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The BRAF inhibitor vemurafenib activates mitochondrial metabolism and inhibits hyperpolarized pyruvate-lactate exchange in BRAF mutant human melanoma cells Teresa Delgado-Goni1, Maria Falck Miniotis1, Slawomir Wantuch1, Harold G. Parkes1, Richard Marais2, Paul Workman3, Martin O. Leach1 and Mounia Beloueche-Babari1 1 Cancer Research UK Cancer Imaging Centre, The Institute of Cancer Research, London, United Kingdom 2 Cancer Research UK Manchester Institute, Manchester, United Kingdom 3 Cancer Research UK Cancer Therapeutics Unit, The Institute of Cancer Research, London, United Kingdom Correspondence: Dr Mounia Beloueche-Babari and Prof. Martin O. Leach Cancer Research UK Cancer Imaging Centre, The Institute of Cancer Research, London, 15 Cotswold Road, Sutton Surrey SM2 5NG, United Kingdom. Phone: +44 208 661 3728, +44 208 661 3338; Fax: +44 208 661 0846 (e-mail: [email protected], [email protected] ) Running title: Metabolic rewiring in melanoma following BRAF inhibition Keywords: BRAF inhibition, melanoma, response biomarkers, metabolism, NMR spectroscopy. Financial support: T. Delgado-Goni and S. Wantuch are supported by MRC project grant (MR/K011057/1), H.G. Parkes, M. O. Leach and M. Beloueche-Babari are supported by a CRUK Centre for Cancer Imaging grant C1090/A16464. P. Workman is supported by CRUK programme grant (C309/A11566). M. Falck Miniotis was funded by an EPSRC Platform grant EP/H046526/1. We also acknowledge grant C1060/A10334 from CRUK and EPSRC Cancer Imaging Centre in association 1 with the MRC and Department of Health (England). P. Workman is a Cancer Research UK Life Fellow (C309/A8992). M.O. Leach is a NIHR Biomedicine Research Senior Investigator. Conflict of interest: The authors declare that there are no conflicts of interest. Number of figures: 5, number of tables: 6, word count: 5202 (excluding References and Figure Legends). 2 Abstract Understanding the impact of BRAF signaling inhibition in human melanoma on key disease mechanisms is important for developing biomarkers of therapeutic response and combination strategies to improve long term disease control. This work investigates the downstream metabolic consequences of BRAF inhibition with vemurafenib, the molecular and biochemical processes that underpin them, their significance for antineoplastic activity and potential as non-invasive imaging response biomarkers.1H NMR spectroscopy showed that vemurafenib decreases the glycolytic activity of BRAF mutant (WM266.4 and SKMEL28) but not BRAFWT (CHL-1 and D04) human melanoma cells. In WM266.4 cells, this was associated with increased acetate, glycine and myo-inositol levels and decreased fatty acyl signals, while the bioenergetic status was maintained. 13 C NMR metabolic flux analysis of treated WM266.4 cells revealed inhibition of de novo lactate synthesis and glucose utilization, associated with increased oxidative and anaplerotic pyruvate carboxylase mitochondrial metabolism and decreased lipid synthesis. This metabolic shift was associated with depletion of hexokinase 2, acyl-CoA dehydrogenase 9, 3phosphoglycerate dehydrogenase and monocarboxylate transporter (MCT) 1 and 4 in BRAF mutant but not BRAFWT cells and, interestingly, decreased BRAF mutant cell dependency on glucose and glutamine for growth. Further, the reduction in MCT1 expression observed led to inhibition of hyperpolarized 13 C-pyruvate-lactate exchange, a parameter that is translatable to in vivo imaging studies, in live WM266.4 cells. In conclusion, our data provide new insights into the molecular and metabolic consequences of BRAF inhibition in BRAF-driven human melanoma cells that may have potential for combinatorial therapeutic targeting as well as non-invasive imaging of response. 3 Introduction The RAS-RAF-MEK-ERK is one of the most important signaling cascades in cancer (1). Growth factor receptor stimulation activates RAS leading to recruitment of RAF kinases (ARAF, BRAF and CRAF) which in turn activate MEK1/2, ERK1/2 and a range of target proteins, including transcription factors regulating proliferation, differentiation, survival and invasion. Aberrant ERK1/2 signaling occurs in many cancers through mutation or overexpression of components of the pathway (2). For example, activating mutations in BRAF, most often involving the V600E substitution, lead to malignant transformation and occur in about half of all cases of malignant melanoma (3). The importance of ERK1/2 signaling in driving melanoma has prompted interest in blocking this pathway for mechanism-based therapy, with several BRAF and MEK inhibitors now approved for the treatment of BRAF-driven melanoma (e.g. the BRAF inhibitors vemurafenib and debrafenib, and the MEK inhibitor trametinib (1)) and many more undergoing clinical testing. These drugs have shown remarkable activity in BRAF mutant melanoma patients (4, 5) but responses are invariably short-lived with tumor relapse observed within few months of treatment initiation (6). This is due to mechanisms such as re-activation of ERK1/2 signaling (e.g. via mutation in MEK, overexpression of COT) or activation of ERK1/2-independent signaling pathways (e.g. through receptor tyrosine kinase overexpression) (7-9), an understanding that has informed combination therapeutic strategies targeting the compensatory oncogenic activity (10) that are now being 4 evaluated. Understanding the consequences of treatment with BRAF and MEK inhibitors on fundamental cellular processes will enable the identification of additional combinatorial treatment options to refine the use of these drugs and achieve better disease control in the clinic. Cancer cells exhibit altered metabolism relative to normal tissues, characterized by increased dependency on aerobic glycolysis, fatty acid and nucleotide synthesis and glutaminolysis (11). This ‘metabolic transformation’ is considered an enabling hallmark for cancer maintenance and progression that is tightly linked to oncogenic signaling, and as such is being pursued as a promising therapeutic strategy (12). In the context of BRAF-MEK-ERK signaling, mutant BRAF stimulates glycolytic activity and inhibits oxidative phosphorylation (13). We and others have also shown that inhibitors of MEK and BRAF reverse this metabolic phenotype by attenuating the glycolytic activity of BRAF mutant human melanoma cells (14, 15) and reactivating mitochondrial oxidative phosphorylation (OxPhos) (16) linked to reduced expression of hexokinase 2 (HK2) and glucose transporters 1 and 3, following the downregulation of CMYC (14) and HIF1 alpha (15) downstream of the ERK1/2 pathway. Indeed, reduced uptake of the radioactive glucose analogue 2 [18F]fluoro-2deoxy-D-glucose (FDG), as monitored by positron emission tomography (PET) in pre-clinical models as well as BRAF-driven melanoma patients, has proved to be very useful for monitoring response to BRAF/MEK targeted drugs (17) but relatively nonspecific. The re-programming of glucose metabolism following BRAF/MEK inhibition could be considered as an adaptive response necessary to mitigate drug-induced 5 metabolic stress (13). How such alterations are brought about in terms of glycolytic pathway flux changes, their significance for cell