Paula M Wagner1,2, Natalia M Monjes1,2, Mario E Guido1,2. 1. CIQUIBIC-CONICET, Facultad de Ciencias Químicas, Universidad Nacional de Córdoba, Córdoba, Argentina. 2. Departamento de Química Biológica "Ranwel Caputto," Facultad de Ciencias Químicas, Universidad Nacional de Córdoba, Córdoba, Argentina.
Carcinogenesis is a complex and multi-etiological process resulting in the
accumulation of genetic alterations primarily in genes involved in the
regulation of signaling pathways relevant to the control of cell growth and
division (reviewed in Hanahan and Weinberg, 2011). Neoplastic processes include a
number of typical characteristics such as sustained proliferative
activation, growth suppressor evasion, cell death resistance, replicative
immortality, induction of angiogenesis, and invasiveness and metastasis, all
of which are based on genome instability and inflammation.Under physiological conditions, circadian clocks are near 24-h endogenous
oscillators that control a complex net of physiological and behavioral
processes such as the daily sleep and wake cycle, body temperature, feeding
behavior, hormone secretion, drug and xenobiotic metabolism, glucose
homeostasis, and cell cycle progression (Lowrey and Takahashi, 2004; Bell-Pedersen et al.,
2005). At the cellular level, a redox/metabolic oscillator
(R/MO) has been described to interact with the circadian molecular clock
(Dibner and
Schibler, 2015; Wagner et al., 2018); this R/MO
has been shown to be ancestral and highly conserved through evolution
(review in Edgar et al.,
2012). Taken together, we may infer that the cellular clock
that temporarily controls cellular processes is made up of a molecular clock
(transcription/translation feedback loop) and an R/MO. In mammals,
disruption of circadian rhythms increases cancer incidence and metabolic
disorders. Cell-autonomous clocks are composed of a
transcription–translation-based feedback loop made up of a set of genes that
include Clock (and its paralogue Npas2)
and Bmal1 as activator components and
Per1, Per2, Cry1, and
Cry2 as repressor components.(King et al., 1997; Gekakis et al.,
1998). The entire cycle of transcription and translation takes
approximately 24 h to be completed. In addition, the CLOCK–BMAL1 complex may
activate a second alternative cycle involving the nuclear receptors REV-ERBα
and REV-ERBβ which compete at the retinoic acid-related orphan receptor
(ROR)-binding elements with the activators RORα, RORβ, and RORγ (Preitner et al.,
2002; Sato
et al., 2004; Zhang et al., 2015). The rhythmic
expression of REV-ERBα/β leads to the repression of BMAL1 and CLOCK, which
in turn induces a rhythm in these genes that is in antiphase with period
(PER) expression rhythms (Preitner et al., 2002). In fact,
REV-ERBs and RORs are crucial components of the circadian clock that links
the core circadian oscillator to the regulation of clock-controlled genes,
which in turn regulate metabolic pathways and several physiological
processes, including metabolism, development, and immunity. In consequence,
loss-of-function studies both in vitro and in
vivo support the REV-ERB key role in lipid metabolism,
regulation of plasma glucose levels (Delezie et al., 2012; Solt et al.,
2012), as well as the oxidative capacity of skeletal muscle and
mitochondrial biogenesis (Woldt et al., 2013).The development and characterization of pyrrole derivatives SR9009 and SR9011
(Solt et al.,
2012) as specific REV-ERB agonists opened up the possibility of
targeting these receptors to treat several circadian disorders, including
metabolic diseases (obesity, dyslipidemia, and glucose intolerance; Green et al.,
2008; Bass
and Takahashi, 2010; Bass, 2012; Eckel-Mahan and Sassone-Corsi,
2013; Gamble and Young, 2013), sleep disorders (Solt et al.,
2012) and cancer (Sulli et al., 2018). Indeed, pharmacological modulation of
circadian rhythms by these agonists affects tumor cell viability by
restraining pathways that are aberrantly activated in cancer (Sulli et al.,
2018). Consistent with the range of metabolic effects noted in
REV-ERBα-null mice, pharmacological activation of REV-ERB with SR9009 and
SR9011 had additional metabolic effects in mice including weight loss in
diet-induced obesemice, events associated with an increase in energy
expenditure without alterations in locomotor behavior or food intake (Solt et al.,
2012). Taking into account the role of REV-ERBs on lipid, glucose,
and energetic metabolism regulation and the high metabolic demands of cancer
cells, we postulated that a pharmacological modulation of circadian
components repressors such as REV-ERBs could alter metabolic pathways that
compromise cancer cell survival.Although disruption of the biological clock altering metabolic pathways can
lead to diverse pathologies, little is known about the temporal regulation
of cellular metabolism in tumor cells. Glioblastoma multiforme (GBM) is the
most aggressive human brain tumor characterized by the aberrant
proliferation growth of glial-like tumor cells. In this connection, the
humanglioblastomaT98G cells constitute an appropriate cancer cell model to
investigate the tumor-intrinsic circadian clock. In our previous work, we
found that proliferating T98G cells contain a functional intrinsic
oscillator that controls diverse metabolic processes including lipid
metabolism, levels of reactive oxygen species (ROS), peroxiredoxin oxidation
cycles and susceptibility to treatment with the proteasome inhibitor
Bortezomib (BOR; Wagner
et al., 2018).Here, we investigated the effects of SR9009 treatment in T98G cell cultures and
compared it with BOR treatment assessing cell viability, differential time
responses to chemotherapy after synchronization with dexamethasone (DEX),
and metabolic processes involving ROS and lipid droplet (LD) levels. In
addition, we extended these studies to HepG2 cells, a nonneuronal tumor cell
line derived from humanliver hepatocellular carcinoma.
