Pan-RAF inhibitor exarafenib targets BRAF class II/III NSCLC and reveals ARAF-KSR1 resistance and combination strategies

Domain: neuroscience
Published: 2026-02-07
Editorial outcome: major_revision

Abstract
Oncogenic BRAF mutations, including those in non-small cell lung cancer (NSCLC), are classified as Class I, II, or III. While approved therapies exist for BRAF Class I mutants, no approved therapies exist for Class II and III BRAF-mutated NSCLC. Analysis of a circulating tumor DNA database reveals Class II and III mutations comprise ~65% of BRAF-mutant NSCLC cases, with Class II patients showing worse outcomes than Class I. Exarafenib, a distinct pan-RAF inhibitor, demonstrates potent activity against BRAF Class II and III mutant preclinical models and initial clinical activity. Resistance studies reveal rewiring to an ARAF-mediated bypass pathway, characterized by RAS-mediated ARAF-KSR1 complexes maintaining MAPK signaling despite pan-RAF inhibitor treatment. RAS or MEK inhibition co-targeting is effective against this resistance mechanism. This study provides preclinical rationale for clinical testing of exarafenib in BRAF Class II/III cancers and unveils RAS-mediated ARAF-KSR1 complex formation as a resistance mechanism and rational co-therapy strategies.

Introduction
The RAF family of serine/threonine kinases, consisting of ARAF, BRAF, and CRAF, plays a pivotal role in the mitogen-activated protein kinase (MAPK) signaling pathway by transducing signals from RAS GTPases to downstream effectors, including MEK and ERK, ultimately regulating cell proliferation, differentiation, and survival1. Under normal physiological conditions, this tightly regulated signaling cascade is essential for normal cell growth and development. However, in cancer, the MAPK pathway is frequently dysregulated, often through oncogenic mutations in RAS or RAF genes, leading to increased pathway activation and oncogenic cell growth2. BRAF mutations are present in a wide range of human cancers, with varying frequency across different tumor types3. These mutations represent a critical therapeutic target, as evidenced by the transformative impact of BRAF inhibitors in melanoma and other cancers. From recent studies, these mutations can be divided into three distinct classes based on their biochemical and signaling mechanisms: Class I mutations (e.g., V600E) are often considered RAS-independent and function as monomers; Class II mutations are independent of RAS and function as homodimers; and Class III mutations depend on RAS and act through heterodimer formation4,5. While selective BRAF inhibitors have transformed the treatment of Class I BRAF V600E-mutant cancers6–8, there remains an unmet need for novel therapeutic strategies that can effectively target a broader spectrum of BRAF mutations that are classically refractory to current approved BRAF inhibitors, such as BRAF Class II and III mutants.

In non-small cell lung cancer (NSCLC), the leading cause of cancer mortality worldwide, BRAF mutations are present in approximately 2-4% of cases9. It is important to note that even a small percentage frequency of a specific genomic subset of NSCLC can equate to a substantial clinical cohort (e.g., tens of thousands of patients annually), given the high incidence of NSCLC in the US and worldwide10,11. Previous studies reporting the frequency and classification of BRAF mutations in NSCLC have been limited by relatively small sample sizes, likely due to the invasive nature of tissue biopsies and the associated risks for patients12,13. This has potentially led to an incompletely accurate estimation of the true prevalence and diversity of these mutations. Furthermore, despite the growing recognition that BRAF mutations are classified into three classes, the clinical characteristics and outcomes of each in patients with NSCLC are not yet fully established12,14–16. Recent advancements in genomic platforms and data repositories, such as the GuardantINFORM™ database17, which is a comprehensive and validated resource of genomic data obtained through non-invasive liquid biopsies from patients with advanced solid tumors, now offer fresh opportunities to more thoroughly investigate the prevalence and distribution of BRAF mutations (and other genomic alterations) in cancers. The use of liquid biopsies, despite certain caveats, can allow for a comprehensive analysis of the tumor genomic landscape, as it can capture tumor heterogeneity and enable the detection of mutations that may be missed by traditional tissue biopsies18,19. By leveraging this valuable resource, we aimed to gain insights into the clinical landscape of BRAF-mutant tumors, with a focus on NSCLC, and identify potential differences in patient outcomes across mutation classes, addressing current knowledge gaps.

Given that there are limited effective therapeutic options for patients with Class II and III BRAF mutations, we also conducted a comprehensive investigation of the therapeutic potential of exarafenib, a novel type 2 pan-RAF inhibitor and ATP-competitive small molecule agent20, in BRAF-mutant NSCLC. Exarafenib targets both monomeric and dimeric forms of mutant BRAF, potentially overcoming the limitations of selective V600X inhibitors, which target monomers4,21. Through systematic preclinical studies, we show that exarafenib achieves potent anti-tumor activity across all mutation classes, with robust efficacy in diverse cell lines and patient-derived xenograft models. To identify potential biomarkers of response and rational combination partners that could enhance therapeutic efficacy and maintain tolerability, we systematically profiled exarafenib-resistant derivatives. Through this approach, we uncovered an unexpected adaptive resistance pathway involving drug-induced ARAF-KSR1 scaffold complex formation that maintains MAPK signaling despite pan-RAF inhibitor treatment. This mechanistic discovery led us to identify MEK inhibition as a synergistic combination strategy that prevents resistance by targeting a key convergence point of both canonical and bypass signaling pathways.

Our study provides comprehensive insights into the prevalence, clinical characteristics, and outcomes in patients harboring different classes of BRAF mutations and also underscore exarafenib as a targeted therapeutic approach for this molecularly defined patient population. Results of this study support the ongoing clinical development of exarafenib and have the potential to transform the clinical management of BRAF-mutant NSCLC and improve outcomes for the substantial number of patients with this challenging and deadly disease.

Results
Genomics, features, and outcomes of BRAF class mutant subtypes in patients including those with NSCLC
To gain additional insight into the biology and clinical relevance of the different BRAF mutations present in human cancer patients, we investigated the detection rate of oncogenic BRAF mutations (excluding fusions, large structural variants, or copy number variants) across various malignancies using the GuardantINFORM™ database, which contains targeted genomic data from over 160,000 patients diagnosed with advanced or metastatic cancer. In our analysis, we ensured that each patient was counted only once within each BRAF class to provide an accurate assessment of BRAF mutation prevalence. The classification of BRAF alterations is shown in Supplementary Table 1. Notably, while BRAF Class I mutations detected in circulating tumor DNA (ctDNA) were observed at rates exceeding 10% in specific cancers such as Erdheim-Chester disease (ECD), Langerhans cell histiocytosis (LCH), thyroid cancers, and melanoma (Fig. 1a), these mutations were comparatively less frequent in lung cancer (1.67%). However, despite the lower frequency of Class I mutations in lung cancer compared to other malignancies, lung cancer represented the largest number of patients with BRAF alterations across all cancers surveyed, given the large number of patients diagnosed annually10,11 (Fig. 1a and Supplementary Table 2). Since lung cancer had the highest absolute number of tumors with BRAF mutations, we focused our subsequent analyses on the clinical characteristics and outcomes of NSCLC patients with BRAF alterations. Specifically, among the 51,783 lung cancer patients with detectable ctDNA, 2398 patients (4.63%) had tumors with non-overlapping BRAF mutations belonging to one of the three functional classes (Class I, II, or III only) (Supplementary Table 2). An additional 23 NSCLC patients had multiple BRAF alterations across functional classes (e.g., Class I and II, II and III), and these patients were counted as BRAF mutation positive in the overall analysis but excluded from individual BRAF class counts to avoid duplication. In NSCLC, BRAF Classes II and III are present in 65% of the BRAF-positive patients (Fig. 1b), with distinct frequencies among different mutations within each class (Supplementary Tables 3, 4 and 5). Interestingly, this distribution of BRAF mutation classes in NSCLC, with a higher proportion of Class II and III mutations, differs from patterns typically observed in many other cancers where BRAF V600E (Class I) mutations predominate3,22. These findings, consistent with prior tissue-based genomic studies3,15, highlight an important unmet need for effective therapies targeting this large subgroup of patients with BRAF Class II and III mutations, which we address below.

The clinical characteristics of NSCLC patients with non-overlapping BRAF Class I, II, or III alterations are summarized in Supplementary Table 6. Across all three BRAF classes, the median age of patients was 70 years, consistent with a previous study15. Class I mutations were more frequently observed in females compared to males (Class I vs II: *P = 0.0451; Class I vs III: *P = 0.0373). BRAF Class II and III mutations were more prevalent in patients with a history of tobacco use compared to Class I mutations (Class I vs II: ****P = 8.18×10−9; Class I vs III: ****P = 4.52×10−8), in line with a previous report15. Our study, leveraging liquid biopsy technology, successfully extended these prior findings by enabling the analysis of a larger patient cohort to provide a more comprehensive understanding of the genomic landscape of BRAF alterations in lung cancer.

Given the distinct clinical characteristics observed in patients with different BRAF mutation classes, we sought to investigate potential associations between these genomic alterations and patient outcomes. Real-world overall survival (rwOS), defined as the time from the first detection of BRAF mutation in circulating tumor DNA to death from any cause, was evaluated in 813 unique NSCLC patients with BRAF alterations. The Kaplan-Meier survival curves for each BRAF mutation class are presented in Fig. 1c. The median rwOS was significantly longer in BRAF Class I compared to BRAF Class II (818 vs 514 days, HR: 1.4 (1.1−1.8), adj. *P = 0.0395). The median rwOS for BRAF Class III was 774 days, which was not significantly different from Class I (HR: 1.2 (0.9−1.5), adj. P = 0.6173) or Class II (HR: 1.2 (0.9−1.6), adj. P = 0.5946). These survival differences could reflect differential access to effective targeted therapies (Fig. 1d). Class I patients had access to FDA-approved targeted therapy, with nearly a quarter (23.8%) receiving trametinib plus dabrafenib as first-line treatment. In contrast, Class II and III patients, lacking effective targeted options, predominantly received immunotherapy-based regimens, including carboplatin plus pemetrexed plus pembrolizumab (19.6% and 17.9%, respectively) or pembrolizumab monotherapy (complete treatment information is provided in Supplementary Data 1).

Overall, our analysis confirms and extends prior observations, demonstrating that NSCLC patients with BRAF Class II mutations have worse prognosis compared to those with Class I mutations, potentially due to the lack of effective targeted therapy options. These findings highlight BRAF Class II and III mutants as a substantial clinical patient cohort with aggressive disease that represents an important unmet therapeutic need.

The novel pan-RAF inhibitor exarafenib potently and selectively inhibits RAF proteins
Current approved BRAF V600X inhibitors are less effective against other forms of mutant BRAF4,21 and paradoxically activate wild-type isoforms, a phenomenon where mutant-selective BRAF inhibitors induce wild-type RAF heterodimerization (e.g., BRAF:CRAF) and transduce MEK-ERK pathway activity23,24. These limitations led to the development of pan-RAF inhibitors, which can target various RAF isoforms, including CRAF and ARAF, to overcome these limitations25–27. Exarafenib, a novel pan-RAF inhibitor, was discovered through a distinct structure-based drug design strategy to target the αC-helix-IN and DFG-out conformations of RAF kinases20. This strategic innovation allows exarafenib to inhibit both monomeric and dimeric forms of RAF28, ensuring robust cellular potency across a broad range of RAF alterations and excellent pharmacokinetic properties while avoiding paradoxical activation of the pathway.

We evaluated the specificity of exarafenib in ex vivo biochemical assays across a panel of 368 wild-type kinases at 1 μM concentration, as visualized in kinometree diagrams (Fig. 2a, left)20. Exarafenib exhibited potent inhibition of all three RAF isoforms while maintaining minimal off-target effects, with DDR1 being the only wild-type kinase showing >70% inhibition. In this study, we expanded our analysis by comparing exarafenib’s specificity to that of other pan-RAF inhibitors, including naporafenib26,29 and belvarafenib27,30, which are also under development. In contrast to exarafenib, naporafenib, and belvarafenib displayed a higher number of off-target effects, with 4 and 15 wild-type kinases showing >70% inhibition, respectively, as is evident from the more numerous and larger off-target nodes in their kinome trees (Fig. 2a, middle and right). These findings highlight exarafenib’s notable selectivity profile compared to the other clinical pan-RAF inhibitors evaluated, as well as its strong on-target potency.

Mechanism of action: exarafenib inhibits RAF monomers and dimers
To establish the mechanism of action (MOA) by which exarafenib could exert anti-tumor effects in human cancer cells, we conducted a series of experiments using patient-derived lung cancer cell lines harboring BRAF mutations (Fig. 2b). Here, we focused on two key aspects: (1) the effects of exarafenib on RAF isoform protein interactions, and (2) the extent to which exarafenib inhibited each RAF isoform. Since recent studies have shown that RAF inhibitors can disrupt intramolecular interactions between the kinase domain and its N-terminal regulatory region and thereby induce RAF dimerization to varying degrees depending on their binding mode23–25,31, we investigated RAF dimerization in the context of elucidating exarafenib’s MOA.

To study these protein interactions under RAF inhibitor treatment, we performed immunoprecipitation (IP)-western blot analysis examining endogenous ARAF, BRAF, and CRAF protein complexes in three patient-derived lung cancer cell lines, each representing a different BRAF mutation class: HCC364 (Class I; BRAF V600E), NCI-H2405 (Class II; BRAF L485_P490delinsY), and NCI-H1666 (Class III; BRAF G466V). Upon analysis, despite the distinct biological features of each BRAF mutation class, exarafenib and belvarafenib induced significant RAF heterodimerization across all classes (Fig. 2b). In contrast, vemurafenib, an approved mutant BRAF V600X inhibitor8, did not induce dimerization under the tested conditions, aligning with reports that it has a lower propensity for inducing RAF dimerization25,31. These observed dimerization patterns prompted us to further investigate how exarafenib affects the kinase activity of different RAF isoforms across various BRAF-mutant protein contexts.

Accordingly, we conducted two complementary in vitro kinase assays. First, we treated lung cancer cell lines in situ with the inhibitors for 4 h, followed by protein extraction and subsequent IP-kinase assay (Supplementary Fig. 1a, top). This approach allowed us to evaluate each inhibitor’s ability to block RAF kinase activity in a cellular context. Second, we performed a BRAF-IP from untreated cell lysates and then added the inhibitors directly to the kinase reaction ex vivo (Supplementary Fig. 1a, bottom). This latter cell-free assay enabled us to assess the direct inhibitory effects of the inhibitors on BRAF kinase activity, largely independent of cellular uptake or off-target effects. Under both conditions, exarafenib efficiently inhibited BRAF kinase activity (Supplementary Fig. 1b), confirming its ability to enter cancer cells and bind to and selectively inhibit endogenous BRAF. Based on this result and to ensure the physiological relevance of our findings, we used the first experimental design for subsequent experiments. We extended the study to three lung cancer cell lines used in the co-IP experiments and assessed the effects of each RAF inhibitor on endogenous ARAF, BRAF, and CRAF kinase activity. In HCC364 cells, all three inhibitors effectively inhibited BRAF kinase activity (Fig. 2c, left). As expected, only exarafenib and belvarafenib inhibited BRAF and CRAF kinase activity in Class II NCI-H2405 cells (Fig. 2c, middle). In Class III NCI-H1666 cells, the effects on BRAF kinase activity were modest (Fig. 2c, right), likely due to the weak or absent kinase activity of the mutated BRAF typically found in Class III cell lines5. However, baseline CRAF kinase activity was strongly detected in NCI-H1666 cells and was significantly inhibited by exarafenib and belvarafenib (Fig. 2c, right), aligning with previous work showing that these mutants are CRAF-dependent in activating the downstream MAPK pathway5. Interestingly, endogenous ARAF kinase activity at an acute time point remained largely unaffected by drug exposure, contrasting with inhibition observed in the cell-free biochemical assay (Fig. 2a). This divergence likely reflects assay-context differences: the cell-free system maximizes active-site accessibility and catalytic output, whereas the endogenous IP-kinase assay may preserve native protein complexes (including scaffold-mediated interactions and dimer composition) and is further constrained by ARAF’s low basal catalytic activity32, limiting the dynamic range for detecting acute inhibition. These results demonstrate that although exarafenib induces RAF dimerization, it can directly target the dimerized RAF isoforms and effectively inhibit RAF kinase activity across the BRAF mutation classes.