survival and potential as metabolic imaging biomarkers of drug action, besides the previously described and relatively non-specific FDG-PET uptake (18), remains largely unclear. This work is centered on the metabolic aspects of BRAF mutant melanoma cell response to BRAF inhibition with vemurafenib. Our aims are to characterize the metabolic and molecular response of BRAF mutant melanoma to BRAF inhibitors and investigate the potential of the changes induced by treatment as non-invasive imaging biomarkers of response. Accordingly, we investigate the effects of the BRAF inhibitor vemurafenib on cellular metabolism as well as glycolytic pathway fluxes in BRAF mutant human melanoma cells using NMR spectroscopy, a technique that enables the steady state as well as dynamic study of metabolism in cells and whole tissues both in vitro and in vivo (19). We show that vemurafenib decreases glycolytic activity and reactivates TCA cycle metabolism by increasing oxidative and anaplerotic flux through pyruvate decarboxylase (PC) reducing cell dependency on glucose and glutamine metabolism. We also show that vemurafenib depletes monocarboxylate transporter 1 (MCT1) protein expression resulting in decreased hyperpolarized 13 C-pyruvate-lactate exchange, thus providing support for investigating this process as a new biomarker for non-invasive monitoring of BRAF signaling inhibitor action. 6 Materials and Methods Cell lines and Reagents The following human melanoma cell lines were used and acquired at the American Tissue Type Collection: WM266.4 (BRAFV600D/RASWT), SKMEL28 (BRAFV600E/RASWT, STR profiled in house (LGC Standards, UK) on the 16th October 2015) and CHL-1 (BRAFWT/RASWT). D04 (BRAFWT/RASQ61L) cells were a kind gift from Dr. Amine Sadok (Cancer Biology Division, The Institute of Cancer Research, London) and were tested by STR profiling on the 13th June 2014. Vemurafenib and 13 C-glucose were purchased from Chemietek (Indianapolis, USA) and Sigma-Aldrich (Gillingham, UK), respectively. Cell culture and treatments Cells were grown as monolayers and routinely cultured as previously described (14). For steady state metabolic investigations, the following vemurafenib concentrations were used with WM266.4 cells: 0.5x, 1.25x, 2.5x and 5xGI50 (0.2, 0.5, 1 and 2µM respectively). CHL-1 cells were treated with 0.02x, 0.05x, 0.1x, 0.2, 1x, 2.5x and 5xGI50 (0.2, 0.5, 1, 2, 9, 22.5 and 45µM) vemurafenib, while SKMEL28 and D04 cells were treated with an equimolar concentration of 2µM (under these conditions ERK signaling was effectively inhibited in SKMEL28 (BRAFV600E) but not in D04 (BRAFWT) cells). Cell counts and viability were monitored with trypan blue staining using Vi-CELL™ Cell Viability Analyzer (Beckman Coulter). For 13C-glucose flux analyses, WM266.4 cells were incubated in media containing 5mM [1-13C]glucose, as this is physiologically relevant and provided similar results 7 to the standard medium used in the 1H NMR experiments (25mM glucose, Figure S1). Either 0.01% DMSO or 5xGI50 vemurafenib (2µM) was added for 24h. For nutrient deprivation experiments, cells were seeded in four different media conditions: 5mM glucose, 1mM glucose, 1mM glucose without glutamine, 1mM glucose without glutamine and pyruvate (48h before treatment) and were then exposed to either 0.01% DMSO or 2µM vemurafenib for 24h,48h or 72h in the presence of these media. NMR metabolic analyses of cells Control and vemurafenib-treated WM266.4 cells were extracted with a methanolchloroform-water method as previously described (20). The aqueous fraction was reconstituted in D2O using 3-(trimethylsilyl) propionic-2,2,3,3-d4 acid and methylenediphosphonic acid as 1H and 31 P NMR standards respectively. Lipid fractions were re-suspended after chloroform evaporation in a d-chloroform solution with tetramethylsilane as reference. Further details on this section are provided in the supplementary material. Hyperpolarized 13C-pyruvate-lactate exchange experiments 13 C-pyruvate-lactate exchange was monitored in intact WM266.4 human melanoma cells (~8.5x106 cells/sample) following exposure to DMSO or vemurafenib for 24h as previously described (21). Dynamic 13C spectra were acquired every 2s for 4 minutes immediately after the addition of 10mM hyperpolarised [1-13C]pyruvic acid and 10mM unlabeled lactate in a total volume of 500µl. For data analysis, the ratio of the area under the curve for the summed lactate and pyruvate signals 8 (LactateAUC/PyruvateAUC) from the dynamic spectra was determined to estimate pyruvate-lactate exchange (21). NMR data acquisition and processing NMR data were acquired on a Bruker Avance III 500MHz NMR spectrometer (Bruker Biospin, Ettlingen, Germany). Spectra were processed using MestRe-C version 4.9.9.6 (University of Santiago de Compostela, Spain) and metabolite content was measured by peak integration relative internal standards and corrected for cell number per sample. Further details on acquisition parameters are provided in the supplementary material. Multivariate analysis of NMR spectroscopy data 1 H NMR data from WM266.4 cells were subjected to unbiased metabolic profiling using partial least squares discriminant analysis (PLS-DA), a method performed after principal component analysis (PCA) to sharpen the separation between groups of observations, determining the variables carrying the class separation information. For this, spectra were processed as previously described (22) and data analyzed in SIMCA v13.0 (Umetrics-Umeå, Sweden) using a PLS-DA model. Western blotting Target protein expression and phosphorylation levels following BRAF inhibition were assessed by western blotting using standard conditions as previously described (23). Antibody information is provided in the Supplementary section. Quantitative real-time PCR (qRT-PCR) 9 Total RNA was extracted using the RNAeasy kit (Qiagen; Crawley, West Sussex, UK) and 1µg was reverse transcribed using the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems; Carlsbad, California, USA). Samples were diluted 1:10 and 1μl used in the Taqman assay, using Taqman universal master mix. Primer information is provided in Supplementary section. Pyruvate carboxylase activity 2x106 cells were lyzed in Ripa buffer (Cell Signaling Technology, Hertfordshire, UK) containing PhosSTOP Phosphatase Inhibitor Cocktail Tablets (Roche, Hertfordshire, UK) and cOmplete ULTRA Tablets (Roche, Hertfordshire, UK), and processed as previously described (24). A spectrophotometric reading in kinetic mode at 412nm was taken for 10 minutes at 30°C (Ultrospec 2100pro, GE Healthcare Life Sciences, Buckinghamshire, UK) and data normalized for protein content. Cell cycle analysis Flow cytometry was performed to analyze the effect of drug on cell cycle distributions as previously described (20). Statistical analysis For metabolite analysis, Student t-test with Sidak-Bonferroni correction for multiple comparisons (P≤0.05) was applied. mRNA levels, cell number and PC activity were analyzed using a single comparison two-tailed unpaired Student’s t test with P≤0.05 considered significant. Results are expressed as mean±standard deviation (SD). 