Material and Methods
Cell Cultures
T98G cells are derived from the human GBM (ATCC, Cat. No. CRl-1690, RRUD:
CVCL0556, Manassas, VA, USA) and tested positive for glial cell
markers and negative for mycoplasma contamination. HepG2 cells (ATCC,
Cat. No. HB-8065, RRID:
CVCL0027) are derived from the human hepatocellular
carcinoma. Both cell lines were grown in Dulbecco's modified Eagle´s
medium (DMEM) (Gibco, BRL, Invitrogen, Carlsbad, CA, USA) supplemented
with 10% fetal bovine serum (FBS) according to ( Portal et al., 2007) at
37°C and 5% CO2.
SR9009 Treatment and Determination of Cell Viability by MTT
Assay
Cells were plated in 96-well plates at a density of 1 × 104
and were allowed to attach overnight at 37°C. Cultured cells were
incubated with DMSO (vehicle) or REV-ERB agonist (SR9009) at different
concentrations (10, 20, and 40 µM) and incubation time (24, 48, and
72 h). Stock solutions of SR9009 were resuspended in DMSO to a final
concentration of 50 mM (stock solution) according to manufacturer’s
instructions. After incubation, 10 µL of
3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT)
reagent (5 mg/mL; Sigma) were added to each well, and plates were
further incubated for 2 h at 37°C as described (Vlachostergios et al.,
2013). Then, 100 µL of DMSO:isopropanol (1:1, v/v) was added to
each well followed by incubation for a few minutes at room temperature
protected from light. Samples were analyzed at a wavelength of 570 nm
with a reference at 650 nm in an Epoch Microplate Spectrophotometer.
Vehicle-treated cells (DMSO) were considered as 100% of viability.In other series of experiments, 5 × 103 HepG2 cells were
allowed to attach overnight at 37°C in a 96-well plate. Cultured cells
were incubated with DMSO (vehicle) or REV-ERB agonist (SR9009) at
different concentrations (5, 10, 20, and 40 µM) for 96 h. Then, cell
viability was analyzed by MTT assay considering vehicle-treated cells
(DMSO) as 100% of viability.
SR9009 Treatment of T98G Cells and Determination of Cell Viability by
alamarBlue Assay
Cells were plated in 96-well plates at the density of
1.5 × 103 and allowed to attach overnight at 37°C.
Cultured cells were incubated with DMSO (vehicle) or REV-ERB agonist
(SR9009) at final concentration of 20 µM for 48 or 72 h. After
incubation, 10 µL of alamarBlue reagent (Invitrogen) were added to
each well (final volume: 100 µL in 96-well plates) and plates were
further incubated for 3 h at 37°C protected from light. Fluorescence
intensity was analyzed at an excitation wavelength of 540 to 570 nm,
and fluorescence emission reads at 580 to 610 nm in a Biotek
microplate reader. Vehicle-treated cells (DMSO) were considered as
100% of viability.
Differential Temporal Susceptibility to SR9009 or BOR
Treatment
T98G cells were plated in 96-well plates at the density of
1 × 104 and allowed to attach overnight in a
CO2 incubator at 37°C. Cell cultures were
synchronized by a 20-min shock with 100 nM DEX and were treated with
SR9009 (20 µM 48 h) or BOR (500 nM 36 h; Comba et al., 2019) at
different times postsynchronization. After incubation, cell viability
was determined by MTT assay as described earlier and analyzed at 570
nm with a reference at 650 nm in an Epoch Microplate
Spectrophotometer. Vehicle-treated cells (DMSO) were considered as
100% of viability.
Combined Chemotherapeutic Treatments on T98G Cells
In other series of experiment, T98G cells were treated with both drugs
together to evaluate the additive/synergistic effect between them. For
this, T98G cells were synchronized by a 20 min shock with 100 nM DEX
at 37°C and maintained in 5% FBS-DMEM. Cells were treated with
different drug concentrations alone or in combination as follows: BOR
(50 or 500 nM), SR9009 (10 or 20 µM), BOR (50 nM) + SR9009 (10 µM), or
BOR (500 nM) + SR9009 (20 µM), 18 h postsynchronization, and were
incubated for 36 h at 37°C. Cell viability was analyzed by MTT assay
as described earlier. Vehicle-treated cells (DMSO) were considered as
100% of viability.
Cell Cycle Progression Analysis in SR9009-Treated T98G Cells
T98G cells incubated with DMSO (vehicle) or SR9009 (20 µM) were arrested
in serum-free DMEM for 36 h. Then, the medium was removed and either
vehicle or SR9009-treated cells were stimulated with 20% serum for
16 h in the presence of DMSO or SR9009, respectively. Finally, cells
harvested by trypsinization were washed in cold phosphate buffered
saline (PBS) and fixed with cold 70% ethanol at 20°C for at least
24 h. Cell pellets were resuspended in 150 µL of staining solution
(PBS containing 50 µg/mL propidium iodide and 10 µg RNAse A) as
reported (Acosta-Rodríguez et al., 2013). Cell cycle analysis was
performed by a flow cytometer running at least 50,000 cells. The
analysis program used was FlowJo software (Verity Software House,
Topsham, ME, USA).
Redox State in SR9009-Treated Cells
Redox state was analyzed in T98G cells incubated with SR9009 (20 µM, 48
h) or BOR (500 nM, 24 h) and in SR9009-treated-HepG2 cells (40 µM,
48 h). Briefly, the culture medium was removed and cells were washed
with cold PBS 1X and harvested by trypsinization. Then, cells were
incubated with 2,7-dichlorodihydrofluorescein diacetate at 2 µM final
concentration for 40 min at 37°C, washed twice with PBS 1X, and the
fluorescence intensity was measured by flow cytometry at 530 nm when
the sample was excited at 485 nm (Eruslanov and Kusmartsev,
2010). Cells without the fluorescent indicator were used
as negative control, and propidium iodide (50 µg/mL) staining was used
to discriminate viable cells. FlowJo software was
used to analyze fluorescence intensity (Verity Software House).
Determination of LDs on Cells Treated With SR9009 or BOR
T98G cells were incubated with SR9009 (20 µM, 48 h) or BOR (500 nM, 24
h), and LD levels were analyzed by confocal microscopy and flow
cytometry. For microscopy visualization, cultured cells were fixed for
15 min in 4% paraformaldehyde in PBS and washed twice with PBS 1X.
