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Inhibition of the Warburg effect with a natural compound reveals a novel measurement for determining the metastatic potential of breast cancers

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Metabolism is an important differentiating feature of cancer cells. Lactate dehydrogenases (LDH) A/B are metabolically important proteins and are involved in the critical step of inter-conversion of lactate to pyruvate. Panepoxydone (PP), a natural NF-kB inhibitor, significantly reduces the oxygen consumption and lactate production of MCF-7 and triple negative (MDA-MB-231, MDA-MB-468 and MDA-MB-453) breast cancer cells. We further observed that PP inhibited mitochondrial membrane potential and the ATP synthesis using flow cytometry. PP also up-regulated LDH-B and down-regulated LDH-A expression levels in all breast cancer cells to similar levels observed in HMEC cells. Over-expression of LDH-B in cancer cell lines leads to enhanced apoptosis, mitochondrial damage, and reduced cell migration. Analyzing the patient data set GDS4069 available on the GEO website, we observed 100% of non TNBC and 60% of TNBC patients had less LDH-B expression than LDH-A expression levels. Herein we report a new term called Glycolytic index, a novel method to calculate utilization of oxidative phosphorylation in breast cancer cells through measuring the ratio of the LDH-B to LDH-A. Furthermore, inhibitors of NF-kB could serve as a therapeutic agent for targeting metabolism and for the treatment of triple negative breast cancer.
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Oncotarget1
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www.impactjournals.com/oncotarget/ Oncotarget, Advance Publications 2014
Inhibition of the Warburg effect with a natural compound
reveals a novel measurement for determining the metastatic
potential of breast cancers
Ritu Arora1, David Schmitt1, Balasubramanyam Karanam2, Ming Tan1, Clayton
Yates2, Windy Dean-Colomb1,3
1Department of Oncologic Sciences, University of South Alabama Mitchell Cancer Institute, Mobile, AL 36604, USA
2Department of Biology and Center for Cancer Research, Tuskegee University, Tuskegee, AL 36088, USA
3Department of Oncologic Research, University Hospital and Clinics, Lafayette General Health, Lafayette, LA 70503, USA
Correspondence to:
Windy Dean-Colomb, e-mail: wmdeancolomb@lgh.com
Keywords: Warburg effect, Metabolism, Panepoxydone, LDH-A, LDH-B, Breast cancer
Received: August 15, 2014 Accepted: November 02, 2014 Published: January 07, 2015
ABSTRACT
Metabolism is an important differentiating feature of cancer cells. Lactate
dehydrogenases (LDH) A/B are metabolically important proteins and are involved
in the critical step of inter-conversion of lactate to pyruvate. Panepoxydone (PP),
a natural NF-kB inhibitor, signicantly reduces the oxygen consumption and
lactate production of MCF-7 and triple negative (MDA-MB-231, MDA-MB-468 and
MDA-MB-453) breast cancer cells. We further observed that PP inhibited mitochondrial
membrane potential and the ATP synthesis using ow cytometry. PP also up-regulated
LDH-B and down-regulated LDH-A expression levels in all breast cancer cells to
similar levels observed in HMEC cells. Over-expression of LDH-B in cancer cell lines
leads to enhanced apoptosis, mitochondrial damage, and reduced cell migration.
Analyzing the patient data set GDS4069 available on the GEO website, we observed
100% of non TNBC and 60% of TNBC patients had less LDH-B expression than LDH-A
expression levels. Herein we report a new term called Glycolytic index, a novel method
to calculate utilization of oxidative phosphorylation in breast cancer cells through
measuring the ratio of the LDH-B to LDH-A. Furthermore, inhibitors of NF-kB could
serve as a therapeutic agent for targeting metabolism and for the treatment of triple
negative breast cancer.
INTRODUCTION
Relative to normal cells, cancer cells are highly
proliferative and thus require increased ATP to meet their
metabolic demand. Cancer cells fulll this requirement by
depending on a faster mode of energy production, even in
the presence of oxygen, a phenomenon commonly referred
to as the Warburg effect [1, 2]. In the presence of oxygen,
normal cells generate energy from glycolysis coupled
with oxidative phosphorylation, an efcient process
yielding approximately 38 molecules of ATP for each
molecule of glucose consumed [3]. Glucose enters the
cell and, after a series of enzymatic reactions, generates
pyruvate. Pyruvate then enters the mitochondria, where it
is metabolized to CO2 and water through the formation of
ATP [4]. Under anaerobic conditions, pyruvate undergoes
fermentation and is converted to lactate by a reaction
catalyzed by lactate dehydrogenase (LDH). However,
in cancer cells, pyruvate is preferentially converted into
lactate even in the presence of oxygen [5, 6].
LDH is a tetrameric enzyme, containing 2 major
subunits (A and B), encoded by 2 different genes, LDH-A
and LDH-B [7, 8]. Lactate dehydrogenase A (LDH-A;
also known as LDH-M and LDH-5), which is the
predominant form in skeletal muscle, kinetically favors
the conversion of pyruvate to lactate. The other isoform,
lactate dehydrogenase B (LDH-B; also known as LDH-H
and LDH-1) preferentially catalyzes the reverse reaction,
in which lactate is converted back to pyruvate [9].
LDH-A is over-expressed in various tumor types,
including breast cancer [10, 11]. Several LDH-A inhibitors
are reported in the literature [12, 13]. Inhibition of LDH-A
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leads to a reduction in cellular transformation, delayed
tumor initiation, and inhibition of growth of breast cancer
xenografts [14, 15]. Further, in both ER-positive and
-negative breast cancer cells, loss of LDH-A results in
increased mitochondrial-induced apoptosis via production
of reactive oxygen species [16]. Thus, LDH-A is involved
in breast cancer tumorigenesis.
In contrast to LDH-A expression, LDH-B is highly
expressed in non-malignant tissues relative to tumors [17].
In malignant tumors, LDH-B is silenced by promoter
hypermethylation; this occurs at a high frequency in
primary breast tumors (100%, 25/25) and in primary
prostate tumors (45%, 14/31) [17, 18]. Although most
reports indicate that LDH-B expression is decreased in
breast tumors [17], integrative genomic analysis found
that LDH-B expression is higher in the basal-like versus
luminal subtype of cells in triple-negative breast cancers
(TNBCs), and silencing of LDH-B expression in MDA-
MB-231 cells decreases tumor growth [19]. While these
ndings appear contradictory, one caveat is that, in
most of these studies, LDH-A and LDH-B were studied
individually, thus hampering a broader view of their roles
in cancer metabolism.
