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The anti-rheumatic drug, leflunomide, synergizes with MEK inhibition to suppress melanoma growth

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Cutaneous melanoma, which develops from the pigment producing cells called melanocytes, is the most deadly form of skin cancer. Unlike the majority of other cancers, the incidence rates of melanoma are still on the rise and the treatment options currently available are being hindered by resistance, limited response rates and adverse toxicity. We have previously shown that an FDA approved drug leflunomide, used for rheumatoid arthritis (RA), also holds potential therapeutic value in treating melanoma especially if used in combination with the mutant BRAF inhibitor, vemurafenib. We have further characterized the function of leflunomide and show that the drug reduces the number of viable cells in both wild-type and BRAFV600E mutant melanoma cell lines. Further experiments have revealed leflunomide reduces cell proliferation and causes cells to arrest in G1 of the cell cycle. Cell death assays show leflunomide causes apoptosis at treatment concentrations of 25 and 50 μM. To determine if leflunomide could be used combinatorialy with other anti-melanoma drugs, it was tested in combination with the MEK inhibitor, selumetinib. This combination showed a synergistic effect in the cell lines tested. This drug combination led to an enhanced decrease in tumor size when tested in vivo compared to either drug alone, demonstrating its potential as a novel combinatorial therapy for melanoma.
Leflunomide reduces the cell viability of melanoma cell lines. (A) Leflunomide causes a dose-dependent decrease in cell viability in eight human melanoma cell lines. BRAF WT cell lines; M202 (blue), M285 (red), M375 (green) and M296 (purple). BRAF V600E mutant cell lines; A375 (orange), M229 (grey), SKmel28 (khaki) and SKmel5 (black). Cell viability was determined by using CellTiter-Glo reagent and all values are represented as a percentage (%) relative to the vehicle control. Data is presented as the mean ± SEM of three independent experiments each performed with cell culture triplicates. (B) Leflunomide reduces cell viability at a similar rate in BRAF WT (wtBRAF) melanoma cells and BRAF V600E mutant (mBRAF) cell lines. The data from the four wildtype cell lines was averaged (black). The same was done for the four BRAF V600E mutant lines (red). Cell viability was determined by using CellTiter-Glo reagent and all values are represented as a percentage (%) relative to the vehicle control. Data is presented as the mean ± SEM of twelve independent experiments each performed with cell culture triplicates. (C) Leflunomide causes a dose-dependent decrease in cell viability in melanocytes, HEK293 and RD1 cells. Melanocytes (black), HEK293 cells (red) and RD1 cells (blue). Cell viability was determined using CellTiter-Glo reagent and all values are represented as a percentage (%) relative to the vehicle control. Data is presented as the mean ± SEM of three independent experiments each performed with cell culture triplicates.
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Leflunomide causes a G1 cell cycle arrest in A375 melanoma cells and induces apoptosis. (A) Leflunomide inhibits cell proliferation in A375 cells. Percentage of BrdU positive A375 cells after 72 hours treatment with leflunomide. Data is presented as the mean ± SEM of the three independent experiments each performed with cell culture triplicates. Asterisks indicate the degree of statistical difference determined by one-way ANOVA with Turkey's post-hoc test. * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001 and **** P ≤ 0.0001. (B) Representative DNA histogram plots of the cell cycle analysis performed in A375 cells treated for 72 hours with leflunomide. (Bi) shows DMSO treated cells. (Bii), (Biii) and (Biv) show cells treated with 25, 50 and 100 μM leflunomide respectively. (C) Leflunomide causes a G1 cell cycle arrest in A375 melanoma cells and induces apoptosis. Cell cycle phase distribution for A375 cells treated for 72 hours with leflunomide. Data is presented as the mean ± SEM of three independent experiments each performed with cell culture triplicates. Asterisks indicate the degree of statistical difference comparing DMSO control to the varying concentrations of Leflunomide using student's t-tests. * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001 and **** P ≤ 0.0001. (D) Representative pseudo plots of cell death analysis determined by flow cytometry. A375 cells were treated with DMSO, 25, 50 and 100 μM leflunomide for 72 hours and stained with annexin V and PI. The numbers indicate the percentage of cells present in each quadrant. (E) Graph quantifying the percentage of A375 cells that are viable, early apoptotic, late apoptotic and necrotic after 72 hours of treatment with leflunomide. Data is presented as the mean ± SEM of three independent experiments each performed with cell culture triplicate. Asterisks indicate the degree of statistical difference comparing each leflunomide condition to the DMSO control determined by two-way ANOVA with Turkey's post-hoc test. * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001 and **** P ≤ 0.0001.
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Oncotarget1
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The anti-rheumatic drug, leunomide, synergizes with MEK inhibition
to suppress melanoma growth
Kimberley Hanson1, Stephen R. Robinson1, Karamallah Al-Yousuf2,3, Adam E.
Hendry1, Darren W. Sexton4,5, Victoria Sherwood2,3 and Grant N. Wheeler1
1School of Biological Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK
2School of Pharmacy, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK
3Present address: Division of Cancer Sciences, School of Medicine, Ninewells Hospital and Medical School, University of
Dundee, Dundee, DD1 9SY, UK
4Norwich Medical School, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK
5Present address: Pharmacy and Biomedical Sciences, Liverpool John Moores University, Liverpool, L3 3AF
Correspondence to: Grant N. Wheeler, email: grant.wheeler@uea.ac.uk
Victoria Sherwood, email: v.sherwood@dundee.ac.uk
Keywords: melanoma; leunomide; selumetinib; MEK inhibitors; combinatorial therapy
Received: May 27, 2017 Accepted: November 26, 2017 Published: December 17, 2017
Copyright: Hanson et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License
3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and
source are credited.
ABSTRACT
Cutaneous melanoma, which develops from the pigment producing cells called
melanocytes, is the most deadly form of skin cancer. Unlike the majority of other
cancers, the incidence rates of melanoma are still on the rise and the treatment options
currently available are being hindered by resistance, limited response rates and adverse
toxicity. We have previously shown that an FDA approved drug leunomide, used for
rheumatoid arthritis (RA), also holds potential therapeutic value in treating melanoma
especially if used in combination with the mutant BRAF inhibitor, vemurafenib. We
have further characterized the function of leunomide and show that the drug reduces
the number of viable cells in both wild-type and BRAF
V600E
mutant melanoma cell lines.
Further experiments have revealed leunomide reduces cell proliferation and causes
cells to arrest in G1 of the cell cycle. Cell death assays show leunomide causes
apoptosis at treatment concentrations of 25 and 50 µM. To determine if leunomide
could be used combinatorialy with other anti-melanoma drugs, it was tested in
combination with the MEK inhibitor, selumetinib. This combination showed a synergistic
effect in the cell lines tested. This drug combination led to an enhanced decrease in
tumour size when tested in vivo compared to either drug alone, demonstrating its
potential as a novel combinatorial therapy for melanoma.
www.impactjournals.com/oncotarget/ Oncotarget, Advance Publications 2017
INTRODUCTION
Melanoma is the most deadly form of skin cancer,
causing the majority of skin cancer deaths despite only
accounting for 5% of reported skin cancer cases (Skin
Cancer Foundation, 2017; [1]) and unlike most other
cancers, incidence rates are still on the rise. The cause of
melanoma is a combination of exogenous (environmental)
and endogenous (genetic) factors [2]. If detected early
cutaneous melanomas are easily curable through resection,
as unlike many other cancers, they are externally visible
and it is only once they have metastasized in later
stages that the disease becomes difcult to treat (Skin
Cancer Foundation, 2017). Until recently treatment for
metastatic melanoma was limited. However, in recent
years, a number of new therapies have been developed
that provide a better prognosis for patients. These include
immunotherapies, in particular immune checkpoint
inhibitors such as ipilimumab, pembrolizumab and
nivolumab that show remarkable clinical responses in
some melanoma patients [3–5]. These therapies however
are not without their drawbacks, including immune-related
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adverse events, limited response rates and possibly also
therapy-induced acquired resistance, where modications
to improve the clinical application of these treatments are
currently ongoing [6].