Exarafenib shows potent effects in BRAF-mutated isogenic Ba/F3 cells
To assess the activity of exarafenib on cell viability specifically driven by BRAF mutations in an isogenic background, we employed Ba/F3 cell models engineered to express Class I and Class II BRAF mutations that exhibit strong and readily detectable kinase activity. These models allow for a uniform cellular background, enforcing that the observed effects are due to the BRAF mutations and the inhibitors tested33. It is important to note that generating Ba/F3 models with BRAF Class III mutations is challenging due to the low or absent kinase activity5, limiting our ability to assess exarafenib’s effects on this class of mutations in this particular context. The results demonstrated that vemurafenib only inhibited cell proliferation in the V600E model, whereas exarafenib and belvarafenib displayed potent effects against all series of BRAF mutations tested (Fig. 2d and Supplementary Fig. 1c).

Given that oncogenic RAS mutations are upstream activators of RAF signaling and represent another major oncogenic driver in NSCLC, we sought to evaluate exarafenib’s therapeutic potential beyond BRAF-mutated cancers. Using the same system, we conducted a screen of a series of oncogenic KRAS and NRAS mutations. We evaluated exarafenib’s effects along with the selective KRAS G12C inhibitor sotorasib, which is an approved treatment for KRAS G12C mutant NSCLC34, for benchmarking against KRAS G12 cells. Notably, we observed favorable exarafenib sensitivity across multiple oncogenic RAS mutations (Fig. 2e and Supplementary Fig. 1d), suggesting the potential utility of using emerging pan-RAF inhibitors in a wider range of cancer types driven by these oncogenic RAS mutations.

Exarafenib inhibits BRAF-mutated and RAS-mutated lung cancer cells
Next, we evaluated the inhibitory effects of exarafenib on cell proliferation using NSCLC cell lines with endogenous oncogenic BRAF mutations. We used the non-cancerous bronchial epithelial cell line, AALE, to determine potential non-specific cellular effects of exarafenib35. Vemurafenib, a mutant-specific Class I BRAF inhibitor, showed excellent sensitivity in cell lines with BRAF V600E mutations but had little effect on cells with Class II or III mutations (Fig. 3a and Supplementary Fig. 2a). In contrast, exarafenib and belvarafenib demonstrated efficacy against Class II and Class III cancer cells, albeit to varying degrees (Fig. 3a and Supplementary Fig. 2a). It is worth noting that some cell lines exhibited lower sensitivity to these compounds, with IC50 values above 1 μM. Specifically, NCI-H1395, NCI-H2087, and Cal-12T showed IC50 values of 9441 nM, 2935 nM, and 3257 nM, respectively, for exarafenib. This variation in sensitivity within each class likely reflects the complexity of clinically relevant lung cancer cells and is an important preclinical model of the heterogeneity of real-world clinical cases, where genetic co-alterations and/or non-genetic mechanism(s) may modulate response to targeted therapies. Next, we investigated the MAPK pathway signaling status in cell lines from each class. The results revealed that exarafenib inhibited the components of this pathway in a dose-dependent and time-dependent manner (Fig. 3b). Western blot analyses under the same conditions in lower exarafenib sensitivity cells revealed more modest inhibitory effects on the MAPK pathway compared to the sensitive cells (Supplementary Fig. 2b), potentially due to compensatory or redundant signaling mechanisms, among other possible explanations.

Additionally, we extended our analysis to lung cancer cell lines harboring upstream KRAS mutations to assess whether the Ba/F3 findings translate to more clinically relevant cellular contexts. We found that exarafenib exhibited notable cell proliferation inhibitory effects in several KRAS mutant cell lines and highlight those in particular with non-KRAS G12C mutations that currently lack approved direct RAS inhibitors (Supplementary Fig. 2c). The sensitivity of exarafenib against non-KRAS G12C mutations suggests a broader spectrum of exarafenib activity that warrants further investigation for some of the RAS mutations.

Exarafenib is potent against a BRAF V600E p61 splice variant that confers resistance to BRAF Class I inhibitors
Beyond the intrinsic BRAF molecular subtypes, we also investigated exarafenib’s activity in a model of acquired resistance to the Class I mutant BRAF inhibitor vemurafenib in NSCLC cells. Vemurafenib-resistant subclones, such as HCC364-VR1, were previously generated by continuous vemurafenib exposure in BRAF V600E-containing HCC364 cells36. HCC364-VR1 derivatives express a BRAF V600E p61 splice variant that functions as a dimerized BRAF, resulting in insensitivity to agents such as vemurafenib36, which can only bind to monomers37. In HCC364-VR1 cells, exarafenib showed potent cell growth inhibition compared to vemurafenib, with IC50 values of 721 nM and 7551 nM, respectively (Supplementary Fig. 2d). Further, both inhibitors suppressed p-MEK, p-ERK, and p-RSK levels in parental HCC364 cells, but only exarafenib demonstrated robust inhibition in the p61 splice-variant expressing cells (Supplementary Fig. 2e). These findings suggest that exarafenib may have potential utility in addressing acquired resistance to vemurafenib in patients harboring the BRAF V600E p61 splice variant.

Exarafenib shows robust PK/PD and tumor suppression in vivo
Given its promising in vitro activity, exarafenib was advanced into in vivo studies focusing on lung cancer, using cell line-derived xenograft (CDX) and patient-derived xenograft (PDX) models of BRAF-mutated human cancers. These included the Class II cell line-derived xenograft (CDX) model NCI-H2405 and the Class III patient-derived xenograft (PDX) models CTG-1444, LUN023, and LUN037. Based on our previous study testing exarafenib in pancreatic ductal adenocarcinoma (PDAC) and melanoma xenograft models20, we administered the drug twice daily (BID), replicating the prior effective and safe protocol. Compared to the vehicle-treated group, exarafenib treatment led to dose-dependent tumor growth inhibition in all models (Fig. 3c), and all dose levels were well-tolerated (Supplementary Fig. 3a). In vivo pharmacokinetics/pharmacodynamics (PK/PD) relationships were measured using exarafenib in a cohort of BALB/c nude mice bearing Class II BRAF-mutant NCI-H2405 tumors treated with 3 or 10 mg/kg BID and observed for up to 72 h after the last dose. By monitoring the kinetics of plasma concentrations, we detected a rapid increase in drug concentration after administration, followed by a gradual decrease over time (Supplementary Fig. 3b, blue line). Additionally, exarafenib demonstrated a dose-dependent suppression of p-ERK, with the 10 mg/kg dose achieving a more pronounced maximum suppression (~80%) compared to the 3 mg/kg dose (~60%) at the 1-h timepoint (Supplementary Fig. 3b, purple line). Although p-ERK levels gradually rebounded, reaching nearly baseline by 24 h, the twice-daily (BID) dosing regimen ensures sustained target engagement and optimal therapeutic efficacy, while maintaining tolerability (Supplementary Fig. 3a). Next, examination of the correlation between the plasma concentration of unbound exarafenib and p-ERK inhibition revealed an in vivo EC50 of 14.67 nM (Supplementary Fig. 3c). To further confirm the pharmacodynamic effects, western blot analysis was performed in NCI-H2405 tumor samples. The results showed dose-dependent inhibition of both p-MEK and p-ERK levels in tumors treated with 3 mg/kg and 10 mg/kg BID doses of exarafenib compared to the vehicle control (Supplementary Fig. 3d). These data demonstrate that exarafenib exhibits potent in vivo effects and pharmacodynamic modulation with achievable tolerability.

The efficacy observed across our PDX models may have broader clinical implications. Notably, the CTG-1444 PDX model used in our study harbors both BRAF G466V and NRAS Q61R mutations and demonstrated sensitivity to exarafenib treatment. Analysis of our patient cohort revealed that concurrent BRAF and RAS mutations occur in a substantial proportion of NSCLC patients: 9.0% in Class I, 20.7% in Class II, and 21.5% in Class III (Supplementary Fig. 3e; specific mutations and their frequencies are provided in Supplementary Data 2). The higher co-occurrence rates in Class II and III patients are particularly noteworthy, as BRAF-RAS co-mutations are traditionally considered rare or mutually exclusive in other cancer types, such as colorectal cancer, where they occur in <1% of cases38. In NSCLC, however, several genomic studies have shown that non-V600E BRAF mutations, particularly those in Class II and III, are often accompanied by KRAS alterations12,39,40, in line with our findings. Combined with our in vitro findings showing exarafenib’s activity against RAS-driven signaling, PDX results suggest that pan-RAF inhibition may offer therapeutic potential for the substantial subset of NSCLC patients harboring concurrent BRAF-RAS mutations, though clinical validation will be essential.

Further identifying potential biomarkers of exarafenib efficacy and resistance in BRAF-mutant lung cancer
Exarafenib exhibited promising efficacy, PK/PD relationships, and tolerability in our preclinical studies. However, as a pan-RAF inhibitor, we reasoned that it is important to consider potential biomarkers and targets that may impact on therapeutic efficacy and/or mediate resistance. This line of investigation could enable identification of potential rational combination therapies to enhance efficacy and maintain or improve safety, similar to the current standard of care for BRAF Class I inhibitors with combination BRAF and MEK inhibitor treatment which shows heightened efficacy safely in patients41,42. Toward this end, we leveraged the established approach of generating and profiling exarafenib resistant cell line derivatives from parental treatment sensitive cells through long-term dose-escalation exposure to exarafenib for over three months (NCI-H2405-ER, NCI-H1755-ER, and NCI-H1666-ER; ER: Exarafenib Resistant derivative) (Fig. 4a). The resistant cell lines demonstrated significantly increased IC50 values, with more than 5-fold changes observed in all resistant cells compared to their parental cell line ancestors, and exhibited cross-resistance to another pan-RAF inhibitor, belvarafenib (Fig. 4b and Supplementary Figs. 2a and 4a). Furthermore, under continuous exposure to exarafenib (1 μM), the acquired resistant cells exhibited cell proliferation capabilities roughly equivalent to those of the parental cells (Supplementary Fig. 4b). Whole Exome Sequencing (WES) analysis of the resistant cells did not identify any genomic alterations previously reported to contribute to resistance, or that could be linked to resistance in an obvious manner43,44.

To characterize the resistant cells further, we next investigated the activation status of MAPK pathway signaling in these resistant cell lines. The resistant cell lines, which were maintained under 1 μM exarafenib exposure, showed relatively sustained levels of p-MEK, p-ERK, and p-RSK compared to their parental counterparts treated with the same concentration of the drug (Supplementary Fig. 4c). To elucidate the mechanism of this sustained MAPK signaling activation, we analyzed pathway dynamics under varying doses and timepoints.

Given the known crosstalk between MAPK and PI3K/AKT pathways in cancer signaling and resistance mechanisms45,46, we also extended our analysis to include p-AKT levels. Additionally, for all subsequent experiments using these resistant cell lines, unless otherwise noted, we implemented a 48-h drug-free period before each experiment to model consistent baseline conditions between the resistant and sensitive cell lines. At a relatively acute time point (4 h post-drug exposure following the drug-free period), all resistant cell lines showed dose-dependent inhibition of the MAPK pathway upon re-treatment with exarafenib (Supplementary Fig. 4d). However, under time-varying conditions, NCI-H2405-ER and NCI-H1666-ER cells exhibited a rebound in p-MEK, p-ERK, and p-RSK levels over time (Fig. 4c). In contrast, NCI-H1755-ER cells initially showed modest inhibition of MAPK signaling but maintained a relatively high activation state. Furthermore, all resistant cell lines demonstrated time-dependent increases in p-AKT levels (Fig. 4c).

To better understand these complex temporal dynamics and gain deeper mechanistic insights into MAPK and PI3K/AKT pathway behavior during drug withdrawal and re-challenge, we conducted comprehensive time-course analyses across both drug withdrawal and re-challenge periods. Following 72 h of exarafenib treatment, NCI-H2405-ER cells were subjected to drug-free periods of varying durations (−4 h, −24 h, −48 h) followed by drug re-exposure for up to 48 h (+4 h, +24 h, +48 h) (Supplementary Fig. 5a). During drug withdrawal, MAPK pathway components (p-MEK, p-ERK, p-RSK) showed progressive elevation, reaching levels substantially higher than those observed during the 72 h drug treatment. Conversely, p-AKT levels decreased during the drug-free period. Upon drug re-challenge, MAPK pathway components exhibited the previously observed pattern of initial suppression followed by reactivation, though the rebound levels remained moderate compared to the drug-free state. Similarly, p-AKT levels increased upon drug re-exposure. Additionally, we performed parallel cell proliferation analyses by cell counting under the same experimental conditions during drug withdrawal and re-challenge periods (Supplementary Fig. 5b). The results demonstrate that resistant cells maintain their proliferative capacity throughout the drug re-challenge period, confirming that the transient MAPK pathway suppression does not translate to meaningful growth inhibition.

Notably, this continuous proliferative capability throughout the drug withdrawal and re-challenge contrasts with the drug-dependent growth phenotype often observed with MAPK pathway inhibitor resistance, where cells become dependent on continued drug exposure to prevent excessive MAPK activation and subsequent cell death47,48. To investigate whether our resistant cells might exhibit such drug dependence, we examined cellular stress markers (Supplementary Fig. 5a). Western blot analysis across withdrawal timepoints (−4 h, −24 h, −72 h) showed no significant induction of DNA damage markers (p-γH2AX and p-CHK2), apoptosis marker (cleaved PARP), or pro-apoptotic protein (BIM). While some markers showed modest fluctuation (such as p-γH2AX elevation comparable to 72-h treatment levels), these changes did not indicate significant cellular stress or death, as indicated by our cell proliferation analyses (Supplementary Fig. 5b). The absence of such drug dependence in our exarafenib-resistant cells suggests a distinct resistance mechanism that enables cells to tolerate both drug withdrawal and re-exposure while maintaining viability and proliferative capacity.

These findings collectively demonstrate that exarafenib resistance in involves adaptive mechanisms characterized by dynamic pathway remodeling rather than simple target mutation. These signaling phenotypes in both the MAPK and PI3K/AKT pathways suggested the potential involvement of upstream pathway activation, likely through the key immediate upstream signaling node RAS, which we hypothesized might re-activate either or both of these pathways to promote resistance.