In this study we determined enhanced apoptosis,
mitochondrial damage, and reduced migration of cancer
cells in over-expressed LDH-B breast cancer cells.
Herein, we report that the LDH-B/LDH-A ratio reects
the metabolic capacity of breast cancer cells. We propose
a new measurement, the “Glycolytic Index,” which
quantitates the ratio in cancer cells and demonstrate
the value of this ratio as a biomarker of breast cancer
aggressiveness. Further, this measurement can be utilized
in predicting the metastatic behavior of breast cancers.
RESULTS
PP treatment modulates bioenergetics in human
breast cancer cells
We recently reported that, in TNBC cells, PP, a
natural NF-ĸB inhibitor, induces apoptosis and causes a
reversal of the epithelial-mesenchymal transition [20].
We determined the effect of PP on breast cancer cells
to form colonies. In the presences of PP, the number of
colonies formed by breast cancer cells was signicantly
less than the control cells (Supplementary Figure 1). Since
NF-κB regulates energy homeostasis via engagement of
the cellular networks governing glycolysis and respiration
[21], PP was utilized to investigate the role of NF-ĸB in
cancer-related bioenergetics, a feature that differentiates
cancer cells from normal cells [22].
The IC50 values of PP in different cell lines were
4uM, 5uM, 8uM and 15uM, respectively for MDA-
MB-453, MCF-7, MDA-MB-468 and MDA-MB-231
cell lines. All these breast cancer cell lines were treated
with concentrations of PP equal to- half the IC50, the IC50,
and double the IC50 for 24 hr and were analyzed for their
oxygen consumption rate (OCR), an indicator of oxidative
phosphorylation (OXPHOS), and their extracellular
acidication rate (ECAR), utilizing the Seahorse Analyzer.
All breast cancer cell lines showed decreases in OCR after
24 hr of exposure to PP (Figure 1A). However, signicant
decreases in ECAR were noticed only in MDA-MB-231
and MDA-MB-453 cells (Figure 1B). Overall, the results
suggest that PP reduces lactate production in breast cancer
cells. The ratio OCR/ECAR, an indicator of oxidative
phosphorylation, was increased in all the TNBC cells
after PP treatment; this was not observed for MCF-7 cells
(Figure 1C).
PP induces apoptosis through reduced
mitochondrial membrane potential (Δψm)
Previously, we showed that PP activates caspase-3
expression and concomitant cleavage of PARP [20].
Mitochondrial Δψm is a measure of the capacity of the
respiratory chain to generate ATP. To determine if PP
has an effect on Δψm, the cationic lipophilic dye, JC-1,
which accumulates within the mitochondria in a potential-
dependent manner, was used. Δψm was measured in all
breast cancer cells by ow-cytometry (Figure 2A). PP
treatment resulted in a concentration-dependent increase
in mitochondrial damage (Figure 2B), which corresponded
to decreased Δψm. This damage was more pronounced in
MDA-MB-231 cells relative to other breast cancer cells.
Thus, PP-mediated apoptosis in breast cancer cells is
apparently through disruption of Δψm.
Mitochondrial Δψm is necessary for the activity of
ATP synthase, which generates ATP [23]. To determine the
role of Δψm in ATP production, the effect of PP on ATP
production was assessed. Decreases in ATP levels were
observed in all PP-treated breast cancer cells relative to
their respective controls (Figure 3). MDA-MB-453 cells
were less sensitive than MCF-7 and the other TNBC cells.
LDH-A and LDH-B expression
LDH-A and LDH-B expression levels in the breast
cancer cell lines were determined by qRT-PCR. PP
treatment caused a decrease in the LDH-A expression
and increase in the LDH-B expression in all the cell
lines. MCF-7 control and PP treated cells did not express
LDH-B (Figure 4).
The basal expression levels of LDH-A and LDH-B
proteins in all breast cancer cells and in normal human
mammary epithelial cells (HMEC) were determined by
immunoblotting. HMEC cells expressed both LDH-A and
LDH-B at the protein level (Figure 5A). However, LDH-B
expression was absent in MCF7. As previously reported
[14], there was higher LDH-A expression in the breast
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Figure 1: PP treatment inhibits oxidative phosphorylation (OXPHOS) in breast cancer cells. (A) Effect of PP on oxygen
consumption rate (OCR), an indicator of OXPHOS, in MCF-7, MDA-MB-231, MDA-MB-468 and MBA-MD-453 cells following 24 hr
of treatment with DMSO (control) or the indicated concentrations of PP. * D1, D2, and D3s are half the IC50, the IC50, and double the IC50
concentrations.
(Continued )
A
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Figure 1 (Continued ): (B) Effect of PP on basal ECAR levels.
(Continued )
B
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Figure 1 (Continued ): (C) Effect of PP on OCR to ECAR ratio in breast cancer cells. Data shown are means ± SEM of two independent
experiments, each performed in triplicate. Asterisks indicate statistically signicant differences between PP-treated and untreated cells,
p < 0.05 (*), and p < 0.01(**), as determined by Student’s t-test.
C
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cancer cells and almost similar level of expression was
observed in HMEC cells; however, LDH-B expression
was higher in HMEC cells relative to breast cancer cells
(Figure 5A). The LDH-B expression was comparatively
low in MDA-MB-453, and MDA-MB-468 and MDA-
MB-231 cells.
PP treatment caused a decrease in ECAR, which
corresponds to a decrease in lactate production through
LDH-A. To conrm this, the expressions of LDH-A
and LDH-B expression were determined in PP-treated
breast cancer cells. There was up-regulation of LDH-B
expression in these cells, except that, in MCF-7 cells,
LDH-B expression was not observed (Figure 5B).
Since there was a loss of LDH-A and increased
LDH-B expression after PP treatment, the ratio of LDH-B/
LDH-A, i.e., the Glycolytic Index (GI), was calculated.
A higher GI was observed for HMEC cells (0.9) relative to
breast cancer cells (Figure 5C). PP treatment increased the
LDH-B/LDH-A ratio in a concentration-dependent manner
(Figure 5D). Thus, the GI is an indicator of utilization of
OXPHOS instead of lactate by cancer cells for their energy
needs, and thus provides a measurement for determining
which cells exhibit the Warburg effect.
Increased LDH-B reduces cell growth
Effect of ectopic LDH-B expression on breast
cancer cell growth was determined at different time points.
Compared with cells transfected with the scrambled
plasmid DNA, cells transiently transfected with LDH-B
plasmid DNA demonstrated lower viability (Figure 6A).