Another class of drugs that has been revolutionizing
the way in which patients with advanced melanoma
are treated is targeted therapies that block oncogenic
driver mutations. In particular, targeted therapies that
block components of the pro-proliferative mitogen-
activated protein kinase (MAPK) pathway such as
BRAF (vemurafenib/dabrafenib) and MEK (trametinib/
selumetinib). Indeed selective RAF inhibitors have
demonstrated clear survival benet in oncogenic BRAF
(predominantly the BRAF
V600
mutation)-driven melanomas
(approximately 50% of patients; [7–10]) and results in
near-complete abrogation of MAPK signaling in tumors
harboring such mutations [11].
The effects of these MAPK treatments are however
only transient due to the emergence of a variety of drug
resistance mechanisms [12, 13–16] and as a result,
metastatic melanoma patients receiving these treatments
as monotherapies eventually succumb to their disease.
Hence, resistance to such treatments is currently a key
issue researchers within the melanoma eld are faced with
and it is now evident that monotherapy is not the answer.
Combinatorial therapy targeting multiple signalling
pathways or components within the same pathway is
where future strategies lie to try and delay or override
tumor resistance, and so provide stronger, more durable
responses for patients. A number of drug combinations are
currently being investigated in clinical trials with some
proving hopeful. Such combinations include combined
immunotherapies, BRAF inhibitors in combination with
immunotherapies and BRAF inhibitors in combination with
MEK inhibitors [17–21].
Leunomide is an FDA approved drug for the
treatment of RA and is an inhibitor of the enzyme
dihydroorotate dehydrogenase (DHODH) [22–24], which
is the rate limiting enzyme in the de novo pyrimidine
synthesis pathway. The pyrimidine synthesis pathway
consists of six enzymatic reactions, which generate
ribonucleotide uridine monophosphate (rUMP). DHODH
is located in the inner mitochondrial membrane and
catalyses the conversion of dihydroorotate to orotate, the
fourth step of this pathway [25]. Inhibition of DHODH
prevents the synthesis of pyrimidines, which has a knock-
on effect on the synthesis of pyrimidine derivatives such as
the nucleotide bases cytosine and thymine. This ultimately
decreases the pool of nucleotides available to make new
DNA (as well as RNA). From our previous work carrying
out chemical genetic screens on zebrash and X. laevis
embryos, leunomide was shown to have potential
therapeutic value in treating melanoma [26]. We further
showed that leunomide inhibits neural crest development
by inhibiting transcriptional elongation of genes necessary
for neural crest development and also melanoma growth.
Genes such as sox10 and dct, which are necessary
for normal neural crest and melanocyte development,
respectively, exhibited reduced expression [26, 27]. The
effect leunomide has on Xenopus and zebrash embryos
is phenotypically similar to the suppressors of Ty 5 and 6
(spt5/spt6) mutant in zebrash embryos. Spt5/spt6 have
been shown to be involved in transcriptional elongation
[28]. Our previous work showed that leunomide reduced
cell viability in three melanoma cell lines harboring the
BRAFV600E mutation [26]. However, it is not known if
leunomide affects melanoma cells that do not harbor
BRAF mutations and details of how leunomide exerts its
anti-melanoma effects are currently unknown.
In this present study we investigate the action of
leunomide in melanoma cells. We then go on to show
that as well as combinatorialy acting with vemurafenib
[26], leunomide synergizes with selumetinib to inhibit
melanoma cell growth and decrease tumour size in vivo.
Taken together our data suggest that leunomide used
in combination with MEK inhibition acts as a potent
therapeutic drug combination for the treatment of advanced
stage melanoma.
RESULTS
Leunomide decreases the viability of melanoma
cells by inducing cell cycle arrest and cell death
In clinical practice, assessment of BRAFV600 mutation
status is the only molecular determinant currently used to
inuence standard-of-care in melanoma patients. We have
selected a panel of eight human melanoma cell lines to
further characterize the potential effects of leunomide as
an anti-melanoma drug (Supplementary Table 1), where
half habour the BRAFV600E mutation and the remainder are
wildtype for BRAF (BRAFWT; Supplementary Table 1).
As expected BRAF
V600
mutant cells are more sensitive to
vemurafenib treatment than BRAF
WT
lines (Supplementary
Figure 1 and Table 1).
Cell viability assays using CellTiter-Glo showed that
leunomide reduced the viability of all eight melanoma cell
lines in a dose dependent manner (Table 1 and Figure 1A).
Both BRAFWT and mutant BRAF lines were sensitive to
leunomide treatment to comparable levels (Table 1 and
Figure 1B). Overall, we observed no obvious differences
in leunomide efcacy based on the mutational status of
the melanoma cells (compare Supplementary Table 1 and
Table 1). In addition, we analyzed a number of normal
human cells and found that they too were sensitive to
leunomide; melanocytes were more resistant than most
of the melanoma cells analyzed (Table 1 and Figure 1C).
A375 cells are representative of the panel of
melanoma cells in their clear response to leunomide
treatment, which can be easily observed in treated
monolayers (Supplementary Figure 2A). To determine
why there was a reduction in cell viability upon treatment
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with leunomide we rst investigated cell proliferation
in response to treatment by staining A375 cells with
BrdU to determine cell proliferation. The number of
BrdU positive cells in each of the treatment conditions
showed a clear dose-dependent decrease in the number of
proliferating cells in response to increasing concentrations
of leunomide (Figure 2A, Supplementary Figure 2B).
To determine if leunomide was affecting a
particular stage of the cell cycle, analysis was carried out
using propidium iodide (PI) to stain for cellular DNA
content. A375 cells were stained with PI following a
72-hour treatment with DMSO, 25, 50 or 100 μm
leunomide (Figure 2B). The G0-G1 phase of the cell
cycle, increased in a dose-dependent manner in response
to leunomide treatment (Figure 2C). From the DMSO
control 45.71% of cells are actively cycling through G1,
which increased to 46.56%, 55.05% and 73.56% upon
treatment with 25, 50 and 100 μM leunomide, respectively.
In contrast the number of cells in S-phase decreased from
40.26% in DMSO control cells to 42.93% in 25 μM
leunomide treated cells, 30.41% in 50 μM leunomide
treated cells and 11.60% at 100 μM leunomide (Figure 2C).
Thus, with increasing concentrations of leunomide, the
cells become arrested in the G1 phase of the cell cycle and
the number of cells in S phase signicantly decreases. The
percentage of cells in G2-M at 25 µM was reduced by 50%
compared to the DMSO control, however the percentage
of cells in G2-M for 50 and 100 µM leunomide does
not alter drastically compared to the 25 µM leunomide.
Interestingly, the percentage of cells populated in sub-G1
gradually increased in a dose-dependent manner. In DMSO
treated cells 2.60% cells were in sub-G1. This increased
to 5.36%, 9.12% and 11.84% upon treatment with 25, 50
and 100 μM leunomide respectively, suggesting that there
could be an increase in the number of cells undergoing
apoptosis in response to the drug treatment (Figure 2B, 2C).
To further examine if the cells were undergoing
apoptosis we tested their response to leunomide treatment
using Annexin V staining. In control samples the majority
of the cells were viable as expected, but treatment with
leunomide led to pro-apoptotic effects, which was most
prominent when cells were treated with 50 µM of the drug
(Figure 2D(iii)). At 100 µM leunomide unexpectedly
led to an increase in the number of viable cells (from
5.91% up to 51.4%), with concomitant decrease in the
number of early apoptotic (from 49.3% to 28.5%) and late
apoptotic/necrotic cells (from 44.2% to 19.1%; Figure 2D).
Overall, we postulate that leunomide induces apoptosis
in melanoma cells (as opposed to necrosis), which can
be easily observed when the data is summarized as the
percentage of cells undergoing types of cell death upon
treatment with increasing doses of leunomide (Figure 2E).
At 100 µM we are still seeing cell death, but the
apoptosis marker (PS exposure) is lost. The cells could be
undergoing toxic effects leading to oncosis or necrosis as
indicated by the loss of cell density, but absence of PS
exposure (Figure 2D).
In mammalian cells, activation of apoptosis is
often strongly controlled by mitochondrial activity [33].