To test this hypothesis, we next performed cellular RAS activation state profiling (RAS-GTP detection via RAS-Ras-Binding-Domain [RBD] assays49). These studies revealed that RAS activation was induced in NCI-H2405-ER cells after 4 h of exarafenib treatment (Fig. 4d). In the case of NCI-H1666 cells, which are BRAF Class III mutant and generally sensitive to ERK-mediated feedback5, the parental cells also showed an increase in RAS-GTP levels upon exarafenib treatment (Fig. 4d). However, the resistant cells exhibited stronger baseline activation and response to exarafenib (Fig. 4d). Notably, NCI-H1755-ER cells displayed a marked increase in RAS-GTP levels at baseline, consistent with the high activation of p-MEK, p-ERK, and p-RSK levels shown in Fig. 4c and Supplementary Fig. 4d. Upon exarafenib treatment, the NCI-H1755-ER cells showed a slight further increase in RAS-GTP, whereas parental cells showed no significant change (Fig. 4d). Moreover, the same experimental condition shown in Supplementary Fig. 4c, where the resistant cell lines were maintained under 1 μM exarafenib exposure, also demonstrated elevation of RAS-GTP, suggesting that this effect is sustained during prolonged and continuous drug administration (Supplementary Fig. 5c).

To investigate the biological ramifications of the robust RAS activation present in the resistant cells, we evaluated the effect of pan-RAS knockdown in cell viability assays. Parental NCI-H2405 cells did not show any increase in exarafenib sensitivity following RAS knockdown (Fig. 4e, left). In contrast, resistant NCI-H2405-ER cells exhibited an increase in sensitivity to exarafenib upon RAS silencing, compared to their non-silenced counterparts (Fig. 4e, left). RAS knockdown alone did not affect either the parental or resistant cells in this model (Fig. 4e, left). In NCI-H1755 cells, RAS knockdown demonstrated an additional inhibitory effect on cell viability in both parental and resistant cells, beyond exarafenib alone (Fig. 4e, middle). NCI-H1755 cells harbor the BRAF G469A mutation, which is classified as a Class II BRAF mutation and considered RAS-independent; yet, both parental and resistant cells exhibited a marked dependence on RAS for cell proliferation, even in the absence of drug treatment (Fig. 4e, middle). This observation may challenge the conventional understanding of Class II BRAF mutations and suggest that the relationship between BRAF mutation class and RAS dependence may be more complex than previously thought, particularly in the context of clinically relevant cancer cell lines. Notably, due to the strong RAS dependence in NCI-H1755 cells, our knockdown experiments in this cell line were limited to individual KRAS knockdown, as simultaneous silencing of multiple RAS isoforms was not feasible. In NCI-H1666 cells, RAS knockdown alone suppressed cell viability in both parental and resistant cells, while exarafenib treatment further enhanced this effect (Fig. 4e, right), aligning with the fact that these cells harbor a RAS-dependent BRAF Class III mutation.

Taken together, these studies revealed that RAS silencing led to more pronounced inhibition of cell proliferation in each resistant cell line compared to their non-silenced counterparts (Fig. 4e). Furthermore, this effect was more substantial in resistant cells than in parental cells, suggesting that resistant cells have high dependency on RAS activation.

Next, protein expression analysis was performed to assess the changes in signaling upon RAS knockdown. In all resistant cells, RAS knockdown combined with exarafenib treatment resulted in more pronounced MAPK signaling inhibition compared to the scrambled control (SCR) (Supplementary Fig. 5d). In contrast, RAS knockdown showed minimal impact on p-AKT levels (Supplementary Fig. 5d), highlighting the complex nature of signaling pathway regulation and interaction in cancer cells. These results suggest that RAS activation may primarily promote the activation of the MAPK pathway, which appears to be a critical signaling cascade in the context of exarafenib resistance.

The potential role of receptor tyrosine kinases (RTKs) in exarafenib resistance
To investigate the potential mechanism for elevated RAS-MAPK pathway signaling in the exarafenib resistant derivative cell lines, we performed phospho-RTK arrays comparing parental and exarafenib resistant cells. This approach allowed us to profile activation of upstream RTKs that are well-known to promote RAS and MAPK pathway signaling in various contexts36,50,51. While prolonged exarafenib treatment may lead to increased RAS activation through multiple mechanistic factors, such as relieving the negative feedback on the MAPK pathway52, our primary goal was to identify druggable strategies to enhance exarafenib’s efficacy. Thus, we reasoned that examining RTK activation status was a useful first step. The results revealed activation of multiple phospho-RTKs in NCI-H2405-ER and NCI-H1755-ER cells, including strong phosphorylation of AXL and MET, and less significant RTK increases in NCI-H1666-ER cells (Supplementary Fig. 6a).

Based on these findings, we first examined whether the RTKs contribute to the elevated RAS activation observed in resistant cells. To test this hypothesis, we performed knockdown experiments in NCI-H2405-ER cells, selecting AXL as the top hit from our phospho-RTK array, along with EGFR, based on previous reports suggesting EGFR’s involvement in the development of resistance to RAF inhibitors36,50,51. Individual knockdown of AXL and EGFR showed modest reductions in RAS-GTP levels, while combined knockdown demonstrated a more pronounced reduction in RAS-GTP levels (Supplementary Fig. 6b). The greater efficacy of combined versus individual RTK knockdown may indicate functional redundancy among multiple RTKs in maintaining elevated RAS-GTP levels in resistant cells.

Given the established connection between RTK activation and RAS-GTP levels, we next conducted functional studies across all resistant cell lines to assess the biological consequences of RTK silencing. We performed knockdown experiments targeting AXL and MET, which exhibited the strongest upregulation in NCI-H2405-ER and NCI-H1755-ER cells, respectively, including EGFR as described above. The knockdown of individual RTKs did not substantially impact sensitivity to exarafenib, with the only exception of EGFR knockdown in NCI-H2405-ER cells, which modestly enhanced sensitivity (Supplementary Fig. 6c). Similarly, in western blot analysis, EGFR knockdown in NCI-H2405-ER cells only modestly inhibited p-ERK and p-RSK (Supplementary Fig. 6d). AXL knockdown in NCI-H2405-ER cells did not affect MAPK signaling but significantly reduced p-AKT levels. However, the contribution of AXL-induced AKT activation to drug sensitivity appears to be limited, as AXL knockdown had little effect on cell viability (Supplementary Fig. 6c).

Since individual RTK knockdowns had limited effects in sustaining the MAPK signaling, we next investigated whether resistant cells were dependent on extracellular growth factor stimulation, which could coordinate multiple RTK activities. Analysis under varying serum conditions revealed that MAPK signaling in resistant NCI-H2405-ER cells was strongly serum-dependent, with higher serum concentrations maintaining robust p-ERK and p-RSK activation even in the presence of exarafenib (Supplementary Fig. 6e). Notably, p-AKT levels showed minimal changes under these conditions. By comparison, parental NCI-H2405 cells showed no difference from low serum conditions in maintaining MAPK activity under exarafenib treatment (Supplementary Fig. 6e), indicating that the acquired ability to respond to extracellular growth factors is a specific characteristic of the resistant cells rather than an inherent property of the parental cell line.

These findings collectively demonstrate that exarafenib resistant cells exhibit strong dependence on the MAPK pathway for survival and proliferation, with multiple RTKs functioning cooperatively to promote RAS-MAPK pathway activation. The cooperative nature of RTK activation, combined with serum-dependent maintenance of pathway signaling, suggests that resistance involves adaptive rewiring of growth factor responsiveness rather than simple upregulation of individual RTKs. These observations are consistent with other reports in the context of targeted therapy resistance52,53 and highlight the multi-factorial nature of acquired resistance mechanisms.

Exarafenib resistance involves an adaptive switch to ARAF-dependent MAPK signaling
Our findings demonstrating RAS activation and cooperative RTK signaling in resistant cells prompted us to investigate whether resistant cells might exhibit altered dependencies on specific RAF isoforms that enable bypass of drug inhibition.

To test this hypothesis, we performed individual RAF isoform knockdown experiments in both parental and resistant cell lines. Cell viability assays revealed that in parental cells harboring Class II BRAF mutants that are hyperactive (NCI-H2405 and NCI-H1755), BRAF knockdown resulted in the greatest reduction of exarafenib IC50 values, as expected (Fig. 5a and Supplementary Fig. 7a). In the Class III BRAF mutant NCI-H1666, both BRAF and CRAF knockdowns contributed to exarafenib IC50 reduction, reflecting the kinase-dead Class III BRAF mutation characteristics. Notably, ARAF knockdown also reduced IC50 values in Class III parental cells, suggesting a previously unreported ARAF dependency in Class III BRAF mutant cells. This unexpected ARAF dependency in Class III mutants, while not the primary focus of our study, represents an intriguing baseline characteristic that warrants further mechanistic investigation in drug-naïve contexts. Moreover, all Class II and III BRAF mutant, exarafenib resistant cell lines consistently showed the greatest IC50 reduction upon ARAF knockdown, demonstrating a clear convergent shift in RAF isoform dependency at acquired resistance (Fig. 5a and Supplementary Fig. 7a).

Protein analysis in NCI-H2405-ER cells provided mechanistic insight into this isoform switch. Under drug-free conditions, only BRAF knockdown reduced p-MEK, p-ERK, and p-RSK levels, indicating BRAF dependency similar to parental cells (Fig. 5b). However, under exarafenib treatment, ARAF knockdown resulted in the most profound suppression (Fig. 5b). These results demonstrate for the first time that resistant cells undergo a switch to an ARAF-dependent MAPK activation maintenance mechanism in the presence of pan-RAF inhibitor treatment.

To further characterize this mechanism in detail, we examined time-dependent signaling changes following pan-RAF inhibitor treatment under ARAF knockdown conditions. Consistent with our earlier observations (Fig. 4c), resistant cells exhibited time-dependent recovery of MAPK activity after drug treatment under control conditions (Fig. 5c). However, cells transfected with ARAF siRNA showed markedly suppressed signal recovery (Fig. 5c). This temporal analysis provides evidence that ARAF mediates the transition from conventional oncogenic-BRAF-dependent signaling (suppressed by exarafenib) to an alternative bypass pathway that enables sustained MAPK activation. Furthermore, we investigated whether this ARAF-mediated pathway reactivation depends on extracellular growth factor signaling by examining MAPK activity under different serum concentrations with and without exarafenib treatment. Resistant cells showed enhanced MAPK pathway reactivation under high serum (10% FBS) conditions compared to low serum (3% FBS) during drug treatment, while ARAF knockdown abolished this elevated pathway reactivation (Fig. 5d). These serum-dependency experiments demonstrate that the ARAF-mediated bypass mechanism requires upstream RTK-RAS activation specifically in the context of exarafenib treatment, establishing a functional link between growth factor signaling and the ARAF-dependent resistance pathway.

ARAF-KSR1 complex formation mediates resistance-associated MAPK reactivation
These selective ARAF dependency observed in resistant cells prompted us to investigate the molecular mechanisms by which ARAF maintains MAPK signaling under pan-RAF inhibition. To elucidate ARAF’s functional interactions, we examined its binding partners through co-immunoprecipitation analysis. We focused on other RAF isoforms (BRAF and CRAF) to assess potential heterodimerization changes, as differential RAF heterodimerization has been linked to variations in MAPK pathway activation and therapeutic response27,54,55. Additionally, we examined KSR1 (Kinase Suppressor of Ras1), a critical scaffolding protein that organizes RAF-MEK-ERK signaling complexes and has been implicated in facilitating RAF isoform-specific MAPK activation56. Notably, KSR1 has been previously implicated in resistance mechanisms to RAF and MEK inhibitors, where it can facilitate alternative signaling pathways that bypass drug inhibition57,58.

Our co-immunoprecipitation studies reveal striking differences in ARAF protein interaction patterns between parental and resistant cells (Fig. 5e). In resistant cells, ARAF-BRAF interactions were significantly reduced compared to parental cells, indicating a distinct interaction profile from the previously observed exarafenib-induced BRAF-ARAF heterodimerization in drug-sensitive contexts (Fig. 2b). Conversely, exarafenib treatment specifically induced both ARAF-CRAF and ARAF-KSR1 binding in resistant cells but not in parental cells (Fig. 5e). CRAF knockdown in resistant cells did not significantly impact exarafenib sensitivity (Fig. 5a). Therefore, we focused our subsequent mechanistic studies on this new ARAF-KSR1 interaction we found.

We wondered why exarafenib was unable to effectively inhibit ARAF (or CRAF)-MEK signaling in the resistant cells. One possibility is that exarafenib is not able to bind the ARAF-KSR1 or ARAF-CRAF complex due to allosteric or structural effects of increased ARAF-KSR1 protein interactions. Our finding that exarafenib treatment induced the ARAF-KSR1 and ARAF-CRAF binding suggested against this scenario (Fig. 5e). Nevertheless, to more directly address this question, we performed cellular thermal shift assays59 (CETSA). In parental cells, exarafenib stabilized BRAF, indicating binding, but showed minimal engagement with ARAF, CRAF, and KSR1 (Supplementary Fig. 7b). In contrast, the resistant cells demonstrated enhanced exarafenib engagement with both ARAF and CRAF in addition to the maintained BRAF binding observed in parental cells, while KSR1 showed minimal exarafenib-induced thermal stabilization (Supplementary Fig. 7b).

Consistent with the upstream growth factor/RTK/RAS dependence we show, EGF stimulation further amplifies this ARAF-KSR1 interaction in resistant cells (Fig. 5f). Conversely, pharmacological inhibition of RAS with RMC-6236, a pan-RAS (ON) inhibitor that targets the active GTP-bound form of both wild-type and mutant RAS isoforms60, markedly reduced ARAF-KSR1 complex formation, as shown by co-immunoprecipitation (Supplementary Fig. 7c). These reciprocal effects demonstrate that growth factor/RTK/RAS activation controls the ARAF-KSR1 interaction in resistant cells. Supporting this RAS-dependent regulation, EGF-induced enhancement of complex formation coincided with enhanced exarafenib-induced thermal stabilization of all RAF proteins, while KSR1 showed minimal change, as demonstrated by CETSA (Supplementary Fig. 7d). Mechanistically, these results align with recent work showing that RAS activation primes RAF into a dimer-competent αC-IN state, which enhances the affinity of type II RAF inhibitors55. Inhibitor binding then further stabilizes this conformation and promotes RAF protein complex formation. Proximity ligation assays (PLA) provide additional validation, demonstrating increased ARAF-KSR1 proximity in resistant cells following exarafenib treatment compared to DMSO control, with less interaction observed in parental cells (Fig. 5g).

To gain structural insights into the exarafenib-binding mode within this complex, we performed AlphaFold-based molecular structural modeling. Docking analysis suggested that exarafenib primarily occupies the ATP-binding site of ARAF within the ARAF–KSR1 complex, contacting the gatekeeper residue (Thr382), residues in the hinge region (Gln383–Cys385), and the DFG motif (Asp447–Gly449), while also making limited contacts with a short KSR1 segment (Pro408–Asn413) that lies adjacent to the pocket edge (Supplementary Fig. 7e and Supplementary Table 7). These observations indicate that exarafenib is structurally compatible with binding at the kinase active site while the ARAF–KSR1 complex retains its scaffolding architecture and generally align with our experimental data discussed above.