The change in the viability over time was not detected
in any of the cell line tested. These results suggested the
role of LDH-B in the proliferation and survival of breast
cancer cells.
Over-expressed LDH-B induces apoptosis
and reduces cell motility
To determine if high levels of LDH-B have an effect
on apoptosis and cell motility, MCF-7, MDA-MB-231,
MDA-MB-468, and MDA-MB-453 breast cancer cells were
Figure 2: PP induces a loss of mitochondrial membrane potential. Breast cancer cells were seeded in 6-well plates and treated
with different concentrations of PP for 24 hr. Cells treated with the vehicle or with PP were stained with JC-1 and subjected to ow cytometric
analysis. (A) Flow cytometric measurement of mitochondrial membrane potential (B) Histogram showing increased mitochondrial damage
corresponds to decreased mitochondrial membrane potential. The average percentage (± SEM) of cells with decreased membrane potential
is indicated. Asterisks indicate statistically signicant differences between PP-treated and untreated cells, p < 0.05 (*), and p < 0.01(**), as
determined by Student’s t-test.
AB
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Figure 3: PP reduces ATP levels. Breast cancer cells were treated with different concentrations of PP for 24 hr and counted. ATP levels
(mean ± SEM, n = 3 experiments) were determined by a luciferin–luciferase-based assay on equal numbers of live cells. Asterisks indicate
statistically signicant differences between PP-treated and untreated cells, p < 0.05 (*), p < 0.01(**), and p < .001(***) as determined by
Student’s t-test.
Figure 4: PP modulates expression of LDH-A and LDH-B. qRT-PCR analysis of the mRNA expression of LDH-A and LDH-B
was accomplished for breast cancer cells after PP treatment (D3 dose). Relative expressions of LDH-A and LDH-B as compared to
respective controls are plotted in the graph. GAPDH was used as internal control. The data represented as mean ± standard deviation (n = 3).
Asterisks indicate statistically signicant differences between PP-treated and untreated cells, p < 0.05 (*), and p < 0.01(**), as determined
by Student’s t-test.
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transiently transfected with an LDH-B plasmid (Figure 6B).
Over-expression of LDH-B led to an increase in the
percentage of apoptotic cells, as measured by PE Annexin
apoptosis kits and analyzed by ow cytometry. MDA-
MB-468 and MDA-MB-453 cells showed increases (2.7-
to 3.2-fold) in apoptotic cells relative to their respective
control cells (Figure 6C & 6D, p < 0.01 and p < 0.05
levels, respectively). LDH-B over-expression led to a
1.5–5 fold increase in the percentage of cells with damaged
mitochondria, in particular, in MDA-MB-468 and MDA-
MB-453 cells (Figure 6E & 6F, p < 0.05). Further, LDH-B
over-expression in MCF-7, MDA-MB-231, MDA-MB-468,
and MDA-MB-453 cells caused less cell migration relative
to control (empty vector) cells. Their migration was reduced
2–3 fold (Figure 6G & 6H, p < 0.01 and p < 0.05).
To determine the clinical signicance of the
LDH-B/LDH-A ratio, we analyzed individual mRNA
expression levels of LDH-A and LDH-B using the Yang
et al. GDS4069 data set available on the GEO website
http://www.ncbi.nlm.nih.gov/geo/) [24]. Lower levels of
LDH-B relative to LDH-A levels was observed in 14/14
non-TNBC breast cancers and in 3/5 TNBCs (Figure 7).
Thus, LDH-B is generally lower in breast cancers. Further,
the ratio of LDH-B to LDH-A would be more useful than
either of these markers alone.
DISCUSSION
A distinguishing feature of cancer cells relative to
normal cells is bioenergetics. Lactate provides cancer
cells with a major source of energy; a phenomenon
known as the Warburg effect. In contrast, normal cells
rely mainly on oxidative phosphorylation [2, 25].
Figure 5: PP alters LDH protein expression. Total protein was isolated from control and PP-treated breast cancer cells and subjected
to immunoblotting. Membranes were stripped and re-probed with anti-actin antibody to ensure equal protein loading. (A) Immunoblotting
of LDH-A and LDH-B in control cells. (B) Bar diagram indicating the ratio of LDH-B to LDH-A in control cells. (C) Immunoblotting of
LDH-A and LDH-B in PP-treated cells. (D) Bar diagram indicating the ratio of LDH-B to LDH-A in PP-treated cells.
A
C
B
D
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Figure 6: Over-expression of LDH-B leads to reduced viability, apoptosis and less mobility. LDH-B was transiently
over-expressed in MCF-7, MDA-MB-231, MDA-MB-468, and MBA-MD-453 cells. Effect of LDH-B over-expression was determined
on cell viability assay, apoptosis, mitochondrial membrane potential, and migration assays. (A) Cell viability assay after ectopic LDH-B
expression at 24, 48 and 72 hrs. (B) Immunoblotting of LDH-B to conrm its over-expression in breast cancer cells. (C) Flow cytometric
measurement of apoptosis in breast cancer cells after LDH-B over-expression. Figure 6: (D) Histogram showing increased numbers of
apoptotic cells in breast cancer cell lines after LDH-B over-expression.
(Continued)
A
B C
D
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Figure 6 (Continued ): (E) Flow cytometric measurement of mitochondrial damage in breast cancer cells after LDH-B over-expression.
(F) Histogram showing increased mitochondrial damage in breast cancer cell lines after LDH-B over-expression. (G) Microscopic
photograph of cell migration after LDH-B over-expression.
(Continued)
E
G
F
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Targeting metabolism is a new approach for treatment
of cancer, especially to overcome therapeutic resistance
[26]. Currently, there is a focus on inhibition of enzymes
involved in energy metabolism. LDH-A has gained
attention, as it is up-regulated in many tumors and is
involved in tumor initiation and growth [27]. In contrast,
there have been contradictory reports on the role of
LDH-B in breast tumors [17, 19, 28].
Our results indicate that both LDH-A and LDH-B
have functions in breast cancer and that their levels
can be modulated through a pharmacological inhibitor,
PP, which targets NF-κB. The results show that PP
reduces Δψm and ATP levels in breast cancer cells.
Previous studies also reported decreased ATP level
in the mitochondria-targeted vitamin E analog ( Mito-
chromanol, Mito-ChM) and mitochondrial ErBB2
over-expressing cells. Decreased ATP level in MCF-
7 and MDA-MB-231 cells identied to be effective in
inhibiting energy metabolism in breast cancer cells
and in mice xenografts [29, 30]. Thus, PP induces
nonproductive mitochondrial respiration, as reported
previously for cells with knockout LDH-A and for cells
treated with FX-11 (LDH-A inhibitor) [14, 27] .