Given the pro-apoptotic effects of leunomide at lower
concentrations observed in melanoma cells (Figure 2),
we decided to investigate if the drug could also affect
mitochondrial activity in these cells. JC-1 staining was
conducted as this is commonly used to measure and
detect changes in mitochondrial membrane potential and,
thus, is a commonly used indicator of healthy cells and a
Table 1: Response of melanoma cells to leunomide, vemurafenib and selumetinib*
Cell type** IC50 (µM)
Leunomide
IC50 (µM)
Vemurafenib
IC50 (µM)
Selumetinib
BRAF
Status
NRAS
Status
M202 68.1 1.7 0.5 wt Q61L
M285 61.5 n/a 0.5 wt wt
M375 64.1 n/a 0.1 wt wt
M296 111.8 20.47 wt Q61L
A375 57.4 0.7 0.19 Homo V600E wt
M229 58.2 0.3 0.2 Homo V600E wt
SKmel28 166.9 0.8 0.43 Homo V600E wt
SKmel5 122.5 0.15 1.01 Het V600E wt
Melanocytes 147.7 nd n/a - -
HEK293 48.1 nd n/a - -
RD1 84.2 nd 1.05 - -
*IC50 values for eight melanoma cell lines, HEK293, RD1 cells and melanocytes are shown for each of the three drugs.
Abbreviations; n/a, not applicable; nd, not determined; wt, wild-type; Homo, homozygous; and Het, heterozygous. Where
applicable amino acid substitutions for NRAS and BRAF are indicated.
**Additional genetic information of these cells is provided in Supplementary Table 1.
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detector of early apoptosis which involves mitochondrial
depolaristion (Supplementary Figure 3A). With increasing
concentrations of leunomide the main population
appeared to increase in the FL-2 y-axis, which suggests
an increase in red uorescence and a potential increase in
mitochondrial membrane potential (ΔψM), albeit this is a
relatively subtle effect. However, there is an increase along
the FL-1 channel with rising concentrations of leunomide,
Figure 1: Leunomide reduces the cell viability of melanoma cell lines. (A) Leunomide causes a dose-dependent decrease
in cell viability in eight human melanoma cell lines. BRAFWT cell lines; M202 (blue), M285 (red), M375 (green) and M296 (purple).
BRAFV600E mutant cell lines; A375 (orange), M229 (grey), SKmel28 (khaki) and SKmel5 (black). Cell viability was determined by using
CellTiter-Glo reagent and all values are represented as a percentage (%) relative to the vehicle control. Data is presented as the mean ±
SEM of three independent experiments each performed with cell culture triplicates. (B) Leunomide reduces cell viability at a similar
rate in BRAFWT (wtBRAF) melanoma cells and BRAFV600E mutant (mBRAF) cell lines. The data from the four wildtype cell lines was
averaged (black). The same was done for the four BRAFV600E mutant lines (red). Cell viability was determined by using CellTiter-Glo
reagent and all values are represented as a percentage (%) relative to the vehicle control. Data is presented as the mean ± SEM of twelve
independent experiments each performed with cell culture triplicates. (C) Leunomide causes a dose-dependent decrease in cell viability
in melanocytes, HEK293 and RD1 cells. Melanocytes (black), HEK293 cells (red) and RD1 cells (blue). Cell viability was determined
using CellTiter-Glo reagent and all values are represented as a percentage (%) relative to the vehicle control. Data is presented as the mean
± SEM of three independent experiments each performed with cell culture triplicates.
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Figure 2: Leunomide causes a G1 cell cycle arrest in A375 melanoma cells and induces apoptosis. (A) Leunomide
inhibits cell proliferation in A375 cells. Percentage of BrdU positive A375 cells after 72 hours treatment with leunomide. Data is presented
as the mean ± SEM of the three independent experiments each performed with cell culture triplicates. Asterisks indicate the degree of
statistical difference determined by one-way ANOVA with Turkey’s post-hoc test. *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001 and ****P ≤ 0.0001. (B)
Representative DNA histogram plots of the cell cycle analysis performed in A375 cells treated for 72 hours with leunomide. (Bi) shows
DMSO treated cells. (Bii), (Biii) and (Biv) show cells treated with 25, 50 and 100 μM leunomide respectively. (C) Leunomide causes a
G1 cell cycle arrest in A375 melanoma cells and induces apoptosis. Cell cycle phase distribution for A375 cells treated for 72 hours with
leunomide. Data is presented as the mean ± SEM of three independent experiments each performed with cell culture triplicates. Asterisks
indicate the degree of statistical difference comparing DMSO control to the varying concentrations of Leunomide using student’s t-tests.
*P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001 and ****P ≤ 0.0001. (D) Representative pseudo plots of cell death analysis determined by ow cytometry.
A375 cells were treated with DMSO, 25, 50 and 100 μM leunomide for 72 hours and stained with annexin V and PI. The numbers indicate
the percentage of cells present in each quadrant. (E) Graph quantifying the percentage of A375 cells that are viable, early apoptotic, late
apoptotic and necrotic after 72 hours of treatment with leunomide. Data is presented as the mean ± SEM of three independent experiments
each performed with cell culture triplicate. Asterisks indicate the degree of statistical difference comparing each leunomide condition
to the DMSO control determined by two-way ANOVA with Turkey’s post-hoc test. *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001 and ****P ≤ 0.0001.
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suggesting the mitochondria become depolarized in the
presence of the drug, which is indicative of a pro-apoptotic
state in these cells (Supplementary Figure 3A).
Finally, to see if overall mitochondrial content was
affected upon treatment with leunomide, Mitotracker
green dye, which is independent of ΔψM, was used to
assess mitochondrial mass (Supplementary Figure 3B).
At 100 μM of leunomide treatment, there was a
substantial increase in the intensity of green uorescence,
suggesting an increase in mitochondrial mass at this
drug concentration in the melanoma cells. Indeed,
there was a 3-fold increase in the amount of green
uorescence at 100 μM leunomide when compared to
the DMSO control, which was not observed at lower
leunomide concentrations (Supplementary Figure 3C).
This, however, is not the correct interpretation. Keij et al.
(2000) reported that mitochondrial swelling (oncosis) can
lead to increased uorescence signals, since the normally
densely-packed self-quenched probes are capable of
releasing more photons in the swollen mitochondrion.
Thus, at 100 μM leunomide we are observing mitotoxicity
through loss of mitochondrial volume control. This is
consistent with oncotic cell death which leads to the loss
of cell density in these samples; it was noted that there
was a 3-fold increase in the time it took for the 100 μM
of leunomide treatment sample to reach 5000 events
for counting by ow cytometry relative to the 25 μM and
50 μM treated sample sets (Supplementary Figure 3D). Loss
of ion ux control also explains the loss of the apoptotic
marker (PS exposure) at the 100 µM dose (Figure 2D).
Overall, we conclude that the differences seen at
100 µM are potentially due to mitochondrial oncosis, which
is often linked to a complete overdose of a toxin and is
associated with a loss of cells, but at lower concentrations
(25 μM and 50 μM) leunomide induces apoptosis in
melanoma cells.
Investigating the possibility of using leunomide
in combination with a MEK inhibitor to treat
melanoma
In recent years it has become widely accepted that
combinatorial therapy is a better approach for treating
cancer. Within the skin cancer eld, there is substantial
clinical data supporting MEK inhibitors being used for
the treatment of melanoma [34]. Indeed the standard-
of-care for BRAF-targeting in melanoma has now
predominantly shifted from the use of single BRAF
inhibitors to use in combination with MEK inhibitors.
Taking this into account, the possibility of using
leunomide in combination with the MEK inhibitor,
selumetinib was investigated. The rationale for this is
that melanomas are addicted to MEK for proliferation
and survival. Therefore inhibition of MEK might reduce
survival signaling and sensitize cells to the cytotoxic
effects of leunomide.
Selumetinib (AZD2644) treated cell viability assays
were carried out using CellTiter-Glo on all eight of the
melanoma cell lines (Table 1 and Figure 3A). A dose-
dependent decrease can be seen in the number of viable
cells upon 72-hours treatment with selumetinib in all eight
of the melanoma cell lines (Figure 3A). There was a broad
range of variation in the level of sensitivity to selumetinib,
which is similar to the variation observed for leunomide
(Table 1 and Figure 1A). For example the most sensitive
melanoma cell line to selumetinib was M375 with an IC
50
of
0.10 µM, whereas the least sensitive melanoma cell line was
SKmel5 with an IC50 of 1.01 μM (Table 1 and Figure 3A).
Non-melanoma cells including melanocytes
were also treated with selumetinib (Figure 3A and
Supplementary Figure 4) and their sensitivity to the drug
determined (Table 1). Interestingly, all three non-melanoma
cell types were less sensitive to selumetinib compared to
the eight melanoma cell lines. The RD1 cell line was the
most sensitive with cell viability being reduced to 55% at
1 μM selumetinib (Table 1 and Supplementary Figure 4).