To assess the functional significance of KSR1 in maintaining resistance, we performed KSR1 knockdown experiments. KSR1 silencing selectively restored exarafenib sensitivity in resistant cells, with IC50 shifting from 5276 nM to 884 nM while having minimal impact on parental cell viability (Fig. 5h and Supplementary Fig. 7f). Protein analysis revealed that KSR1 depletion further suppressed MAPK pathway activation (p-MEK, p-ERK, p-RSK) in resistant cells following exarafenib treatment, while showing no change in parental cells (Supplementary Fig. 7g). Collectively, these findings establish KSR1 as an essential scaffolding hub that enables ARAF-dependent MAPK reactivation, thereby sustaining exarafenib resistance.

Given that KSR1 functions as a scaffold protein that enhances RAF kinase efficiency56, we hypothesized that the drug-bound ARAF-KSR1 complex maintains functional signaling capacity by recruiting MEK. Consistent with this hypothesis, MEK immunoprecipitation revealed a marked increase in MEK–KSR1 association in resistant cells under exarafenib treatment, whereas MEK–ARAF complexes were not detected, perhaps due to lack of substantial close physical proximity or the transient nature of the MEK-ARAF protein interaction (Supplementary Fig. 7h). Although weak associations with BRAF and CRAF were detected, these appeared unlikely to play a major role in resistance, as their genetic depletion produced minimal effects on exarafenib sensitivity (Fig. 5a). While exarafenib binding reduces ARAF intrinsic kinase activity, increased upstream RAS activation coupled with enhanced KSR1 scaffolding of the ARAF/KSR1/MEK protein complex in the resistant cells may compensate for this reduction by improving MEK recruitment and positioning, thereby enabling the residual ARAF catalytic activity to sustain MAPK pathway signaling more efficiently despite drug treatment. A prediction of our general model is that supra-physiologic doses of exarafenib should overcome this mechanism and resistance. Our dose-response analysis supports this model: we show that the resistant cells retain sensitivity to supra-clinical exarafenib concentrations and display a sigmoid response curve rather than complete resistance (Supplementary Fig. 7f, siSCR). This pattern indicates that at therapeutic doses, KSR1 scaffolding buffers the loss of significant ARAF activity despite drug binding, but at higher concentrations, the remaining kinase function becomes insufficient to sustain cell viability even with enhanced scaffolding efficiency.

These findings collectively establish a resistance mechanism wherein exarafenib-resistant cells undergo adaptive rewiring from conventional oncogenic-BRAF-dependent signaling to an ARAF-KSR1-dependent bypass pathway. The formation of a drug-bound yet partially active ARAF-KSR1 scaffold complex enables resistant cells to maintain MAPK signaling despite pan-RAF inhibition through enhanced scaffolding complex formation driven by upstream RAS activation. This mechanism underscores the continued RAF dependency in resistant cells, albeit through an alternative configuration that reduces drug efficacy within the therapeutic window.

Potential effective exarafenib combination therapy strategies
Our mechanistic characterization of exarafenib resistance revealed a complex adaptive rewiring process involving upstream RTK activation, RAS-GTP accumulation, ARAF-KSR1 scaffolding complex formation, and sustained MAPK pathway signaling. While these findings identified specific resistance mechanisms, the cooperative nature of multiple RTKs and the multi-layered architecture of this resistance network suggested that targeting individual RTK components might be insufficient to overcome resistance comprehensively. Therefore, we reasoned that combination strategies targeting downstream convergence points—particularly at the level of RAS or within the MAPK cascade itself—would provide more effective therapeutic intervention. Based on these mechanistic insights, we systematically evaluated potential combination partners for exarafenib, focusing on agents that could disrupt the key signaling dependencies characterized in resistant cells.

As candidate drugs, we first took a direct approach targeting RAS, given its central role in driving RTK-mediated pathway activation and its direct regulation of ARAF-KSR1 complex formation in resistant cells. We selected RMC-6236, the pan-RAS (ON) inhibitor used earlier to demonstrate RAS-dependent regulation of ARAF-KSR1 complex formation (Supplementary Fig. 7c). This broad-spectrum noncovalent inhibitor, which targets the active GTP-bound state of both mutant and wild-type RAS variants60, is particularly relevant for cell lines like ours lacking a RAS mutation but still exhibiting RAS-driven signaling and resistance through the ARAF-KSR1 scaffolding mechanism. Preclinical data show potent anticancer activity across multiple RAS-addicted cancer models, and early clinical studies (NCT05379985) have demonstrated objective responses in patients with KRAS G12X-driven solid tumors60. We also included the SHP2 inhibitor RMC-4550, which targets a common hub (SHP2) operating downstream of multiple RTKs to promote RAS-MAPK pathway signaling61. Additionally, considering the sustained MAPK signaling maintained through the ARAF-KSR1 mechanism, we selected two MAPK pathway inhibitors to suppress this pathway more potently: the MEK inhibitor binimetinib and the ERK inhibitor ASTX029. These downstream MAPK pathway inhibitors were expected to be particularly effective as they target the final convergence points of both canonical oncogenic-BRAF-dependent signaling and the alternative ARAF-KSR1-mediated bypass pathway. Binimetinib, which is FDA-approved for use in combination with encorafenib for BRAF V600E or V600K mutant melanoma, was chosen for its established clinical efficacy and capability for clinical translation62,63. ASTX029, currently in phase I-II clinical trials (NCT03520075), was selected for its novel dual-mechanism ERK inhibition, which offers potent and complete MAPK pathway suppression compared to traditional single-mechanism inhibitors64,65.

Furthermore, as a fourth candidate, we included the pan-AKT inhibitor ipatasertib66. Ipatasertib’s mechanism of action and initial encouraging clinical results in multiple solid tumors, including lung cancer, provided additional rationale for inclusion in our studies here to further address the observed increase in p-AKT levels that might play a role in promoting exarafenib resistance apart from the MAPK reactivation we have demonstrated67 (Fig. 4c and Supplementary Fig. 4d).

To establish a baseline reference for interpreting combination effects and to assess the individual potency of each agent, we first examined the monotherapy results from our drug screening analysis (leftmost column of each heatmap in Supplementary Fig. 8a). Binimetinib and ASTX029 demonstrated varying degrees of efficacy across the tested parental and exarafenib resistant models with the only exception being NCI-H2405-ER cells (Supplementary Fig. 8a, 1st and 2nd row). Both RMC-4550 (a SHP2 inhibitor) and RMC-6236 (a RAS (ON) multi-selective inhibitor) monotherapy exhibited anti-tumor activity in Class III BRAF-mutant NCI-H1666 parental and resistant cell lines, consistent with a previous report61. In cell lines harboring BRAF Class II mutations, particularly in H1755 parental cells, RMC-6236 monotherapy showed efficacy, which was consistent with the previously demonstrated growth inhibitory effects observed with KRAS knockdown alone (Fig. 4e, middle). In contrast, RMC-4550 monotherapy showed limited efficacy in all tested BRAF Class II cell lines (both parental and exarafenib-resistant H1755 and H2405 cells). While these two agents converge at or near the level of RAS, they showed different results, possibly due to their distinct mechanisms of action: RMC-4550 indirectly affects RAS activation by inhibiting SHP2, whereas RMC-6236 directly inhibits the active, GTP-bound form of RAS. Lastly, ipatasertib alone showed minimal response in most cell lines (Supplementary Fig. 8a, 5th row).

Moving beyond the monotherapy results, the combinational screening data revealed that binimetinib and ASTX029 significantly reduced exarafenib IC50 values and demonstrated robust additional effects compared to exarafenib alone in both parental and exarafenib resistant cell lines, consistently across all BRAF mutation classes (Fig. 6a and Supplementary Fig. 8a, 1st and 2nd row). The broad efficacy of these MEK and ERK inhibitors likely reflects their ability to target the final common pathway outputs from both canonical oncogenic-BRAF-dependent signaling (as observed in treatment-sensitive parental cells) and the alternative ARAF-KSR1 bypass mechanism. Combining either RMC-4550 or RMC-6236 with exarafenib showed efficacy in Class III BRAF-mutant NCI-H1666 parental and exarafenib-resistant cell lines, aligning with the monotherapy findings (Fig. 6a and Supplementary Fig. 8a, 3rd and 4th row). In Class II BRAF-mutant NCI-H2405 cells, while neither RMC-4550 nor RMC-6236 monotherapy had any impact on the parental or exarafenib-resistant line, combining either inhibitor with exarafenib produced an additional anti-tumor cell effect exclusively in the exarafenib-resistant cells, consistent with the observed upstream RAS activation (Fig. 6a and Supplementary Fig. 8a, 3rd and 4th row). In NCI-H1755 cells (also Class II BRAF-mutant cells), combining exarafenib with RMC-4550 or RMC-6236 resulted in additional effect in both the parental and exarafenib-resistant lines, with RMC-6236 showing more pronounced combinatorial effects (Fig. 6a and Supplementary Fig. 8a, 3rd and 4th row). The combination of ipatasertib and exarafenib showed additional inhibitory effects in Class II BRAF-mutant NCI-H2405 parental cells and Class III BRAF-mutated NCI-H1666 parental and exarafenib resistant cell lines, but the extent was limited compared to binimetinib and exarafenib (Fig. 6a and Supplementary Fig. 8a, 4th row).

Synergy calculations based on the same assay data confirmed the results of the cell proliferation assay, with binimetinib and ASTX029 showing large degrees of synergy with exarafenib in virtually all cell lines (Supplementary Fig. 8b). The distribution of synergy areas at moderate drug concentrations for these two agents suggested promising potential translatability to in vivo models and clinical settings in a feasible and tolerable manner. Furthermore, RMC-6236 exhibited robust synergy, particularly in resistant cells (Supplementary Fig. 8b, 4th row), reflecting the dependence on RAS activation in exarafenib-resistant cells. However, in parental cells, the synergistic effects were limited compared to those of the MEK and ERK inhibitors. Taken together, these differential response patterns, wherein inhibition of the MAPK pathway via MEK or ERK targeting elicited more pronounced antiproliferative effects compared to AKT inhibition in both parental and exarafenib resistant models, further suggest a predominant dependence on the MAPK pathway in these cellular models (Fig. 6a and Supplementary Fig. 8a, b).

To assess whether these findings could extend beyond exarafenib-resistant lines, we tested the same synergy approach in the previously studied HCC364-VR1 vemurafenib-resistant cell line. These cells harbor a BRAF V600E p61 splice variant that confers resistance to Class I BRAF inhibitors by a mechanism that is largely RAS independent but still promotes downstream MAPK pathway activation36. In these cells, significant additional effects and synergy were observed with the combination of binimetinib and ASTX029, confirming the broad spectrum of these two agents against diverse MAPK pathway activation mechanisms (Fig. 6b). In contrast, combining exarafenib with targeting upstream of RAF using RMC-4550 (SHP2) or RMC-6236 (RAS) did not yield significant additional effects or synergy in this BRAF Class I resistant model that achieves MAPK pathway activation in a largely RAS-independent manner (Fig. 6b). This distinct response pattern serves as an important mechanistic control, demonstrating that RAS-targeting agents are specifically effective against resistance mechanisms involving RAS-dependent processes like ARAF-KSR1 complex formation, while MEK/ERK inhibitors retain broad efficacy regardless of the upstream resistance architecture.

Further validation of the exarafenib-MAPK pathway inhibitor combinations
We examined the changes in MAPK signaling upon binimetinib and ASTX029 combinations with exarafenib. As these drugs target MEK and ERK, respectively, we probed activity markers of the MAPK pathway68,69, and included BIM, a pro-apoptotic protein that is suppressed by MAPK pathway signaling70,71. The concentrations of exarafenib (500 nM), binimetinib (50 nM), and ASTX029 (50 nM) used here were selected based on their high synergistic effects observed in all cell lines during the initial drug screening, and to use doses within clinically relevant levels to enable tolerability20,62–65,72. In all three sets of experiments, the drug combination more potently suppressed the pathway in both parental and resistant cells (Fig. 6c and Supplementary Fig. 9a). To further understand the temporal dynamics underlying these combination effects, we performed time-course western blot analysis in NCI-H2405-ER cells (Fig. 6d). Exarafenib monotherapy demonstrated progressive reactivation of MAPK pathway activity over 48 h, recapitulating the temporal rebound pattern described earlier (Fig. 4c). In contrast, combination treatment with binimetinib effectively prevented this reactivation, maintaining pathway inhibition throughout the treatment period (Fig. 6d).

Western blot analysis of the RMC-4550 combination with exarafenib also yielded results consistent with the cell viability assay, with the combination further inhibiting the MAPK pathway in all resistant cells as well as parental NCI-H1755 and NCI-H1666 cells (Supplementary Fig. 9b). Similarly, the combination of RMC-6236 with exarafenib showed enhanced MAPK pathway suppression in both NCI-H1755 and NCI-H1666 parental cells and enhanced inhibition in all resistant cells (Supplementary Fig. 9c). Immunoblotting analysis of the AKT inhibitor ipatasertib combination with exarafenib to measure expression of the MAPK activity markers DUSP6, Cyclin D1, EphA2, and BIM, did not show additional inhibitory effects, as expected (Supplementary Fig. 9d).

These findings suggest that two types of MAPK pathway inhibitors, targeting different nodes of the pathway (MEK, ERK), enhance the therapeutic efficacy of exarafenib in BRAF-mutant lung cancer cells by effectively disrupting both conventional oncogenic-BRAF signaling (predominant in parental cells and non-treated resistant cells) and ARAF-KSR1-mediated bypass signaling (activated in resistant cells under drug treatment). To determine whether this effect is specific to these drugs or can be achieved with other compounds with similar mechanisms of action, we expanded our investigation to additional inhibitors. We first conducted IC50 studies testing several MEK and ERK inhibitors as single agents using NCI-H2405, NCI-H1755, and NCI-H1666 cell lines (Supplementary Fig. 10a). Our aim was to identify compounds with potencies similar to binimetinib and ASTX029, allowing for a more direct comparison of combination effects by minimizing potential confounding factors related to significantly differing drug potencies. From these studies, we selected cobimetinib, a clinically established MEK inhibitor42,73, and SCH772984, an experimental ERK inhibitor74, based on their comparable potencies to our initially tested compounds. Subsequent experiments confirmed that cobimetinib, and to some extent SCH772984, enhanced the anti-tumor effects of exarafenib in the resistant cells (Supplementary Fig. 10b, c). These results support the robustness of our findings and suggest that the observed synergy is not strictly limited to specific MEK or ERK inhibitors but is likely to be a broader biological effect across these drug classes targeting the downstream MAPK pathway convergence points.

Among the agents that showed notable synergy with exarafenib, we considered binimetinib as highly promising given its established clinical use and favorable tolerability profile62,63. The consistent efficacy of MEK inhibition across all tested models further supports the rationale for targeting downstream convergence points where both conventional oncogenic-BRAF-dependent signaling and ARAF-KSR1-mediated bypass signaling ultimately converge. To further validate the broad applicability of the exarafenib and binimetinib combination, we tested its efficacy in BRAF-mutant Class II and III cell lines that were less responsive to exarafenib monotherapy. These models included the NCI-H1395, NCI-H2087, and Cal-12T cell lines, which we found to be sensitive to the combination of exarafenib and binimetinib, as evidenced by the reduction in cell viability and significant synergy scores (Supplementary Fig. 10d, e). The efficacy of MEK inhibitor combination in these intrinsically less sensitive cells, which may harbor baseline compensatory signaling, suggests that certain patients could benefit from initial combination therapy rather than sequential treatment.