Our observed changes in the LDH-A, LDH-B
level correlates with the changes in the OCR and ECAR.
Reduced LDH-A reect decrease in lactate production
as we also observed decreased ECAR level. We detected
increased LDH-B level after PP treatment similarly we
nd increase in the OCR to ECAR ratio which indicates
total OXPHOS. An abrogated LDH-A and induced LDH-B
expression both are capable of generating more pyruvate
for further utilization in OXPHOS.
Although LDH-A was over-expressed in all the
breast cancer cell lines examined, expression of LDH-B
was higher in HMEC cells relative to breast cancer cells.
In MCF-7 cells, LDH-B expression was not found, an
observation similar to previous reports, with one exception
[31]. Thus we were unable to access the function of
LDH-B in this cell line.
The LDH-B promoter is hypermethylated in
breast and prostate cancers [17, 18], and PP treatment
results in down-regulation of LDH-A in four different
breast cancer cell lines and up-regulation LDH-B in
three cell lines. This suggests the possibility that PP,
via modulation of NF-κB, is involved in demethylation
of the LDH-B promoter. This premise is supported by
our previous work showing that PP treatment results
in increased expression of E-cadherin, the promoter
of which is hypermethylated in MDA-MB-231 breast
cancer cells [22, 32].
Figure 6 (Continued ): (H) Histogram showing decreased migration of breast cancer cell lines after LDH-B over-expression. The data
represented as mean ± standard deviation (n = 3). Asterisks indicate statistically signicant differences between PP-treated and untreated
cells, p < 0.05 (*), and p < 0.01(**), as determined by Student’s t-test.
H
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There was also a decrease in Δψm after PP
treatment and after over-expression of LDH-B. Since
LDH-A is responsible for converting pyruvate to
lactate, its restriction should lead to an accumulation
of pyruvate, thus making pyruvate available as a source
to generate ATP for the metabolic demands of cell
growth [33, 34]. Once the OXPHOS chain is activated,
more electrons are generated from the chain and, after
combining with oxygen, form reactive oxygen species,
which damage the mitochondrial membrane and cause
mitochondrial pathway apoptosis [35]. Thus, decreased
Δψm supports a role for the mitochondrial pathway
during apoptosis. In summary, our data support the
hypothesis that accumulation of pyruvate through
LDH-A inhibition and/or re-expression of LDH-B is
required for cancer cells to utilize OXPHOS as their
energy source (Figure 8).
Interestingly, ectopic expression of LDH-B has
signicantly decreased the Δψm and induced apoptosis
in MDA-MB-468 and MDA-MB-453 cells but in MCF-7
and MDA-MB-231 cells the changes were not signicant.
The reason for this could be because of the differential
behavior of the TNBC cells. Each TNBC behave
differently and that is why we need different treatment
therapy for specic tumor type.
LDH-A is a biomarker for glycolysis activity.
Further, its expression positively correlates with tumor
size, indicating that LDH-A expression inuences
tumor cell proliferation and that inhibition of LDH-A
augments apoptosis [36]. As shown here, LDH-B
over-expression resulted in an increase in apoptosis in
all breast cancer cell lines, even the LDH-B decient
MCF-7 cells. The induction of apoptosis is one of the
protective mechanisms against cancer initiation and
progression [37]. Our ndings are similar to those
related to inhibition of glycolysis, for which specic
inhibitors, 3-bromopyruvate and 2-deoxyglucose,
result in mitochondrial pathway-induced apoptosis
[38, 39]. Thus, targeting NF-κB with pharmacological
inhibitors, such as PP, could induce mitochondrial
pathway apoptosis through damage to the mitochondrial
membrane. More work should be accomplished to
determine the clinical relevance of targeting NF-κB for
breast cancer patients.
Figure 7: LDH-A and LDH-B expression in TNBC and non-TNBC breast cancer samples. The Yang et al. data set was used
to determine mRNA expression levels of LDH-A and LDH-B in breast tumor samples (5 TNBCs and 14 non-TNBCs). Data are based on a
ratio of the raw signal intensities from the microarray GDS4069 NCBI/GEO database plotted on the y axis.
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It is well documented that the intracellular ratio of
Bax/Bcl-2 protein can strongly inuence the ability of a
cell to respond to an apoptotic signal [40]. Similarly, our
results indicate that the LDH-B/LDH-A ratio provides
a way to identify tumor cells with aggressive behavior.
High levels of LDH-B are present in both benign and
non-malignant prostate and breast tissue [17, 18]. The
fact that PP, which causes a reversal of aggressive
features, also causes increased expression of LDH-B
in breast cancer cells, similar to HMECs, suggests that
LDH-B generates more pyruvate, a substrate for the
tricarboxylic acid cycle, followed by OXPHOS, thus
rendering the cells less dependent on lactate for cellular
respiration.
Altogether, our ndings suggest that the ratio of
LDH-B/LDH-A is more relevant than either LDH-A
or LDH-B expression alone. LDH-B expression is
up-regulated in basal-like TNBCs [28]. Our analysis
of 5 TNBCs and 14 non-TNBCs support the concept
that LDH-B levels are higher in TNBCs. Nevertheless,
LDH-B was lower than LDH-A in 3/5 TNBCs. Further,
a lower LDH-B/LDH-A ratio was observed in 100% of
non-TNBCs. Thus, the LDH-B/LDH-A ratio could be
a biomarker of tumor aggressiveness, particularly as it
relates to breast cancer subtypes in TNBCs, particularly
the luminal versus basal-like subtypes, which have
different prognoses [41]. Targeting of both LDH-A and
LDH-B could be a promising therapeutic strategy for the
treatment of breast cancer.
The present study has a limitation as it does not a
include a large patient cohort to validate the LDH-A and
LDH-B expression level, however it does highlight the
possibly that the LDH-B/LDH-A ratio could be utilized
to determine the glycolytic index of breast tumors.
Non-invasive assays, which accurately reect the
“state of the tumor” are essential to not only detect
Figure 8: A proposed model of PP targeted metabolic alterations. PP down-regulates LDH-A and up-regulates LDH-B to
generate more pyruvate, which is available for OXPHOS. The shift in energy usage may change the phenotype of cells. PP also reduces
mitochondrial Δψm, which leads to energy crises and to cell death.