This sensitivity was very close to the least sensitive of
the melanoma lines, SKmel5, where its cell viability was
reduced to just 51.80% at the same concentration (Table 1).
Overall, these ndings are in support of previous work
showing that melanoma cells are more sensitive to
MEK inhibition than normal cells, with drug sensitivity
to selumetinib in the same range as detected here (as
previously reviewed [35]).
To conrm selumetinib was active and acting ‘on-
target’ as a MEK inhibitor, western blots were performed
to detect the levels of phospho-ERK (pERK) on treated
A375 and M202 cells. As ERK is a direct substrate
of MEK a decrease in pERK would be anticipated in
response to selumetinib treatment. It can be clearly seen
that the amount of pERK protein decreases in a dose-
dependent manner in melanoma cells in response to
selumetinib treatment (Figure 3B and 3C). Overall, this
conrms that selumetinib is effectively inhibiting its target
and can reduce cell viability in melanoma cells.
Leunomide and selumetinib exhibit synergistic
activity in human melanoma cells
The preceding results showed both leunomide
(Figure 1) and selumetinib (Figure 3) were effective at
reducing cell viability in the melanoma lines. Prompted by
these results, experiments were designed to determine if the
combination of leunomide and selumetinib could reduce
cell viability further than either drug alone. Combinatorial
cell viability assays were carried out on all eight of
the melanoma lines. For these cell viability assays the
concentrations of leunomide used were 12.5, 25 and 50 μM
and for selumetinib the concentrations used were 0.025,
0.05 and 0.1 μM. Two cell viability graphs were generated
for each melanoma line (Figure 4A and Supplementary
Figure 5). This was done in order to complete statistical
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analysis comparing the drug combinations to each drug
alone. The statistics shown on these graphs determined
that the drug combinations were signicantly better at
killing melanoma cells than either drug alone. All of the
eight melanoma cell lines responded to the combinations
of leunomide and selumetinib. The most statistically
signicant combination of leunomide and selumetinib was
at 50 μM leunomide and 0.1 μM selumetinib (a ratio of
500:1). Therefore this specic combination of leunomide
and selumetinib indicates that these concentrations could
be within the optimal working concentration range for this
drug combination in melanoma cells.
The next question was are the drugs acting
synergistically or not? One approach of determining drug
synergy is by calculating combination index (CI) values
for multiple drug combinations using the Chou and Talalay
method [32]. CI values were calculated for each separate
combination of leunomide and selumetinib (non-constant
ratio). This was done for all eight of the melanoma cell
lines. For each cell line, two graphs were plotted to
demonstrate the synergism of the two drugs as shown in
Figure 4B(i) and 4B(ii). For the majority of the lines tested,
high dose leunomide (50 μM) showed synergistic effects
when used in combination with selumetinib (Table 2).
It was further investigated whether addition of
Leunomide or Selumetinib alone 24 hours before addition
of the other drug had any effect on their synergy. We
selected four lines; one that showed obligate antagonism
to the drug combination treatment (A375) to see if
drug interactions could be improved, one that showed
obligate drug synergy (M375) to check if the desired
drug interactions might be lost with a different dosing
Figure 3: MEK inhibition reduces the viability of melanoma cells. (A) Selumetinib caused a dose-dependent decrease in cell
viability in eight human melanoma cell lines. Melanoma cell lines include M202 (blue), M285 (red), M375 (green) and M296 (purple), A375
(orange), M229 (grey), SKmel28 (khaki), SKmel5 (black) and melanocytes (pink; open triangle). Cell viability was determined by using
CellTiter-Glo reagent and all values are represented as a percentage (%) relative to the vehicle control. Data is presented as the mean ± SEM
of three independent experiments each performed in triplicate. (B) Western blot analysis conrming the decrease in phospho-ERK upon
treatment with 0.1 or 1 µM selumetinib in A375 and M202 melanoma cell lines in triplicate. The molecular weights are shown on the left.
Results for pERK and total ERK (tERK) are from a single experiment representative of three independent experiments. (C) Quantication
data from Western blot.
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Table 2: Summary CI values for all melanoma cell panel*
Leunomide 12.5 µM Leunomide 25 µM Leunomide 50 µM
Melanoma
cell line
MEKi
0.025 µM
MEKi
0.05 µM
MEKi
0.1 µM
MEKi
0.025 µM
MEKi
0.05 µM
MEKi
0.1 µM
MEKi
0.025 µM
MEKi
0.05 µM
MEKi
0.1 µM
A375 1.621 1.526 1.561 1.59 1.699 1.814 1.414 1.507 1.646
M375 0.528 0.661 0.834 0.473 0.549 0.754 0.328 0.327 0.519
M296 0.837 1.103 1.479 1.249 1.13 1.381 0.897 0.703 0.655
M202 1.059 1.182 1.42 1.1 1.013 1.13 0.947 0.532 0.603
M229 0.827 0.743 0.939 1.011 0.831 0.94 0.801 0.617 0.846
M285 0.704 0.95 1.033 0.657 0.709 0.777 0.568 0.665 0.515
SKMEL28 0.536 0.699 1.279 0.812 0.841 1.444 1.031 0.85 1.058
SKMEL 5 1.397 1.393 0.3 1.301 1.445 0.237 1.381 1.152 0.112
*Purple indicates antagonism, orange indicates additive and green indicates synergism.
Figure 4: Leunomide and Selumetinib synergize in melanoma cells. Cell viability plots when different concentrations of
Selumetinib and Leunomide are added to the cells simultaneously. Graph A(i) shows he concentrations of leunomide along the x-axis.
The statistical analysis on this graph compared the combinations of drugs to leunomide alone. Graph A(ii) shows the concentrations of
selumetinib along the x-axis. The statistical analysis on this graph compared the drug combinations to selumetinib alone. All values are
represented as a percentage (%) relative to the vehicle control. Data is presented as the mean ± SEM of three independent experiments
each performed in triplicate. Asterisks indicate the degree of statistical difference comparing each leunomide and selumetinib condition to
leunomide alone (graph A(i)) or selumetinib alone (graph A(ii)). Statistical analysis was determined by two-way ANOVA with Turkey’s
post-hoc test. *P ≤ 0.05, **P ≤ 0.01, and ****P ≤ 0.0001. (A) Combination index values for M375 melanoma cell line with leunomide and
selumetinib in combination at increasing concentrations. B(i) Along the x-axis is the Fraction Affected (FA) which corresponds to the cell
viability data inputted (i.e. what fraction of the cells were affected/how much of the cell viability was being reduced by this combination
of leunomide and selumetinib). Along the y-axis is the CI values. A dotted line placed across the CI value of 1 makes it easier to see if
a particular combination of leunomide or selumetinib was synergistic or not. A CI value of 1 suggests that drug combination is acting
additively. A value greater that 1 suggests the drug combination is acting antagonistically and a value below 1 suggests they are working
synergistically. The closer the value to 0 the stronger the synergism. B(ii) This graph utilises the CI value data with the CI values again
shown along the y–axis but along the x-axis is the concentration of selumetinib with the data sets on the graph corresponding to the
leunomide concentrations. The degree of synergism increases with increasing concentrations of leunomide. The Synergy graphs for the
other melanoma lines tested are shown in Supplementary Figure 5.
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regime and two lines that showed mostly synergistic,
but also some additive response (M229, and M285; i.e.
borderline drug synergy response) to treatment (Table 2).
Supplementary Tables 2–5 show the CI values for these
treatments of the four melanoma lines. For A375 cells
there was a slight improvement when the drugs were added
incrementally, but this was only at one concentration and
the synergy effect was mild (Supplementary Table 2). For
M229 and M375 cells, incremental drug addition led to
loss of drug synergy at most of the concentrations tested
(Supplementary Table 3 and Supplementary Table 4).
M285 on the other hand did show drug synergy for every
concentration tested when the drugs were added one after
the other, but this represented only a mild improvement to
when the drugs were added simultaneously (Supplementary
Table 5). Overall, these ndings suggest that there is
likely to be a greater chance of achieving drug synergy in
melanoma cells when leunomide and selumetinib are co-
administered at the same time.