Then, cells were incubated with Nile Red (1 µg/mL, Sigma, Tokyo,
Japan) for 15 min at room temperature protected from light. Coverslips
were finally washed thoroughly and visualized by confocal microscopy
(FV1200; Olympus, Tokyo, Japan). Cellular nuclei were visualized by
4′,6-diamidino-2-phenylindole (DAPI) staining. Average size
quantification of LD was carried out with ImageJ
software.For flow cytometry analysis, either control or treated cells were
harvested by trypsinization and washed twice with PBS 1X. Cell pellets
were resuspended in 200 µL of PBS containing 1µg/mL Nile Red and were
incubated for 15 min at room temperature protected from light. Then,
cells were washed twice with PBS 1X, and the fluorescence intensity
was measured by flow cytometry (BD LSRFortessa™ cell analyzer) with
575/26 filter. A negative control including cells without the
fluorescent indicator was used. FlowJo software was used to analyze
fluorescence intensity.HepG2 cells were treated with SR9009 (10 or 40 µM, 96 h), and LD content
was assessed by Nile Red (1 µg/mL) staining as described earlier.
Average size and area of LDs were performed by the ImageJ software.
Cellular nuclei were visualized by DAPI staining.
Immunocytochemistry
Immunocytochemistry was performed as described (Morera et al., 2016).
Briefly, cultured cells were fixed for 15 min in 4% paraformaldehyde
in PBS and 10 min in methanol. Coverslips were washed in PBS, were
treated with blocking buffer (PBS supplemented with 0.1% bovine serum
albumin, 0.1% Tween 20, and 0.1% glycine) and were incubated overnight
with primary antibodies (Table 1) at 4°C. Coverslips
were washed 3 times and were incubated with goat antirabbit
immunoglobulin G (IgG; Jackson 549 antibody 1:1,000) or goat antimouse
IgG (Jackson 488 antibody 1:1,000) for 1 h at room temperature.
Coverslips were finally washed thoroughly and visualized by confocal
microscopy (FV1200; Olympus). Cellular nuclei were visualized by DAPI
staining.
Table 1.
Antibody List.
Antibody
Host
Catalogue
Dilution
Glutamine synthase
Mouse
Millipore Cat# MAB302, RID:AB_2110656
1:100
Vimentin
Mouse
Sigma-Aldrich Cat# V5255, RRID:AB_477625
1:750
GFAP
Rabbit
Agilent Cat# Z0334, RRID:AB_10013382
1:250
REV-ERBα
Mouse
Santa Cruz Biotechnology Cat# sc-100910,
RRID:AB_2154647
1:100
Note. Summary of antibodies used
indicating antibody name, host, catalogue number,
and dilution for immunochemistry. GFAP = glial
fibrillary acidic protein.
Antibody List.Note. Summary of antibodies used
indicating antibody name, host, catalogue number,
and dilution for immunochemistry. GFAP = glial
fibrillary acidic protein.
Statistics
Statistical analyses involved a one- or two-way analysis of variance
(ANOVA) to test the time or drug treatment effects and Kruskal–Wallis
(K-W), the nonparametric one-way ANOVA or Scheirer–Ray–Hare test when
the normality assumption of residuals was violated. Pairwise
comparisons involved the Student t test, Bonferroni,
or Dunn–Bonferroni post hoc when appropriate as stated in figure
legends. For Scheirer–Ray–Hare test, all analyses were followed by K-W
test with Bonferroni correction as post hoc analysis. Data are
expressed as mean ± standard error of the mean. In all cases,
significance was considered at p < .05.
Results
Here, we investigated SR9009 effects and compared it with BOR, a proteasome
inhibitor previously used, on T98G cell viability, differential chemotherapy
time responses, and underlying metabolic processes concerning ROS and LD
levels. Also, we extended these studies to HepG2 cells to evaluate the
SR9009 effects on cell viability, LD, and ROS levels.
Characterization of T98G Cells and Susceptibility to SR9009
Treatment
HumanT98G cells kept in culture under proliferative conditions (5%
FBS-DMEM) expressed typical markers for glial cells such as vimentin,
glutamine synthase, and glial fibrillary acidic protein (Figure 1(a) to
(c)) as well as the circadian clock component REV-ERBα
(Figure
1(d)). In addition, T98G cells were previously shown to
express the clock protein PER1 and display temporal fluctuations on
PER1-like protein by immunocytochemistry with highest levels at 18 and
24 h after synchronization (Wagner et al., 2018).
Figure 1.
Protein expression in T98G cells by immunocytochemistry and
SR9009 treatment effect. T98G cells express typical
markers of glial cells such as vimentin (a—green) and GS
(b—green) visualized by immunofluorescence with specific
primary antibodies and confocal microscopy. T98G cells
were incubated with vehicle (DMSO) or SR9009 (20 µM) for
48 h and immunolabeled for GFAP (c and e—red) or REV-ERBα
(d and f—green) with specific primary antibodies and
confocal microscopy; insets on the right further magnified
a single cell in both conditions (DMSO and SR9009
treatment). See “Materials and Methods” section for
further detail. Scale bar = 10 µm. GFAP = glial fibrillary
acidic protein; GS = glutamine synthase.