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tumors earlier, but to monitor treatment effectiveness
as well. Since LDH is already utilized in the clinic
for other cancer types, it is possible that the LDH-B/
LDH-A ratio could be better or more effective method
to further characterize breast tumors, however judicious
selection of which breast cancer subtypes is essential
to accurately use this index to monitor treatment
response. Furthermore, since increased glycolysis leads
to chemoresistance in breast cancer, determining the
LDH-B/LDH-A ratio, would suggest a rationale that
either NF-kB or LDH-A inhibitors could be added to
current treatment regimens.
MATERIALS AND METHODS
Drug and reagents
Panepoxydone (PP), a natural NF-ĸB inhibitor,
was purchased from Alexis Biochemicals (San Diego,
CA). Dimethyl sulfoxide (DMSO, vehicle control),
Triton X-100, and bovine serum albumin (BSA)
were obtained from Sigma-Aldrich (St. Louis, MO).
Dulbecco’s Modied Eagle Medium (DMEM), fetal
bovine serum (FBS), trypsin-EDTA, penicillin, and
streptomycin were purchased from Invitrogen (Carlsbad,
CA). For measurement of ATP, the CellTiter-Glo Assay
was purchased from Promega (Madison, WI) and JC-1
dye from Sigma-Aldrich (St. Louis, MO). Primary
antibodies against LDH-A and LDH-B were purchased
from Cell Signaling Technology (Beverly, MA) and
Abcam (Cambridge, MA), respectively. Anti-rabbit and
horseradish peroxidase-conjugated secondary antibodies
were obtained from Santa Cruz Biotechnology (Santa
Cruz, CA). The β-actin (mouse monoclonal) antibody was
from Sigma-Aldrich (St. Louis, MO).
Human breast cancer cell lines
and culture conditions
The estrogen receptor-positive MCF-7 cell line and
three TNBC cell lines (MDA-MB-231, MDA-MB-468,
and MDA-MB-453) were acquired from ATCC (Manassas,
VA) and cultured in DMEM supplemented with 10% fetal
bovine serum, penicillin (100 U/ml), and streptomycin
(100 μg/ml) in a humidied 5% CO2 incubator at 37°C.
Cells were sub-cultured biweekly with a split ratio of
1:3. For treatments, a stock solution of PP (50 mM) was
prepared in DMSO and stored at −20°C in aliquots. At
the time of experiments, dilutions were freshly prepared in
complete growth medium. Equal volumes of DMSO (nal
concentration, 0.2%) were added to the controls.
Cell metabolism assays
Rates of glycolysis and oxidative phosphorylation
were determined by measuring the oxygen consumption
rates (OCR) and extracellular acidication rates (ECAR,
a measure of lactic acid release) by use of a Seahorse
XF24 Analyzer (Seahorse Bioscience, Billerica, MA).
Briey, 5 × 104 cells/well were seeded in XF24 cell culture
microplates (Seahorse Bioscience). After 4–5 hr, cells
were treated with different concentrations of PP (based on
IC50 values), and plates were incubated at 37°C for 24 hr.
The next day, medium was changed to XF Assay Media,
and the plates were loaded into the XF24 analyzer. Data
were collected and analyzed.
Mitochondrial membrane
potential measurement
The lipophilic cationic dye JC-1 (5,5′,6,
6′-tetrachloro-1,1′,3,3′tetraethyl- benzimidazolcarbocyanine
iodide) was used to detect Δψm of the cell lines. 3 × 105
cells were seeded on 6-well plates and, after overnight
incubation, treated with PP for 24 hr. Cells were
collected and stained with JC-1 (10 μg/ml) at 37°C for
30 min. Formation of J-aggregates was assessed by ow
cytometry.
ATP analysis
Cellular ATP content was determined by a luciferin–
luciferase-based bioluminescence assay (Promega,
Madison, WI), as outlined in the manufacturer’s protocol.
MCF-7, MDA-MB-231, MDA-MB-468, and MDA-
MB-453 cells were treated with PP for 24 hr and counted.
ATP levels were determined on equal numbers of cells
(5000/well) according to a standard protocol. Equal
volumes of CellTiter-Glo reagent were added and mixed
for 2 min, followed by 10 min of incubation at room
temperature (RT). Luminescence was measured using a
VictorV (PerkinElmer, Waltham, MA) plate reader.
cDNA synthesis and Real-time RT-PCR
Total RNA was extracted from control and high
dose PP-treated cells (double IC50 value) with Trizol
reagent (Sigma-Aldrich, Dorset, UK) according to
the manufacturers instructions. RNA was quantied
spectrophotometrically. RNA (2 μg) was reverse-
transcribed into cDNA using a High Capacity cDNA
Reverse Transcription Kit (Applied Biosystems, Carlsbad,
CA) with 250 ng of random primers according to the
manufacturer’s instructions.
Quantitative real-time PCR was performed in 96-
well plates using SYBR Green Master Mix (Roche) on an
iCycler system (Bio-Rad, Hercules, CA) with previously
published primers [42]. The thermal conditions for real-
time PCR assays were as follows: cycle 1: 95°C for
10 min, cycle 2 (x40): 95°C for 10 sec and 58°C for 45 sec.
Threshold cycle (CT) values for LDH-A and LDH-B were
normalized against CT values for control GAPDH, and a
relative fold-change in expression with respect to a control
sample was calculated by the 2-ΔΔCt method.
Oncotarget15
www.impactjournals.com/oncotarget
Immunoblotting
Cells exposed to various concentrations of PP
for 24 hr were lysed, and protein concentrations were
determined with DC Protein Assay kits (Biorad, Hercules,
CA) following the manufacturer’s instructions. Total
protein (80 μg) of each cell lysate were subjected to
resolution on 10% sodium dodecyl sulfate polyacrylamide
gel electrophoresis (SDS-PAGE) and electro-transferred
onto polyvinylidene diuoride (PVDF) membranes. The
membranes were incubated with blocking buffer (5%
non-fat dry milk in phosphate-buffered saline) for 1 hr at
room temperature (RT) and then incubated with specic
antibodies diluted 1:1000 times in 5% non-fat dry milk
overnight at 4°C. After washing with a Tris-buffered
saline solution containing 0.1% Tween 20 (TBST),
membranes were incubated with horseradish peroxidase-
conjugated secondary antibodies for 2 hr at RT followed
by washing with TBST. Blots were then treated with
chemiluminescence reagents using Super Signal West
Femto Kits (Pierce, Rockford, IL), and signals were
detected with an LAS-3000 image analyzer (Fuji Photo
Film Co., Tokyo, Japan). Each membrane was stripped
and re-probed with anti-β-actin antibody to ensure equal
protein loading. Densitometry was performed with an
AlphaImager (Alpha Innotech Corp., San Leandro, CA).