Finally, we investigated if the drug combination
could increase apoptosis in melanoma cells with respect
to monotherapy by analyzing PARP1 cleavage (cPARP),
which is a sensitive marker of cells undergoing apoptosis.
cPARP is increased in melanoma cells in response to the
drug combination, with concomitant decrease in levels
of the anti-apoptotic Bcl-2 family member, MCL-1
(Supplementary Figure 6), showing that combined
leunomide and selumetinib treatment increases apoptosis
in melanoma cells compared with individual drug
treatment. Selumetinib treatment however results in higher
levels of the BH3-only pro-apoptotic protein, BIM, than
the drug combination (Supplementary Figure 6). These
ndings are more difcult to interpret as aside from the
pro-apoptotic activity of BIM in inducing BAX/BAK
oligomerization on mitochondria to release cytochrome c
and induce intrinsic apoptosis, BIM has also been shown
to possess pro-survival effects in cancer cells [36]. Overall,
we conclude that combined leunomide and selumetinib
can increase apoptosis in melanoma cells to a higher level
than individual drug treatment alone.
Leunomide and selumetinib combine to repress
tumour growth in vivo
Because the combination of leunomide and
selumetinib showed synergistic activity in a range of
melanoma cell lines in our in vitro experiments (Figure 4,
Table 2, Supplementary Tables 2–5 and Supplementary
Figure 5), we wanted to investigate whether the drug
combination could also show improved efcacy in vivo
compared to monotherapy treatment. The M375 cell
line showed synergistic activity of the drug combination
at all concentrations tested (Figure 4 and Table 2), so
we investigated if these cells could be easily engrafted
in immunodecient mice as compared to other human
melanoma cells, for in vivo studies. Using SCID mice,
we developed an engraftment protocol for these cells and
compared them to other melanoma lines known to engraft
in immunocompromised mice, to ensure palpable M375
tumors could develop in a relatively rapid time-frame
(Supplementary Figure 7).
Following 4-weeks of tumour growth, drugs
were administered in 4 treatment groups; vehicle alone,
leunomide alone, selumetinib alone and leunomide
and selumetinib in combination (10 animals/group) with
a daily treatment regime as shown in Figure 5A. In the
vehicle control arm, the average tumour volume increased
from 46 mm3 on day 0 to 650 mm3 on day 12, indicating
a steady increase in tumour growth over the course of
the experiment (Figure 5B). Unexpectedly, leunomide
treatment alone did not reduce tumour volume when
compared to the vehicle control. In contrast, selumetinib
treatment signicantly reduced the average tumour
volume, albeit the tumors did continue to grow during
the duration of the experiment. Interestingly however,
when leunomide and selumetinib was administered in
combination, the tumour volume not only decreased to
levels signicantly smaller than either drug treatment
alone, but importantly tumour growth was suppressed, with
tumour volumes remaining steady at the same size over the
12-day treatment period (Figure 5B).
The tumours from the sacriced mice at the end
of the experiment were excised, weighed (Figure 5C)
and imaged (Figure 5D). Overall, there is a remarkable
drop in tumour size and weights when leunomide and
selumetinib were used in combination. The combination
of leunomide and selumetinib on the effect on the tumour
weights was signicantly better than either of the two
drugs alone (Figure 5C). Taken together, our data show
that combination of leunomide and selumetinib has the
capability of not only reducing tumour volume, but also
preventing tumour growth in vivo.
DISCUSSION
In recent years the development of new therapies
for melanoma has led to a revolution in treatment, which
has reected decades of basic research into the genomic
landscape and fundamental immune system behaviour
of the disease. The advent of BRAF and MEK inhibitors
used in combination has become a standard therapeutic
approach in patients with BRAF-mutated melanoma. In
addition, immunotherapies such as anti-PD-1 antibodies
have been effective. In many cases, particularly with small
molecule treatments as monotherapies the main problem
has been the development of tumour resistance. Therefore,
it is important to develop new combination therapies and
to identify novel drugs that can be added to the arsenal of
anti-melanoma therapies available for patients.
Leunomide is an immunosuppressive drug which
was approved by the FDA in 1998 for the treatment of
RA. It has also been shown to inhibit the growth of a
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Figure 5: The combination of Leunomide and Selumetinib reduces tumour growth in vivo. (A) SCID mice xenotransplanted
with human melanoma cells (M375; 3 × 106/animal, subcutaneous injection) until tumours were palpable (4-weeks post implantation),
were treated daily with leunomide/selumetinib as individual drugs or in combination as indicated for 12 days. A control arm was also
included where comparable vehicle only treatments were administered. Tumour volumes were measured at 4 time-points (T1–T4) during
the 12-day treatment period as indicated. I.P., intraperitoneal. O.G., oral gavage. (B) The combination of leunomide and selumetinib
reduced the average tumour volume greater than either drug alone. Data is presented as the mean ± SD of one independent experiment.
Statistical analysis compares either drug alone to them in combination determined by two-way ANOVA with Turkey’s post-hoc test.
*P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001 and ****P ≤ 0.0001. (C) The combination of leunomide and selumetinib reduced tumour weight greater
than either drug alone. Data is presented as the mean ± SD of one independent experiment. Asterisks indicate the degree of statistical
difference comparing the combination of leunomide and selumetinib to each drug alone determined by unpaired student t-test. *P ≤ 0.05,
**P ≤ 0.01, ***P ≤ 0.001 and ****P ≤ 0.0001. (D) Visualisation of the excised tumours from the xenograft study.
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number of different cell types including human myeloma
cells [37], mitogen-stimulated T-lymphocytes [38],
normal human mast cells [39], prostate cancer cells
[40] neuroblastoma cells [41] and melanoma cells [26].
In these different cell types the optimum concentration
of leunomide varies. For instance Zhu et al. [41] use
100 µM as an optimal concentration for their cell cycle
analysis and apoptosis studies. Here we have determined
50 µM to be the optimal concentration to use in vitro for
apoptosis induction. At higher concentrations we detect
potentially off target toxic effects and the cells undergo
oncosis. Baumann et al. [37] have themselves noted
that leunomide may act independently of DHODH
at higher concentrations. That is not to preclude higher
doses from therapeutic consideration. Lytic modes of cell
death are proinammatory and in solid tumours, where
several mechanisms exist to downregulate innate immune
responses and consequent adaptive immune responses,
targeted cytotoxicity may facilitate immune activation. In
melanoma cells the mechanism of leunomide action is
to inhibit transcriptional elongation [26] which leads to a
decrease in cell proliferation.
We have previously identied leunomide as
having therapeutic value in treating melanoma in a mouse
xenograft model both on its own and in combination with
a BRAF inhibitor [26]. We have now expanded upon these
initial studies to show that leunomide affects the growth
of both BRAFWT and mutant melanoma cells (Figure 1).
This potential allows for leunomide to be used in
all melanoma cases, not just for tumours harbouring
BRAF mutations. We show that at intermediate dose
concentrations, leunomide inhibits G1 arrest and induces
apoptosis (Figure 2). To the best of our knowledge, this is
the rst time the mechanism of action of leunomide has
been investigated in melanoma cells. Finally we also show
that leunomide can act in combination with the MEK
inhibitor, selumetinib (Figure 3), to inhibit melanoma
growth (Figure 4 and Figure 5).
To determine if the synergism observed in vitro
between leunomide and selumetinib had a similar effect
in vivo, a mouse xenograft study was carried out. This
study used the M375 cell line for a drug treatment duration
of 12 days. What was obvious from the results of this study
was that selumetinib was the more effective drug compared
to leunomide (Figure 5). In this experiment leunomide
alone did not reduce the tumour volume or weight
compared to the vehicle control. It is possible that the dose
of leunomide used in this experiment may have been on
the border of efcacy on its own. However, the cells were
strongly sensitized by leunomide treatment to the anti-
melanoma effect of the MEK inhibitor. Although from
this study it cannot be said that the drug synergy observed
in vitro for M375 translates in vivo, what can be stated
is that the combination of leunomide and selumetinib
signicantly decreased the growth of melanoma in vitro
and in vivo compared to using either drug alone.
Recently leunomide has been shown to work
in combination with doxorubicin to inhibit growth of
triple-negative breast cancer [42]. The mechanism the
authors suggest is based on their nding that pyrimidine
synthesis increases in response to genotoxic stress.
