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Blood First Edition Paper, prepublished online January 28, 2015; DOI 10.1182/blood-2014-08-594408
AML cells have low spare reserve capacity in their respiratory chain
that renders them susceptible to oxidative metabolic stress
Shrivani Sriskanthadevan1&*, Danny V Jeyaraju1*, Timothy E. Chung1, Swayam Prabha1, Wei
Xu1, Marko Skrtic1, Bozhena Jhas1, Rose Hurren1, Marcela Gronda1, Xiaoming Wang1, Yulia
Jitkova1, Mahadeo A. Sukhai1, Feng-Hsu Lin1, Neil Maclean1, Rob Laister1, Carolyn A. Goard1,
Peter J. Mullen1, Stephanie Xie2, Linda Z. Penn1, Ian M Rogers3, John E. Dick2, Mark D.
Minden1, Aaron D. Schimmer1**
1
Princess Margaret Cancer Centre, Ontario Cancer Institute, Toronto, ON, M5G 2M9 Canada
2
Division of Stem Cell and Developmental Biology, Campbell Family Institute for Cancer
Research/Ontario Cancer Institute, Toronto, Ontario M5G 1L7, Canada
3
Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, ON, M5G 1X5, Canada
&
Current address: Clark Smith Brain Tumour Centre, Southern Alberta Cancer Research
Institute, Calgary, Alberta T2N 4N1, Canada
*Contributed equally to this publication
**To whom correspondence should be addressed:
Aaron D. Schimmer
Princess Margaret Cancer Centre, Rm 7-116
610 University Ave, Toronto, ON, Canada M5G 2M9
Tel: 416-946-2838
Fax: 416-946-6546
Email: [email protected]
Running title: Low spare reserve capacity in AML cells
Keywords:
Acute myeloid leukemia
Spare reserve capacity
Oxidative metabolism
Oxidative phosphorylation
Mitochondria
Reactive oxygen species
Copyright © 2015 American Society of Hematology
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Key Points:
•
AML cells have increased mitochondrial mass, low respiratory chain complex activities
and low spare reserve capacity compared to normal cells
•
AML cells have heightened sensitivity to inhibitors of the respiratory chain complexes
and oxidative stressors
ABSTRACT
Mitochondrial respiration is a crucial component of cellular metabolism that can become
dysregulated in cancer. Compared to normal hematopoietic cells, acute myeloid leukemia (AML)
cells and patient samples have higher mitochondrial mass, without a concomitant increase in
respiratory chain complex activity. Hence these cells have a lower spare reserve capacity in the
respiratory chain and are more susceptible to oxidative stress. We therefore tested the effects of
increasing the electron flux through the respiratory chain as a strategy to induce oxidative stress
and cell death preferentially in AML cells. Treatment with the fatty acid palmitate induced
oxidative stress and cell death in AML cells, and suppressed tumor burden in leukemic cell lines
and primary patient sample xenografts in the absence of overt toxicity to normal cells and
organs. These data highlight a unique metabolic vulnerability in AML, and identify a new
therapeutic strategy that targets abnormal oxidative metabolism in this malignancy.
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INTRODUCTION
Oxidative metabolism is a critical mitochondrial process that generates intracellular
energy and metabolic intermediates necessary to maintain and increase cellular biomass. To meet
their energy and biosynthetic requirements, cells metabolize substrates such as glucose,
glutamine, and fatty acids to generate electrons that flow into respiratory chain complexes.1-4
Electrons are passed along this respiratory chain, with oxygen as the final acceptor. During this
process, protons are pumped across the inner mitochondrial membrane, establishing an
electrochemical gradient across the membrane. The energy stored in this gradient is used to drive
ATP production. In cancer cells, the requirement of energy and biosynthetic precursors is higher;
therefore, oxidative metabolism is also frequently amplified to meet these demands.5-7
Mitochondrial biogenesis is a reflection of energy, metabolic and signaling requirements
of a cell.8 In response to physiological, metabolic, and genetic signals, cells can modulate
mitochondrial biogenesis and mass to alter the energy produced through oxidative
phosphorylation.9,10 Recently, we demonstrated that inhibiting mitochondrial translation reduced
the levels of mitochondrially-translated respiratory chain proteins, decreased oxygen
consumption, and preferentially induced cell death in acute myeloid leukemia (AML) cells
compared to normal hematopoietic cells. These effects were observed by both inhibiting the
mitochondrial ribosome with the small molecule tigecycline or through knocking down the
mitochondrial elongation factor EF-Tu/TUFM.11 The heightened sensitivity of AML cells to the
inhibition of mitochondrial translation was associated with greater mitochondrial mass, higher
oxygen consumption, and a greater reliance on oxidative phosphorylation for survival compared
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to normal hematopoietic cells.11 As such, this study highlighted a unique metabolic vulnerability
that could be exploited therapeutically in this disease.
Here, we further explored the unique mitochondrial characteristics of AML cells. In
comparison to normal hematopoietic cells, we demonstrated that a subset of AML cells had
increased mitochondrial mass. This occurred without a corresponding increase in activity of
respiratory chain complexes, including mitochondrial DNA encoded subunits. As a result, the
spare reserve capacity of these complexes was lower. Low spare reserve capacity may impede
the ability of cells to cope with oxidative stress. Accordingly, we demonstrated that increasing
the electron flux through the respiratory chain in AML cells preferentially increased oxidative
stress, and induced cell death, in comparison to normal hematopoietic cells.
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MATERIALS AND METHODS
See supplemental material for additional methods
Primary AML and normal hematopoietic cells
Primary human AML samples were isolated from peripheral blood or marrow samples from
consenting patients with AML, who had at least 80% malignant cells among low-density cells.
AML cells were isolated by Ficoll density centrifugation.
Except where otherwise noted,
primary normal hematopoietic cells refer to normal mononuclear cells obtained from healthy
consenting volunteers donating peripheral blood stem cells (PBSCs) for allogeneic stem cell
transplantation after G-CSF mobilization. Normal human bone marrow was obtained from Stem
Cell Technologies (Vancouver, BC). Normal CD34+ cells were isolated from primary normal
hematopoietic cells using the Human CD34 selection kit (StemCell Technologies). Primary cells
were cultured at 37°C in IMDM, supplemented with 20% fetal bovine serum (FBS), and
appropriate antibiotics. The University Health Network institutional review board approved the
collection and use of human tissue for this study. AML patient information and per-sample
experimental results are provided in Supplementary Tables.