Transient transfection for over-expression
of LDH-B
The LDH-B plasmid (pCMV-6-AC-GFP vector)
was expanded by use of One Shot® TOP10 chemically
competent E. coli cells (Invitrogen) following the standard
transformation procedure on LB agar plates supplemented
with ampicillin [43]. Plasmids were isolated, and MCF-7,
MDA-MB-231, MDA-MB-468, and MDA-MB-453 cells
were transiently transfected. Briey, 1 × 105 cells were
seeded in 6-well plates. After overnight incubation, cells
were transfected with the LDH-B expression plasmid
(2 μg) or pCMV-6-AC-GFP control plasmid using
Lipofectamine RNAiMax (Invitrogen) as a transfection
reagent. After overnight incubation, media containing
the transfection mixture was replaced with fresh serum-
containing media and incubated for 48 hr. Cells collected
after 48 hr of transfection were utilized for cell migration,
apoptosis, mitochondrial Δψm assays, and Western blot
analyses. Cell migration and apoptosis procedures were
followed as reported previously [20].
Cell viability assay
The effect of ectopic expression of LDH-B on cell
growth was measured using AQueous One Solution Cell
Proliferation Assay (MTS assay, Promega) according
to the manufacturer’s protocol. Briey, MCF-7, MDA-
MB-231, MDA-MB-468 and MDA-MB-453 cells seeded
in 96-well plates (5,000 cells/well) and were transfected
with control and plasmid DNA as described above. After
24, 48 and 72 hrs of transfection, medium was removed
and 20 ul MTS reagent with 100 μl media was added to
each well. Plates were incubated at 37°C for 30 min- 2 hrs.
The uorescent intensity was measured at 490nm using
Gen5 (Beckman coulter, Inc., Brea, CA, USA).
Statistical analysis
Student’s t-test was used to evaluate the statistical
signicance of the results. p < 0.05 was considered
statistically signicant. All the data analysis was done
using GraphPad Prism version 5.0 software and graphs
were also created using this software.
ACKNOWLEDGEMENTS
Authors would like to thank Dr. Ajay P. Singh
and Dr. Sanjeev Srivastava for providing directions on
transfection assay and gifting competent cells. Authors
also thank Steven McClellan for ow cytometric analysis.
This study was supported by the University of South
Alabama Mitchell Cancer Institute Research Award to
Dr. Windy Dean-Colomb and by G12 RR03059- 21A1
(NIH/RCMI) [CY], U54 CA118623 (NIH/NCI) [CY]; and
U54706CA118948 (NIH/NCI) [CY].
Conict of interest
The authors declare no conict of interest.
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Supplementary resource (1)

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Multi-level optimization stems from the need to tackle complex problems involving multiple decision makers. Two-level optimization, referred as ``Bi-level optimization'', occurs when two decision makers only control part of the decision variables but impact each other (e.g., objective value, feasibility). Bi-level problems are sequential by nature and can be represented as nested optimization problems in which one problem (the ``upper-level'') is constrained by another one (the ``lower-level''). The nested structure is a real obstacle that can be highly time consuming when the lower-level is $\mathcal{NP}-hard$. Consequently, classical nested optimization should be avoided. Some surrogate-based approaches have been proposed to approximate the lower-level objective value function (or variables) to reduce the number of times the lower-level is globally optimized. Unfortunately, such a methodology is not applicable for large-scale and combinatorial bi-level problems. After a deep study of theoretical properties and a survey of the existing applications being bi-level by nature, problems which can benefit from a bi-level reformulation are investigated. A first contribution of this work has been to propose a novel bi-level clustering approach. Extending the well-know ``uncapacitated k-median problem'', it has been shown that clustering can be easily modeled as a two-level optimization problem using decomposition techniques. The resulting two-level problem is then turned into a bi-level problem offering the possibility to combine distance metrics in a hierarchical manner. The novel bi-level clustering problem has a very interesting property that enable us to tackle it with classical nested approaches. Indeed, its lower-level problem can be solved in polynomial time. In cooperation with the Luxembourg Centre for Systems Biomedicine (LCSB), this new clustering model has been applied on real datasets such as disease maps (e.g. Parkinson, Alzheimer). Using a novel hybrid and parallel genetic algorithm as optimization approach, the results obtained after a campaign of experiments have the ability to produce new knowledge compared to classical clustering techniques combining distance metrics in a classical manner. The previous bi-level clustering model has the advantage that the lower-level can be solved in polynomial time although the global problem is by definition $\mathcal{NP}$-hard. Therefore, next investigations have been undertaken to tackle more general bi-level problems in which the lower-level problem does not present any specific advantageous properties. Since the lower-level problem can be very expensive to solve, the focus has been turned to surrogate-based approaches and hyper-parameter optimization techniques with the aim of approximating the lower-level problem and reduce the number of global lower-level optimizations. Adapting the well-know bayesian optimization algorithm to solve general bi-level problems, the expensive lower-level optimizations have been dramatically reduced while obtaining very accurate solutions. The resulting solutions and the number of spared lower-level optimizations have been compared to the bi-level evolutionary algorithm based on quadratic approximations (BLEAQ) results after a campaign of experiments on official bi-level benchmarks. Although both approaches are very accurate, the bi-level bayesian version required less lower-level objective function calls. Surrogate-based approaches are restricted to small-scale and continuous bi-level problems although many real applications are combinatorial by nature. As for continuous problems, a study has been performed to apply some machine learning strategies. Instead of approximating the lower-level solution value, new approximation algorithms for the discrete/combinatorial case have been designed. Using the principle employed in GP hyper-heuristics, heuristics are trained in order to tackle efficiently the $\mathcal{NP}-hard$ lower-level of bi-level problems. This automatic generation of heuristics permits to break the nested structure into two separated phases: \emph{training lower-level heuristics} and \emph{solving the upper-level problem with the new heuristics}. At this occasion, a second modeling contribution has been introduced through a novel large-scale and mixed-integer bi-level problem dealing with pricing in the cloud, i.e., the Bi-level Cloud Pricing Optimization Problem (BCPOP). After a series of experiments that consisted in training heuristics on various lower-level instances of the BCPOP and using them to tackle the bi-level problem itself, the obtained results are compared to the ``cooperative coevolutionary algorithm for bi-level optimization'' (COBRA). Although training heuristics enables to \emph{break the nested structure}, a two phase optimization is still required. Therefore, the emphasis has been put on training heuristics while optimizing the upper-level problem using competitive co-evolution. Instead of adopting the classical decomposition scheme as done by COBRA which suffers from the strong epistatic links between lower-level and upper-level variables, co-evolving the solution and the mean to get to it can cope with these epistatic link issues. The ``CARBON'' algorithm developed in this thesis is a competitive and hybrid co-evolutionary algorithm designed for this purpose. In order to validate the potential of CARBON, numerical experiments have been designed and results have been compared to state-of-the-art algorithms. These results demonstrate that ``CARBON'' makes possible to address nested optimization efficiently.