Thus, in our results selumetinib could be inducing this
response of increased pyrimidine synthesis which in turn
is inhibited by leunomide, thus making the cells less
likely to survive. This does not answer why leunomide
has an effect on its own, but does highlight that it could
make a potent contribution to combinatorial treatments of
malignancies. Whilst future clinical studies are needed to
investigate this intriguing possibility further, our ndings
do highlight some important discoveries about the
leunomide/selumetinib drug combination for such future
work. Firstly, the combination shows drug synergy in both
BRAF
MUT
and BRAF
WT
melanoma cells (Table 2, Figure 4
and Supplementary Figure 5), suggesting it could be a
potent anti-melanoma treatment for patients regardless of
genotype. Furthermore, we found no patterns with other
common melanoma mutations (Supplementary Table 1)
that dictated response rates of the cell lines tested to the
combination. Secondly, dosing of the combination has
an improved chance of yielding potent synergistic anti-
melanoma effects, when administered simultaneously
to the cell panel tested (Supplementary Tables 2–5),
suggesting designing future dosing regimens where both
drugs are administered at the same time. Lastly our pre-
clinical in vivo model not only demonstrated the potent
efcacy of the drug combination at blocking tumour
growth (Figure 5), but also highlighted that the therapy is
tolerable, as no overt toxicities were detected in the mice
during the treatment period.
In conclusion we have shown leunomide to work
in combination both with BRAF and MEK inhibitors
in preventing melanoma growth. Future work will
determine the mechanism of drug synergy afforded by
combined treatment of melanoma cells with leunomide
and selumetinib. Furthermore, additional pre-clinical
experiments are needed to determine if melanoma cells
can acquire resistance to leunomide and whether the drug
could also be successfully used in combination with anti-
melanoma immunotherapies.
MATERIALS AND METHODS
Compounds
Vemurafenib (ChemieTek) was dissolved in
dimethyl sulphoxide (DMSO; Sigma-Aldrich) and stored
at –20ºC at stocks of 100 mM. Leunomide (Sigma-
Aldrich) was dissolved in DMSO and stored at 4ºC at
stocks of 10 mM. AZD6244 (selumetinib; SelleckChem)
was dissolved in DMSO and stored at –20ºC at stocks of
2 mM. When aliquots of the stock were in use they were
stored at 4ºC for no longer than two weeks.
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Cell lines and culture
The human melanoma M285, M375 and M296,
cell lines were a kind gift from Antoni Ribas (University
of California, Los Angeles), and the M202, A375, M229,
SKmel28 and SKmel5 cells were a kind gift from Randall
T. Moon and Andy J. Chien (University of Washington,
Seattle). Primary human melanocytes adult (HEMa-LP)
were obtained from Gibco. Human embryonic kidney
cells (HEK-293) and rhabdomyosarcoma cells (RD-1)
were obtained from the Biomedical Research Centre
(University of East Anglia, UK). Human melanoma cells
were cultured as previously described [29]. HEMa-LP cells
were cultured in Medium-254 (Gibco) with the addition
of PMA-Free Human Melanocyte Growth Supplement-2
(HMGS-2; Gibco). HEK-293 cells were cultured in
Dulbecco’s modied Eagle medium (DMEM) + GlutMAX
(Gibco) supplemented with 10% FBS, 1% L-glutamine and
penicillin and streptomycin. RD-1 cells were cultured in
Dulbecco’s modied Eagle medium (DMEM) + GlutMAX
(Gibco) supplemented with 10% FBS and penicillin and
streptomycin. All cells were maintained at 37ºC in a 5%
CO
2
air-humidied incubator, were routinely screened for
mycoplasma and not cultured beyond passage 25.
Cell viability assays
Cells that had been seeded 24 hours earlier on
poly-L-lysine coated 96-well plates (Sigma-Aldrich) to
subconuency, were treated with drugs at the indicated
concentrations for 72 hours. Cytochalasin D (Sigma
Aldrich) was used as a positive control. All conditions
were repeated in triplicate. Cell viability was determined
on day 5 using the CellTiter-Glo Luminescence assay
(Promega), according to the manufacturer’s instructions.
Luminescence from the plate was read on a BMG LabTech
Omega Series plate reader (data analysed using OMEGA
software). Cell viability was calculated as a percentage of
the mean vehicle control.
5-Bromo-2ʹ-deoxyuridine (BrdU) proliferation
assay
A375 melanoma cells were seeded in 12-well plates
at a density of 10,000 cells and grown on gelatin-coated
coverslips. After 24 hours leunomide was added to cells
at 12.5, 25 or 50 μM (or a vehicle control) for 72 hours.
Cells were pulsed for 2 hours with BrdU (Sigma-Aldrich)
at a nal working concentration of 10 μM. Cells were
permeabilised in 2N-HCL + 0.5% Triton X-100. Primary
BrdU antibody diluted 1:100 in 1% goat serum was
applied and incubated overnight at 4ºC followed by Alexa
Fluor-488 anti-mouse secondary antibody Cells were
counterstained with DAPI. Cells were mounted onto slides
using hydromount and examined under a Zeiss AxioPlan
2ie wideeld microscope with an AxioCam HRm CCD
camera. Images were analysed using Image J software.
Cell cycle analysis
Cell cycle analysis was carried out as previously
detailed [30]. In brief, A375 melanoma cells were seeded
in 24-well plates at a density of 4,600 cells per well. After
24 hours, the cells were treated with vehicle, 25, 50 and
100 µM of Leunomide. After 72 hours, the cells were
trypsinised and pelleted along with the culture medium.
Cells were washed in PBS and xed in ice-cold absolute
ethanol. Cells were then stained with 200 µl PI/RNase A
solution (Cell Signalling Technology). Cells were analysed
using a BD Accuri
TM
C6 ow cytometer (BD Biosciences)
and the data was analysed using the BD AccuriTM C6
Software and FlowJo (FLOWJO, LLC).
Annexin V apoptosis assay
Apoptosis was assessed using an Annexin V-FITC
Apoptosis detection kit FITC (eBioscience), according
to the manufacturer’s instructions. Briey, cells were
seeded in 24-well plates at a density of 4,600 cells per
well. After 24 hours, the cells were treated with vehicle
or leunomide (at concentrations of 25, 50 and 100 µM).
After 72 hours cells were trypsinised, washed in PBS and
treated with uorochrome-conjugated Annexin V and
propidium iodide as indicated in the protocol. Cells were
analysed on the BD Accuri
TM
C6 ow cytometer and the
data analysed using the instrument software.
Western blot analysis
A375 melanoma cells were seeded and treated for
72 hours in varying drug conditions. Total protein extracts
were then made using high SDS content lysis buffer
(60 mM sucrose, 65 mM Tris-HCl, pH 6.8. 3% SDS).
Protein concentration was determined using the DC protein
assay (BIORAD). 10 μg of whole-cell protein lysate
was loaded onto a 10% SDS-PAGE gel and transferred
onto polyvinylidene diuoride membranes (Bio-Rad). A
standard Western blot protocol was used for detection of
the specic proteins as previously described [29].
Antibodies used included; Rabbit polyclonal
phospho-ERK (1:1000, Cell Signalling Technology);
Rabbit polyclonal phospho-p44/42 MAPK (1:1000,
ERK1/2; Cell Signalling Technology); Mouse monoclonal
HSC-70 (1:1000, Santa-Cruz Biotechnology); Rabbit
polyclonal Mcl-1 (1:500, Santa-Cruz Biotechnology);
Rabbit polyclonal anti-BIM (1:500, Merck-Millipore);
Rabbit polyclonal PARP (1:1000, Cell Signalling
Technology); Rabbit polyclonal PUMA (1:1000, Cell
Signalling Technology); anti-rabbit IgG HRP linked
secondary antibody (1:2000, Jackson ImmunoResearch);
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Anti-mouse IgG HRP linked secondary antibody (1:2000,
Jackson ImmunoResearch); All anti-rabbit IgG HRP linked
secondary antibody (1:2000, Cell Signalling Technology).
Mouse xenograft study
8–10-week-old female severe immunodeciency
(SCID) mice were purchased from Charles River
Laboratories. All procedures were performed under UK
Home Ofce approved protocols and the University of
East Anglia local guidelines. Experiments were conducted
strictly in accordance with the locally approved animal
handling protocol.
