competitively inhibited NF1 drove wild-type RAS activation in an EGFR-independent manner, whereas KRASG13D weakly interacted with and could not competitively inhibit NF1 and, thus, KRASG13D cells remained dependent on EGFR for wild-type RAS activity. Overall, our work demonstrates how systems approaches enable mechanism-based inference in genomic medicine and can help identify patients for selective therapeutic strategies.