Protein expression in T98G cells by immunocytochemistry and
SR9009 treatment effect. T98G cells express typical
markers of glial cells such as vimentin (a—green) and GS
(b—green) visualized by immunofluorescence with specific
primary antibodies and confocal microscopy. T98G cells
were incubated with vehicle (DMSO) or SR9009 (20 µM) for
48 h and immunolabeled for GFAP (c and e—red) or REV-ERBα
(d and f—green) with specific primary antibodies and
confocal microscopy; insets on the right further magnified
a single cell in both conditions (DMSO and SR9009
treatment). See “Materials and Methods” section for
further detail. Scale bar = 10 µm. GFAP = glial fibrillary
acidic protein; GS = glutamine synthase.When cells were treated with the REV-ERB-specific agonist SR9009 at
different concentrations going from 10 to 40 µM for 24, 48, or 72 h
(Figures
1 and 2(a)), significant effects on cell morphology (Figure 1(e) and
(f)) and reduction in cell viability were observed at
final concentrations of 20 and 40 µM for 48 and 72 h (Figure 2(a))
as compared with vehicle-treated controls
(p < .0001 by K-W). It is noteworthy that a
significant decrease in cell viability is observed after SR9009
treatment with only approximately 20% of cells remaining viable under
the tested conditions (20 and 40 µM of SR9009 for 72 h). Moreover, a
significant reduction in cell viability was also observed on
SR9009-treated HepG2 cells (40 µM for 96 h;
p < .0002 by K-W; Figure 2(b)). Nevertheless,
although hepatic tumor cells seemed to be more resistant to
chemotherapy because higher drug concentrations and longer treatment
durations were required to cause less than 25% of cell survival (40 µM
for 96 h), we cannot discard any significant drug effect in cell
viability at earlier times in combination with a higher drug
concentration.
Figure 2.
Cell susceptibility to SR9009 treatment in cultures of T98G
(a) and HepG2 (b) cells. (a) T98G cells were treated with
different SR9009 concentrations (10, 20, and 40 µM) for
24, 48, or 72 h at 37°C. Cell viability that was analyzed
by MTT assay revealed a significant effect of SR9009
concentration (p < .001) and duration
of treatment (p < .05) but not of
interaction by Scheirer–Ray–Hare test. Post hoc
comparisons revealed that viability of T98G cells
incubated with a final concentration of 10 µM of SR9009
differed from values of cells treated with 20 or 40 µM
(**p < .017) while 24 h of
treatment differed from those at 48 h or 72 h
(**p < .017). The results are
mean ± standard error of the mean of two independent
experiments (n = 5–6/group). (b) HepG2
cells were treated with different SR9009 concentrations
(5, 10, 20, and 40 µM) for 96 h. A significant reduction
in cell viability was observed when HepG2 cells were
treated with 40 µM for 96 h as compared with untreated
cells (***p < .0002 by K-W). The
results are mean ± standard error of the mean of two
independent experiments
(n = 5–6/group).
Cell susceptibility to SR9009 treatment in cultures of T98G
(a) and HepG2 (b) cells. (a) T98G cells were treated with
different SR9009 concentrations (10, 20, and 40 µM) for
24, 48, or 72 h at 37°C. Cell viability that was analyzed
by MTT assay revealed a significant effect of SR9009
concentration (p < .001) and duration
of treatment (p < .05) but not of
interaction by Scheirer–Ray–Hare test. Post hoc
comparisons revealed that viability of T98G cells
incubated with a final concentration of 10 µM of SR9009
differed from values of cells treated with 20 or 40 µM
(**p < .017) while 24 h of
treatment differed from those at 48 h or 72 h
(**p < .017). The results are
mean ± standard error of the mean of two independent
experiments (n = 5–6/group). (b) HepG2
cells were treated with different SR9009 concentrations
(5, 10, 20, and 40 µM) for 96 h. A significant reduction
in cell viability was observed when HepG2 cells were
treated with 40 µM for 96 h as compared with untreated
cells (***p < .0002 by K-W). The
results are mean ± standard error of the mean of two
independent experiments
(n = 5–6/group).In addition, to further support these observations, cell viability was
also analyzed by alamarBlue assay after T98G cells incubation with
SR9009 (20 µM) for 48 or 72 h at 37°C. Similar to findings found for
MTT assay, a significant reduction in cell viability was observed when
cells were treated with SR9009 (20 µM) for 48 or 72 h
(p < .0005 by ANOVA; Supplementary Figure
1).
Differential Temporal Susceptibility to SR9009 Treatment
T98G cells were synchronized with DEX (100 nM) and were treated with
SR9009 (20 µM) for 48 h at different times postsynchronization along
36 h. Cell viability was analyzed by MTT assay in SR9009-treated
cells, and showed a significant temporal effect of drug treatment,
with the lowest levels of viability during a time window going from 18
to 30 h after synchronization. The statistical analysis clearly
revealed a significant effect of treatment versus time
(p < .0041 by K-W; Figure 3(a)). These
observations agree with those previously found in synchronized T98G
cells treated with BOR (500 nM) for 36 h (Wagner et al., 2018)
exhibiting the lowest cell viability in a time window going from 12 to
24 h postsynchronization (p < .0007 by K-W; Figure
3(b)).
Figure 3.
Temporal response to SR9009 (a) or BOR (b) treatment in T98G
cells. (a) Cells were synchronized with DEX (100 nM), and
SR9009 was added to a final concentration of 20 µM at
different times postsynchronization for 48 h. Cell
viability was analyzed by MTT assay as described in
“Materials and Methods” section. A significant temporal
variation was observed in levels of T98G cell viability
(p < .004 by K-W). Pairwise
comparisons by Dunn–Bonferroni post hoc revealed that the
treatment beginning at 6 h post synchronization
significantly differed from those starting at 18, 24, and
30 h after synchronization. The results are
mean ± standard error of the mean of three independent
experiments (n = 5–6/group). (b)
DEX-synchronized cells were treated with BOR (500 nM) for
36 h at different times postsynchronization and cell
viability assessed by MTT assay. A significant time effect
was observed in levels of T98G cell viability
(p < .0007 by K-W) as previously
observed in Wagner et al.
(2018). Results are mean ± standard error of
the mean from one representative experiment
(n = 5–6/group).
BOR = Bortezomib.