10 Results Vemurafenib alters the metabolic profile of BRAF mutant human melanoma cells Treatment with vemurafnib (2µM, 24h) led to inhibition of BRAF signaling, as evidenced by the reduced phosphorylation of ERK1/2 and MEK, in BRAFV600D WM266.4 and BRAFV600E SKMEL28 but not in BRAFWT CHL-1 and D04 human melanoma cells. These effects were concomitant with a decrease in extracellular lactate (LactateE) levels exclusively in BRAF mutant cells (Figure 1A), consistent with previous reports (13, 14). The vemurafenib-induced reduction in LactateE was concentration-dependent in WM266.4 cells being observed with as little as 0.2µM (Figure 1B). In contrast, BRAFWT CHL-1 cells showed no significant changes in LactateE even with exposure to concentrations of vemurafenib up to 45µM (Figure 1B). After confirming that vemurafenib induces a significant reduction in LactateE in BRAF mutant cells, comparable to that previously reported using MEK inhibitors (14), we next assessed the effect of BRAF inhibition on additional metabolic processes by investigating the changes in cellular metabolic profiles induced by vemurafenib in WM266.4 cells. As shown in Figure 1C, PLS-DA unbiased multivariate analysis of the 1H NMR spectral data from the aqueous phase of WM266.4 melanoma cell extracts indicated separate clustering of control and vemrafenib-treated (2µM, 24h) cell data, consistent with a shift in metabolic 11 phenotype. The score scatter plot indicated that 40.1% of total data was explained by two main principal components (PCs) in the model (PC1: 13.5%, PC2: 26.6%). The high R2 and Q2 values (90.1 and 66.7 % respectively) indicated that the classification has good reproducibility and predictivity. The resonances with the highest contribution to the classification model are shown in Figure 1C and include branchedchain amino acids (BCAAs) (0.91-1.06 ppm), lactate (1.33 and 4.12 ppm), acetate (1.92 ppm), creatine (Cr) + phosphocreatine (PCr) (3.03 ppm), glycine (3.56 ppm) and myo-inositol (4.07 ppm). The individual 1H NMR resonances in the control and treated spectra were manually integrated and included in a univariate analysis to corroborate significant metabolic differences identified in the PLS-DA. Table 1 shows data from the main metabolites analyzed, with a significant increase in glycine and myo-inositol, and a significant decrease in lactate and acetate in vemurafenib-treated compared to control cells. The effect sizes described are in the range of relevant findings described in previous publications using this methodology (14). 31 P NMR analysis revealed no significant differences in the levels of measured 31P- containing metabolites, including NTP and PCr, between control and vemurafenibtreated samples (Supplementary Figure S2). Furthermore, vemurafenib treatment in WM266.4 cells had no significant effect on the ADP/ATP ratio assessed using a bioluminescence assay (Figure S2). Thus, WM266.4 cells are able to maintain their bioenergetic status during BRAF inhibition despite reduced glycolytic metabolism. 1 H NMR analysis of the lipid phase obtained from the same cell extracts, showed that BRAF inhibition with vemurafenib was associated with a decrease in the fatty 12 acyl chain signal at 0.9 ppm (-CH3) (% change within the range of previous studies on tumor lipids (25, 26)), whilst the remaining signals were mostly unchanged (Figure 1D). Taken together, our data suggest that vemurafenib reduces glycolytic activity and alters glycine, myo-inositol, acetate and lipid metabolism without compromising cellular bioenergetics. Vemurafenib induces differential glucose utilization in BRAF mutant melanoma cells favoring anaplerotic mitochondrial metabolism via pyruvate carboxylase We next investigated the alterations in glucose metabolic pathway activity that could underpin the observed metabolic changes. BRAF inhibitor treatment has previously been shown to reactivate mitochondrial OxPhos leading to increased reactive oxygen species (ROS) levels (13). We thus assessed ROS in WM266.4 cells following exposure to vemurafenib and found that, consistent with a previous report (16), BRAF inhibition in BRAFV600D WM266.4 cells for 24h led to a concentrationdependent increase in ROS production (up to 197.8±62.8% of controls (P=0.03), indicating that OxPhos may also be increased in our cells (Figure S3). Next, and to further explore the effect of vemurafenib on metabolic fluxes and investigate if the ROS changes are related to altered mitochondrial activity, we monitored the fate of [1-13C]glucose in BRAFV600D WM266.4 human melanoma cells and growth media using 13C NMR (Figure 2A). Analysis of culture media following a 24h incubation revealed a reduction in [3-13C]lactateE levels in vemurafenib-treated cells relative to controls (down to 62.9±13.1%; P=0.01), consistent with reduced de novo lactate production being responsible for the fall in steady state lactateE. A trend towards decreased glucose consumption was also observed but did not reach 13 statistical significance (59.5±30.1%; P=0.07). Analysis of intracellular 13 C-labeled metabolites also showed a reduction in [3-13C]lactate (to 51.9±16.3%, P=0.003) concomitant with a significant increase in [1-13C]glucose (up to 245.8±21.9%, P=0.03), and myo-inositol (up to 561.8±250.1% P=0.01) in vemurafenib-treated relative to control BRAFV600D WM266.4 cells, indicating decreased glycolysis and glucose utilization after internalization and increased routing towards myo-inositol production (Figure 2C). The relative contribution of the oxidative (pyruvate dehydrogenase (PDH)) versus anaplerotic (pyruvate carboxylase (PC)) glucose metabolism was assessed using the resonances of 13 C-labeled glutamate and glutamine (labeled in carbons 2, 3 and 4) (Figure 2B). Our data showed that the [4-13C]glutamate signal was always far greater than that from [2-13C] and [3-13C]glutamate, in keeping with PDH flux being the primary route for pyruvate entry into the TCA cycle in melanoma cells (27). [413 C]glutamate levels were not altered with treatment (103.3±12.5% of controls, P=0.6) despite the significant reduction in pathway (following intracellular 13 13 C-label incorporation in the glycolytic C-glucose accumulation), suggesting a relative increase in PDH flux. In addition, a significant elevation in [2-13C] and [313 C]glutamate (to 190.5±39.7% and 160.9±41.4% of controls, respectively, P<0.05), [2-13C]glutamine (134.2±13.5, P=0.01) and [2-13C] aspartate (351.2±206.4) was also observed, indicating increased PC flux. The [2-13C]/[4-13C] glutamate ratio rose from 0.13±0.03 to 0.25±0.06 (P=0.01), consistent with an increase in the PC/PDH flux in vemurafenib-treated compared to control WM266.4 cells (Figure 2B and 2C). To investigate the metabolic basis for the 13 C NMR findings, we performed an independent analysis of PC enzyme activity. This showed a significant increase 14 (159±67 %, P=0.04) in treated samples relative to controls (Figure 2D), providing independent confirmation of the increase in PC flux following vemurafenib treatment. Analysis of the 13 C-labeled lipid phase of treated cells revealed a decrease in the fatty acyl chain signal (-CH3 and –CH2 at 14.15 and 29.7 ppm respectively, Figure 2E) after 24h of treatment (70±18 % and 72±19% of controls, respectively, P=0.05), in agreement with the 1H NMR data, indicating reduced glucose routing towards lipid biosynthesis following vemurafenib treatment. In summary, the 13 C flux analysis indicates that vemurafenib treatment leads to decreased glucose utilization coupled with diversion towards myo-inositol and TCA cycle metabolism (particularly via PC flux) at the expense of lactate and lipid synthesis. BRAF inhibition reprograms the expression of key glucose metabolic enzymes To investigate the molecular mechanisms underlying the metabolic shift observed with vemurafenib in BRAF mutant WM266.4 human melanoma cells, we assessed the expression of key enzymes in the glycose metabolism pathway, initially using qRTPCR. Our data showed a significant decrease in the mRNA expression of HK2 (14.7±2% of controls), in line with our previous findings with MEK inhibition (14). Further, we observed a reduction in the mRNA level of LDH-A (to 18.5±6.5%), PDK-1 (28.9±6.6% respect to control), 3-PHGDH (to 46±2.4%) and GCAT (to 62.1±12.3%) in treated relative to controls. The mRNA expression of PSAT-1, GLDC, PC, IDH-1, GLS and ISYNA-1 remained unchanged (Figure 3A). 