Oxygen consumption rate and spare reserve capacity
Measurement of oxygen consumption rate (OCR) was performed using a Seahorse XF96
analyzer (Seahorse Bioscience, North Billerica, MA, USA). After treatment, cells were resuspended with un-buffered medium and seeded at 1 x 105 cells/well (cell lines) or 1 x 106
cells/well (primary cells) in XF96 plates. Cells were equilibrated in the un-buffered medium for
45 min at 37ºC in a CO2-free incubator before being transferred to the XF96 analyzer. Basal
OCR and the change in oxygen consumption were measured upon drug treatment.
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Spare reserve capacity of the mitochondrial respiratory chain was measured by treating cells with
oligomycin and FCCP (carbonyl cyanide p-trifluoromethoxyphenylhydrazone) in succession.
Oxygen consumption was measured as above. The spare reserve capacity of individual
respiratory complexes was determined by treating cells with complex inhibitors. The
concentrations of rotenone, antimycin, and oligomycin required to reduce oxygen consumption
rate by 50% (EC50) and the concentration of sodium azide required to reduce oxygen
consumption by 25% (EC25) were determined.
Determination of ROS generation
Intracellular reactive oxygen species (ROS) were detected by staining cells with MitoSOX (5
μM) and followed by flow cytometric analysis as described.11 Briefly, cells were stained with
MitoSOX in HBSS buffer at 37°C for 30 min, and then re-suspended in binding buffer with
Annexin V to identify viable cells and assess their reactive oxygen intermediate levels. For
detection of the progenitor population in PBSCs and primary AML samples, CD34-PE-Cy7
(clone 8G12) and CD38-PE-Cy5 (clone H1T2) were used. Data were analyzed with FlowJo
version 7.7.1 (TreeStar).
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RESULTS
AML cells have increased mitochondrial mass and biogenesis factors
To extend our previous studies, we sought to better understand the mitochondrial
characteristics of AML cells. Compared to normal hematopoietic cells, primary AML samples
had increased mitochondrial mass, as measured by both the activity of the mitochondrial matrix
enzyme citrate synthase and mitochondrial DNA copy number (Figure 1A and B). We also
measured mRNA expression of factors known to positively regulate mitochondrial biogenesis,
such as, NRF1 (nuclear respiratory factor 1), TFAM (transcription factor A, mitochondrial) and
EF-Tu, along with c-Myc, a positive regulator of these genes and mitochondrial biogenesis.12
Compared to normal hematopoietic cells, a subset of primary AML samples had increased
mRNA expression of these genes (Figure 1C-F). In addition, we also demonstrated a higher
mRNA expression of NRF1, TFAM, and c-Myc in functionally-defined AML stem cells
compared to normal hematopoietic stem cells (HSC) (Figure 1G). Increased mitochondrial mass
and mRNA expression of the above genes in the primary AML samples occurred across FAB
subtypes, cytogenetic risk groups, and known molecular mutations (Tables S1 and S2). In
addition, we analyzed the expression of the above mitochondrial biogenesis factors using a
public dataset of 283 primary AML samples.13 Similar to the above findings, a subset of AML
patients had increased expression of mitochondrial biogenesis factors (Figure S1). Thus, our
findings suggest that increased mitochondrial biogenesis in AML is a downstream consequence
of multiple dysregulated pathways.
An increase in mitochondrial mass can be indicative of larger and/or more numerous
mitochondria. Therefore, we evaluated the size and number of mitochondria in normal
hematopoietic cells and primary AML samples by transmission electron microscopy (TEM).
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Mitochondria in AML cells were generally larger than those in normal hematopoietic cells,
although fewer in number (Figure S2 and S3). As such, total mitochondrial area was higher in
most primary AML samples compared to normal hematopoietic cells (Figure S3).
Respiratory chain complex activity does not increase concomitantly with
mitochondrial mass in AML
Next, we compared the activity of mitochondrial respiratory chain complexes in AML
and normal hematopoietic cells (Figure 2) as well as in AML and solid tumor cell lines (Figure
S4). When normalized for total protein concentration, the enzymatic activity of complexes I and
II were higher in AML cell lines and primary AML patient samples compared to normal
hematopoietic cells or solid tumor cell lines. However, the activity of complexes III, IV, and V
were similar between cell types (Figure 2A and Figure S4G-H upper panel). When viewed
relative to mitochondrial mass, AML cell lines and primary AML samples had substantially
lower activities of respiratory complexes III, IV and V compared to normal hematopoietic cells
(Figure 2B and Figure S4G-H lower panel). The activity of complex I was similar between AML
and normal hematopoietic cells. In contrast, the activity of respiratory complex II was higher in
primary AML cells compared to normal hematopoietic. Of note, complex II is the only complex
that is comprised exclusively of subunits encoded by the nuclear genome. Thus, taken together,
the increased mitochondrial mass observed in AML cell lines (Figure S4) and primary AML
samples (Figure 1) was not accompanied by a corresponding increase in the activities of
respiratory complexes III, IV and V.
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Genetic modulation of mitochondrial mass does not concomitantly change
respiratory chain complex activity
To further explore the relationship between mitochondrial mass and respiratory complex
activity, we manipulated mitochondrial mass genetically by knocking down Myc or TFAM. As a
genetic model to manipulate mitochondrial mass and metabolism, we employed P493-6 cells
with inducible c-Myc knockdown (- Myc).12 Previously, we and others have used P493-6 cell
system to evaluate the effects of genetically altering mitochondrial biogenesis.11,12,14 P493-6 cells
expressing c-Myc (+ Myc) had increased mitochondrial mass (Figure S5A-B), as well as
increased expression of TFAM, NRF1, and EF-Tu compared to - Myc cells (Figure S5C). By
TEM analysis, + Myc cells also had larger mitochondria compared to - Myc cells, although the
number of mitochondria per cell was the same (Figure S6C). When normalized for total protein
concentration, enzymatic activities of complexes II and V were significantly higher in + Myc
cells compared to - Myc cells, and activities of the other complexes did not differ (Figure S5D).
However, when viewed relative to mitochondrial mass, + Myc cells had lower activities of
respiratory complexes I, III, IV and V compared to - Myc cells (Figure S5E). Similar to AML
cells, the lack of increase in activity compared to elevated mitochondrial mass was higher for
complexes III and IV.