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Background: Triple-negative breast cancer (TNBC) is a highly diverse group that is associated with an aggressive phenotype. Its treatment has been challenging due to its heterogeneity and absence of well-defined molecular targets. Thus, there is an urgent need to identify novel agents with therapeutic application. NF-κB is over-expressed in many breast cancers; thus, inactivation of the NF-κB pathway could serve as a therapeutic target. Here we report for the first time the anti-tumor activity of panepoxydone (PP), a NF-κB inhibitor isolated from an edible mushroom, in several breast cancer cell lines. Methods: We investigated the effects of PP on cell growth, migration-invasion, apoptosis and EMT-related proteins expression in MCF-7 and TNBC cell lines MDA-MB-231, MDA-MB-468 and MDA-MB-453. Results: Significant antitumor activity was seen in all cell lines, with differential responses noted in cell-line specific manner. Treatment with PP resulted in significant cytotoxicity, decreased invasion, migration and increased apoptosis in all cell lines tested. Up-regulation of Bax and cleaved PARP and down-regulation of Bcl-2, survivin, cyclin D1 and caspase 3 were noted in PP-treated breast cancer cells. The antitumor effect of PP appeared related to its ability to inhibit the phosphorylation of inhibitor of NF-κB (IκBα) with cytoplasmic accumulation. PP treatment also down-regulated FOXM1 which resulted in a reversal of EMT. Similar results were obtained after silencing of NF-kB and FOXM1. Conclusion: Altogether, these studies show, for the first time the antitumor activity of PP against breast cancer cells, in particular TNBC cells. Furthermore, it highlights the concept that optimal treatment of TNBC warrants attention to the differential sensitivity of various TNBC subtypes to therapeutic agents. These results suggest that the PP may be a potentially effective chemopreventive or therapeutic agent against breast cancer. However, additional studies are required to more fully elucidate the mechanism of antitumor effect of PP.
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Most cancer cells use aerobic glycolysis to fuel their growth. The enzyme lactate dehydrogenase-A (LDH-A) is key to cancer's glycolytic phenotype, catalysing the regeneration of nicotinamide adenine dinucleotide (NAD(+)) from reduced nicotinamide adenine dinucleotide (NADH) necessary to sustain glycolysis. As such, LDH-A is a promising target for anticancer therapy. Here we ask if the tumour suppressor p53, a major regulator of cellular metabolism, influences the response of cancer cells to LDH-A suppression. LDH-A knockdown by RNA interference (RNAi) induced cancer cell death in p53 wild-type, mutant and p53-null human cancer cell lines, indicating that endogenous LDH-A promotes cancer cell survival irrespective of cancer cell p53 status. Unexpectedly, however, we uncovered a novel role for p53 in the regulation of cancer cell NAD(+) and its reduced form NADH. Thus, LDH-A silencing by RNAi, or its inhibition using a small-molecule inhibitor, resulted in a p53-dependent increase in the cancer cell ratio of NADH:NAD(+). This effect was specific for p53(+/+) cancer cells and correlated with (i) reduced activity of NAD(+)-dependent deacetylase sirtuin 1 (SIRT1) and (ii) an increase in acetylated p53, a known target of SIRT1 deacetylation activity. In addition, activation of the redox-sensitive anticancer drug EO9 was enhanced selectively in p53(+/+) cancer cells, attributable to increased activity of NAD(P)H-dependent oxidoreductase NQO1 (NAD(P)H quinone oxidoreductase 1). Suppressing LDH-A increased EO9-induced DNA damage in p53(+/+) cancer cells, but importantly had no additive effect in non-cancer cells. Our results identify a unique strategy by which the NADH/NAD(+) cellular redox status can be modulated in a cancer-specific, p53-dependent manner and we show that this can impact upon the activity of important NAD(H)-dependent enzymes. To summarise, this work indicates two distinct mechanisms by which suppressing LDH-A could potentially be used to kill cancer cells selectively, (i) through induction of apoptosis, irrespective of cancer cell p53 status and (ii) as a part of a combinatorial approach with redox-sensitive anticancer drugs via a novel p53/NAD(H)-dependent mechanism.
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The expression and biological consequences of Kaiso, a novel bi-modal transcription factor, in infiltrating ductal carcinomas (IDCs) have not been widely investigated. In the present study, we determined Kaiso expression and subcellular localization in 146 normal tissues, 376 IDCs, and 85 lymph node metastases. In IDCs, there was higher Kaiso expression in both the cytoplasmic and nuclear compartments, which correlated with age <48 (cytoplasmic p < 0.0093; nuclear p < 0.0001) and moderate differentiation (cytoplasmic p < 0.0042; nuclear p < 0.0001), as determined by Chi square analysis. However, only nuclear Kaiso correlated with poor prognostic factors, i.e., race (African Americans) (p < 0.0001), poor differentiation (p < 0.0001), and metastases (p < 0.0001). Nuclear Kaiso was also associated with worse overall survival (p < 0.0019), with African American patients displaying worse survival rates relative to Caucasian patients (p < 0.029). MCF-7 (non-metastatic), MDA-MB-468 (few metastases), and MDA-MB-231 (highly metastatic) breast cancer cells demonstrated increasing Kaiso levels, with more nuclear localization in the highly metastatic cell line. Over-expression of Kaiso in MCF-7 cells increased cell migration and invasion, but treatment of MDA-MB-468 and MDA-MB-231 cells with si-Kaiso decreased cell migration and invasion and induced expression of E-cadherin RNA and protein. E-cadherin re-expression was associated with a reversal of mesenchymal associated cadherins, N-cadherin and cadherin 11, as well as decreased vitamin expression. Further, Kaiso directly bound to methylated sequences in the E-cadherin promoter, an effect prevented by 5-aza-2-deoxycytidine. Immunofluorescence co-staining of poorly differentiated IDCs demonstrated that nuclear Kaiso is associated with a loss of E-cadherin expression. These findings support a role for Kaiso in promoting aggressive breast tumors.