15 Protein expression changes in genes that showed a significant difference in mRNA abundance were next assessed by western blotting in the same cell line (BRAFV600D WM266.4, Figure 3B) and in three additional human melanoma cell lines: BRAFV600E SKMEL28 cells, BRAFWT D04 and BRAFWT CHL-1 cells, Figure 3C). Our data show that both BRAF mutant cell lines (but not BRAFWTcells) exhibited a decrease in HK2 and 3-PHGDH protein levels, in agreement with qRT-PCR. However, the decrease in LDH-A expression was not as pronounced as observed with qRT-PCR, probably due to a longer protein half-life. We additionally probed for monocarboxylate transporter (MCT) 1 and 4 and, interestingly, observed depletion of both proteins in vemurafenib-treated compared to control in BRAF mutant WM266.4 and SKMEL28 cells but not BRAFWT D04 or CHL-1 cells, suggesting inhibition of lactate transport in BRAF mutant cells (28). Given the observed changes in lipid metabolism, we further assessed the levels of ACAD9 (fatty acid breakdown), ACC and P-ACL (lipid synthesis). Our data showed that vemurafenib treatment was associated with a reduction in ACAD9 and P-ACL levels in both BRAF mutant WM266.4 and SKMEL28 cell lines but not in BRAFWT CHL-1 and D04 cells, while no consistent trends were observed with ACC expression following exposure to vemurafenib (Figure 3B- C). Overall, these data show that BRAF inhibition produces a metabolic enzyme expression profile suggestive of inhibition of glycolysis, lactate transport, glycine synthesis/breakdown as well as lipid synthesis and catabolism. The vemurafenib-induced metabolic shift confers a growth advantage to BRAF mutant human melanoma cells under nutrient-deprived conditions 16 Next, and to evaluate the biological significance of the metabolic shift observed following exposure to vemurafenib, and examine cell dependency on the various metabolic routes, we assessed the growth of BRAFV600E SKMEL28 and BRAFV600D WM266.4 melanoma cells under different nutrient-restricted conditions in the presence or absence of vemurafenib for 24h (WM266.4 cells), 48h (WM266.4 and SKMEL28 cells) and 72h (WM266.4 cells). The conditions were: control (5mM glucose), low glucose (1mM glucose), low glucose with glutamine deprivation (1mM glucose/no glutamine) and low glucose with glutamine and pyruvate deprivation (1mM glucose/no glutamine/no pyruvate). These conditions tested the dependence of cells on glycolysis, glutamine and TCA metabolism, respectively. Cell numbers for both BRAF mutant cell lines relative to the seeding density are represented in Figure S4. As shown in Figure 4A-B, both control and treated samples exhibited significant reduction in cell counts when grown in low glucose (1mM) media relative to control conditions (5mM glucose) and even a greater fall when glutamine was removed after 24h (WM266.4 cells) and 48h (WM266.4 and SKEML28) of treatment. Importantly, however, the effect of nutrient deprivation was less dramatic in vemurafenib-treated cells indicating that vemurafenib reduces the dependency of these cells on glucose and glutamine. There was no evidence for overt apoptosis (as indicated by the absence of cleaved PARP, Figure S4) following cell exposure to the nutrient-limited media with and without vemurafenib, indicating that the differences in cell counts observed here are related to growth rather than cell kill. These results were corroborated for WM266.4 cells after 72h of treatment (Figure 4A), confirming the growth advantage with vemurafenib under low glucose/no glutamine conditions. When pyruvate was removed in addition to glutamine under 17 low glucose, higher cell counts were also observed in vemurafenib-treated WM266.4 compared to control cells at 24h, but this was abolished with prolonged exposure (48h) for both melanoma cell lines, consistent with the dependency of vemurafenibtreated cells on mitochondrial metabolism, with PC flux requiring pyruvate availability (29). The increased cell counts in treated relative to control WM266.4 cells under glucose and glutamine deprivation at 48h was abolished by co-addition of phenylacetic acid (PAA), an inhibitor of PC (30) that led to 35.8±16.4% reduction in PC activity (30), (Figure 4C), confirming the involvement of anaplerotic PC metabolism in the growth advantage conferred by vemurafenib. Interestingly, the effect of nutrient deprivation on cell cycle profiles, characterized in WM266.4 cells, was different in control and vemurafenib-treated cells. Under control conditions (5mM glucose), treated cells showed a G1 phase arrest, as expected (P=0.042) (31). Sequential removal of nutrient from control cells lead to a G1 arrest coupled with a gradual decrease in the S phase population (Figure 4D) relative to complete media conditions (5 mM glucose). In contrast, BRAF inhibitor-treated cells (already G1 arrested at baseline) showed a gradual increase in the G2 phase with sequential nutrient removal (Figure 4D, Figure S5), consistent with inhibition of the G2/M cell cycle checkpoint. Taken together, these data suggest that vemurafenib reduces BRAF mutant cell dependency on glucose (by downregulating glycolytic metabolism) and glutamine (by increasing PC anaplerotic flux), and imposes a G2/M cell cycle block under nutrient deprivation. 