We also measured expression levels of COX-1 (mitochondrially encoded cytochrome c
oxidase I) and COX-2 (mitochondrially encoded cytochrome c oxidase II), subunits of
respiratory complex IV encoded by the mitochondrial genome, as well as those of COX-4
(cytochrome c oxidase subunit IV), a subunit of respiratory complex IV encoded by the nuclear
genome. Consistent with our previous findings, despite alterations in mitochondrial mass, the
expression of COX-1, COX-2 and COX-4 proteins did not differ between + Myc and - Myc cells
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when normalized for total cellular protein (Figure S6). Likewise, COX-1 and COX-2 mRNA
levels showed little difference between + Myc and - Myc cells, although COX-4 mRNA levels
were slightly decreased (Figure S6). Thus, these results further support our findings that the
regulation of respiratory chain activity can be dissociated from the regulation of mitochondrial
mass.
As an additional genetic approach, we knocked down TFAM in OCI-AML2 and K562
cells using shRNA in lentiviral vectors. Target knockdown was confirmed by QRT-PCR and
immunoblotting (Figure 3A-B). Knockdown of TFAM decreased mitochondrial mass (Figure
3C-D) and oxygen consumption (Figure 3E and Figure S7). However, despite the decrease in
mitochondrial mass after TFAM knock down, the activity of respiratory chain complex III did
not change when normalized for total protein content. In fact, complex III activity increased
upon TFAM knock down when viewed relative to mitochondrial mass (Figure 3F, Figure S7).
AML cells have low spare reserve capacity in their respiratory chain complexes
To understand the functional implications of these findings, we evaluated spare reserve
capacity in AML cell lines, primary AML samples, primary normal hematopoietic cells, and
solid tumor cell lines. Spare reserve capacity reflects the difference between basal and maximal
respiratory rate, and was determined by measuring oxygen consumption after treatment with
oligomycin to block ATP synthesis and FCCP to uncouple ATP synthesis from the electron
transport chain.15-17 The spare reserve capacity in primary AML samples and cell lines was lower
than that in normal hematopoietic cells or solid tumor cell lines (Figure 4A and B) (Summary of
results in Table S3).
The above studies measured the reserve capacity in the respiratory chain as a whole. We
next sought to measure the spare reserve capacity in individual respiratory chain complexes. For
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these studies, we focused on respiratory chain complexes I, III, IV, and V. Respiratory chain
complex II was not tested in these assays as its activity was higher in AML cells than normal
cells when viewed relative to mitochondrial mass. AML cell lines, primary AML samples,
normal hematopoietic cells and solid tumor cell lines were treated with increasing concentrations
of rotenone, antimycin, sodium azide (NaN3), or oligomycin, to inhibit complexes I, III, IV, and
V, respectively. After treatment, oxygen consumption was measured, and the concentration of
complex inhibitor required to reduce oxygen consumption by 50% (EC50) was determined
(Figure 4C-H). Of note, when evaluating complex IV, we determined the concentration of NaN3
required to reduce oxygen consumption by 25% (EC25), as we could not inhibit 50% of oxygen
consumption in normal hematopoietic cells, consistent with previously described results.18 In
these assays, greater sensitivity to the complex inhibitor reflects lower spare reserve capacity in
the respiratory complex. Compared to normal hematopoietic cells and solid tumor cell lines,
AML cell lines and primary AML samples had less spare reserve capacity in complexes I, III, IV
and V (Figure 4C-H). Importantly, complexes III and IV demonstrated the most striking
differences in spare reserve capacity between AML and normal hematopoietic cells (Figure 4DE), and the activity of these complexes was lowest in AML cells when normalized for
mitochondrial mass (Figure 2B). As complex III showed the most striking difference in spare
reserve capacity, and since we could block at least 50% of oxygen consumption in AML cells
using the complex III inhibitor antimycin, we focused further studies on this complex.
As a genetic approach to investigate the relationship between mitochondrial mass and
spare reserve capacity, we knocked down Myc in P493-6 and measured changes in reserve
capacity. Despite reductions in mitochondrial mass (Figure S5A-B), activity of complex III was
unchanged (Figure S5D) and spare reserve capacity in complex III increased (Figure S5F).
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As an additional strategy to assess the reserve capacity in the respiratory complexes in
primary AML and normal cells, we treated primary AML and normal hematopoietic peripheral
blood stem cells (PBSCs) with increasing concentrations of the complex I inhibitor rotenone and
the complex III inhibitor antimycin. We then measured mitochondrial ROS production by flow
cytometry. Primary AML cells were equally sensitive to rotenone-induced ROS production
compared to normal hematopoietic cells (Figure 5A-B). In contrast, compared to normal
hematopoietic, a subset of primary AML cells (Figure 5C-F), were more sensitive to antimycininduced mitochondrial ROS production. We also investigated sensitivity towards antimycin in
bone marrow cells from AML patients and normal volunteers. Similar to the results obtained
above with the peripheral blood samples, AML cells from patients’ bone marrow showed
increased sensitivity towards antimycin (Figure S8). Of note, there was no difference in levels of
the major mitochondrial antioxidants MnSOD and Cu/ZnSOD between primary AML and
normal cells (Figure 5G). Thus, these results provide further evidence that reserve capacity is
reduced in a subset of primary AML cells at the level of complex III.
AML cells are more sensitive to mitochondrial oxidative stress
In addition to being sensitive to inhibitors of the respiratory chain, we hypothesized that
AML cells would be more vulnerable to mitochondrial oxidative stress. Towards this end, we
increased electron flux through the respiratory chain by treating AML cells with increasing
concentrations of the fatty acid palmitate to increase the production of oxidative metabolites.
Treatment with palmitate increased levels of the TCA cycle component succinate, decreased
spare reserve capacity, increased mitochondrial ROS production, and induced cell death in AML
cells (Figure 6A-B and Figure S9). Palmitate-induced cell death appeared ROS-dependent, as
pre-treatment with the ROS scavenger NAC blocked cell death (Figure 6C). Further supporting
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the proposed mechanism, reductions in spare reserve capacity after treating cells with the
respiratory chain complex III inhibitors antimycin and myxothiazol enhanced ROS production
after palmitate treatment (Figure S10). Of note, the combination of palmitate with cytarabine or
daunorubicin, the standard chemotherapeutic agents used in the treatment of AML, produced
primarily additive cytotoxicity towards AML cells (Figure S11).