Temporal response to SR9009 (a) or BOR (b) treatment in T98G
cells. (a) Cells were synchronized with DEX (100 nM), and
SR9009 was added to a final concentration of 20 µM at
different times postsynchronization for 48 h. Cell
viability was analyzed by MTT assay as described in
“Materials and Methods” section. A significant temporal
variation was observed in levels of T98G cell viability
(p < .004 by K-W). Pairwise
comparisons by Dunn–Bonferroni post hoc revealed that the
treatment beginning at 6 h post synchronization
significantly differed from those starting at 18, 24, and
30 h after synchronization. The results are
mean ± standard error of the mean of three independent
experiments (n = 5–6/group). (b)
DEX-synchronized cells were treated with BOR (500 nM) for
36 h at different times postsynchronization and cell
viability assessed by MTT assay. A significant time effect
was observed in levels of T98G cell viability
(p < .0007 by K-W) as previously
observed in Wagner et al.
(2018). Results are mean ± standard error of
the mean from one representative experiment
(n = 5–6/group).
BOR = Bortezomib.
Effects of Cell Cycle Progression of SR9009 Treatment on T98G Cells
To further investigate whether SR9009 treatment alters cell cycle
progression, T98G cells were arrested in serum-free medium for 36 h in
the presence of DMSO (vehicle) or SR9009 (20 µM). Then, medium was
removed and either control or treated cells were stimulated with 20%
serum for 16 h in the presence of DMSO or SR9009 respectively. Flow
cytometry analysis showed a higher proportion of SR9009-treated cells
(∼58%) in
G0/G1
phases after serum stimulation as compared with vehicle-treated cells
(∼43%; p < .0053 by t test). By
contrast, vehicle-treated cells showed a higher proportion of cells in
S phase (∼40%) with respect to SR9009-treated cells (∼22%;
p < .0121 by t test; Figure 4(a) to
(c)).
Figure 4.
Effects of SR9009 treatment on cell cycle distribution of
T98G cells. T98G cells incubated with DMSO (vehicle) or
SR9009 (20 µM) were arrested in serum-free DMEM for 36 h.
Then, the medium was removed and either vehicle or treated
cells were stimulated with 20% fetal bovine serum for 16 h
in the presence of DMSO or SR9009 as appropriate. Cell
cycle phases were analyzed by staining with propidium
iodide and flow cytometry. Representative cell cycle
distributions are shown in control (a) or SR9009-treated
cells (b). (c) Quantification of the percentage of cells
in each phase showed a higher proportion of SR9009-treated
T98G cells in
G0–G1
phase
(G0–G1
*p < .0053, S
*p < .01 by t
test). The results are mean ± standard error of the mean
of three independent experiments
(n = 4/group).
Effects of SR9009 treatment on cell cycle distribution of
T98G cells. T98G cells incubated with DMSO (vehicle) or
SR9009 (20 µM) were arrested in serum-free DMEM for 36 h.
Then, the medium was removed and either vehicle or treated
cells were stimulated with 20% fetal bovine serum for 16 h
in the presence of DMSO or SR9009 as appropriate. Cell
cycle phases were analyzed by staining with propidium
iodide and flow cytometry. Representative cell cycle
distributions are shown in control (a) or SR9009-treated
cells (b). (c) Quantification of the percentage of cells
in each phase showed a higher proportion of SR9009-treated
T98G cells in
G0–G1
phase
(G0–G1
*p < .0053, S
*p < .01 by t
test). The results are mean ± standard error of the mean
of three independent experiments
(n = 4/group).
SR9009 Effect on Redox and Lipid Metabolism
To investigate whether oxidative stress could be involved in the effects
of SR9009 treatment in cell viability, we analyzed ROS levels and
compared it with those in BOR-treated cells. To this end, T98G cells
were incubated with SR9009 (20 µM) for 48 h, and the redox state was
analyzed by incubation with 2′,7′-dichlorodihydrofluorescein diacetate
(2 µM) for 40 min at 37°C. When fluorescence intensity was measured by
flow cytometry, a significant reduction in ROS levels was seen in
SR9009-treated cells as compared with vehicle-treated controls
(p < .007 by t test; Figure 5(a)).
In contrast, T98G cells previously incubated with BOR (500 nM) for
24 h showed higher levels of ROS with respect to those in control
cells (p < .04 by t test; Figure 5(b)).
Moreover, SR9009 (40 µM) treatment in HepG2 cells for 96 h also showed
a significant decreased on ROS levels as compared with vehicle-treated
cells (p < .0001 by ANOVA; Figure 7(f)).
Figure 5.
ROS levels in T98G cells treated with SR9009 or BOR. T98G
cells were treated either with SR9009 (a, 20 µM 48 h) or
BOR (b, 500 nM 24 h), and ROS levels were analyzed with
the fluorescent probe 2,7-dichlorodihydrofluorescein
diacetate to a final concentration of 2 µM as described in
“Materials and Methods” section. Fluorescence intensity
was analyzed by flow cytometry. The results are mean ±
standard error of the mean of two/three independent
experiments (n = 3–5/group). The
statistical analysis revealed a significant effect for
SR9009 (**p < .001 by
t test) and for BOR
(*p < .04 by t
test) as compared with vehicle-treated controls.
BOR = Bortezomib.
Figure 7.
Lipid droplets (LDs) and ROS levels in HepG2 cells treated
with SR9009. (a to c) Representative microphotographs of
Nile Red-stained LDs in HepG2 cells treated with the
vehicle (a) or SR9009 (b, 10 µM; c, 40 µM). Scale
bar = 10 µm. (d) Bar graph showing quantification of LD
average size in SR9009-treated HepG2 cells that revealed a
significant increase as compared with controls
(***p < .0001 by ANOVA,
Bonferroni post hoc). (e) Bar graph showing quantification
of LD percentage area in SR9009-treated HepG2 cells. A
significant increase was observed with 40 µM SR9009
treatment for 96 h (***p < .0001 by
K-W). (f) Determination of ROS levels by flow cytometry in
HepG2 cells treated with SR9009 (5 and 40 µM for 96 h). A
significant reduction was observed at 40 µM SR9009-treated
cells as compared with vehicle and 5 and 20 µM of SR9009
(***p < .0001 by ANOVA,
Bonferroni post hoc). ROS = reactive oxygen species.