In vivo efficacy of exarafenib plus binimetinib in NSCLC
To validate the promising combination effects of exarafenib and binimetinib observed in vitro, we evaluated the efficacy of the combination in three patient-derived lung cancer models in vivo, including PDXs: NCI-H1755 (BRAF G469A), CTG-3703 (EGFR exon 19 deletion; AGK-BRAF PDX), and ST5570 (EGFR exon 19 deletion; TRIM24-BRAF PDX) (Fig. 6e). These models represent different BRAF alterations found in lung cancer, including point mutations and gene fusions. Notably, both the CTG-3703 and ST5570 models were derived from EGFR-mutant NSCLC patients who had progressed on EGFR inhibitors. These patients subsequently acquired clinically relevant BRAF fusion proteins, which are known to cause resistance to EGFR-tyrosine kinase inhibitors75–78; importantly, we found that exarafenib is effective against certain BRAF fusions in our preclinical profiling using the Ba/F3 system (Fig. 2d and Supplementary Fig. 1c). While we also attempted to establish CDX models using exarafenib-resistant cells, these efforts were unsuccessful due to altered tumorigenic capacity of the adapted cells.

In the NCI-H1755 and ST5570 models, the exarafenib plus binimetinib combination significantly suppressed tumor growth compared to both vehicle control and each monotherapy (Fig. 6e, right and left). Although the difference between the combination and exarafenib monotherapy did not reach statistical significance in the CTG-3703 model, a trend towards enhanced efficacy was also observed (Fig. 6e, middle). Notably, in all cases, the combination achieved tumor suppression that was at least comparable to, and in some cases better than, the higher dose of exarafenib monotherapy, while being well-tolerated, with no significant body weight loss or observed adverse effects (Supplementary Fig. 11a). To further elucidate the MAPK signaling changes induced by the exarafenib and binimetinib combination, we conducted western blot analysis in H1755 xenograft tumor samples at 1- and 7-h post-dosing (Supplementary Fig. 11b). The results revealed strong inhibition of p-ERK by the combination therapy at 1-h post-treatment, with this effect sustained at 7 h post-dosing compared to each monotherapy. Additionally, the combination treatment showed a more pronounced effect on reducing levels of EphA2 and DUSP6, two downstream targets of ERK signaling, further supporting the enhanced pathway inhibition achieved with dual RAF and MEK blockade (Supplementary Fig. 11b).

Although CDX models from exarafenib-resistant cells could not be established due to technical limitations, the activity demonstrated across diverse BRAF-altered models, including clinically relevant PDX models with acquired EGFR inhibitor resistance, validates the broad therapeutic potential of this combination approach. These findings demonstrate exarafenib and binimetinib combination as a promising therapeutic strategy for BRAF-mutant lung cancer, offering superior efficacy and the potential to decrease exarafenib doses to maintain or enhance therapeutic index while eliciting efficacy. Furthermore, evaluating this combination in these models provides valuable insights into possible strategies for overcoming resistance to EGFR inhibitors in EGFR-mutated NSCLC caused by certain BRAF variants.

Combination therapy resistance reveals sustained ARAF dependency
Given the robust efficacy of exarafenib plus binimetinib combination therapy, we sought to understand potential resistance mechanisms that might emerge under this dual RAF-MEK blockade. To model this clinically relevant scenario, we generated combination-resistant cells by treating established exarafenib-resistant NCI-H2405-ER cells with gradually escalating doses of binimetinib over 3 months, resulting in NCI-H2405-EBR (Exarafenib-Binimetinib Resistant) cells. Notably, attempts to generate resistance by treating parental cells with both drugs simultaneously were unsuccessful despite 6 months of continuous selection, underscoring the potent synergistic efficacy of upfront combination therapy.

To characterize the molecular mechanisms underlying combination resistance, we first examined RAS activation status, given its central role in monotherapy resistance. RAS-GTP pulldown assays revealed that NCI-H2405-EBR cells exhibited elevated RAS-GTP levels under combination drug treatment compared to parental cells (Supplementary Fig. 11c), mirroring the RAS activation pattern observed in exarafenib monotherapy-resistant cells. This finding indicated that combination-resistant cells retain the ability to elevate RAS-GTP levels under dual RAF-MEK inhibition.

Based on our concurrent findings that ARAF mediates resistance to exarafenib monotherapy through RAS-dependent mechanisms, we investigated whether this mechanism also contributes to combination therapy resistance. Remarkably, ARAF knockdown dramatically restored sensitivity to the drug combination in NCI-H2405-EBR cells, reducing IC50 values in the presence of binimetinib plus exarafenib (Fig. 6f). Western blot analysis further confirmed that ARAF knockdown enhanced MAPK pathway suppression under drug treatment (Supplementary Fig. 11d). These new data suggest that ARAF (or upstream RAS) activation could emerge as a conserved mechanism of resistance clinically. Thus, selective ARAF or RAS inhibition (for instance, with RMC-6236) could overcome multiple resistance layers and may warrant clinical investigation.

Clinical activity I: exarafenib treatment of a NSCLC patient with TMEM106B-BRAF fusion
Lastly, to validate the clinical relevance of our preclinical findings regarding exarafenib’s anti-tumor activity, we examined the clinical outcomes of patients with advanced BRAF-mutant lung cancer treated with exarafenib in the ongoing phase I/Ib clinical trial, KN-8701 (NCT04913285; interim monotherapy results reported)79. The first case presented is a patient with stage 4 lung adenocarcinoma harboring an oncogenic TMEM106B-BRAF fusion (considered a BRAF Class II variant)80 (Fig. 7a). The patient received standard first-line therapy consisting of 4 cycles of cisplatin, pemetrexed, and pembrolizumab, followed by 2 cycles of maintenance therapy. Subsequently, the patient underwent radiotherapy to all observed lung and bone lesions and was closely monitored for over 2 years without recurrence or further treatment. Upon progression on prior therapies, the patient enrolled in the KN-8701 trial (NCT04913285). After starting on exarafenib at 800 mg/day (400 mg BID), the patient demonstrated a confirmed partial response, with a significant reduction in target lesions (2 liver metastases) (Fig. 7b). Additionally, while various cancer-associated genes were detected in ctDNA at baseline, a rapid decrease was observed after treatment (the original BRAF fusion was not detected, possibly due to technical limitations of liquid biopsy which can have varying degrees of fusion detection sensitivity) (Fig. 7c). During treatment, the patient experienced CTCAE v5 Grade 2 dermatitis acneiform, prompting a dose reduction of exarafenib to 600 mg/day (300 mg BID). This adjustment allowed for continued treatment with manageable side effects, with a prolonged therapeutic response. At the 32-week CT radiographic evaluation, despite sustained reduction and control of the target lesions, new lymph node metastases were detected, leading to a diagnosis of progressive disease. This case highlights both the potential clinical efficacy of exarafenib and the need to test rational combination therapies such as combined RAF plus MEK (or RAS) inhibition, supported by our findings, to enhance the clinical impact.

Clinical activity II: exarafenib treatment of a NSCLC patient with BRAF G469S mutation
The second patient presented is a patient with stage 4 lung adenocarcinoma harboring a BRAF Class II, G469S mutation (Fig. 7d). The patient received standard first-line therapy consisting of 4 cycles of carboplatin, pemetrexed, and pembrolizumab, followed by maintenance therapy. The adenocarcinoma demonstrated progressive disease, and the patient was subsequently enrolled in the exarafenib clinical trial. At the time of trial enrollment, the patient had suspected lymphangitic carcinomatosis (a condition where cancer spreads through the lymphatic system in the lungs) and required oxygen therapy. After initiating exarafenib at 400 mg/day (200 mg BID), the patient was weaned off oxygen within 2 weeks, and a significant improvement in bilateral lung infiltrates was observed after 2 cycles (28-day cycle) (Fig. 7e). The patient had two lymph node metastases as target lesions at baseline, and achieved a partial response approximately 60 weeks after treatment initiation. The disease remained controlled, and despite experiencing CTCAE v5 Grade 2 acneiform rash, which was manageable, the patient has continued exarafenib treatment with sustained disease control throughout the observation period (over 2 years).

These clinical cases provide initial evidence of the promising clinical activity with manageable toxicity of exarafenib in BRAF-mutant NSCLC patients with unmet clinical need, consistent with our supporting preclinical dataset.

Methods
Cell lines and reagents
NSCLC cell lines harboring BRAF mutations (NCI-H2405, NCI-H1755, NCI-H1666, HCC364, NCI-H1395, NCI-H2087, Cal-12T) and various RAS mutations (NCI-H358, NCI-H23, NCI-H2030, SW-1573, A-427, A549, NCI-H441, NCI-H1944, Calu-6, NCI-H2347) were used in this study. HCC364-VR1, a vemurafenib-resistant subclone, was previously generated in our laboratory36. Cells were maintained in RPMI-1640 medium (Cytiva), except for A-427, which was cultured in DMEM (Cytiva). All media were supplemented with 10% fetal bovine serum (FBS; Avantor) and 1% penicillin-streptomycin (Cytiva), and cells were cultured at 37°C in a humidified atmosphere containing 5% CO2. AALE, a normal epithelial cell line35, was kindly provided by Eric Collison, University of Washington School of Medicine, and was maintained in SABM supplemented with SAGM SingleQuots (Lonza). HCC364 was kindly provided by David Solit, Memorial Sloan Kettering Cancer Center (MSKCC), New York. All other cell lines were obtained from the American Type Culture Collection (ATCC).

Establishment of exarafenib-resistant cell lines
To generate exarafenib-resistant cell lines, parental cells were seeded at 50% confluence in 10-cm dishes and initially exposed to exarafenib at a concentration corresponding to the IC50 value. The drug-containing medium was replenished every 5 days. When cells reached confluence, they were passaged, and exarafenib was added the following day after cell attachment. The drug concentration was incrementally increased after every two passages until it reached 1 μM. Once this concentration was achieved, cells were continuously cultured with 1 μM of exarafenib. This process of continuous exarafenib exposure was maintained for over 3 months to establish stable drug-resistant cell lines, designated as NCI-H2405-ER, NCI-H1755-ER, and NCI-H1666-ER, derived from their respective parental cell lines. For combination-resistant cells, NCI-H2405-ER cells maintained in 1 μM exarafenib were exposed to escalating doses of binimetinib (escalated to 50 nM over 3 months), generating the NCI-H2405-EBR cell line. Attempts to generate EBR cells directly from parental cells using simultaneous drug exposure were unsuccessful.

Compounds
The RAF inhibitors vemurafenib, exarafenib, naporafenib, and belvarafenib were provided by Kinnate Biopharma, while binimetinib (S7007), cobimetinib (S8041), ASTX029 (S0872), SCH772984 (S7101), RMC-4550 (S8718), RMC-6236 (E1597), ipatasertib (S2808), and sotorasib (S8830) were purchased from Selleck Chemicals (Houston, TX, USA).

Antibodies
Complete list of antibodies can be seen at Supplementary Table 8.

Western blotting and in vitro kinase assay
Following treatment, cells were washed with cold PBS and lysed in RIPA buffer supplemented with protease and phosphatase inhibitors (Thermo Scientific). Protein concentrations were determined using the BCA protein assay kit (Pierce). Equal amounts of protein (10 μg) were separated by SDS-PAGE and transferred to nitrocellulose membranes. Membranes were blocked with 5% non-fat dry milk in TBS-T for 30 min at room temperature and then incubated with primary antibodies overnight at 4°C. After washing with TBS-T, membranes were incubated with the appropriate HRP-conjugated secondary antibodies for 30 min at room temperature. Signals were detected using the ECL western blotting substrate (Thermo Scientific) and visualized with the ImageQuant LAS4000 (GE Healthcare). Quantified bands were normalized to GAPDH as a loading control.

For the in vitro kinase assay, cells were lysed in IP lysis buffer (Pierce) supplemented with protease and phosphatase inhibitors. Protein A/G magnetic beads (Pierce) were incubated with the appropriate antibodies (anti-ARAF, anti-BRAF, or anti-CRAF) for 1 h at 4°C. The antibody-conjugated beads were then incubated with 150 μg of protein for 4 h to overnight at 4°C. Beads were washed three times with cold PBS and twice with kinase buffer (Cell Signaling Technology) using a magnetic separator. Kinase reactions were performed by incubating the beads in kinase buffer containing 50 μM ATP and 0.4 μg of inactive MEK1 (Millipore) for 30 min at 30°C. Reactions were terminated by the addition of SDS sample buffer, and the samples were boiled for 2 min. Proteins were separated by SDS-PAGE, transferred to nitrocellulose membranes, and analyzed by western blotting using an anti-p-MEK antibody. The kinase assay results were normalized to total MEK levels.

RAS activation assay
RAS activation was assessed using the RAS-RBD (Ras-binding domain) assay kit (Cytoskeleton), which measures the amount of active, GTP-bound RAS. Cells were lysed in ice-cold lysis buffer provided in the kit, supplemented with protease and phosphatase inhibitors. Lysates were clarified by centrifugation at 10,000 × g for 2 min at 4°C. Equal amounts of protein (150 μg) were incubated with 10 μL of Raf-RBD protein beads for 1 h at 4°C with gentle rotation. The beads were washed with the kit’s wash buffer, and bound proteins were eluted by boiling in 2× SDS sample buffer for 2 min. The eluted proteins were separated by SDS-PAGE, transferred to nitrocellulose membranes, and analyzed by western blotting using the anti-RAS antibody provided in the kit. Total RAS levels were determined by western blotting of the cell lysates used for the RAS-RBD pull-down assay. The levels of active RAS were normalized to GAPDH as a loading control to account for any variations in total protein content between samples.

Phospho-RTK array analysis
Phospho-receptor tyrosine kinase (RTK) levels were assessed using the Human Phospho-RTK Array Kit (R&D Systems) according to the manufacturer’s instructions. For each array, 300 μg of protein was used, and the arrays were incubated overnight at 4°C. Pixel density was quantified using ImageJ software (National Institutes of Health), and the data were normalized to the positive control spots.

Cell viability assays and drug screening
2D and 3D cell viability assays were performed to assess the efficacy of exarafenib, belvarafenib, vemurafenib, and sotorasib in various cell lines. For 2D assays, BRAF-mutant cells were seeded into 96-well plates at 2500 cells per well and incubated with either a vehicle control (DMSO) or serial 3-fold dilutions of compounds. In the preparation of 3D assays, KRAS-mutant lung cancer cells were seeded at a density of 2500 cells per well in 50 μL of growth medium into 96-well ultra-low attachment plates (Corning). In order to induce spheroid formation, centrifugation at 300 × g for 5 min was carried out. After incubation for 72 h, the spheroids were treated in triplicate with serial 3-fold dilutions of compounds or vehicle control, DMSO, to a final volume of 100 μL per well. Unless otherwise indicated, plates were incubated for 120 h at 37°C in a humidified atmosphere containing 5% CO2. Cell viability was measured for 2D cultures using the CellTiter-Glo® 2.0 Assay (Promega) and for 3D cultures using the CellTiter-Glo 3D Cell Viability Assay (Promega), according to the manufacturer’s instructions. In each of these assays, luminescence was measured with a SpectraMax M5 plate reader (Molecular Devices) and cell viability determined as percent relative to vehicle control. IC50 values were calculated by non-linear regression analysis using GraphPad Prism 7.0 by fitting the data to a four-parameter logistic curve. This form of normalization and calculation of IC50 was applied consistently to all cell lines and compounds tested in 2D and 3D assays. Statistical significance for cell viability data was determined through a two-tailed Student’s t-test.