To determine whether the effects of palmitate were mediated through mitochondrial fatty
acid oxidation, we knocked down CPT1a (carnitine palmitoyltransferase 1a [liver]) and PPARα
through lentiviral vector-mediated shRNA in OCI-AML-2 cells. CPT1a is a transmembrane
protein of the mitochondrial outer membrane, which converts long-chain acyl-CoA such as
palmitoyl to acyl carnitine, which enters the mitochondrial matrix and undergoes fatty acid
oxidation.19 PPARα is a transcription factor that positively regulates β-fatty acid oxidation.20
Thus, CPT1a and PPARα knockdown would prevent palmitate oxidation and entry of electrons
through the respiratory chain. Consistent with the proposed mechanism, knockdown of CPT1a
and PPARα abrogated the effects of palmitate on cell viability and mitochondrial ROS
production (Figure 6D-K). Similar results were obtained for CPT1a knockdown in K562 cells
(Figure S12).
As an alternate approach to induce oxidative stress by promoting electron flux through
the respiratory chain, we treated cells with the cell-permeable TCA cycle component dimethyl
succinate. Similar to the effects of palmitate, dimethyl succinate increased mitochondrial ROS
production, and induced cell death in AML cells (Figure S13). Further supporting our proposed
mechanism, sensitivity of AML cells to dimethyl succinate was increased by shifting metabolism
towards oxidative phosphorylation by culturing AML cells in galactose containing medium
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increased (Figure S13C-D). In addition, reducing dependence on mitochondrial metabolism by
knockdown of Myc rendered cells resistant to dimethyl succinate (Figure S13F).
Palmitate induces oxidative stress in primary AML cells in vitro and in vivo
Next, we evaluated the effects of increasing oxidative stress on primary AML samples
and normal hematopoietic cells. Similar to the above mentioned results using cell lines, primary
AML cells were more sensitive to palmitate treatment than normal hematopoietic cells (Figure
7A). In addition, pre-treatment of cells from primary AML samples with palmitate reduced their
clonogenic growth in colony formation assays and reduced their ability to engraft immune
deficient mice suggesting a selective effect on the AML progenitor population. In contrast,
treatment of normal hematopoietic cells with palmitate did not inhibit their clonogenic growth or
their ability to engraft mice (Figure 7B). Palmitate treatment increased ROS production in
primary AML samples and had no effect on ROS production in normal hematopoietic cells
(Figure 7C). Taken together, these results further support that promoting electron flux through
the respiratory chain can target AML progenitor cells by increasing oxidative stress.
To assess the in vivo anti-leukemic efficacy of oxidative stress, we first utilized a
leukemia xenograft model with the OCI-AML2 cells. Mice were treated with palmitate or
vehicle control for 11 days after tumors became palpable. Compared to vehicle control, palmitate
decreased tumor mass and volume without any gross or histologic changes to the organs at
necropsy (Figure 7D-E and Figure S14).
As an additional approach to assess the in vivo anti-leukemic efficacy of palmitate, we
evaluated palmitate in mice engrafted with cells from primary AML samples. Primary AML cells
were injected intra-femorally into irradiated NOD/SCID mice preconditioned with anti-CD122.
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Compared to vehicle control, 2 of 3 AML patient samples treated with palmitate decreased
human leukemic burden in the mouse bone marrow without altering renal or liver functions
(Figure S14G). Furthermore, engrafted AML cells harvested from the bone marrow of palmitatetreated primary mice had a dampened ability to engraft NOD/SCID mice in secondary transplant
experiments (Figure 7F and Figure S15). Thus, our results suggest that overwhelming the
respiratory chain displays anti-leukemic activity, including the ability to target AML stem and
progenitor cells.
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DISCUSSION
In this study, we showed that AML cells have increased mitochondrial mass without a
corresponding increase in the activity of the respiratory chain enzymes that contain
mitochondrially-encoded subunits (Complexes I, III, IV and V). As a result, AML cells display
lower spare reserve capacity in their respiratory chain compared to normal hematopoietic cells, a
potential metabolic vulnerability.
Low spare reserve capacity in AML cells suggests that a subset of patients might benefit
from strategies that target the oxidative phosphorylation (OXPHOS) chain. The antidiabetic
agent and a known inhibitor of complex I, metformin, has been evaluated in preclinical and
clinical studies of solid tumors and shown promising results.21 Potentially, this agent could also
be evaluated in AML. In addition, a potent inhibitor of respiratory complex I, IACS-1131,
selectively induced death in a subset of AML cells and patient samples preferentially over
normal hematopoietic cells.22 Adding to the potential value of targeting the OXPHOS chain, a
report by Lagadinou et al23 demonstrated that AML cells and stem cells cannot upregulate
glycolysis after the inhibition of OXPHOS.
Interestingly, some of our results in AML appear consistent with the metabolic
consequences of aging. In studies of rat neuron cells, respiratory rates increase, spare reserve
capacity declines and mitochondrial mass increases with aging.24-27 The cause of the decline in
the spare reserve capacity in these aging rat cells is unclear, but may relate to the accumulation
of nitric oxide that damages respiratory complexes.10,27 The aging mitochondria and
dysfunctional respiratory complexes lead to increased ROS production, which results in further
damage to the mitochondria. In addition, aging mitochondria accumulate mitochondrial DNA
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damage that can also impair respiratory complex activity and increase ROS production.25,28,29
Thus, we speculate that the increased demands on mitochondrial activity in AML lead to
premature aging with a resultant decline in spare reserve capacity of the respiratory chain.
Previous studies have demonstrated that AML cells have increased rates of fatty acid
oxidation.2 As such, attention has focused on inhibiting fatty acid oxidation as a therapeutic
strategy for AML. In contrast, we demonstrated that AML cells were vulnerable to strategies that
promote oxidative metabolism and increase electron flux through the respiratory chain. Using
palmitate and dimethyl succinate, we increased cellular levels of TCA cycle substrates and
electron flux through the respiratory chain. This induced oxidative stress in AML cells,
triggering cell death. This work is not meant to suggest that patients with AML should be placed
on high fat diets. Rather, it highlights that strategies that promote electron flux through the
respiratory chain may a new therapeutic strategy for some AML patients. Through its ability to
increase mitochondrial mass and β-oxidation,30,31 the PPARα agonist bezafibrate may have antileukemic activity. Alternatively, promoting OXPHOS flux with compounds such as 2deoxyglucose, 3-bromopyruvate32,33 or dichloroacetic acid34 may also selectively induce death in
a subset of AML, and could be evaluated alone or in combination with standard
chemotherapeutic agents.