ROS levels in T98G cells treated with SR9009 or BOR. T98G
cells were treated either with SR9009 (a, 20 µM 48 h) or
BOR (b, 500 nM 24 h), and ROS levels were analyzed with
the fluorescent probe 2,7-dichlorodihydrofluorescein
diacetate to a final concentration of 2 µM as described in
“Materials and Methods” section. Fluorescence intensity
was analyzed by flow cytometry. The results are mean ±
standard error of the mean of two/three independent
experiments (n = 3–5/group). The
statistical analysis revealed a significant effect for
SR9009 (**p < .001 by
t test) and for BOR
(*p < .04 by t
test) as compared with vehicle-treated controls.
BOR = Bortezomib.Figure 5.In other series of experiments, we proceeded to evaluate the LD levels
after treatments with SR9009 or BOR. LDs are cytoplasmic organelles
responsible for storing the excess of cellular lipids (Farese and
Walther, 2009; Beller et al., 2010; Brasaemle and
Wolins, 2012) and mainly involved in energy storage.To investigate whether SR9009 treatment alters lipid accumulation in LDs,
we used Nile Red which is intensely fluorescent and can serve as a
sensitive vital stain for the detection of cytoplasmic LDs. To this
end, SR9009 or BOR-treated cells were stained with Nile Red and LDs
visualized by confocal microscopy and flow cytometry. First, LDs in
SR9009-treated cells showed a higher average size as compared with
vehicle-treated cells (p < .003 by
t test; Figure 6(a) to (c)). In
agreement with this, a higher fluorescence intensity was visualized by
flow cytometry either in SR9009 or BOR-treated cells as compared with
untreated cells (p < .002 and
p < .025, respectively, by t
test; Figure 6(d) to
(f)).
Figure 6.
Lipid droplet (LD) levels in T98G cells treated with SR9009
or BOR. T98G cells were treated either with SR9009 (20 µM,
48 h; a to d) or BOR (500 nM, 24 h; e to f) and LD levels
were analyzed by Nile Red staining. Representative
microphotography of LDs observed in vehicle (a) or
SR9009-treated T98G cells (b) stained with Nile Red were
visualized by confocal microscopy, further magnified in
the insets on the right. Scale bar = 10 µm. (c) Bar graphs
showing quantification of average size of LDs in
SR9009-treated T98G cells. Results revealed a higher
average size of LDs in cells treated with SR9009
(*p < .003 by t
test) as compared with controls. (d and f) Bar graphs
showing quantification of fluorescence intensity of LDs
stained with Nile Red and analyzed by flow cytometry. In
both treatments, results showed a higher fluorescence
intensity when T98G cells were treated with SR9009 (d,
*p < .002 by t
test) or BOR (f, *p < .025 by
t test) as compared with controls.
(e) Representative histograms of fluorescence intensity of
LDs were analyzed by flow cytometry in BOR-treated cells.
Data are mean ± standard error of the mean. The results
are mean of three independent experiments
(n = 3–5/group).
BOR = Bortezomib.
Lipid droplet (LD) levels in T98G cells treated with SR9009
or BOR. T98G cells were treated either with SR9009 (20 µM,
48 h; a to d) or BOR (500 nM, 24 h; e to f) and LD levels
were analyzed by Nile Red staining. Representative
microphotography of LDs observed in vehicle (a) or
SR9009-treated T98G cells (b) stained with Nile Red were
visualized by confocal microscopy, further magnified in
the insets on the right. Scale bar = 10 µm. (c) Bar graphs
showing quantification of average size of LDs in
SR9009-treated T98G cells. Results revealed a higher
average size of LDs in cells treated with SR9009
(*p < .003 by t
test) as compared with controls. (d and f) Bar graphs
showing quantification of fluorescence intensity of LDs
stained with Nile Red and analyzed by flow cytometry. In
both treatments, results showed a higher fluorescence
intensity when T98G cells were treated with SR9009 (d,
*p < .002 by t
test) or BOR (f, *p < .025 by
t test) as compared with controls.
(e) Representative histograms of fluorescence intensity of
LDs were analyzed by flow cytometry in BOR-treated cells.
Data are mean ± standard error of the mean. The results
are mean of three independent experiments
(n = 3–5/group).
BOR = Bortezomib.Similar results were observed in HepG2 cells exhibiting a higher average
size of LDs after SR9009 treatment (10 and 40 µM, 96 h) as compared
with control cells (p < .0001 by ANOVA; Figure 7(a) to
(d)). Moreover, the percentage of LD area related to the
total area of each cell was increased after drug treatment (40 µM, 96
h; Figure
7(e); p < .0001 by K-W).Lipid droplets (LDs) and ROS levels in HepG2 cells treated
with SR9009. (a to c) Representative microphotographs of
Nile Red-stained LDs in HepG2 cells treated with the
vehicle (a) or SR9009 (b, 10 µM; c, 40 µM). Scale
bar = 10 µm. (d) Bar graph showing quantification of LD
average size in SR9009-treated HepG2 cells that revealed a
significant increase as compared with controls
(***p < .0001 by ANOVA,
Bonferroni post hoc). (e) Bar graph showing quantification
of LD percentage area in SR9009-treated HepG2 cells. A
significant increase was observed with 40 µM SR9009
treatment for 96 h (***p < .0001 by
K-W). (f) Determination of ROS levels by flow cytometry in
HepG2 cells treated with SR9009 (5 and 40 µM for 96 h). A
significant reduction was observed at 40 µM SR9009-treated
cells as compared with vehicle and 5 and 20 µM of SR9009
(***p < .0001 by ANOVA,
Bonferroni post hoc). ROS = reactive oxygen species.Even though SR9009 or BOR treatments showed marked effects in cell
viability, we explored whether the combination of these two drugs
could improve chemotherapeutic effects. To this end, T98G cells were
treated with BOR (50 or 500 nM), SR9009 (10 or 20 µM), and their
combination (BOR 50 nM + SR9009 10 µM or BOR 500 nM + SR9009 20 µM) at
18 h postsynchronization for 36 h, and cell viability was analyzed by
MTT assay. When BOR or SR9009 treatments were given alone at low
doses, a 60% of cells still remained viable; however, the combination
of these compounds at low concentrations (BOR 50 nM + SR9009 10 µM)
reduced cell viability to 28% (Figure 8(a)) as compared with
each drug alone (p < .003 by K-W). In addition, at
high drug concentration, 28% and 34% of cells remained viable, after
BOR or SR9009 treatment, respectively; whereas, when both drugs were
applied together to T98G cells at high doses, a significant reduction
in cell viability was observed and only 17% of cells were still viable
(p < .0001 by ANOVA; Figure 8(b)). The results
clearly demonstrated an important additive or synergistic effect of
drug combination.