For the comprehensive drug screening, to ensure data quality and enable reliable synergy calculations, exarafenib was used at 9 dosages (3-fold change from 10 μM) and each drug partner candidate at 5 dosages (3-fold change), with the addition of DMSO controls. The range of dosages for each drug was determined by referring to previous in vitro studies61,64–66,82, considering varying potencies across the different compounds. The initial screening was performed in triplicate on 6 cell lines, comprising 3 sets of parental and resistant cells, and then expanded to cells of interest. Loewe synergy scores were calculated for each drug combination based on the drug screening assay data using the Combenefit software83.

To assess the proliferation capabilities of exarafenib-resistant cell lines compared to their parental counterparts, cells were seeded in 96-well plates. Resistant cells were cultured in the presence of 1 μM exarafenib, while parental cells were grown without drug exposure. Cell viability was measured using the CellTiter-Glo® 2.0 Assay on day 1 and day 3. Relative cell viability was calculated as fold change compared to day 1 measurements. Each condition was tested in triplicate.

Cell proliferation analysis by direct cell counting
NCI-H2405-ER cells were seeded at 30,000 cells/well in 6-well plates and treated with 1 μM exarafenib for 72 h. Following treatment, cells underwent drug withdrawal (complete medium replacement with drug-free RPMI-1640) with counts at −4 h, −24 h, and −48 h. For re-challenge, cells at −48 h were re-exposed to 1 μM exarafenib with counts at +4 h, +24 h, and +48 h. Viable cells were quantified using trypan blue exclusion with a Vi-CELL XR counter (Beckman Coulter). Data from three replicates per timepoint were normalized to the 72-h treatment baseline (fold change = 1.0) and expressed as mean ± SD.

Ba/F3 cell viability assay
The effect of exarafenib, belvarafenib, vemurafenib, and sotorasib on cell viability was evaluated in Ba/F3 cells expressing various BRAF and KRAS mutations. The experiments were conducted at KYinno Biotechnology (Beijing) Co., Ltd., a contract research organization. Ba/F3 cells were seeded at 3000 cells per well in a 96-well plate in 90 μL growth media and incubated overnight at 37°C with 5% CO2. Compounds were serially diluted from a 10 μM top dose for a 9-point 3-fold dilution curve in DMSO. After 72 h of incubation at 37°C with 5% CO2, cell viability was assessed using the CellTiter-Glo® 2.0 Assay (Promega) according to the manufacturer’s instructions.

siRNA-mediated Gene Knockdown
To perform gene knockdown, siRNAs targeting specific genes were used. The following siRNAs were purchased from Dharmacon (Horizon Discovery): non-targeting control (D-001810-10-50), KRAS (L-005069-00-0020), NRAS (L-003919-00-0020), HRAS (L-004142-00-0020), AXL (L-003104-00-0020), MET (L-003156-00-0020), EGFR (L-003114-00-0020), ARAF (L-003563-00-0020), BRAF (L-003460-00-0010), CRAF (L-003601-00-0010), and KSR1 (L-003570-00-0005). Cells were seeded into appropriate plates, and transfection was performed the following day using Lipofectamine RNAiMAX (Invitrogen, Thermo Fisher Scientific) according to the manufacturer’s protocol. Twenty-four hours after transfection, cells were plated and incubated for the appropriate time periods prior to the performance of different types of experiments. The efficiency of gene knockdown was confirmed by Western blot analysis.

Proximity ligation assays (PLA)
Cells were seeded in 4-well Lab-Tek chambers and cultured overnight. Proximity ligation assays were performed using the Duolink In Situ Red Detection Kit (Millipore Sigma). Cells were fixed in 4% paraformaldehyde for 10 min at 37°C, permeabilized with −20°C methanol for 10 min, then treated with 0.25% Triton X-100 for 10 minutes before blocking for 1 h at 37°C. Primary antibodies (1:200 dilution) were incubated overnight at 4°C. PLA probes were applied at 1:5 dilution for 1 h at 37°C, followed by ligation (30 min) and amplification (100 min) at 37°C. Nuclei were stained with DAPI, and images were acquired using a 60× oil objective. PLA puncta per cell were quantified using Fiji ImageJ software.

Three-dimensional (3D) structure prediction
For three-dimensional (3D) structure prediction, we used the protein sequences of ARAF (NP_001645.1, 606 amino acids) and KSR1 (Q8IVT5, 923 amino acids) as inputs to the AlphaFold3 server. The predicted structures were downloaded in .cif format and subsequently converted to PDB format using the PyMOL software package for downstream structural analysis.

Because no experimentally determined crystal structure of the pan-RAF inhibitor Exarafenib bound to either ARAF alone or to the ARAF–KSR1 complex is currently available, we adopted a homology-based modeling strategy. Specifically, we utilized the BRAF–Exarafenib co-crystal structure (PDB ID: 8QQG) as a reference. In PyMOL, the kinase domain of ARAF was aligned with the corresponding kinase domain of BRAF, and the coordinates of Exarafenib were transferred into the predicted ARAF binding pocket to generate an ARAF–Exarafenib binding model.

To evaluate the potential influence of KSR1 binding on inhibitor accommodation, we further superposed the ARAF–Exarafenib model with the ARAF–KSR1 predicted complex. By aligning the ARAF kinase domain in both structures, Exarafenib was transferred into the ARAF binding pocket within the ARAF–KSR1 complex. To identify molecular interactions, we extracted the contact residues from both ARAF and KSR1 that lie within 5 Å (angstrom) of Exarafenib.

GuardantINFORM™ database analysis
Data for this real-world evidence analysis were obtained from the GuardantINFORM™ database, which contains targeted genomic data from circulating tumor DNA linked to a claims database for patients in the United States with advanced stage solid tumors who underwent testing with a Guardant360 assay between March 2014 and June 2021. At the time of data cut, the database included over 160,000 patients diagnosed with advanced or metastatic cancer. Within this population, the Guardant360 liquid biopsies were collected at various time points, with some obtained at initial diagnosis and others during disease progression. The database was queried for ctDNA tests of patients with a BRAF mutation. ctDNA was extracted from whole blood and isolated for digital targeted panel sequence. At the time of the study, Guardant360 included analysis of single-nucleotide variants in up to 83 genes, as well as small insertions or deletions, amplifications, and gene rearrangement/fusions in select genes. Nonsynonymous mutations and focal copy number alterations were processed using the SAS 9.4 statistical computing program. All nonsynonymous BRAF mutations and focal amplifications were included, while synonymous mutations and those associated with clonal hematopoiesis were excluded. The analysis focused on patients exhibiting Class I, II, or III BRAF alterations, with a specific emphasis on NSCLC (n = 2398). Sex and age were determined based on the linked claims database. Sex was considered as a biological variable in the study design to assess potential associations with BRAF mutation classes. No participant compensation was provided for this database analysis. BRAF alterations were classified according to Supplementary Table 1, which was summarized by referencing previous studies3,12,15,84.

Patient characteristics and statistical analysis
Patient characteristics of NSCLC cases with BRAF Class I, II, or III alterations were analyzed using the GuardantINFORM™ database. Cases with multiple BRAF alterations across functional classes were excluded from the analysis. Age, gender, and tobacco use history were identified as potential covariates. To compare the distribution of covariates across BRAF classes, we employed pairwise chi-squared tests with Holm-adjusted P-values.

Survival analysis and statistical methods
Overall survival was measured from the time of the detection of BRAF, with patients censored at the date of their last known claim activity if no death date was available. Cohorts were compared pairwise using the log-rank test, and Kaplan–Meier curves were used to visualize survival probabilities over time. Descriptive statistics were reported for each BRAF class. Comparisons were made between the classes using chi-square tests when outcomes were binary and Student’s t tests when outcomes were continuous, with a *P-value < 0.05 considered statistically significant. Unadjusted Cox proportional hazard model was run to assess the relationship between BRAF classes. Outcomes from the model were reported as hazard ratios (HRs) with 95% confidence intervals. An HR of 1 indicates no difference in risk between groups, while an HR > 1 suggests increased risk, and an HR < 1 indicates decreased risk for the comparison group relative to the reference group.

Kinome specificity profile
The kinase specificity profiles for 1 μM exarafenib, naparafenib, and belvarafenib were tested across a panel of 368 wild-type kinases using the HotSpot Technology85 (Reaction Biology) at 10 μM ATP. Kinase inhibition was calculated as (100 – Enzyme activity), relative to DMSO controls.

In vivo efficacy and pharmacokinetic (PK) and pharmacodynamic (PD) studies
The in vivo efficacy of exarafenib was evaluated, both as a single agent and in combination with binimetinib, using cell line-derived xenograft (CDX) and patient-derived xenograft (PDX) models. These studies were conducted at various institutions, including Pharmaron (Beijing, China), Champions Oncology (Hackensack, New Jersey, USA), XenoSTART (San Antonio, Texas, USA), and Genen Design (Shanghai, China). Animals were housed under controlled environmental conditions with a 12 h light/12 h dark cycle, ambient temperature of 20–26°C, and relative humidity of 30–70%. The maximal tumor size permitted by the institutional ethics committees was 2500 mm³. All animals were immediately euthanized upon reaching this limit.

Pharmaron used NCI-H1755 CDX model for efficacy and NCI-H2405 CDX model for efficacy and PK/PD studies. Female BALB/c nude mice (6-8 weeks) were inoculated subcutaneously into the right flank with cells cultured in RPMI1640 medium with 5% HI FBS. For CDX studies, cells were inoculated into mice in 0.1 ml of a 1:1 mixture of media and Matrigel. Efficacy studies began at ~300 mm3 tumor volume, with mice (n = 9 per group) receiving vehicle (0.5 methyl cellulose, 0.1% Tween 80 in water), exarafenib (1.5–30 mg/kg), binimetinib (2–3 mg/kg), or a combination twice daily. Animals were euthanized if in deteriorating condition or tumor size exceeded 2500 mm3. For PK and PD analyses, animals were treated for 3 days, then plasma samples were collected at 0, 0.25, 0.5, 1, 3, 7, 12, 18, and 24 h post-last dose, while tumor samples were collected at 1, 7, 24, 48, and 72 h post last dose (n = 3 per timepoint). Plasma concentrations were measured by LC/MS/MS, and tumor lysates were assessed for p-ERK1/2 and total ERK1/2 levels using the MSD Phospho/Total ERK1/2 Whole Cell Lysate Kit (Meso Scale Diagnostics, #K15107D).

Champions Oncology (CTG-1444, CTG-3703 PDX) and XenoSTART (ST5570 PDX) implanted subcutaneous tumor fragments into the right flank of female athymic nude-Foxn1nu mice (6–8 weeks). Studies began at 175–300 mm3 mean tumor volume. Animals were euthanized if tumor volume was reached 2500 mm3. GenenDesign used LUN023 and LUN037 PDX models, following the same procedures but using Balb/c nude mice (n = 9 per group).

For all xenograft studies, tumors width and length were measured by calipers, and tumor volume was calculated by width2 × length × 0.5. Tumor growth inhibition (TGI) was calculated as [1 − (TVf − TV0)treated/(TVf − TV0)control] × 100, where TVf and TV0 are the mean tumor volumes on the final day and the initial day of treatment, respectively. Statistical analysis was performed using one-way ANOVA with Bonferroni correction for multiple comparisons. Significance levels were set at *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

Patient case studies from the KN-8701 clinical trial
Two patients with advanced BRAF-mutant lung cancer treated with exarafenib in the phase I/Ib clinical trial, KN-8701 (NCT04913285), were selected for in-depth case studies. The first patient was treated at Stanford University School of Medicine, and the second patient was treated at the University of California, San Diego, Moores Cancer Center. Clinical data, including patient demographics, disease characteristics, treatment history, and response to exarafenib, were collected from the respective study sites. Tumor response was assessed using the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. Adverse events were graded according to the Common Terminology Criteria for Adverse Events (CTCAE) version 5.0. In addition to clinical data, circulating tumor DNA (ctDNA) analysis was performed for the first patient to monitor treatment response. ctDNA was isolated from plasma samples collected at baseline and at various time points during treatment. The clinical information presented was current up to December 2023.