In summary, AML cells have dysregulated mitochondrial biogenesis and metabolism.
These abnormalities highlight new vulnerabilities and potential novel therapeutic strategies for
the treatment of this disease. Thus, while the genetic heterogeneity of AML may be difficult to
target therapeutically, the resultant metabolic dysfunction may be more amenable to therapeutic
intervention.
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Study Approvals
The University Health Network and Mount Sinai Hospital institutional review boards approved
the collection and use of human tissue for this study. All animal studies were carried out
according to the regulations of the Canadian Council on Animal Care and with the approval of
the Ontario Cancer Institute animal ethics review board.
ACKNOWLEDGMENTS
This work was supported by the Canadian Stem Cell Network, the Leukemia and Lymphoma
Society, the National Institutes of Health (NCI 1R01CA157456), The Ontario Ministry of
Research and Innovation, the Princess Margaret Hospital Foundation, and the Ministry of Long
Term Health and Planning in the Province of Ontario. A.D.S. supported by the Barbara Baker
chair in Leukemia and Related Diseases. D.V.J is a Fonds de recherche du Québec – Santé (FRQS)
postdoctoral scholar. We thank Jill Flewelling for administrative assistance and Aisha ShamasDin for help with preparing the final manuscript.
Author contributions
S.S. & D.V.J designed the study, collected and analyzed data and wrote the paper. S.P, T.E.C,
M.S., B.J., R.H., M.G., X.W., Y.J., M.A.S., F.-H. L., N.M., R.L., and S.X. performed
experiments, collected and analyzed data. C.A.G. analyzed data and helped write the manuscript.
P.J.M., L.Z.P., and J.E.D. contributed technical expertise and resources. I.R. and M.D.M
contributed patient material. A.D.S. designed the study and wrote the paper. All authors
reviewed and edited the paper.
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Conflicts of interest: The authors have no conflicts of interest to disclose.
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17. Xun Z, Lee DY, Lim J, et al. Retinoic acid-induced differentiation increases the rate of
oxygen consumption and enhances the spare respiratory capacity of mitochondria in SH-SY5Y
cells. Mech Ageing Dev. 2012;133(4):176-185.
18. Macchioni L, Corazzi T, Davidescu M, Francescangeli E, Roberti R, Corazzi L. Cytochrome
c redox state influences the binding and release of cytochrome c in model membranes and in
brain mitochondria. Mol Cell Biochem. 2010;341(1-2):149-157.
19. Henique C, Mansouri A, Fumey G, et al. Increased mitochondrial fatty acid oxidation is
sufficient to protect skeletal muscle cells from palmitate-induced apoptosis. J Biol Chem.
2010;285(47):36818-36827.
20. Minnich A, Tian N, Byan L, Bilder G. A potent PPARalpha agonist stimulates mitochondrial
fatty acid beta-oxidation in liver and skeletal muscle. Am J Physiol Endocrinol Metab.
2001;280(2):E270-E279.
21. Leone A, Di Gennaro E, Bruzzese F, Avallone A, Budillon A. New perspective for an old
antidiabetic drug: metformin as anticancer agent. Cancer Treat Res. 2014;159:355-376.
22. Polina Matre, Marina Protopopova, Ningping Feng, et al. Novel Nanomolar Potency
Mitochondrial Complex I Inhibitor Iacs-1131 Selectively Kills Oxphos-Dependent AML Cells.
Paper presented at 56th ASH Annual Meeting & Exposition. December 8, 2014. San Francisco,
CA.
23. Lagadinou ED, Sach A, Callahan K, et al. BCL-2 inhibition targets oxidative
phosphorylation and selectively eradicates quiescent human leukemia stem cells. Cell Stem Cell.
2013;12(3):329-341.
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24. Jones TT, Brewer GJ. Age-related deficiencies in complex I endogenous substrate
availability and reserve capacity of complex IV in cortical neuron electron transport. Biochim
Biophys Acta. 2010;1797(2):167-176.
25. Shmookler Reis RJ, Goldstein S. Mitochondrial DNA in mortal and immortal human cells.
Genome number, integrity, and methylation. J Biol Chem. 1983;258(15):9078-9085.
26. Barrientos A, Casademont J, Cardellach F, et al. Qualitative and quantitative changes in
skeletal muscle mtDNA and expression of mitochondrial-encoded genes in the human aging
process. Biochem Mol Med. 1997;62(2):165-171.
27. Lee HC, Yin PH, Lu CY, Chi CW, Wei YH. Increase of mitochondria and mitochondrial
DNA in response to oxidative stress in human cells. Biochem J. 2000;348 Pt 2:425-432.
28. Wei YH, Lee HC. Oxidative stress, mitochondrial DNA mutation, and impairment of
antioxidant enzymes in aging. Exp Biol Med (Maywood). 2002;227(9):671-682.
29. Lee HC, Wei YH. Mitochondrial biogenesis and mitochondrial DNA maintenance of
mammalian cells under oxidative stress. Int J Biochem Cell Biol. 2005;37(4):822-834.
30. Bonnefont JP, Bastin J, Behin A, Djouadi F. Bezafibrate for an inborn mitochondrial betaoxidation defect. N Engl J Med. 2009;360(8):838-840.
31. Yamaguchi S, Li H, Purevsuren J, et al. Bezafibrate can be a new treatment option for
mitochondrial fatty acid oxidation disorders: evaluation by in vitro probe acylcarnitine assay.
Mol Genet Metab. 2012;107(1-2):87-91.
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32. Raez LE, Papadopoulos K, Ricart AD, et al. A phase I dose-escalation trial of 2-deoxy-Dglucose alone or combined with docetaxel in patients with advanced solid tumors. Cancer
Chemother Pharmacol. 2013;71(2):523-530.
33. Hulleman E, Kazemier KM, Holleman A, et al. Inhibition of glycolysis modulates
prednisolone resistance in acute lymphoblastic leukemia cells. Blood. 2009;113(9):2014-2021.
