Download The BRAF inhibitor vemurafenib activates mitochondrial metabolism

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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. Parkes, 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
Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs
Road, Sutton, Surrey SM2
5PT, 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
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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).
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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 HKII, acyl-CoA dehydrogenase 9, 3-phosphoglycerate
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.
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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
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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 HKII 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-2-deoxy-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 non-specific.
The re-programming of glucose metabolism following BRAF/MEK inhibition
could be considered as an adaptive response necessary to mitigate drug-induced
metabolic stress (13). How such alterations are brought about in terms of glycolytic
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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.
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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 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
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.
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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
(LactateAUC/PyruvateAUC) from the dynamic spectra was determined to estimate
pyruvate-lactate exchange (21).
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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)
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
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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).
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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
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
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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
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).
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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
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%,
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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
(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.
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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 HKII
(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-PGDH (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).
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
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that both BRAF mutant cell lines (but not BRAFWTcells) exhibited a decrease in HKII
and 3-PGDH 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
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
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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
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
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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.
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Vemurafenib treatment leads to reduced pyruvate-lactate exchange detectable in
live BRAF mutant human melanoma cells using hyperpolarised
13
C 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
BRAF and MEK inhibitors have shown unprecedented clinical responses in BRAF
mutant malignant melanoma (4, 5); however, the emergence of drug resistance
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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 HKII 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
(0.9 ppm). The bioenergetic status of treated cells, as assessed by
31
P NMR analysis
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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
significantly increased PC enzymatic activity (with a magnitude in the range of other
reports in the literature (37)) under BRAF inhibition.
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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 HKII expression (14, 15), a decrease in MCT1, MCT4 (involved in
glycolytic and lactate metabolism), 3-PHGDH3 (serine-glycine metabolism), ACAD9
(fatty acid β-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 myoinositol observed by both 1H and 13C NMR suggests increased de novo synthesis from
glucose following the reduction in HKII flux. Further, the significant decrease in 13C22
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lactate 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.
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
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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
in BRAF mutant melanoma. Future work will aim to assess the translatability of our
findings to in vivo tumor models.
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Dynamic imaging of metabolic processes using hyperpolarized
recently entered the clinic with
13
13
C NMR has
C-pyruvate-lactate exchange measurements being
the first to be reported in prostate cancer patients, and many more 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 FDG-PET 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.
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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
GPCho
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
30
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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,
PtdCho:
phosphatidylcholine, PtdEtn: phosphatidylethanolamine, Tau: taurine.
31
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Figure 2: Vemurafenib induced-alterations in
13
C-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. Below, the representative
13
C-
labeled signals of glutamate in control and treated samples are shown. B)
Representative 13C 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 [413
C]glutamate (Glu C2, Glu C3 and Glu C4) showing the decreased [3-13C]lactate and
increased [2-13C], [3-13C]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 13C NMR spectra. D) PC assay summary
showing increased activity with vemurafenib treatment (2 µM, 24h) in WM266.4
cells. E) Representative
13
C-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
32
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HKII, LDH-A, 3PGDH, ACAD9, MCT1 and MCT4 expression. Reduced ERK and
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) PC inhibition in WM266.4 cells under 20 mM PAA (left) and % cell
number change in vemurafenib-treated cells growing in 1 mM gluose no glutamine
media with and without PAA (right). 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 pyruvate. Gln,
33
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glutamine; Pyr, pyruvate. ; * P < 0.05, ** P < 0.01 and *** P ≤ 0.001 using Student’s ttest.
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 (top panel). Summary of
13
C-lactate production (LactateAUC/PyruvateAUC) measured 5 minutes after the
addition of hyperpolarized 13C-pyruvate to live WM266.4 cells treated with DMSO or
vemurafenib for 24h. Lactate signal intensity is represented relative to the maximum
intensity of
13
C-pyruvate in each sample. ** P < 0.01.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. 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 nutrient-restricted conditions. Moreover,
vemurafenib depletes MCT1 and MCT4, leading to reduced pyruvate and lactate
transport and hyperpolarized (HP) 13C-pyruvate-lactate exchange.
34
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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-Goni, Maria Falck Miniotis, Slawomir Wantuch, et al.
Mol Cancer Ther Published OnlineFirst October 7, 2016.
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