A total of 3 × 106 M375 melanoma cells were
injected subcutaneously into 40 SCID mice. After
approximately 4 weeks when the tumours were palpable,
the mice were randomised into 4 arms. The 4 arms were;
vehicle alone, leunomide alone, selumetinib alone and
leunomide and selumetinib in combination. There were
10 mice in each arm. The drug regime was administered for
12 days. Leunomide was administered by intraperitoneal
(IP) injection daily at 7.5 mg/kg. Selumetinib was
administered by oral gavage (OG) twice daily at 30 mg/
kg for the rst two days and was then delivered once
daily thereafter. The tumour volume was measured every
three days with calipers. Tumour volume was measured
by the formula 0.52 (length × width2). At the end of the
experiment, the mice were culled and the excised tumours
were weighed.
Statistical analysis
Either one- or two-way ANOVA was used to analyse
statistical signicance of the data (as indicated in the
gure legends), apart from in vivo tumour volume, where
an unpaired student’s t-test was used. For all in vitro data,
experiments were repeated a minimum of 3 times. The
P-value was considered signicant as follows; *P < 0.05,
**P < 0.01, ***P < 0.001 and ****P < 0.0001.
For pharmacological analysis, IC50 values were
generated using Prism Graphpad software (Graphpad
Software, Inc.) and calculated using a nonlinear regression
model. Combinatorial drug synergy was assessed by
determination of combination index (CI), which was
calculated using CalcuSyn (Biosoft) software using the
median effects methods as described by Chou and Talalay
[31, 32], CI values less than 0.7 indicated synergy, 0.7–0.9
weak synergy, 0.9–1.1 additivity, 1.1–1.45 indicated weak
antagonism and greater than 1.45 antagonism.
Author contributions
GW, VS, KH designed the study. KH, SR, AH, KA,
DW performed experiments and acquired data. KH, GW,
VS, DW, SR interpreted the results. GW and VS drafted
the manuscript and KH, SR, DW, GW and VS edited it. All
Authors approved the nal content for journal submission
and publication.
ACKNOWLEDGMENTS
We would like to thank members of the Münsterberg
and Wheeler labs for their help and support during this
project. We would also like to especially thank Simon
Cook, Andrea Munsterberg and Dylan Edwards for helpful
discussions. Funding: SDR is supported by funding from the
BBSRC and BigC. KA is supported by the Iraqi Ministry
of Higher Education and Scientic Research, Republic of
Iraq and VS is supported by a CRUK programme grant
awarded to the CRUK-Skin Tumour Laboratory, University
of Dundee. AH was supported by the UEA, the John Innes
Centre and AstraZeneca and KH was supported by the John
Jarrold Trust and UEA.
CONFLICTS OF INTEREST
The authors declare no potential conicts of interest.
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... It is a prodrug that is transformed to teriflunomide (active metabolite) that impedes the proliferation of activated T cells by inhibiting dihydroorotate dehydrogenase, a critical enzyme in de novo pyrimidine production, accordingly the proliferation of activated T cells is prevented. Furthermore, it has been proven to be cytotoxic against cancers including bladder (Cheng et al., 2020), head and neck malignancies , and melanoma (Hanson et al., 2018;White et al., 2011). Hanson et al., investigated the anti-melanoma activity of leflunomide along with mitogen-activated protein kinase inhibitor selumetinib against multiple melanoma cells (M202, M285, M375, M296, A375, M229, SKMEL-28, and SKmel5) and in M375 xenograft severe combined immunodeficient (SCID) (8-10-week-old female) mice model. ...
... The cells become halted in the G1 phase of the cell cycle as leflunomide concentrations rise, and the number of cells in the S phase drops dramatically when leflunomide concentrations rise to 25 (42%), 50 (30%), and 100 μM (11%). In all the above eight melanoma cell lines, leflunomide (50 μM) demonstrated synergistic responses in amalgamation with selumetinib (Hanson et al., 2018). ...
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... Вызывают интерес работы, посвящённые изучению противоопухолевого потенциала препаратов, которые используются для лечения воспалительных заболеваний [7,8,9,10]. Среди таких лекарственных средств следует отметить препарат лефлуномид, с его активным метаболитом терифлуномидом, ингибирующим фермент дигидрооротатдегидрогеназу (DHODH). ...
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... In addition, zebrafish were further used to elucidate the neural crest gene expression signature in melanomagenesis, leading to the discovery of new therapeutic targets (e.g. DHODH and SETDB1, involved in transcriptional elongation) and to clinical trials, [19][20][21][22] thus demonstrating the potential of this system for functional genetic studies and drug screening. ...
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Purpose of review: The therapeutic landscape for metastatic melanoma has been revolutionized in recent years. This review will discuss existing evidence for therapeutic approaches for BRAF-mutated metastatic melanoma. Recent findings: Clinical trials involving combined BRAF/MEK inhibition with either vemurafenib plus cobimetinib or dabrafenib plus trametinib have shown improved overall survival compared to monotherapy with BRAF inhibitors alone. In a subset of patients with good prognostic factors, long-term clinical benefit has been noted. Simultaneously, developments in immunotherapy have suggested long-lasting survival for some patients. In advanced BRAF-mutated melanoma, both BRAF/MEK inhibition and immunotherapy agents show improved overall survival and, in a small population of patients, prolonged and long-term benefit as compared to standard chemotherapy. Trials are currently underway evaluating sequencing of these therapies and the safety of targeted therapy plus immunotherapy combinations.
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Treatment options for patients with metastatic melanoma, and especially BRAF-mutant melanoma, have changed dramatically in the past 5 years, with the FDA approval of eight new therapeutic agents. During this period, the treatment paradigm for BRAF-mutant disease has evolved rapidly: the standard-of-care BRAF-targeted approach has shifted from single-agent BRAF inhibition to combination therapy with a BRAF and a MEK inhibitor. Concurrently, immunotherapy has transitioned from cytokine-based treatment to antibody-mediated blockade of the cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4) and, now, the programmed cell-death protein 1 (PD-1) immune checkpoints. These changes in the treatment landscape have dramatically improved patient outcomes, with the median overall survival of patients with advanced-stage melanoma increasing from approximately 9 months before 2011 to at least 2 years - and probably longer for those with BRAF-V600-mutant disease. Herein, we review the clinical trial data that established the standard-of-care treatment approaches for advanced-stage melanoma. Mechanisms of resistance and biomarkers of response to BRAF-targeted treatments and immunotherapies are discussed, and the contrasting clinical benefits and limitations of these therapies are explored. We summarize the state of the field and outline a rational approach to frontline-treatment selection for each individual patient with BRAF-mutant melanoma.
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Chemotherapy resistance is a major barrier to the treatment of triple-negative breast cancer (TNBC), and strategies to circumvent resistance are required. Using in vitro and in vivo metabolic profiling of TNBC cells, we show that an increase in the abundance of pyrimidine nucleotides occurs in response to chemotherapy exposure. Mechanistically, elevation of pyrimidine nucleotides induced by chemotherapy is dependent on increased activity of the de novo pyrimidine synthesis pathway. Pharmacologic inhibition of de novo pyrimidine synthesis sensitizes TNBC cells to genotoxic chemotherapy agents by exacerbating DNA damage. Moreover, combined treatment with doxorubicin and leflunomide, a clinically approved inhibitor of the de novo pyrimidine synthesis pathway, induces regression of TNBC xenografts. Thus, the increase in pyrimidine nucleotide levels observed following chemotherapy exposure represents a metabolic vulnerability that can be exploited to enhance the efficacy of chemotherapy for the treatment of TNBC. Significance: The prognosis for patients with TNBC with residual disease after chemotherapy is poor. We find that chemotherapy agents induce adaptive reprogramming of de novo pyrimidine synthesis and show that this response can be exploited pharmacologically, using clinically approved inhibitors of de novo pyrimidine synthesis, to sensitize TNBC cells to chemotherapy. Cancer Discov; 7(4); 391–9. ©2017 AACR. See related article by Mathur et al., p. 380. This article is highlighted in the In This Issue feature, p. 339
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Background: Immune checkpoint inhibitors and targeted therapies, two new class of drugs for treatment of metastatic melanoma, have not been compared in randomized controlled trials (RCT). We quantitatively summarized the evidence and compared immune and targeted therapies in terms of both efficacy and toxicity. Methods: A comprehensive search for RCTs of immune checkpoint inhibitors and targeted therapies was conducted to August 2016. Using a network meta-analysis approach, treatments were compared with each other and ranked based on their effectiveness (as measured by the impact on progression-free survival [PFS]) and acceptability (the inverse of high grade toxicity). Results: Twelve RCTs enrolling 6207 patients were included. Network meta-analysis generated 15 comparisons. Combined BRAF and MEK inhibitors were associated with longer PFS as compared to anti-CTLA4 (HR: 0.22; 95% confidence interval [CI]: 0.12-0.41) and anti-PD1 antibodies alone (HR: 0.38; CI: 0.20-0.72). However, anti-PD1 monoclonal antibodies were less toxic than anti-CTLA4 monoclonal antibodies (RR: 0.65; CI: 0.40-0.78) and their combination significantly increased toxicity compared to either single agent anti-CTLA4 (RR: 2.06; CI: 1.45-2.93) or anti-PD1 monoclonal antibodies (RR: 3.67; CI: 2.27-5.96). Consistently, ranking analysis suggested that the combination of targeted therapies is the most effective strategy, whereas single agent anti-PD1 antibodies have the best acceptability. The GRADE level of evidence quality for these findings was moderate to low. Conclusions: The simultaneous inhibition of BRAF and MEK appears the most effective treatment for melanomas harboring BRAF V600 mutation, although anti-PD1 antibodies appear to be less toxic. Further research is needed to increase the quality of evidence.