34. Zhang N, Palmer AF. Development of a dichloroacetic acid-hemoglobin conjugate as a
potential targeted anti-cancer therapeutic. Biotechnol Bioeng. 2011;108(6):1413-1420.
Page 23 of 30
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FIGURE LEGENDS
Figure 1. Primary AML samples have increased mitochondrial mass and mRNA level of
mitochondrial biogenesis regulators.
(A) Citrate synthase activity as a marker of mitochondrial mass was determined in primary
normal hematopoietic cells (GCSF mobilized peripheral blood mononuclear cells) and AML
samples.
(B) Mitochondrial DNA copy number was determined in primary normal hematopoietic and
AML samples. DNA was extracted from cells and mRNA levels of the mitochondrial ND1 gene
(mtND1) relative to human globulin (HGB) were measured by qRT-PCR.
(C-F) Expression of NRF1, TFAM, EF-Tu, and c-Myc mRNA was measured in primary normal
hematopoietic and AML samples. Expression was determined by qRT-PCR using 18s RNA as an
internal standard.
(G) Expression of NRF1, TFAM, EF-Tu, and c-Myc mRNA in functionally-defined AML stem
cells (LSC) vs normal hematopoietic cells (HSC) (GCSF mobilized peripheral blood
mononuclear cells). Data was derived from the publically accessible data set GSE 30377,
achieved on the Gene Expression Omnibus.
In all panels, * p < 0.05, ** p < 0.01 *** p < 0.001 as determined by the unpaired Student’s ttest.
Page 24 of 30
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Figure 2. Activities of respiratory chain complexes do not increase in primary AML
samples in parallel with mitochondrial mass.
The activities of respiratory complexes I-V were measured in isolated mitochondria from
primary normal hematopoietic (GCSF mobilized peripheral blood mononuclear cells) and
primary AML samples. (A) Complex activity was normalized to total protein concentration. (B)
Complex activity was normalized to mitochondrial mass using citrate synthase activity. Data
represent the mean complex activity + SD from representative experiments performed in
triplicate. * p<0.05, ** p < 0.001, *** p < 0.0001 as determined by unpaired student t-test.
Figure 3. Genetic inhibition of mitochondrial biogenesis factor, TFAM rescues effects of
oxidative stress.
(A, B) OCI-AML-2 cells were infected with TFAM targeting shRNAs or control sequences in
lentiviral vectors. Four days post-transduction, TFAM mRNA expression relative to 18S was
made by qRT-PCR (A) and TFAM protein expression was determined by immunoblotting (B).
(C) DNA was extracted from cells, and quantitative PCR was used to measure levels of ND1
relative to human globulin (HGB). ND1/HGB ratio is shown relative to control cells.
(D) Citrate synthase activity as a marker of mitochondrial mass was determined in TFAM knock
down clones.
(E) Basal oxygen consumption rate was shown after 1 hr incubation in cell chambers.
(F) Activity of complex III was measured in control and TFAM knockdown cells. Left panel
shows complex activity was normalized to total protein concentration. Right panel shows
complex activity was normalized to mitochondrial mass using citrate synthase activity.
Page 25 of 30
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Data represent the mean complex activity + SD from representative experiments performed in
triplicate. TFAM knock down experiments in AML cells were repeated twice. In all panels, * p <
0.05, ** p < 0.001 *** p < 0.0001 as determined by the unpaired Student’s t-test.
Figure 4. Primary AML cells and leukemic cell lines have lower spare reserve capacity in
their respiratory chain enzymes than normal hematopoietic cells.
Spare reserve capacity measured by oxygen consumption rate (OCR) of primary AML samples
and normal hematopoietic cells (A) and leukemic cell lines and solid tumour cell lines (B) after
the sequential addition of oligomycin and FCCP.
(C) Primary AML and normal hematopoietic cells were treated with increasing concentrations of
antimycin and changes in oxygen consumption were measured. A representative graph is shown.
Primary AML and normal hematopoietic cells (D-E) and leukemia, MCF-7 breast, and OVCAR3 ovarian cancer cells (F-H) were treated with increasing concentrations of inhibitors of complex
I (rotenone) (D & F), complex III (antimycin) (D & G), or complex V (oligomycin) (D & H).
The concentration of the complex inhibitor required to reduce oxygen consumption rate by 50%
(EC50) was determined. Data for cell lines represent the mean complex activity + SD from
representative experiments performed in triplicate. Experiments with cell lines were performed at
least three times.
(E) Primary AML cells and normal hematopoietic cells were treated with increasing
concentrations of complex IV inhibitor, sodium azide (NaN3), and changes in oxygen
consumption were measured. A representative graph is shown. The concentration of NaN3
Page 26 of 30
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required to reduce oxygen consumption rate by 25% (EC25) was determined. In all panels, * p <
0.05, ** p < 0.001 *** p < 0.0001 as determined by the unpaired Student’s t-test.
Figure 5: Primary AML cells have increased sensitivity to complex III inhibition
(A-D) Peripheral blood stem cells (PBSCs) (A & C) and AML patient samples (B & D) were
treated with the indicated concentrations of rotenone or antimycin to block complex I and III,
respectively. After 2 hours (rotenone) or 4 hours (antimycin) of treatment, cells were stained
with 5 µM MitoSOX Red. After 30 minutes, the stain was replaced with Annexin V to detect
apoptotic cells and cells were analyzed using a BD FACS Canto II flow cytometer with a High
Throughput Sampler (HTS). Data represents the mean value of triplicates. Each curve represents
a patient/normal sample.
(E, F) For detection of the progenitor population, , CD34-PE-Cy7 (Clone 8G12) and CD38-PECy5 (Clone HIT2) antibodies were also added with mitosox.
(G) Immunoblots of cell lysates from PBSCs and AML patients probed with the indicated
antibodies against SOD1 (Cu/ZnSOD), present in the intermembrane space as well as cytoplasm,
and SOD2 (MnSOD), present in the matrix. Lower panel shows actin as a loading control. 30 µg
of total protein loaded in each lane.
Page 27 of 30
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Figure 6. Low spare reserve capacity renders AML cells sensitive to oxidative metabolic
stress by palmitate and this sensitivity can be rescued by genetically inhibiting fatty acid
oxidation pathway.
(A) Leukemic cells and MCF-7 cells were treated with increasing concentrations of palmitate for
72 hrs. Cell viability and growth was measured by Cell Titer Fluor viability assay.