18 Vemurafenib treatment leads to reduced pyruvate-lactate exchange detectable in live BRAF mutant human melanoma cells using hyperpolarised 13C NMR spectroscopy BRAF signaling inhibition with vemurafenib in BRAF mutant WM266.4 and SKMEL28 cells led to depletion of MCT1, a transmembrane protein that mediates the bi-directional movement of monocarboxylic acids such as lactate and pyruvate (28). We thus hypothesized that this effect should translate to a fall in hyperpolarized 13Cpyruvate-lactate exchange that can be detectable by 13C NMR spectroscopy and which could have potential as a new non-invasive biomarker of BRAF inhibition. This hypothesis was tested in live WM266.4 cells following 24h treatment with 2µM vemurafenib. As expected based on MCT1 depletion after treatment, our data showed a significant decrease in the ratio of 13C-LactateAUC/13C-PyruvateAUC in vemurafenibtreated compared to control cells (to 64.3±10.2%, P=0.008), consistent with a fall in the 13C label exchange between pyruvate and lactate (21) (Figure 5A-C). In contrast, in BRAFWT D04 cells, where MCT1 expression remained unchanged with vemurafenib treatment, there were no significant changes in hyperpolarized 13 C- pyruvate-lactate exchange (Figure 5D). Thus, 13 C-pyruvate-lactate exchange could serve as a non-invasive imaging biomarker for monitoring the downstream metabolic effects of vemurafenib in BRAF mutant human melanoma cells. Discussion 19 BRAF and MEK inhibitors have shown unprecedented clinical responses in BRAF mutant malignant melanoma (4, 5); however, the emergence of drug resistance remains inevitable. This stresses the need for a better understanding of the consequences of BRAF inhibition on key disease mechanisms in melanoma cells in order to develop biomarkers of response as well as combination strategies that will improve long term disease control. We and others have shown that inhibition of BRAF-MEK-ERK signaling in BRAF mutant melanoma models activates mitochondrial metabolism and decreases lactate production through inhibition of HK2 and glucose transporter expression downstream of CMYC and HIF1-alpha (14-16, 32). In this study we sought to characterize the downstream alterations in metabolic pathways and fluxes triggered by BRAF inhibition and evaluate their significance for drug anti-proliferative activity and potential as non-invasive biomarkers of response to treatment. As expected, vemurafenib treatment in BRAFV600D WM266.4 human melanoma cells led to a significant fall in LactateE that was concentration-dependent, and also recorded in an additional BRAF mutant melanoma cell line (SKMEL28) but not in BRAFWT CHL-1 or D04 human melanoma cells. Our previous work with a MEK inhibitor indicates that this effect is only present in mutant BRAF-driven cancer cells, being absent in mutant BRAF-expressing, but independent, cells and in nontransformed cells (14). NMR metabolic profiling of WM266.4 cells indicated that, in addition to reduced lactate levels, vemurafenib treatment was associated with decreased acetate, increased glycine and myo-inositol and a significant reduction in the fatty acyl chain content 20 (0.9 ppm). The bioenergetic status of treated cells, as assessed by 31P NMR analysis of cellular NTP and PCr levels and bioluminescence-measured ATP/ADP, remained unaffected. These findings indicate that, in addition to downregulation of glycolytic metabolism, BRAF inhibition alters glycine, myo-inositol and lipid metabolism inducing a metabolic shift that is able to maintain cellular energetic status probably by means of activating compensatory pathways, for example, OxPhos (16). Indeed we observed increased ROS production (to a similar extent as in previous publications (33)) following treatment with vemurafenib, indicating that the drug may also be activating OxPhos in our model, in agreement with earlier findings (16, 34). Next, and to better understand the downstream alterations in metabolic flux involved in the vemurafenib-induced metabolic re-programming, we evaluated cellular glycolytic flux with a widely reported method (35, 36), using a glucose analogue. 13 13 C-labeled C NMR confirmed inhibition of de novo lactate formation and glucose utilization, as revealed by the fall in intracellular and extracellular [313 C]lactate and accumulation in intracellular [1-13C]glucose in vemurafenib-treated compared to control cells, indicating decreased glucose utilization. Taking into account the decreased 13 C label incorporated downstream of the glycolytic pathway, our data show a relative increase in the labelling of glutamate at position 4 (PDH flux) in treated relative to control cells. Furthermore, we observed an increase in [2-13C] and [3-13C]glutamate as well as the ratio of [2-13C]/[4-13C]glutamate in treated versus control cells, indicating increased mitochondrial metabolism via anaplerotic PC flux following exposure to vemurafenib. This metabolic shift was concomitant with 21 significantly increased PC enzymatic activity (with a magnitude in the range of other reports in the literature (37)) under BRAF inhibition. It is noteworthy that the steady-state metabolite levels measured by 1H NMR in WM266.4 cells (Table 1) are maintained following vemurafenib treatment. These metabolites represent total levels present in the cell, which are governed by many reactions and pathways (e.g. uptake from media, protein breakdown) as well as the net change between de novo synthesis and breakdown/utilization. In contrast, the metabolites detectable by 13 C NMR are derived from de novo synthesis from 13 C- glucose, which may not necessarily lead to changes in the total 1H NMR-measured metabolite pool. Further, and despite the fall in glucose consumption and glycolytic activity, WM266.4 cells were able to maintain their energetic status, consistent with more efficient metabolism of glucose through the TCA cycle. Molecular analysis of metabolic enzyme expression indicated that the most significant alterations observed with vemurafenib were, in addition to the previously reported decrease in HK2 expression (14, 15), a decrease in MCT1, MCT4 (involved in glycolytic and lactate metabolism), 3-PHGDH3 (serine-glycine metabolism), ACAD9 (fatty acid -oxidation) and P-ACL (lipid biosynthesis). Although PC mRNA levels remained unchanged with BRAF inhibitor treatment, we cannot rule out changes in PC protein expression (resulting from post-transcriptional regulation) or allosteric regulation as potential contributing factors to the elevated PC activity, as previously described (38). The 13 C flux and molecular findings provide key insights into the mechanisms underlying the changes observed in steady state metabolites (Table 1). Our results are consistent with a model (summarized in Figure 5E) in which the increase in myo22 inositol observed by both 1H and 13C NMR suggests increased de novo synthesis from glucose following the reduction in HK2 flux. Further, the significant decrease in 13Clactate and rise in 13 C-labeled aspartate and glutamine/glutamate and 13 C position labelling patterns observed indicate diversion of glucose from glycolysis to TCA cycle metabolism (primarily via PC, but also PDH flux). Under these conditions, acetyl-CoA utilization would be accelerated leading to reduced acetate pool observed by 1H NMR. The tracing of glycine synthesis was not possible with [1,13C]glucose, however it is unlikely that its accumulation in vemurafenib-treated cells is due to increased de novo synthesis from serine, as metabolic precursors derived from glycolysis (including the first intermediate in serine-glycine synthesis 3phosphoglycerate) are reduced by treatment. Accordingly, the build-up in glycine is more likely due to inhibition of its breakdown, which would be consistent with the decrease in GCAT mRNA expression (39). The upregulation of mitochondrial PC flux is of interest since melanoma cells are known to have a functional TCA cycle but with negligible PC anaplerotic metabolism (40). Activation of PC flux in glioblastoma and non-small-cell lung cancer cells has previously been linked to reduced dependency on glutamine (35, 37). Indeed we observed that vemurafenib reduces BRAF mutant cell dependency on glucose and glutamine but commits them to consume pyruvate, that becomes essential under BRAF inhibition, as previously described for cells dependent on upregulated PC flux (29). The growth advantage conferred by vemurafenib under nutrient-depleted conditions was abolished with pharmacologic inhibition of PC activity, consistent with PC involvement in this effect. 