Figure 8.
T98G cell susceptibility to the combined treatment with
SR9009 and BOR. T98G cells were treated with BOR (50 or
500 nM), SR9009 (10 or 20 µM) and their combination (BOR
50 nM + SR9009 10 µM or BOR 500 nM + SR9009 20 µM) at 18 h
postsynchronization for 36 h. Cell viability was analyzed
by MTT assay and results showed a significant reduction in
cell viability when T98G cells were treated with the
combination of drugs (BOR 50 nM + SR9009 10 µM
**p < .003, BOR 500 nM + SR9009
20 µM ***p < .0001 by K-W) as compared
with cells treated with each drug alone. Data are
mean ± standard error. The results are mean of three
independent experiments (n = 5–6/group).
BOR = Bortezomib.
T98G cell susceptibility to the combined treatment with
SR9009 and BOR. T98G cells were treated with BOR (50 or
500 nM), SR9009 (10 or 20 µM) and their combination (BOR
50 nM + SR9009 10 µM or BOR 500 nM + SR9009 20 µM) at 18 h
postsynchronization for 36 h. Cell viability was analyzed
by MTT assay and results showed a significant reduction in
cell viability when T98G cells were treated with the
combination of drugs (BOR 50 nM + SR9009 10 µM
**p < .003, BOR 500 nM + SR9009
20 µM ***p < .0001 by K-W) as compared
with cells treated with each drug alone. Data are
mean ± standard error. The results are mean of three
independent experiments (n = 5–6/group).
BOR = Bortezomib.
Discussion
Our results demonstrated that the pharmacological modulation of tumor-intrinsic
clock components by a specific REV-ERB agonist severely affected tumor cell
metabolism and promoted cytotoxic effects on glioma and hepatocellular
carcinoma cells. These observations showed for the first time that
glioblastoma cells can be treated pharmacologically under a time-dependent
therapy through the modulation of particular circadian clock components such
as REV-ERBs involving the control of metabolism to achieve the highest
antitumor treatment efficacy. SR9009 treatment altered the typical glial
cell morphology (Figure
1), cell viability (Figures 2 and 3), and metabolism by increasing
levels of LDs and decreasing those for ROS (Figures 5 and 6). Moreover, the treatment with
SR9009 further potentiates the effect of BOR (Figure 8), which was previously
shown to have strong effects on cell viability of glioma cells under a
circadian chronotherapy (Wagner et al., 2018). However, the mechanisms used for these
two chemotherapeutic agents seemed to be different in terms that BOR
inhibits the proteasome function while SR9009 acts on the clock-related
cellular metabolism; nevertheless, both of them were shown to substantially
elevate levels of LDs (Figures 6 and 7). Also, and remarkably, both agents exhibited a clear time
window of highest cellular susceptibility to treatment with maximal effects
from 12–18 to 24 h after DEX synchronization (Figure 3 and Wagner et al., 2018). Moreover,
when the circadian clock was disturbed by Bmal1 knock-down,
a circadian variation in BOR treatment susceptibility was still observed but
with a different phase and amplitude than that described in wild-type T98G
cells (Wagner et al.,
2018). In previous reports, proliferative T98G cells were
synchronized by DEX which is commonly used in GBM patients to reduce
inflammation or as a chemotherapy adjuvant; in fact, glucocorticoids can
inhibit cancer cell proliferation by limiting the number of cells in
S phase and additionally increasing the time spent in
the G1 phase (Kiessling et al., 2017; Wagner et al.,
2018).Results shown in Figure
4 strongly indicate that this REV-ERB agonist also affected the
cell cycle progression because approximately 60% of SR9009-treated cells
remained arrested in
G0/G1 phases
as compared with control cells after serum stimulation. It is known that GBM
is the most aggressive brain tumor and that the development of more
effective anticancer strategies can be useful for clinical use. In this
regard, the combination of both agents applied at the right temporal window
and at lower individual doses as seen in glioma cell cultures can offer an
additional opportunity to effectively treat cancer cells in a synergic
manner.Circadian rhythms are intricately linked to the regulation of metabolism, and
genetic perturbations of core clock genes lead to a range of abnormal
metabolic phenotypes in mice, including obesity, dyslipidemia, and glucose
intolerance (Green
et al., 2008; Bass and Takahashi, 2010; Bass, 2012; Eckel-Mahan and
Sassone-Corsi, 2013; Gamble and Young, 2013). In this
connection, modern life including hypercaloric diets, sedentary routines,
artificial illumination at night, the reduction in sleep hours, shiftwork,
and jetlag among others may cause circadian disorganization promoting higher
cancer risk and metabolic disorders.RORs and REV-ERBs play key roles in the regulation of metabolic pathways
linking the core circadian oscillator to the regulation of clock-controlled
genes. Loss-of-function studies both in vitro and
in vivo demonstrate that REV-ERBs have a crucial role
in lipid metabolism as seen in REV-ERBα-null mice exhibiting dyslipidemia
with elevated levels of very-low-density lipoprotein, triglyceride, and
increased serum levels of apolipoprotein C3 (Raspé et al., 2001, 2002). In this
connection, lipids are stored in LDs as neutral lipids, namely, free fatty
acids and cholesterols that are enzymatically converted to triacylglycerol
and cholesteryl esters, respectively, and then incorporated into LDs (Farese and Walther,