(B) OCI-AML-2 and HL-60 cells were treated with increasing concentrations of palmitate for 24
hours. ROS production was measured by staining with MitoSOX and flow cytometry. In all
panels, data represent mean ± SD of representative experiments.
(C) OCI-AML-2 cells were treated with increasing concentrations of palmitate for 72 hours in
the presence and absence of NAC. Cell growth and viability was measured by Cell Titer Fluor
viability assay
(D-F) OCI-AML-2 cells were infected with lentiviral vectors containing shRNAs targeting
CPT1a or non-cellular targets (control). Six days post-infection, CPT1a mRNA expression
relative to 18s RNA was analyzed by qRT-PCR (D) and CPT1a protein expression was
determined by immunoblotting (E). Cell growth and viability was measured by Cell Titer Flo
after treating cells with palmitate for 72 hours (F).
(G) Infected OCI-AML-2 cells were treated with increasing concentrations of palmitate for 24
hours. ROS production was measured by staining with MitoSOX and flow cytometry. In all
panels, error bars represent mean ± SD of representative experiments.
(H-K) OCI-AML-2 cells were infected with lentiviral vectors containing shRNAs targeting
PPARα or non-cellular targets (control). Four days post-infection, PPARα mRNA expression
relative to 18s RNA was analyzed by qRT-PCR (H). Cell growth and viability was measured by
Cell Titer Flo after treating cells with palmitate for 72 hours (I). Infected OCI-AML-2 cells
Page 28 of 30
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were treated with increasing concentrations of palmitate. 72 hours after treatment, cell viability
was measured by Annexin V/PI staining (J). Infected OCI-AML-2 cells were treated with
increasing concentrations of palmitate for 24 hours. ROS production was measured by staining
with MitoSOX and flow cytometry (K).
In all panels, error bars represent mean ± SD of independent/representative experiments. * p <
0.05, ** p < 0.001 as determined by Tukey’s test after one-way ANOVA analysis, comparing to
controls. CPT1a and PPARα knock down experiments were repeated twice.
Figure 7. Palmitate demonstrates therapeutic efficacy on AML growing in vitro and in
vivo.
(A) CD34+ AML cells, normal bulk hematopoietic cells, and CD34+ normal hematopoietic cells
were treated with increasing concentrations of palmitate (stock concentration of 2 mM palmitate
conjugated with 0.17 mM BSA). 24 hours after treatment, cell viability was measured by
Annexin V/PI staining.
(B) Primary AML (n = 3) and normal hematopoietic cells (n = 3) were treated with 50 µM
palmitate for 24 hours and plated in clonogenic growth assays. The number of resultant colonies
was counted, including CFU-GM, BFU-E, and CFU-L colony forming units. The mean
percentage of colonies obtained ± SD compared to buffer control treated cells is shown.
(C) Normal hematopoietic cells and primary AML samples were treated with increasing
concentrations of palmitate. After 4 hours of treatment, levels of ROS were measured by
staining with MitoSOX and flow cytometry.
Page 29 of 30
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(D) Primary AML and Lin- CD34+-enriched human cord blood cells were treated with 50 µM
palmitate or buffer control for 24 hours. After treatment, equal cell numbers were injected into
the right femurs of irradiated NOD/SCID mice preconditioned with anti-CD122. Eight weeks
later, the percentage of human CD45+CD33+CD19- cells in the non-injected femurs was
measured by FACS. *** p < 0.0001 as determined by the unpaired Student’s t-test.
(E) SCID mice were injected subcutaneously with OCI- AM-2 leukemia cells. Once tumors were
palpable (day 7), mice were treated with palmitate or vehicle control as described in Materials
and Methods. Tumor volume was measured over time and tumor mass was measured at the end
of the experiment. Data represent mean + SD. *** p < 0.001, by Student’s t-test.
(F) Sublethally irradiated NOD/SCID mice preconditioned with anti-mouse CD122 were
injected intrafemorally with primary AML cells. Six days after injection, mice were treated with
palmitate or vehicle control as described in Materials and Methods. Engraftment of human AML
cells into the mouse marrow was assessed by determining the percentage of human
CD45+CD33+CD19- cells by flow cytometry. * p < 0.01 by Student’s t-test.
Page 30 of 30
A
B
5
4
R e la tiv e m t N D 1
( n m o le s /m g /m in )
300
C it r a t e S y n t h a s e
***
***
200
100
3
2
1
0
0
N o rm a l
n = 10
C
AML
N o rm a l
AML
n = 17
n = 11
n = 12
D
NRF1
TFAM
**
R e la tiv e m R N A e x p re s s io n
4
3
2
1
0
1
n o rm a l
n = 15
n = 9
AML
n = 15
F
*
R e la tiv e m R N A e x p re s s io n
R e la tiv e m R N A e x p re s s io n
2
n = 9
4
3
2
1
0
cM yc
70
50
30
*
20
10
0
n o rm a l
AML
n = 9
Relative transcription level
*
1.10
1.05
1.00
0.95
LSC
1.3
**
1.2
1.1
1.0
0.9
HSC
AML
n = 16
cMyc
EF-Tu
TFAM
NRF1
Relative transcription level
G
n o rm a l
n = 16
n = 9
Relative transcription level
3
0
5
Figure 1.
4
AML
E F -T u
HSC
5
n o rm a l
E
1.15
6
LSC
9.75
9.50
9.25
9.00
8.75
8.50
8.25
8.00
7.75
Relative transcription level
R e la tiv e m R N A e x p re s s io n
*
5
HSC
LSC
*
1.5
1.4
1.3
1.2
1.1
1.0
0.9
0.8
HSC
LSC
A
B
Complex I
(nmoles/mg/min)
Complex I/Citrate synthase
**
30
25
20
15
10
5
0
normal
0.30
0.25
0.20
0.15
0.10
0.05
0.00
normal
AML
Complex II/Citrate synthase
***
100
80
60
40
20
0
75
50
25
0
normal
AML
Complex IV
(nmoles/mg/min)
40
30
20
10
0
normal
AML
Complex V
(nmoles/mg/min)
18
15
12
9
6
3
0
normal
Figure 2.