23 The fact that treated cells grow better in nutrient-restricted media, which are relevant to tumor growth conditions in vivo, may facilitate the emergence of drugresistant clones in vivo that can lead to tumor relapse under treatment (41, 42). Such differences could determine whether vemurafenib has a growth inhibitory effect in a tumor or not, which is clearly of huge clinical importance. Thus, targeting this metabolic adaptation in combination with BRAF signaling may offer a promising strategy for counteracting drug-induced growth advantage. In fact, inhibiting OxPhos with metformin (43) and mitochondrial respiration inhibitors (44) has already been shown to potentiate the therapeutic efficacy of BRAF inhibitors in human melanoma models. With regard to our findings, inhibition of PC in glutamine-independent glioblastoma models was able to inhibit tumor growth, demonstrating the importance of this metabolic route for cell survival (28). However, it remains to be established whether such effects would be applicable in melanoma tumor models, and whether PC blockade using selective pharmacologic or genetic approaches can enhance the potency of BRAF-targeted therapies in vivo. Finally, vemurafenib depletes MCT1, a bidirectional transporter for monocarboxylic acids such as lactate and pyruvate, resulting in reduced hyperpolarised 13 C-pyruvate-lactate exchange in live BRAFV600D WM266.4 human melanoma cells but not BRAFWT D04 cells. These experiments are translatable to in vivo imaging studies (45) and provide proof-of-principle for developing 13C-pyruvatelactate exchange as a non-invasive metabolic imaging biomarker of the molecular consequences of BRAF signaling inhibition. Hyperpolarized 13 C-pyruvate-lactate exchange has been shown to occur at a very low rate in normal compared to cancer tissues (46) and given the results obtained with BRAFWT D04 cells, we anticipate that this assay will be most useful for monitoring therapeutic response to BRAF inhibition 24 in BRAF mutant melanoma. Future work will aim to assess the translatability of our findings to in vivo tumor models. Dynamic imaging of metabolic processes using hyperpolarized recently entered the clinic with 13 C NMR has 13 C-pyruvate-lactate exchange measurements being the first to be reported in prostate cancer patients, and many more studies are ongoing to assess the value of this approach for cancer imaging (47). This technique can be combined with multiparametric magnetic resonance imaging of the tumor microenvironment (e.g. cellularity, vascularity, pH) and complemented with FDGPET to provide information on different steps of the glucose metabolic pathway. The availability of several response biomarkers can be valuable in applying the Pharmacological Audit Trail to drug development pre-clinically and in patients as in the case of vemurafenib (48), providing a more robust means for assessing drug effects in patients with a greater degree of confidence (49), allowing better evaluation of the downstream metabolic consequences of BRAF signaling inhibition in cancer and more effective monitoring of therapeutic response (48, 49). In conclusion, we show that BRAF inhibition with vemurafenib in BRAF mutant human melanoma cells alters glucose utilization leading to inhibition of lipid synthesis (and breakdown) and activation of oxidative and anaplerotic mitochondrial metabolism with consequences that confer a growth advantage under nutrientdeprived conditions. We also show that BRAF inhibition in BRAF mutant cells leads to depletion of MCT1 and inhibition of hyperpolarized 13C-pyruvate-lactate exchange, providing support and rationale for exploring this metabolic process as a potential non-invasive metabolic imaging biomarker of therapeutic response to BRAF signaling-targeted drugs. 25 26 REFERENCES 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. Roberts PJ, Der CJ. Targeting the Raf-MEK-ERK mitogen-activated protein kinase cascade for the treatment of cancer. Oncogene. 2007;26:3291-310. Santarpia L, Lippman SM, El-Naggar AK. Targeting the MAPK-RAS-RAF signaling pathway in cancer therapy. Expert Opin Ther Targets. 2012;16:10319. Davies H, Bignell GR, Cox C, Stephens P, Edkins S, Clegg S, et al. Mutations of the BRAF gene in human cancer. Nature. 2002;417:949-54. Chapman PB, Hauschild A, Robert C, Haanen JB, Ascierto P, Larkin J, et al. Improved survival with vemurafenib in melanoma with BRAF V600E mutation. NEngl J Med. 2011;364:2507-16. Sosman JA, Kim KB, Schuchter L, Gonzalez R, Pavlick AC, Weber JS, et al. Survival in BRAF V600-mutant advanced melanoma treated with vemurafenib. NEngl J Med. 2012;366:707-14. Flaherty KT, Puzanov I, Kim KB, Ribas A, McArthur GA, Sosman JA, et al. Inhibition of mutated, activated BRAF in metastatic melanoma. NEngl J Med. 2010;363:809-19. Nazarian R, Shi H, Wang Q, Kong X, Koya RC, Lee H, et al. Melanomas acquire resistance to B-RAF(V600E) inhibition by RTK or N-RAS upregulation. Nature. 2010;468:973-7. Poulikakos PI, Persaud Y, Janakiraman M, Kong X, Ng C, Moriceau G, et al. RAF inhibitor resistance is mediated by dimerization of aberrantly spliced BRAF(V600E). Nature. 2011;480:387-90. Villanueva J, Vultur A, Lee JT, Somasundaram R, Fukunaga-Kalabis M, Cipolla AK, et al. Acquired resistance to BRAF inhibitors mediated by a RAF kinase switch in melanoma can be overcome by cotargeting MEK and IGF1R/PI3K. Cancer Cell. 2010;18:683-95. Kwong LN, Davies MA. Targeted therapy for melanoma: rational combinatorial approaches. Oncogene. 2014;33:1-9. Ward PS, Thompson CB. Metabolic reprogramming: a cancer hallmark even warburg did not anticipate. Cancer Cell. 2012;21:297-308. Vander Heiden MG. Targeting cancer metabolism: a therapeutic window opens. Nat Rev Drug Discov. 2011;10:671-84. Haq R, Shoag J, Andreu-Perez P, Yokoyama S, Edelman H, Rowe GC, et al. Oncogenic BRAF regulates oxidative metabolism via PGC1alpha and MITF. Cancer Cell. 2013;23:302-15. Falck Miniotis M, Arunan V, Eykyn TR, Marais R, Workman P, Leach MO, et al. MEK1/2 inhibition decreases lactate in BRAF-driven human Cancer Cells. Cancer Res. 2013;73:4039-49. Parmenter TJ, Kleinschmidt M, Kinross KM, Bond ST, Li J, Kaadige MR, et al. Response of BRAF-mutant melanoma to BRAF inhibition is mediated by a network of transcriptional regulators of glycolysis. Cancer Discov. 2014;4:423-33. Corazao-Rozas P, Guerreschi P, Jendoubi M, Andre F, Jonneaux A, Scalbert C, et al. Mitochondrial oxidative stress is the Achille's heel of melanoma cells resistant to Braf-mutant inhibitor. Oncotarget. 2013;4:1986-98. McArthur GA, Puzanov I, Amaravadi R, Ribas A, Chapman P, Kim KB, et al. Marked, homogeneous, and early [18F]fluorodeoxyglucose-positron emission tomography responses to vemurafenib in BRAF-mutant advanced melanoma. 27 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. Journal of clinical oncology : official journal of the American Society of Clinical Oncol. 