2009; Beller
et al., 2010; Brasaemle and Wolins, 2012). These
organelles are not only restricted to energy storage but also participate in
stress protection, protein sequestration, membrane trafficking, and
signaling having a great impact on physiology, health, and disease (Welte
and Gould, 2017). Nevertheless, the treatment with SR9009 significantly
increased average size of LDs in T98G as well as in HepG2 cells. These
observations agreed with a significant deficiency in surfactant
phospholipids such as phosphatidylcholine or accumulation of phosphatidic
acid under SR9009 treatment increasing LD fusion or coalescence (Guo et al., 2008;
Fei et al.,
2011). In fact, REV-ERB agonists were shown to be inhibitors of
autophagy and de novo lipogenesis, with selective activity
toward malignant and benign neoplasms; the accumulation of LDs may be due to
an uptake and accumulation of fatty acids (Bensaad et al., 2014) and not to
de novo synthesis of lipids as the expression of the
two key enzymes fatty acid synthase and stearoyl- CoA desaturase 1 involved
in de novo lipogenesis were decreased after REV-ERBs
agonist treatment (Sulli
et al., 2018).Interestingly, autophagy contributes to the intracellular catabolism of lipids
in hepatocytes, fibroblasts (Singh et al., 2009), and neurons
(Martinez-Vicente
et al., 2010), while the pharmacologic or genetic inhibition of
autophagy in hepatocytes leads to reduced rates of β oxidation and marked
lipid accumulation in cytosolic LDs (Singh et al., 2009). Autophagy is
an ATP-dependent process (Meijer and Codogno, 2004), and
autophagy inhibition reduces mitochondrial β-oxidation rates (Singh et al.,
2009; Heaton et al., 2010) and energy production.
Autophagy-deficient stellate cells as shown in hepatocytes may be unable to
process LDs by acid lipases, resulting in LD accumulation and decreased free
fatty acid availability, leading to decreased mitochondrial β oxidation.Moreover, BOR treatment at low concentrations (5 nM) was shown to cause lipid
accumulation associated with mitochondrial impairment (Guglielmi et al., 2017). The
mechanisms used for these two chemotherapeutic agents seemed to be different
concerning the redox state because BOR induced ROS levels while
SR9009-treated cells showed decreased levels of them. Even though the
sequence of events leading to apoptosis following proteasome inhibition by
BOR is unclear, by-products of normal cellular oxidative processes such as
ROS have been suggested as regulating the process involved in the initiation
of apoptotic signaling. Tan et al. (1998) previously showed that an increase in ROS
generation induces cytochrome c release from mitochondria. Increased levels
of ROS in BOR-treated cells were also observed in colorectal (Kim, 2012) and
humanH460nonsmall cell lung cancer cells (Ling et al., 2003) as well as in
humanleukemia cells (Yu
et al., 2004). Conversely, SR9009-treated cells showed
decreased ROS levels as compared with untreated cells for both tumor cell
lines. These results support the idea proposed by Sulli et al. (2018) suggesting
that excessive ROS production is not involved in the enhanced sensitivity of
cancer cells to SR9009 treatment.Overall, the pharmacological activation of REV-ERBs by the pyrrole derivative
SR9009 as specific agonist (Solt et al., 2012) has been
clearly shown to affect tumor cell viability restricting abnormally
activated pathways as demonstrated on different tumor cell types, namely,
brain, leukemia, breast, colon, and melanoma (Sulli et al., 2018). Therefore,
and in agreement with these previously reported observations, the antitumor
activity of SR9009 was clearly evidenced in T98G and HepG2 cells displaying
significant cytotoxic effects and pronounced metabolic changes.
Summary
T98G cells constitute a glioblastoma model to evaluate the pharmacological
modulation of tumor-intrinsic circadian clock components as anticancer
strategies. Pyrrole derivatives (SR9009) acting as specific REV-ERBs
agonists (circadian clock repressors) displayed potent in vitro activity on
cancer cell metabolism and viability.
Acknowledgments
Authors are grateful to Mrs. Susana Deza, Gabriela Schanner and Dr. Carlos Mas
for their excellent technical support and to Dr. Cesar Prucca for
experimental advice.Click here for additional data file.Supplemental material, ASN892713 Supplemental Material for
Chemotherapeutic Effect of SR9009, a REV-ERB Agonist, on the HumanGlioblastomaT98G Cells by Paula M. Wagner, Natalia M. Monjes and
Mario E. Guido in ASN Neuro
Authors: Laura A Solt; Yongjun Wang; Subhashis Banerjee; Travis Hughes; Douglas J Kojetin; Thomas Lundasen; Youseung Shin; Jin Liu; Michael D Cameron; Romain Noel; Seung-Hee Yoo; Joseph S Takahashi; Andrew A Butler; Theodore M Kamenecka; Thomas P Burris Journal: Nature Date: 2012-03-29 Impact factor: 49.962
Authors: Rachel S Edgar; Edward W Green; Yuwei Zhao; Gerben van Ooijen; Maria Olmedo; Ximing Qin; Yao Xu; Min Pan; Utham K Valekunja; Kevin A Feeney; Elizabeth S Maywood; Michael H Hastings; Nitin S Baliga; Martha Merrow; Andrew J Millar; Carl H Johnson; Charalambos P Kyriacou; John S O'Neill; Akhilesh B Reddy Journal: Nature Date: 2012-05-16 Impact factor: 49.962
Authors: Gabriele Sulli; Amy Rommel; Xiaojie Wang; Matthew J Kolar; Francesca Puca; Alan Saghatelian; Maksim V Plikus; Inder M Verma; Satchidananda Panda Journal: Nature Date: 2018-01-10 Impact factor: 49.962