Statistics and reproducibility
Quantitative results are reported as the mean ± standard deviation (S.D.) or the standard error of the mean (S.E.M.), as indicated in the figure legends. Statistical analyses were conducted using GraphPad Prism 7.0. Unless otherwise noted, comparisons between two groups were performed using two-tailed Student’s t-tests. For analyses involving multiple independent groups, a one-way ANOVA was performed, followed by Bonferroni correction to account for multiple comparisons. When representative data are presented, they depict one of at least two separate experiments yielding comparable outcomes.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The authors describe characterization of a recently developed pan-RAF inhibitor for lung cancers with class 1, II or III BRAF mutations. They then establish drug resistant derivatives and test a number of combinations of MAPK drugs to overcome resistance. Not surprisingly (based on prior literature), they find that combination with MEK or ERK inhibitor overcomes resistance to exarafenib. The major criticism of this work is that there is really not a lot of novelty in this work. Activation of RAS through RTK activation as a mechanism of resistance to RAF or MEK inhibition has been seen by many and has formed the bases for combination trials with SHP2 inhibitors (and found to be overly toxic). This work deserves to be published, but in a more specialized journal.", "reviewer_2": "We appreciate the thoughtful consideration of, and feedback on our manuscript as well as the enthusiasm for our study. We address the points raised below.\n-Re: Guardant database used - were these liquid biopsies all at initial diagnosis, or some during/after treatment?\nWe thank the reviewer for this important clarification regarding the timing of liquid biopsy collection in our study.\nAll patients included in our GuardantINFORM™ analysis had advanced or metastatic disease, as this is the\nprime clinical use of Guardant360 assay testing. Within this advanced/metastatic population, the Guardant 360\nliquid biopsies were collected at various timepoints that reflect real-world clinical practice - some were performed\nat initial diagnosis while others were conducted during disease progression. This timing diversity provides a\ncomprehensive view of BRAF mutation prevalence across different phases of disease management in the\nmetastatic and real-world clinical setting, offering a valuable contribution to the field. This clarification has been\nadded to the Methods section (Page 46, Line 1562-1582).\n-Re: rwOS from Guardant database - any data available re: Stage/Treatment? What was timeframe looked\nat? (i.e. were these all in the IO era, as differences in types of treatments offered over time could have\nan impact on survival outcomes?)\nWe thank the reviewer for this important question regarding the timing of liquid biopsies and potential bias from\ntreatment evolution during the study period.\nThe GuardantINFORM™ database used in our analysis spans from March 2014 to June 2021, predominantly\nencompassing the immunotherapy era when immune checkpoint inhibitors were established as a standard of\ncare for NSCLC. The most commonly used first-line treatment regimens (top 3) for each BRAF class are\ndisplayed as Fig. 1d. The entire treatment information for 1st, 2nd, and 3rd-line therapies by BRAF mutation\nclass has been provided in Supplementary Data 1-3. As demonstrated in these datasets, immunotherapy-\ncontaining regimens represent a substantial proportion of treatments across all BRAF mutation classes, further\nconfirming that our survival analyses reflect outcomes in the modern immunotherapy era. These treatment data\nand the expanded clinical analysis have been incorporated into the Results section (pages 5, lines 158-163).\n(Fig. 1d) First-line treatment regimens for BRAF-mutant NSCLC patients by mutation class from the\nGuardantINFORM™ database. The table shows the top 3 most frequently used first-line therapies for each\nBRAF mutation class (Class I, II, and III) with corresponding patient numbers and percentages.\nRegarding disease stage, all patients in our analysis had advanced/metastatic disease at the time of testing,\nproviding a consistent baseline for survival comparisons across different BRAF mutation classes. This\nclarification regarding the study timeframe and treatment details has been added to the Methods section (Page\n46, Line 1562-1582).\n-Re: activity seen against V60E p61 slice variant conferring resistance - what proportion of resistance is\ncomprised of this alteration? Do they have data from the Guardant database that can inform prevalence\nof this?\nThank you for raising this important point. While resistance mechanisms, including V600E p61 splice variants,\nhave been well characterized in melanoma, their frequency in NSCLC remains an area of ongoing study due to\nthe challenges in obtaining rebiopsy specimens after progression (Poulikakos PI, Nature, 2011; Tsamis L et al.,\nClin Transl Oncol., 2023). We did detect this variant in human BRAF mutant lung cancer with BRAF inhibitor\nresistance in our prior report describing our discovery of this resistance variant in human BRAF class I mutant\nlung cancers treated with first generation BRAF inhibitors (Lin L et al., PNAS, 2014). Currently, the\nGuardantINFORM™ database's liquid biopsy assay does not include RNA sequencing capabilities, which would\nbe important for readily detecting splice variants. This technical limitation, which is common across many liquid\nbiopsy platforms, highlights the need for continued development of comprehensive molecular profiling\napproaches. Future iterations of the assay are planned to include RNA analysis capabilities, which will help\naddress this knowledge gap.\n-Re: RAS activation seen in exarafenib resistance - the experiments investigating RTKs as a potential\nmediator of RAS activation did not seem to yield a clear mechanism. did the authors perform any other\nmechanistic studies to try to get at how this is occuring?\nWe thank the Reviewer for this insightful question regarding the mechanistic basis of RAS activation in exarafenib\nresistant cells. While our initial RTK profiling identified activation of multiple RTKs (e.g. AXL, MET, EGFR) in\nresistant cells, individual RTK knockdowns showed limited effects on exarafenib sensitivity, suggesting functional\nredundancy and that no single RTK was solely responsible for the RAS activation observed upon exarafenib\ntreatment. To address the Reviewer's question about the underlying mechanism, we performed additional\nmechanistic studies:\n1. Combined RTK Silencing: We conducted combined combined AXL and EGFR knockdown experiments in\nNCI-H2405-ER cells, which demonstrated a more pronounced reduction in RAS-GTP levels compared to\nindividual knockdowns (Supplementary Fig. 7b). This finding supports our hypothesis that multiple RTKs\nfunction cooperatively to promote RAS activation in response to exarafenib exposure in resistant cells.\n(Sup Fig. 7b) Western blot analysis of RAS activation in NCI-H2405-ER resistant cells following individual\nand combined RTK knockdown. Cells were transfected with scrambled control (siSCR), siEGFR, siAXL, or\ncombination of both and treated with exarafenib (+) or vehicle (-). Combined AXL and EGFR knockdown\ndemonstrates more pronounced reduction in RAS-GTP levels compared to individual knockdowns.\n2. Serum Dependency Analysis: We investigated MAPK signaling under varying serum conditions (low vs.\nhigh serum) in the presence of exarafenib and observed that MAPK activation in resistant cells was serum-\ndependent (Supplementary Fig. 7e, red arrows), further supporting the role of extracellular growth factor\nsignaling through RTKs in maintaining RAS-MAPK pathway activation. Notably, in parental NCI-H2405 cells,\nincreased serum concentration showed no difference from low serum conditions in maintaining MAPK activity\nunder exarafenib treatment (Supplementary Fig. 7e, blue arrows), indicating that the acquired ability to\nrespond to extracellular growth factors is a specific characteristic of the resistant cells rather than an inherent\nproperty of the parental cell line.\n(Sup Fig. 7e) Western blot analysis of serum-dependent MAPK signaling in parental NCI-H2405 and\nresistant NCI-H2405-ER cells. Cells were cultured under low (3%) or high (10%) FBS conditions and treated\nwith exarafenib (+) or vehicle (-). Resistant cells show enhanced MAPK pathway activation (p-ERK, p-RSK)\nspecifically under high serum conditions during exarafenib treatment (red arrows), while parental cells show\nconsistent drug sensitivity regardless of serum conditions (blue arrows).\nSHP2 Inhibitor Synergy: We previously demonstrated synergistic effects between SHP2 inhibitor and\nexarafenib in resistant cells (Supplementary Fig. 9b). Since SHP2 is a critical mediator of RTK-to-RAS\nsignaling, we believe this finding also provides additional mechanistic support for the RTK-RAS connection\nin the context of exarafenib-induced resistance mechanisms.\n(Sup Fig. 9b) Heatmap of synergy scores for exarafenib combined with RMC-4550 in parental and\nexarafenib-resistant NCI-H2405, NCI-H1755, and NCI-H1666 cell lines. Synergy scores were calculated\nusing the Loewe model. Positive scores indicate synergy.\nThese findings collectively suggest that exarafenib resistance involves redundant and cooperative RTK signaling\nnetworks that promote RAS activation upon drug exposure, rather than dependence on a single dominant RTK.\nThe additional mechanistic data have been incorporated into the Results section (page 14, lines 473-480 and\n494-503) .\n-preclinical synergy with MEK and ERK inhibitors is a currently active investigational strategy. resistance\nthat develops in this setting would be of interest to understand.\nWe thank the Reviewer for this important comment regarding combination therapy resistance mechanisms.\nWe generated exarafenib plus binimetinib resistant cells by sequentially adding binimetinib to established exarafenib-\nresistant NCI-H2405-ER cells with gradually escalating doses of binimetinib over three months, resulting in NCI-\nH2405-EBR (Exarafenib-Binimetinib Resistant) cells. While we also attempted to generate resistance by treating\nparental cells with both drugs simultaneously, this approach did not yield viable resistant cells for additional\nexperiments despite six months of effort, highlighting the potent efficacy of this combination therapy in vitro.\nTo characterize the molecular mechanisms underlying combination resistance, we first examined RAS activation\nstatus, given its central role in monotherapy resistance. RAS-GTP pulldown assays revealed that NCI-H2405-\nEBR cells exhibited elevated RAS-GTP levels under combination drug treatment compared to parental cells\n(Supplementary Fig. 12c), mirroring the RAS activation pattern observed in exarafenib monotherapy-resistant\ncells. This finding indicated that combination-resistant cells retain the ability to elevate RAS-GTP levels under\ndual RAF-MEK inhibition.\nBased on our concurrent findings that ARAF mediates resistance to exarafenib monotherapy through RAS-\ndependent mechanisms (detailed in Reviewer #1 response), we investigated whether this mechanism also\ncontributes to combination therapy resistance. Remarkably, ARAF knockdown dramatically restored sensitivity\nto the drug combination in NCI-H2405-EBR cells, reducing IC50 values in the presence of binimetinib plus\nexarafenib (Fig. 6f). Western blot analysis further confirmed that ARAF knockdown enhanced MAPK pathway\nsuppression under drug treatment (Supplementary Fig. 12d). These new data suggest that ARAF (or upstream\nRAS) could emerge as conserved mechanism of resistance clinically and thus selective ARAF or RAS inhibition\n(for instance with RMC-6236) could overcome multiple resistance layers and may warrant clinical investigation.\n(Sup Fig. 12c) RAS-GTP pulldown assays in NCI-H2405 parental and combination-resistant (EBR) cells.\nCells were treated with exarafenib (500 nM) in combination with binimetinib (50 nM) for 24 hours. EBR cells\nexhibit elevated RAS-GTP levels under combination drug treatment compared to parental cells. (Fig. 6f)\nHeatmap showing cell viability IC50 values (nM) for exarafenib in NCI-H2405-EBR cells treated with varying\nconcentrations of binimetinib (up to 100 nM) in combination with scrambled control (SCR) or ARAF siRNA\nknockdown. ARAF knockdown restores sensitivity to the drug combination, demonstrating ARAF's critical role\nin mediating resistance to RAF-MEK combination therapy. (Sup Fig. 12d) Western blot analysis of MAPK\npathway components in NCI-H2405-EBR cells following ARAF knockdown. Cells were transfected with\nscrambled control (SCR) or ARAF siRNA and treated with exarafenib (500 nM) and binimetinib (50 nM)\ncombination for 24 hours. ARAF knockdown enhances suppression of p-MEK, p-ERK, and p-RSK levels\nunder drug treatment.\nThese findings are particularly significant because the fact that ARAF knockdown effectively restored sensitivity\nin both monotherapy-resistant and combination-resistant models suggests that ARAF represents a common and\ncritical convergent node for resistance across different therapeutic contexts. This identifies ARAF (and upstream\nRAS) as a potential therapeutic target for overcoming resistance to RAF-based combination therapies and opens\nnew avenues for developing next-generation therapeutic strategies. These findings have been incorporated into\nthe Results section (Page 24, Line 840-864).", "reviewer_3": "In the context of exarafenib resistance, the lack of evident genetic alterations as potential mediators\ntogether with the observed exarafenib re-sensitization following a drug holiday period are all indicative\nof adaptive resistance mechanisms. Yet, the re-challenge experiments described in Figure 4c and Ext\nFig 5 are not entirely clear. The authors implemented a 48 hr drug-free period during which they claim\nthat “the resistant cell lines remain resistant -see text line 331-“ The meaning of this sentence is unclear.\nFurthermore, 4 hours post-drug exposure following the drug-free period all resistant cell lines showed\na dose-dependent inhibition of the MAPK pathway. If the cells respond to the drug re-challenge, it is\nunclear why they were considered “resistant” during the drug holiday period. In order to clarify the\nunderlying mechanisms it would be informative to perform a more detailed time-course analysis of the\nER cells when kept in the absence of drug as well as during the re-addition of exarafenib. Furthermore,\nit would be informative to carry out this exercise with concomitant measurements of cell proliferation.\nWe appreciate the Reviewer's thoughtful consideration and constructive feedback regarding exarafenib\nresistance mechanisms and experimental design. We acknowledge that our initial presentation lacked clarity\nregarding the resistance mechanism and the rationale for our experimental approach. We address these\nimportant points below.\nThe 48-hour drug-free period was implemented as a standardized experimental protocol to establish consistent\nbaseline conditions between parental and resistant cell lines while ensuring that the resistant phenotype was\nmaintained. During this period, the resistant cells retain their acquired resistance characteristics, as evidenced\nby their continued ability to proliferate at drug concentrations that would normally be inhibitory to parental cells.\nThe apparent contradiction noted by the Reviewer—where resistant cells show initial MAPK pathway inhibition\nupon drug re-challenge yet maintain resistance—reflects the complex dynamics of the resistance mechanism.\nOur time course experiments described below demonstrate that while exarafenib can still engage its target (RAF\nkinases) and transiently suppress MAPK signaling, the resistant cells have developed compensatory\nmechanisms that we have now elucidated (RAS-ARAF-KSR1 activation and dependence) that rapidly restore\npathway activation and maintain cell survival.\nTo address the Reviewer's request for more detailed mechanistic insights, we have conducted comprehensive\ntime-course analyses examining the temporal dynamics during both drug withdrawal and re-challenge periods.\nDuring drug withdrawal, MAPK pathway components (p-MEK, p-ERK, p-RSK) showed progressive elevation,\nreaching levels substantially higher than those observed during 72 hours of drug treatment (Supplementary Fig.\n6a). Upon drug re-challenge, MAPK pathway components exhibited the previously observed pattern of initial\nsuppression followed by reactivation, though the rebound levels remained moderate compared to the drug-free\nstate.\nAdditionally, as suggested by the Reviewer, we performed parallel cell proliferation analyses by cell counting\nunder the same experimental conditions during drug withdrawal and re-challenge periods (Supplementary Fig.\n6b). The results demonstrate that resistant cells maintain their proliferative capacity throughout the drug re-\nchallenge period, confirming that the transient MAPK pathway suppression does not translate to meaningful\ngrowth inhibition. This continuous proliferative capability contrasts with the drug-dependent growth phenotype\noften observed with MAPK pathway inhibitor resistance, where cells become dependent on continued drug\nexposure to prevent excessive MAPK activation and subsequent cell death. The absence of such drug\ndependence in our exarafenib-resistant cells suggests a distinct resistance mechanism that we now have\nelucidated (RAS-ARAF-KSR1) that enables cells to tolerate both drug withdrawal and re-exposure while\nmaintaining viability and proliferative capacity. The comprehensive time-course analyses during drug withdrawal\nand re-challenge, including cell proliferation data, have been incorporated into the Results section (page11, lines\n382-396) and are presented in Supplementary Fig. 6a-b.\n(Sup Fig. 6a) Time-course analysis of MAPK pathway components, DNA damage markers, and apoptosis\nmarkers in NCI-H2405-ER cells during drug withdrawal and re-challenge. Cells were initially maintained\nunder exarafenib treatment for 72 hours, then switched to drug-free medium (negative timepoints) followed\nby exarafenib re-treatment (positive timepoints). During withdrawal, MAPK pathway components show\nprogressive elevation without significant induction of DNA damage or apoptotic markers. (Sup Fig. 6b) Cell\nnumber fold change over time for exarafenib-resistant NCI-H2405-ER cells. Cells were initially grown in the\npresence of exarafenib, then subjected to drug withdrawal (white area), followed by drug re-challenge (purple\nshaded area). Data points represent relative cell number normalized to the 72h time point (set as 1-fold).