2012;30:1628-34. Beloueche-Babari M, Workman P, Leach MO. Exploiting tumor metabolism for non-invasive imaging of the therapeutic activity of molecularly targeted anticancer agents. Cell Cycle. 2011;10:2883-93. Yang C, Harrison C, Jin ES, Chuang DT, Sherry AD, Malloy CR, et al. Simultaneous steady-state and dynamic 13C NMR can differentiate alternative routes of pyruvate metabolism in living Cancer Cells. J Biol Chem. 2014;289:6212-24. Beloueche-Babari M, Jackson LE, Al-Saffar NM, Workman P, Leach MO, Ronen SM. Magnetic resonance spectroscopy monitoring of mitogen-activated protein kinase signaling inhibition. Cancer Res. 2005;65:3356-63. Hill DK, Orton MR, Mariotti E, Boult JK, Panek R, Jafar M, et al. Model free approach to kinetic analysis of real-time hyperpolarized 13C magnetic resonance spectroscopy data. PloS One. 2013;8:e71996. Beloueche-Babari M, Box C, Arunan V, Parkes HG, Valenti M, De Haven Brandon A, et al. Acquired resistance to EGFR tyrosine kinase inhibitors alters the metabolism of human head and neck squamous carcinoma cells and xenograft tumours. Brit J Cancer. 2015;112:1206-14. Chung YL, Troy H, Kristeleit R, Aherne W, Jackson LE, Atadja P, et al. Noninvasive magnetic resonance spectroscopic pharmacodynamic markers of a novel histone deacetylase inhibitor, LAQ824, in human colon carcinoma cells and xenografts. Neoplasia. 2008;10:303-13. Izquierdo-Garcia JL, Cai LM, Chaumeil MM, Eriksson P, Robinson AE, Pieper RO, et al. Glioma cells with the IDH1 mutation modulate metabolic fractional flux through pyruvate carboxylase. PloS One. 2014;9:e108289. Delikatny EJ, Chawla S, Leung DJ, Poptani H. MR-visible lipids and the tumor microenvironment. NMR Biomed. 2011;24:592-611. Williams KJ, Argus JP, Zhu Y, Wilks MQ, Marbois BN, York AG, et al. An essential requirement for the SCAP/SREBP signaling axis to protect Cancer Cells from lipotoxicity. Cancer Res. 2013;73:2850-62. Kaplon J, Zheng L, Meissl K, Chaneton B, Selivanov VA, Mackay G, et al. A key role for mitochondrial gatekeeper pyruvate dehydrogenase in oncogeneinduced senescence. Nature. 2013;498:109-12. Halestrap AP. Monocarboxylic acid transport. Compr Physiol. 2013;3:161143. Cardaci S, Zheng L, MacKay G, van den Broek NJ, MacKenzie ED, Nixon C, et al. Pyruvate carboxylation enables growth of SDH-deficient cells by supporting aspartate biosynthesis. Nature Cell Biol. 2015;17:1317-26. Lee JH, Jung IR, Choi SE, Lee SM, Lee SJ, Han SJ, et al. Toxicity generated through inhibition of pyruvate carboxylase and carnitine palmitoyl transferase1 is similar to high glucose/palmitate-induced glucolipotoxicity in INS-1 beta cells. Mol Cell Endocrinol. 2014;383:48-59. Haferkamp S, Borst A, Adam C, Becker TM, Motschenbacher S, Windhovel S, et al. Vemurafenib induces senescence features in melanoma cells. The J Invest Dermatol. 2013;133:1601-9. Haq R, Fisher DE, Widlund HR. Molecular pathways: BRAF induces bioenergetic adaptation by attenuating oxidative phosphorylation. Clin Cancer Res. 2014;20:2257-63. Kluza J, Corazao-Rozas P, Touil Y, Jendoubi M, Maire C, Guerreschi P, et al. Inactivation of the HIF-1alpha/PDK3 signaling axis drives melanoma toward 28 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. 47. 48. 49. 50. mitochondrial oxidative metabolism and potentiates the therapeutic activity of pro-oxidants. Cancer Res. 2012;72:5035-47. Vazquez F, Lim JH, Chim H, Bhalla K, Girnun G, Pierce K, et al. PGC1alpha expression defines a subset of human melanoma tumors with increased mitochondrial capacity and resistance to oxidative stress. Cancer Cell. 2013;23:287-301. Cheng T, Sudderth J, Yang C, Mullen AR, Jin ES, Mates JM, et al. Pyruvate carboxylase is required for glutamine-independent growth of tumor cells. Proc Natl Acad Sci USA. 2011;108:8674-9. Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, et al. Glucoseindependent glutamine metabolism via TCA cycling for proliferation and survival in B cells. Cell Metabolism. 2012;15:110-21. Sellers K, Fox MP, Bousamra M, 2nd, Slone SP, Higashi RM, Miller DM, et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J Clin Invest. 2015;125:687-98. Jitrapakdee S, Wallace JC. Structure, function and regulation of pyruvate carboxylase. Biochem J. 1999;340 ( Pt 1):1-16. Locasale JW. Serine, glycine and one-carbon units: cancer metabolism in full circle. Nat Rev Cancer. 2013;13:572-83. Scott DA, Richardson AD, Filipp FV, Knutzen CA, Chiang GG, Ronai ZA, et al. Comparative metabolic flux profiling of melanoma cell lines: beyond the Warburg effect. J Biol Chem. 2011;286:42626-34. Reid MA, Kong M. Dealing with hunger: Metabolic stress responses in tumors. J Carcinogen. 2013;12:17. Zhang X, de Milito A, Olofsson MH, Gullbo J, D'Arcy P, Linder S. Targeting Mitochondrial Function to Treat Quiescent Tumor Cells in Solid Tumors. Int. J. Mol. Sci. 2015;16:27313-26. Niehr F, von Euw E, Attar N, Guo D, Matsunaga D, Sazegar H, et al. Combination therapy with vemurafenib (PLX4032/RG7204) and metformin in melanoma cell lines with distinct driver mutations. J Trans Med. 2011;9:76. Roesch A, Vultur A, Bogeski I, Wang H, Zimmermann KM, Speicher D, et al. Overcoming intrinsic multidrug resistance in melanoma by blocking the mitochondrial respiratory chain of slow-cycling JARID1B(high) cells. Cancer Cell. 2013;23:811-25. Day SE, Kettunen MI, Gallagher FA, Hu DE, Lerche M, Wolber J, et al. Detecting tumor response to treatment using hyperpolarized 13C magnetic resonance imaging and spectroscopy. Nature Med. 2007;13:1382-7. Albers MJ, Bok R, Chen AP, Cunningham CH, Zierhut ML, Zhang VY, et al. Hyperpolarized 13C lactate, pyruvate, and alanine: noninvasive biomarkers for prostate cancer detection and grading. Cancer Res. 2008;68:8607-15. Nelson SJ, Kurhanewicz J, Vigneron DB, Larson PE, Harzstark AL, Ferrone M, et al. Metabolic imaging of patients with prostate cancer using hyperpolarized [1-(1)(3)C]pyruvate. Sci Trans Med. 2013;5:198ra08. Bollag G, Hirth P, Tsai J, Zhang J, Ibrahim PN, Cho H, et al. Clinical efficacy of a RAF inhibitor needs broad target blockade in BRAF-mutant melanoma. Nature. 2010;467:596-9. Yap TA, Sandhu SK, Workman P, de Bono JS. Envisioning the future of early anticancer drug development. Nature Rev Cancer. 2010;10:514-23. Gottschalk M, Ivanova G, Collins DM, Eustace A, O'Connor R, Brougham DF. Metabolomic studies of human lung carcinoma cell lines using in vitro 29 (1)H NMR of whole cells and cellular extracts. NMR Biomed. 2008;21:80919. 