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Most normal cells in the presence of oxygen utilize glucose for mitochondrial oxidative phosphorylation. In contrast, many cancer cells rapidly convert glucose to lactate in the cytosol, a process termed aerobic glycolysis. This glycolytic phenotype is enabled by lactate dehydrogenase (LDH), which catalyzes the inter-conversion of pyruvate and lactate. The purpose of this study was to identify and characterize potent and selective inhibitors of LDHA. High throughput screening and lead optimization were used to generate inhibitors of LDHA enzymatic activity. Effects of these inhibitors on metabolism were evaluated using cell-based lactate production, oxygen consumption, and 13C NMR spectroscopy assays. Changes in comprehensive metabolic profile, cell proliferation, and apoptosis were assessed upon compound treatment. 3-((3-carbamoyl-7-(3,5-dimethylisoxazol-4-yl)-6-methoxyquinolin-4-yl) amino) benzoic acid was identified as an NADH-competitive LDHA inhibitor. Lead optimization yielded molecules with LDHA inhibitory potencies as low as 2 nM and 10 to 80-fold selectivity over LDHB. Molecules in this family rapidly and profoundly inhibited lactate production rates in multiple cancer cell lines including hepatocellular and breast carcinomas. Consistent with selective inhibition of LDHA, the most sensitive breast cancer cell lines to lactate inhibition in hypoxic conditions were cells with low expression of LDHB. Our inhibitors increased rates of oxygen consumption in hepatocellular carcinoma cells at doses up to 3 microM, while higher concentrations directly inhibited mitochondrial function. Analysis of more than 500 metabolites upon LDHA inhibition in Snu398 cells revealed that intracellular concentrations of glycolysis and citric acid cycle intermediates were increased, consistent with enhanced Krebs cycle activity and blockage of cytosolic glycolysis. Treatment with these compounds also potentiated PKM2 activity and promoted apoptosis in Snu398 cells. Rapid chemical inhibition of LDHA by these quinoline 3-sulfonamids led to profound metabolic alterations and impaired cell survival in carcinoma cells making it a compelling strategy for treating solid tumors that rely on aerobic glycolysis for survival.
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Background Recent research has revealed that targeting mitochondrial bioenergetic metabolism is a promising chemotherapeutic strategy. Key to successful implementation of this chemotherapeutic strategy is the use of new and improved mitochondria-targeted cationic agents that selectively inhibit energy metabolism in breast cancer cells, while exerting little or no long-term cytotoxic effect in normal cells. Methods In this study, we investigated the cytotoxicity and alterations in bioenergetic metabolism induced by mitochondria-targeted vitamin E analog (Mito-chromanol, Mito-ChM) and its acetylated ester analog (Mito-ChMAc). Assays of cell death, colony formation, mitochondrial bioenergetic function, intracellular ATP levels, intracellular and tissue concentrations of tested compounds, and in vivo tumor growth were performed. Results Both Mito-ChM and Mito-ChMAc selectively depleted intracellular ATP and caused prolonged inhibition of ATP-linked oxygen consumption rate in breast cancer cells, but not in non-cancerous cells. These effects were significantly augmented by inhibition of glycolysis. Mito-ChM and Mito-ChMAc exhibited anti-proliferative effects and cytotoxicity in several breast cancer cells with different genetic background. Furthermore, Mito-ChM selectively accumulated in tumor tissue and inhibited tumor growth in a xenograft model of human breast cancer. Conclusions We conclude that mitochondria-targeted small molecular weight chromanols exhibit selective anti-proliferative effects and cytotoxicity in multiple breast cancer cells, and that esterification of the hydroxyl group in mito-chromanols is not a critical requirement for its anti-proliferative and cytotoxic effect.
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Purpose: Although breast cancers are known to be molecularly heterogeneous, their metabolic phenotype is less well-understood and may predict response to chemotherapy. This study aimed to evaluate metabolic genes as individual predictive biomarkers in breast cancer. Experimental design: mRNA microarray data from breast cancer cell lines were used to identify bimodal genes-those with highest potential for robust high/low classification in clinical assays. Metabolic function was evaluated in vitro for the highest scoring metabolic gene, lactate dehydrogenase B (LDHB). Its expression was associated with neoadjuvant chemotherapy response and relapse within clinical and PAM50-derived subtypes. Results: LDHB was highly expressed in cell lines with glycolytic, basal-like phenotypes. Stable knockdown of LDHB in cell lines reduced glycolytic dependence, linking LDHB expression directly to metabolic function. Using patient datasets, LDHB was highly expressed in basal-like cancers and could predict basal-like subtype within clinical groups [OR = 21 for hormone receptor (HR)-positive/HER2-negative; OR = 10 for triple-negative]. Furthermore, high LDHB predicted pathologic complete response (pCR) to neoadjuvant chemotherapy for both HR-positive/HER2-negative (OR = 4.1, P < 0.001) and triple-negative (OR = 3.0, P = 0.003) cancers. For triple-negative tumors without pCR, high LDHB posttreatment also identified proliferative tumors with increased risk of recurrence (HR = 2.2, P = 0.006). Conclusions: Expression of LDHB predicted response to neoadjuvant chemotherapy within clinical subtypes independently of standard prognostic markers and PAM50 subtyping. These observations support prospective clinical evaluation of LDHB as a predictive marker of response for patients with breast cancer receiving neoadjuvant chemotherapy.
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Full Text : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3644012/ Cancer cells are markedly different from normal cells with regards to how their metabolic pathways are used to fuel cellular growth and survival. Two basic metabolites that exemplify these differences through increased uptake and altered metabolic usage are glucose and glutamine. These molecules can be catabolized to manufacture many of the building blocks required for active cell growth and proliferation. The alterations in the metabolic pathways necessary to sustain this growth have been linked to therapeutic resistance, a trait that is correlated with poor patient outcomes. By targeting the metabolic pathways that import, catabolize, and synthesize essential cellular components, drug-resistant cancer cells can often be resensitized to anticancer treatments. The specificity and efficacy of agents directed at the unique aspects of cancer metabolism are expected to be high; and may, when in used in combination with more traditional therapeutics, present a pathway to surmount resistance within tumors that no longer respond to current forms of treatment. Cancer Res; 73(9); 1-9. ©2013 AACR.
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It is hard to begin a discussion of cancer cell metabolism without first mentioning Otto Warburg . A pioneer in the study of respiration, Warburg made a striking discovery in the 1920s. He found that, even in the presence of ample oxygen, cancer cells prefer to ...