\nResults demonstrate that resistant cells maintain proliferative capacity throughout both drug withdrawal and\nre-challenge periods. Data shown as mean ± SD.\nAlong these lines, does the drug holiday result in oncogenic toxicity stress/DNA damage due to MAPK\nhypersignaling? This has been observed in other MAPK driven tumours when inhibitors are eliminated.\nThe Reviewer raises an important point about potential oncogenic stress and DNA damage due to MAPK\nhypersignaling during drug withdrawal, as observed in other MAPK-driven tumors. To address this question, we\nexamined markers of DNA damage, apoptosis, and cellular stress during our comprehensive time-course\nanalysis described above (Supplementary Fig. 6a).\nDespite enhanced MAPK pathway activity during drug withdrawal, western blot analysis across withdrawal\ntimepoints (-4h, -24h, -72h) showed no significant induction of DNA damage markers (p-γH2AX and p-CHK2),\napoptosis marker (cleaved PARP), or pro-apoptotic protein (BIM). While some markers showed modest\nfluctuation (such as γ-H2AX elevation comparable to 72-hour treatment levels), these changes did not indicate\nsignificant cellular stress or death, as indicated by our cell proliferation analyses (Supplementary Fig. 6b).\nThese findings suggest that the exarafenib-resistant cells have adapted mechanisms that allow them to tolerate\nsustained and even enhanced MAPK pathway activity without experiencing the oncogenic stress typically\nassociated with MAPK hyperactivation in other contexts. These data have been added to the Results section\n(page 12, lines 398-409).\nAdaptive resistance mediated by upstream RAS/RTK signalling was demonstrated by performing either\npanRAS or KRAS knockdown. Yet, the underlying mechanisms that promote RAS activation likely differ\nacross the different ER models. SHP2, MEK, ERK or AKT inhibitors were assessed in this resistance\nsetting eventually selecting the MEK inhibitor binimetinib. The biological rationale to select this\ncombination for further characterization is sound. Furthermore, there is also clinical interest given the\nongoing clinical trial KN-8701 comparing monotherapy versus combination therapy. Yet, taking into\naccount the recent developments in the RAS inhibitor field, there is an obvious combination with\npanRAS inhibitors that should have been tested. This combination is potentially applicable across the\ndifferent ER cell models and could be clinically informative.\nWe appreciate this valuable suggestion. While we have tested several combinations including SHP2, MEK,\nERK, and AKT inhibitors, we agree that evaluating multi-RAS inhibitors would be highly relevant given recent\ndevelopments in the field. We expanded our combination studies to include an available multi-RAS inhibitor\n(RMC-6236; Jiang J et al., Cancer Discov, 2024) across our exarafenib-resistant models using full dose-response\nmatrices similar to our other combination studies (Fig. 6a and Supplementary Fig. 9a, b).\nThe multi-RAS inhibitor combination demonstrated differential anti-proliferative effects across the cell line panel.\nWhile NCI-H2405 parental cells showed limited additional benefit from the combination, both NCI-H1755 and\nNCI-H1666 parental cells, as well as all three resistant cell lines (NCI-H2405-ER, NCI-H1755-ER, and NCI-\nH1666-ER), showed effective suppression of cell proliferation when treated with the exarafenib plus RMC-6236\ncombination (Fig. 6a and Supplementary Fig. 9a). More importantly, synergy analysis revealed that the\ncombination showed enhanced synergistic interactions, particularly in the resistant cell lines compared to their\nparental counterparts (Supplementary Fig. 9b).\n(Fig. 6a) Cell viability heatmaps showing IC50 values (nM) for cell proliferation in parental and resistant cell\nlines treated with exarafenib in combination with RMC-6236. NCI-H2405, NCI-H1755, and NCI-H1666\nparental and resistant cells were treated with varying concentrations of RMC-6236 (up to 3 μM). All resistant\ncell lines show enhanced sensitivity to the combination compared to monotherapy treatment. (Sup Fig. 9a)\nCell viability heatmaps showing percentage cell viability for the same experimental conditions as Fig. 6a.\n(Sup Fig. 9b) Loewe synergy score heatmaps for the exarafenib and RMC-6236 combination dataset.\nSynergy scores range from -50 (antagonism) to +50 (synergy). The combination shows enhanced synergistic\ninteractions particularly in resistant cell lines compared to their parental counterparts, supporting the role of\nRAS activation in resistance mechanisms.\nWestern blot analysis confirmed that the exarafenib plus RMC-6236 combination resulted in stronger\nsuppression of MAPK pathway signaling in the resistant cells (Supplementary Fig. 10c), pharmacologically\nrecapitulating and extending our previously shown RAS knockdown experiments. This provides additional\nvalidation that RAS activation represents a key resistance mechanism across the different resistant models, with\nthe synergistic interaction observed across all three resistant cell lines (NCI-H2405-ER, NCI-H1755-ER, and\nNCI-H1666-ER). The RMC-6236 combination studies have been added to the Results section (page 20, lines\n708-717; page 21, lines 726-729; page 22, lines 765-767).\n(Sup Fig. 10c) Western blot analysis of MAPK pathway components and downstream targets in parental and\nresistant cell lines treated with exarafenib and RMC-6236 combination. NCI-H2405, NCI-H1755, and NCI-\nH1666 parental and resistant (-ER) cells were treated with exarafenib (500 nM), RMC-6236 (1 μM), or\ncombination of both for 48 hours. The combination treatment results in stronger suppression of MAPK\npathway signaling in resistant cells compared to monotherapy treatments.\nWhile I have no reason to doubt the outcome of the in vitro results, it is somehow surprising that RAS\nreactivation is a key resistance mediator but, yet, a naïve PDX harbouring a concomitant NRASQ61H\nmutation is clearly sensitive to exarafenib (CTG-1444 PDX in Figure 3). I wonder to what extent the\nresistance mechanisms leading to RAS reactivation identified in the various ER cells would be operative\nunder low mitogenic stimulation. The authors may want to repeat some of the in vitro drug-holiday + re-\nchallenge experiments in low serum conditions.\nWe appreciate this insightful observation regarding the relationship between RAS activation states in different\ncontexts. To address this question, we conducted additional experiments examining the role of mitogenic\nstimulation in the resistance mechanisms we identified. Following a 48-hour drug holiday, we re-treated both\nparental and resistant NCI-H2405 cells with exarafenib under different serum concentrations (3% and 10% FBS)\n(Supplementary Fig. 7e). Western blot analysis revealed that resistant cells showed enhanced MAPK pathway\nreactivation (p-ERK, p-RSK) specifically under 10% FBS conditions compared to 3% FBS (Supplementary Fig.\n7e, red arrows), while parental cells showed consistent drug sensitivity regardless of serum conditions\n(Supplementary Fig. 7e, blue arrows). Given that ARAF emerged as a critical mediator of MAPK pathway\nreactivation in our additional studies, we next examined whether ARAF mediates the serum-dependent effects\ndescribed above (Fig. 5d). Knockdown of ARAF abolished this serum-dependent MAPK pathway reactivation in\nresistant cells, with p-ERK, p-RSK, and p-MEK levels remaining equally suppressed under both serum conditions\n(Fig. 5d, red arrows).\n(Sup Fig. 7e) MAPK pathway analysis in NCI-H2405 parental and resistant cells treated with exarafenib (500\nnM) under low (3%) or high (10%) FBS conditions. Resistant cells show enhanced pathway reactivation under\nhigh serum conditions. (Fig. 5d) ARAF's role in growth factor-dependent pathway reactivation. NCI-H2405-\nER cells transfected with SCR or ARAF siRNA were treated with exarafenib (500 nM) for 24 hours under low\n(3%) or high (10%) FBS conditions. ARAF knockdown abolishes serum-dependent MAPK reactivation.\nIn our broader investigation of ARAF-mediated mechanisms, we identified ARAF-KSR1 protein interactions as\npotentially important. Building on this finding and in the context of the mitogenic signal-dependent resistance\nobserved above, we examined ARAF-KSR1 binding under drug treatment with EGF stimulation (Fig. 5f). We\nobserved that EGF stimulation further enhanced ARAF-KSR1 binding specifically in resistant cells under drug\ntreatment, providing additional evidence that elevated growth factor signaling drives the observed mechanism of\nresistance.\n(Fig. 5f) Co-immunoprecipitation analysis of ARAF protein interactions in NCI-H2405-ER cells. Cells were\ntreated with or without EGF stimulation and exarafenib (500 nM) for 24 hours. Whole cell lysate (WCL) and\nARAF immunoprecipitates (ARAF-IP) were analyzed for ARAF, BRAF, CRAF, and KSR1. EGF stimulation\nenhances ARAF-KSR1 interaction specifically under drug treatment conditions.\nThese mechanistic insights explain the apparent paradox raised by the Reviewer. While RAS activation is\nnecessary for resistance, it is not sufficient on its own in the treatment naïve setting which is what the PDX\nreflects. The key distinction lies in the adaptive rewiring that occurs during acquired resistance development.\nThe CTG-1444 PDX model harbors an endogenous NRAS Q61H mutation that provides constitutive RAS-GTP\nlevels but critically lacks the acquired adaptive changes provided by ARAF-KSR1 co-optation and bypass\nsignaling under drug pressure that are critical for resistance. In other words, this naïve system likely lacks the\nacquired ability to reactivate the MAPK pathway through mitogenic signal-induced ARAF-KSR1 complex\nformation that drives resistance in our models. This would explain why, despite elevated baseline RAS activity,\nthe CTG-1444 PDX remains exarafenib-sensitive because it lacks the sophisticated bypass machinery that\nemerges through prolonged drug exposure and selection pressure. Regarding the Reviewer's question about\nlow mitogenic stimulation, our serum titration experiments demonstrate that the resistance mechanisms we\nidentified are indeed operative and critically dependent on mitogenic signals, with ARAF serving as the key\nmediator of this serum-dependent resistance. These data have been incorporated into the Results section,\nincluding serum titration experiments (page 14, lines 494-503; page 16, lines 545-553) and growth factor\nstimulation studies (page 17, lines 587-588).\nEven more informative would be to assess the exarafenib sensitivity of a subset of these ER cells in vivo\nupon subcutaneous implantation in comparison to their parental counterparts.\nWe appreciate the Reviewer's valuable suggestion regarding the in vivo assessment of exarafenib-resistant cells.\nWe attempted to establish CDX models using the resistant cell lines on multiple occasions over a 4-month period.\nDespite systematic optimization of engraftment conditions—including varying cell injection numbers, testing\ndifferent immunocompromised mouse strains, and adjusting EGF concentrations within Matrigel—we were\nunable to successfully establish tumors from the resistant cells across four independent attempts. In contrast,\nthe parental cells consistently formed robust tumors under identical conditions. We (and other investigators)\nhave noted variable engraftment of tumors with acquired resistance to many targeted therapies in our broader\nand fairly substantial experience in studying acquired resistance in general (Okimoto RA et al., Proc Natl Acad\nSci USA, 2016).\nAs previously demonstrated, the exarafenib-resistant cells exhibit increased dependency on multiple receptor\ntyrosine kinase (RTK) signaling pathways. Furthermore, our additional experiments conducted during this\nrevision revealed that serum concentration is critical for the survival and proliferation of these resistant cells.\nAlthough this dependency is particularly evident under drug treatment conditions, the altered survival signaling\nnetworks that confer drug resistance may simultaneously compromise the cells' ability to adapt to the in vivo\nmilieu. The complex growth factor dependencies that have evolved in these resistant cells could render them\nparticularly vulnerable to the transient nutrient-limited microenvironment encountered during the initial phases of\ntumor establishment in vivo, despite their robust growth in serum-rich culture conditions.\nWhile we acknowledge that in vivo validation would strengthen our findings, the consistent failure to establish\nCDX models from resistant cells across multiple experimental approaches suggests fundamental alterations in\ntheir tumorigenic capacity that warrant further investigation in future studies.\nFollowing this rationale, it would be interesting to know how many of the 2,398 BRAF mutant NSCLC\npatients identified upon scrutiny of the GuardantINFORM repository display concomitant RAS mutations.\nWhile this combination is unlikely to exist in Class I mutants, it could be informative in the case of Class\nII and Class III patients. An extended Table reporting this information could be valuable.\nWe thank the Reviewer for this insightful suggestion. We conducted additional analysis of RAS mutations in the\nGuardantINFORM repository for BRAF-mutant NSCLC patients. For this analysis, we specifically focused on\nestablished functionally significant RAS mutations (G12, G13, and Q61 variants) to exclude variants of uncertain\nsignificance, including silent mutations and rare variants. Interestingly, contrary to our initial expectations, we\nobserved concomitant RAS mutations even in Class I patients, with higher frequencies in Class II and the highest\nrates in the upstream RAS-dependent Class III patients. Specifically, 76/845 (9.0%) Class I patients, 168/810\n(20.7%) Class II patients, and 160/743 (21.5%) Class III patients harbored RAS mutations (Supplementary Fig.\n4e). The higher co-occurrence rates in Class II and III patients are particularly noteworthy, as BRAF-RAS co-\nmutations are traditionally considered rare or mutually exclusive in other cancer types, such as colorectal cancer\nwhere they occur in <1% of cases (Midthun L et al., J Gastrointest Oncol, 2019). In NSCLC, however, several\ngenomic studies have shown that non-V600E BRAF mutations, particularly those in Class II and III, are often\naccompanied by KRAS alterations (Dagogo-Jack I et al., Clin Cancer Res, 2019; Bourhis A et al., Clin Lung\nCancer, 2020; Lin Q et al., J Transl Med, 2019), in line with our findings.\nThe substantial proportion of BRAF-mutant patients harboring concurrent RAS mutations (9-21.5% depending\non BRAF class) demonstrates that RAS co-mutations occur frequently in clinical practice. While exarafenib\ndemonstrated efficacy against individual RAS mutations in our initial studies and showed activity in the CTG-\npatients with concurrent BRAF-RAS mutations remains to be established. Future clinical studies examining\ntreatment outcomes in this subpopulation could provide valuable insights into how concurrent RAS mutations\ninfluence therapeutic response in BRAF-mutant patients. The analysis of RAS co-mutation frequencies across\nBRAF mutation classes has been added to the Results section (page 10, lines 332-343) and is presented in\nSupplementary Figure 4e.\n(Sup Fig. 4e) Frequency of concomitant RAS mutations in BRAF-mutant NSCLC patients from the\nGuardantINFORM™ database. Table shows the number and percentage of patients harboring KRAS, HRAS,\nor NRAS mutations across BRAF Class I (n=845), Class II (n=810), and Class III (n=743) mutations.\nIn summary, we sincerely thank all Reviewers for the thoughtful comments and hope that the expanded,\nimproved revised manuscript is now suitable for publication in Nature Communications.", "reviewer_1_attached": "The authors have convincingly addressed al my requests providing appropriate reasoning and discussion. The only\nexception was the inability to carry out my suggestion to perform in vivo experiments with patient derived material. Yet, I\nunderstand that, as explained by the authors, that failure to establish CDX models from resistant cells is a frequent\nexperimental outcome."}, "author_response": "We sincerely thank all three Reviewers for their thoughtful and constructive feedback on our manuscript. We\ndeeply appreciate the time and expertise they have invested in evaluating our work. Their insightful comments\nhave helped us strengthen our manuscript and better articulate the significant novel contributions of our study.\nIn response to the Reviewers' valuable suggestions, we have conducted additional experiments, expanded our\nanalyses, and clarified our presentation of the data. These revisions include comprehensive mechanistic studies\nrevealing an unanticipated new mechanistic twist: an interesting ARAF-KSR1 signaling axis that emerged as a\nnovel axis regulating pan-RAF inhibitor efficacy/resistance; serum dependency analyses that elucidate the\nmechanistic role of mitogenic signals in resistance pathway reactivation; an expanded clinical analysis from the\nGuardantINFORM™ database; Each of these new experiments and findings was prompted by the Reviewers’\ninsightful comments.\nGiven the substantial nature of these new mechanistic discoveries, particularly the identification of the RAS-\nARAF-KSR1 signaling axis as a previously unrecognized resistance mechanism, we have revised the manuscript\ntitle to \"Targeting BRAF Class II and III Mutations in NSCLC with the pan-RAF inhibitor Exarafenib Reveals\nARAF-KSR1-Mediated Resistance and Rational Combination Strategies\" to more accurately reflect these major\nfindings.\nWe believe these revisions have substantially improved the manuscript and address the comments raised by\nthe Reviewers. We hope that the improved, revised manuscript is now suitable for publication in Nature\nCommunications.\nBelow, we provide detailed responses to each Reviewer's comments."}]

Decision letter