30 TABLES TABLE 1: 1H MRS detectable metabolites in the aqueous phase of control and treated WM66.4 cell extracts (au/ cell number and volume). For comparison of metabolites, Student t-test with Sidak-Bonferroni correction for multiple comparisons (P≤0.05) was applied. Data represent the mean ± SD. * Significant results (P≤0.05) are marked in bold. Cell metabolites Control Vemurafenib 2µM P* BCAA 5.90 ± 1.95 7.23 ± 2.09 0.24 Lactate 6 ± 1.66 3.53 ± 1.55 0.02 Alanine 0.96 ± 0.26 1.06 ± 0.14 0.48 Acetate 1.28 ± 0.48 0.70 ± 0.34 0.04 Glutamate 4.73 ± 1.76 4.58 ± 0.98 0.85 Glutamine 2.78 ± 1.02 2.84 ± 0.67 0.91 Aspartate 0.13 ± 0.08 0.19 ± 0.13 0.26 Creatine 3.5 ± 1.13 4.55 ± 0.73 0.07 Choline 0.67 ± 0.24 0.81 ± 0.23 0.28 Phosphocholine 10.73 ± 3.07 11.00 ± 1.53 0.84 Glycerophosphocholine 1.55 ± 0.73 1.55 ± 0.65 1.00 Taurine 2.35 ± 1.54 2.87 ± 1.73 0.56 Glycine 0.44 ± 0.35 1.27 ± 0.59 0.02 Myo-Inositol 0.23 ± 0.12 0.58 ± 0.29 0.02 Fumarate 0.02 ± 0.01 0.02 ± 0.01 0.40 Formate 0.08 ± 0.01 0.08 ± 0.02 0.62 NADH 0.06 ± 0.03 0.08 ± 0.03 0.32 31 FIGURE LEGENDS Figure 1: metabolic effects of BRAF inhibition with vemurafenib in human melanoma cells: NMR analysis of LactateE levels in the media of BRAF mutant and wild-type cell lines and unbiased metabolomic profiling of treated WM266.4 cells. A) 1H NMR analysis of extracellular lactate (LactateE) changes observed in BRAFV600E SKMEL28, BRAFWT /RASWT CHL-1 and BRAFWT/NRASQ61L D04 human melanoma cells exposed to vemurafenib (2 µM, 24h), * P<0.05. B) LactateE detected in BRAFV600D cells (WM266.4) using different vemurafenib concentrations for 24h. C) Three–dimensional PCA score scatter plot showing separate clustering for 1 H NMR data from WM266.4 control and treated cells (2 µM vemurafenib, 24h). Bottom panel represents score contribution plot with corresponding changes in the 1H NMR peaks (and related metabolites) accounting for the differences between control and treated samples (plot obtained using the Group to Group comparison option in SIMCA). Positive scores represent increased levels while negative scores indicate decreased levels in control relative to treated cells. D) Principle lipid resonances (related to fatty acyl components shown in Figure S6) analysed in 1H NMR spectra of chloroform extracts in control and treated WM266.4 cells. The protons contributing to these resonances are shown in bold (assignments as in (50)) *P≤0.01. Abbreviations: BCAA: branched-chain amino acids, Ch: cholesterol, Cho: choline, Cr: creatine, Gln: glutamine, Glut: glutamate, GPC: glycerophosphocholine, GPE: glycerophosphoethanolamine, Gly: glycine, Glx: glutathione, L: lipids, Myo-Ins: myo-inositol, PCr: phosphocreatine, PC: phosphocholine, phosphatidylcholine, PtdEtn: phosphatidylethanolamine, Tau: taurine. 32 PtdCho: Figure 2: Vemurafenib induced-alterations in 13C-glucose metabolic flux in BRAF mutant human melanoma cells. A) Schematic diagram of [1,13C]glucose metabolism showing the label distribution (black circles) in glycolytic and TCA intermediates via PDH and PC fluxes. Grey circles indicate positions of the 13C-label due to equilibration of oxaloacetate with fumarate. B) Representative 13 C NMR spectra from the aqueous phase of a WM266.4 cell extract and the magnification of the signals corresponding to [2-13C], [3-13C] and [4-13C]glutamate (Glu C2, Glu C3 and Glu C4) showing the decreased [3-13C]lactate and increased 13 [2-13C], [3- C]glutamate signals in treated relative to control samples. C) Summary of the 13 C NMR metabolite analysis showing decreased lactate and concomitant increase in glucose, glutamate and glutamine. Dotted line indicates control metabolite levels (100%) and error bars in the data reflect the variance, mostly due to the small size of some peaks in the 13 C NMR spectra. D) PC assay summary showing increased activity with vemurafenib treatment (2 µM, 24h) in WM266.4 cells. E) Representative 13C-NMR spectra from the lipid phase of a WM266.4 cell extract and the magnification of the signals corresponding to the fatty acyl chain signals (-CH3 and –CH2 at 14.15 and 29.7 ppm respectively) showing the differences between control and treated samples. Figure 3: Molecular changes induced by vemurafenib in BRAF mutant human melanoma cells. A) mRNA expression of genes involved in different metabolic pathways (glycolysis, TCA cycle, glycine, glutamine and myo-inositol metabolism) detected by qRT-PCR in WM266.4 cells. * P < 0.05. ** P < 0.01, *** P < 0.001. B) Molecular biomarkers of response detected at protein level in BRAFV600D WM266.4 cells treated with different concentrations of vemurafenib, showing a decrease in HK2, LDH-A, 3PHGDH, ACAD9, MCT1 and MCT4 expression. Reduced ERK and 33 MEK phosphorylation confirm target inhibition under our experimental conditions. C) The molecular biomarkers of response detected in WM266.4 cells are also observed in BRAF V600E SKMEL28 but not in BRAFWT CHL-1 and D04 human melanoma cells. Figure 4: Cell growth and cell cycle distributions in control and vemurafenibtreated BRAF mutant WM266.4 cells under nutrient-deprived conditions. WM266.4 (A) and SKMEL-28 (B) viable cell number after 24 (n=4) or 48h (n=7 and n=4 respectively) of treatment (DMSO or vemurafenib) under different nutrient depleted media. The number of viable cells in both DMSO and vemurafenib samples decreases significantly in all the nutrient restricted conditions in comparison to the physiological condition (5 mM glucose) but vemurafenib treated cells survive significantly better in 1mM glucose medium and 1mM glucose medium without glutamine after 48h. Treated cells show a significant reduction in viability after 48h under pyruvate deprivation. Data are normalized using the appropriate 5mM control in each case: control 5mM for control samples and vemurafenib 5mM for treated samples. C) On the left, PC inhibition in WM266.4 cells under 20 mM PAA. On the right, percent cell number change in vemurafenib-treated cells growing in 1 mM gluose media without glutamine, with (right bar) and without PAA (left bar). Data are normalized relative to the 5 mM condition for either control or treated cells) D) Control cells (top, n=4) suffer a significant arrest in G1 phase under nutrient-deprived conditions with a decrease in the number of cells in S phase in comparison to physiological conditions. Vemurafenib-treated cells (bottom, n=4) are arrested in G1 as a consequence of the treatment and experience a significant increase in G2 phase with 1mM glucose medium containing either no glutamine or no glutamine and no 34 pyruvate. Gln, glutamine; Pyr, pyruvate. ; * P < 0.05, ** P < 0.01 and *** P ≤ 0.001 using Student’s t-test. Figure 5: Metabolic response to BRAF inhibition detected non-invasively in live BRAFV600D WM266.4 and BRAFWT D04 cells using hyperpolarized 13C NMR. A) Time-course curves showing 13C-lactate and 13C-pyruvate signal intensities during the experiment (5 min) following addition of hyperpolarized 13C-pyruvate to control and 2 µM vemurafenib-treated live BRAFV600D WM266.4 cells. B) Representative 13 C spectra showing the decreased in the summed lactate signal following exposure to vemurafenib. C) 13 vemurafenib-treated C-lactate production (LactateAUC/PyruvateAUC) in control and BRAFV600D live cells. D) 13 C-lactate production (LactateAUC/PyruvateAUC) in control and vemurafenib-treated BRAFWT live cells. Lactate signal intensity is represented relative to the maximum intensity of 13Cpyruvate in each sample. ** P < 0.01. E) Schematic representation of a working model of the main vemurafenib-induced metabolic changes in BRAF mutant melanoma based on our steady state and metabolic flux data. Vemurafenib decreases glycolysis and activates mitochondrial metabolism (PC and PDH flux) leading reduced dependency on glycose and glutamine which enables growth in nutrientrestricted conditions. Moreover, vemurafenib depletes MCT1 and MCT4, leading to reduced pyruvate and lactate transport and hyperpolarized (HP) exchange. 35 13 C-pyruvate-lactate