Article
Raf-mitogen-activated protein kinase (Raf-MAPK) pathway inhibition with the BRAF inhibitors vemurafenib and dabrafenib, alone or in combination with a MEK inhibitor, has become a standard therapeutic approach in patients with BRAF-mutated metastatic melanoma. Both vemurafenib and dabrafenib have shown good safety and efficacy as monotherapy compared with chemotherapy. However, the duration of response is limited in the majority of patients treated with BRAF inhibitor monotherapy because of the development of acquired resistance. The addition of a MEK inhibitor can improve blockade of the MAPK pathway and may help to overcome resistance and thereby prolong efficacy, as well as reduce cutaneous toxicity. Combinations of BRAF inhibitors and MEK inhibitors (dabrafenib plus trametinib and vemurafenib plus cobimetinib) have been approved for the treatment of BRAF-mutant metastatic melanoma and may become a new standard of care. However, acquired resistance is still a significant concern with BRAF and MEK inhibitor combination therapy, and other strategies are being investigated, including the use of sequential and intermittent schedules. The combination of BRAF or MEK inhibitors with immunotherapy has been shown to hold considerable promise, with several combinations being evaluated in clinical trials. Preliminary results from clinical trials involving triple combination therapy with BRAF-MEK inhibitors and anti-PD-L1 antibodies appear promising and may indicate a new strategy to treat patients with BRAF-mutated metastatic melanoma. Biomarkers are needed to help identify patients with BRAFV600 mutations most likely to benefit from first-line BRAF/MEK inhibitor therapy rather than immunotherapy and vice versa.
Article
Regulation of gene expression at the level of transcriptional elongation has been shown to be important in stem cells and tumour cells, but its role in the whole animal is only now being fully explored. Neural crest cells (NCCs) are a multipotent population of cells that migrate during early development from the dorsal neural tube throughout the embryo where they differentiate into a variety of cell types including pigment cells, cranio-facial skeleton and sensory neurons. Specification of NCCs is both spatially and temporally regulated during embryonic development. Here we show that components of the transcriptional elongation regulatory machinery, CDK9 and CYCLINT1 of the P-TEFb complex, are required to regulate neural crest specification. In particular, we show that expression of the proto-oncogene c-Myc and c-Myc responsive genes are affected. Our data suggest that P-TEFb is crucial to drive expression of c-Myc, which acts as a ‘gate-keeper’ for the correct temporal and spatial development of the neural crest.
Article
The age of personalized medicine continues to evolve within clinical oncology with the arsenal available to clinicians in a variety of malignancies expanding at an exponential rate. The development and advancement of molecular treatment modalities, including targeted therapy and immune checkpoint blockade, continue to flourish. Treatment with targeted therapy (BRAF, MEK, and other small molecule inhibitors) can be associated with swift disease control and high response rates, but limited durability when used as monotherapy. Conversely, treatment with immune checkpoint blockade monotherapy regimens (anti-cytotoxic T-lymphocyte antigen 4 and anti-programmed cell death protein 1/programmed cell death protein 1 ligand) tends to have lower response rates than that observed with BRAF-targeted therapy, although these treatments may offer long-term durable disease control. With the advent of these forms of therapy, there was interest early on in empirically combining targeted therapy with immune checkpoint blockade with the hopes of preserving high response rates and adding durability; however, there is now strong scientific rationale for combining these forms of therapy-and early evidence of synergy in preclinical models of melanoma. Clinical trials combining these strategies are ongoing, and mature data regarding response rates and durability are not yet available. Synergy may ultimately be apparent; however, it has also become clear that complexities exist regarding toxicity when combining these therapies. Nonetheless, this increased appreciation of the complex interplay between oncogenic mutations and antitumor immunity has opened up tremendous opportunities for studying targeted agents and immunotherapy in combination, which extends far beyond melanoma to other solid tumors and also to hematologic malignancies.
Article
Since the regulatory approval of ipilimumab in 2011, the field of cancer immunotherapy has been experiencing a renaissance. This success is based on progress in both preclinical and clinical science, including the development of new methods of investigation. Immuno-oncology has become a sub-specialty within oncology owing to its unique science and its potential for substantial and long-term clinical benefit. Immunotherapy agents do not directly attack the tumour but instead mobilize the immune system - this can be achieved through various approaches that utilize adaptive or innate immunity. Therefore, immuno-oncology drug development encompasses a broad range of agents, including antibodies, peptides, proteins, small molecules, adjuvants, cytokines, oncolytic viruses, bi-specific molecules and cellular therapies. This Perspective summarizes the recent history of cancer immunotherapy, including the factors that led to its success, provides an overview of novel drug-development considerations, summarizes three generations of immunotherapies that have been developed since 2011 and, thus, illustrates the breadth of opportunities these new generations of immunotherapies represent.
Article
Background: Nivolumab (a programmed death 1 [PD-1] checkpoint inhibitor) and ipilimumab (a cytotoxic T-lymphocyte-associated antigen 4 [CTLA-4] checkpoint inhibitor) have been shown to have complementary activity in metastatic melanoma. In this randomized, double-blind, phase 3 study, nivolumab alone or nivolumab plus ipilimumab was compared with ipilimumab alone in patients with metastatic melanoma. Methods: We assigned, in a 1:1:1 ratio, 945 previously untreated patients with unresectable stage III or IV melanoma to nivolumab alone, nivolumab plus ipilimumab, or ipilimumab alone. Progression-free survival and overall survival were coprimary end points. Results regarding progression-free survival are presented here. Results: The median progression-free survival was 11.5 months (95% confidence interval [CI], 8.9 to 16.7) with nivolumab plus ipilimumab, as compared with 2.9 months (95% CI, 2.8 to 3.4) with ipilimumab (hazard ratio for death or disease progression, 0.42; 99.5% CI, 0.31 to 0.57; P<0.001), and 6.9 months (95% CI, 4.3 to 9.5) with nivolumab (hazard ratio for the comparison with ipilimumab, 0.57; 99.5% CI, 0.43 to 0.76; P<0.001). In patients with tumors positive for the PD-1 ligand (PD-L1), the median progression-free survival was 14.0 months in the nivolumab-plus-ipilimumab group and in the nivolumab group, but in patients with PD-L1-negative tumors, progression-free survival was longer with the combination therapy than with nivolumab alone (11.2 months [95% CI, 8.0 to not reached] vs. 5.3 months [95% CI, 2.8 to 7.1]). Treatment-related adverse events of grade 3 or 4 occurred in 16.3% of the patients in the nivolumab group, 55.0% of those in the nivolumab-plus-ipilimumab group, and 27.3% of those in the ipilimumab group. Conclusions: Among previously untreated patients with metastatic melanoma, nivolumab alone or combined with ipilimumab resulted in significantly longer progression-free survival than ipilimumab alone. In patients with PD-L1-negative tumors, the combination of PD-1 and CTLA-4 blockade was more effective than either agent alone. (Funded by Bristol-Myers Squibb; CheckMate 067 ClinicalTrials.gov number, NCT01844505.).