AML
Complex III/Citrate synthase
Complex III
(nmoles/mg/min)
100
***
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
AML
normal
AML
Complex IV/Citrate synthase
normal
Complex V/Citrate synthase
Complex II
(nmoles/mg/min)
120
AML
**
1.6
1.2
0.8
0.4
0.0
normal
0.4
AML
***
0.3
0.2
0.1
0.0
AML
normal
*
0.15
0.10
0.05
0.00
normal
AML
Figure 3.
***
50
100
75
50
25
0
sh
R
N
A
TF
AM
1
TF
AM
2
***
0
du
ce
d
sh
R
N
TF A
AM
TF 1
AM
2
100
ct
rl
150
OCR (pMoles/min)
D
ct
rl
C.S. (nmoles/mg/min)
Relative TFAM expression
un
tra
ns
du
ce
ct
d
rl
sh
R
N
TF A
AM
TF 1
AM
2
0.0
Complex III/Citrate synthase
du
ce
d
sh
R
N
TF A
AM
TF 1
AM
2
ct
rl
un
tra
ns
a-tubulin
un
tra
ns
du
ce
ct
d
rl
sh
R
N
TF A
AM
TF 1
AM
2
0.4
un
tra
ns
du
ce
ct
d
rl
sh
R
N
TF A
AM
TF 2
AM
1
un
tra
ns
Complex III
(nmoles/mg/min)
1.0
0.8
0.6
TFAM
Relative mtND1
A
B
C
0.2
E
200
150
100
50
0
F
1.0
*
**
0.8
0.6
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
0.0
C
P
FC
P
C
FC
100
U937
350
300
spare
reserve
capacity
300
% OCR
400
% OCR
150
MCF-7
OVCAR3
AML-2
HL-60
NB4
THP1
OCI-M2
K562
400
O
lig
om
yc
in
450
O
500
lig
om
yc
in
B
A
Normal
200
AML
100
spare
reserve
capacity
250
200
50
0
0
100
80
60
40
20
0
0
10
40
30
20
400
Spare Reserve Capacity
(% increase in OCR)
60
50
90
80
70
TIME (min)
Time (min)
400
350
200
*
Spare Reserve Capacity
(% increase in OCR)
300
*
100
0
AML
Normal
300
250
*
200
**
*
*
150
* **
100
50
Normal
AML
80
60
40
EC50
20
0
10 -8
10 -9
0
10 -7
10 -6
10 -5
Antimycin (M)
*
[Antimycin] at EC50 of OCR (nM)
100
[Rotenone] at EC50 of OCR (nM)
120
50
40
30
20
10
0
Normal
AML
***
40
30
20
10
0
Normal
AML
250
*
200
150
100
50
0
Normal
F
10 -2
0.2
0.0
Normal
AML
**
0
Figure 4.
100
**
50
**
O
C
I-A
M
L2
AR
-3
H
L60
0
VC
H
L60
M
L2
C
I-A
O
O
VC
AR
-3
F7
M
C
al
0
150
O
**
200
F7
**
250
M
C
20
300
al
40
350
N
or
m
60
[Oligomycin] at EC50 of OCR (nM)
H
80
N
or
m
G
[Antimycin] at EC50 of OCR (nM)
O
O
NaN3 (M)
***
20
H
L60
10 -3
M
L2
0
10 -4
10 -5
40
C
I-A
0
0.4
60
AR
-3
20
0.6
80
VC
EC25
40
0.8
100
F7
60
1.0
120
M
C
80
*
1.2
al
[NaN3] at EC25 of OCR (mM)
Normal
AML
100
N
or
m
120
[Rotenone] at EC50 of OCR (nM)
E
OCR (%)
[Oligomycin] at EC50 of OCR (nM)
D
C
OCR (%)
N
or
m
a
M l
C
FO
VC 7
AR
-3
AM
L2
H
L60
N
B4
TH
P1
O
C
I-M
2
U
93
7
K5
62
0
AML
A
B
B u lk A M L p a t ie n t s a m p le s :
100
80
60
40
20
0
0
5
10
15
A n n e x i n V - p o p u la t io n
C o m p le x I in h i b it io n
P e r c e n t a g e o f M it o s o x r e d +
A n n e x i n V - p o p u la t io n
P e r c e n t a g e o f M it o s o x r e d +
P B S C s : C o m p le x I in h ib it io n
100
80
60
40
20
0
0
5
R o te n o n e (u M )
C
10
15
R o te n o n e (u M )
D
B u lk A M L p a t ie n t s a m p le s :
C o m p le x I II i n h ib it io n
100
80
60
40
20
0
0 .0
1 2 .5 2 5 .0 3 7 .5 5 0 .0 6 2 .5 7 5 .0
A n n e x i n V - p o p u la t io n
P e r c e n t a g e o f M it o s o x r e d +
A n n e x i n V - p o p u la t io n
P e r c e n t a g e o f M it o s o x r e d +
P B S C s : C o m p le x III in h ib it io n
100
80
60
40
20
0
0 .0
1 2 .5 2 5 .0 3 7 .5 5 0 .0 6 2 .5 7 5 .0
A n t im y c in ( u M )
A n t im y c in ( u M )
A M L p a t ie n t s a m p le s
C o m p le x I II i n h ib it io n
C D 3 4 + p o p u la t io n : C o m p le x III in h ib it io n
100
80
60
40
20
0
0 .0
1 2 .5 2 5 .0 3 7 .5 5 0 .0 6 2 .5 7 5 .0
A n t im y c in u M
G
PBSCs
A n n e x i n V - p o p u la t io n
P B S C s C D 3 4 + p o p u la t io n :
P e r c e n t a g e o f M it o s o x r e d +
A n n e x i n V - p o p u la t io n
F
P e r c e n t a g e o f M it o s o x r e d +
E
100
80
60
40
20
0
0 .0
1 2 .5 2 5 .0 3 7 .5 5 0 .0 6 2 .5 7 5 .0
A n t im y c in u M
AML patient samples
a-Cu/ZnSOD
a-MnSOD
a-Actin
Figure 5.
B
C
80
60
40
20
0
0
100
200
300
400
*
2.0
1.5
1.0
0.5
0.0
500
Relative mitoROS
MCF-7
AML-2
HL-60
OCI-M2
U937
K562
Relative mitoROS
Growth and Viability (%)
100
AML-2
HL-60
AML-2
120
*
15
10
*
5
0
250 375
0
palmitate (mM)
Growth & Viability (%)
A
250 375
0
palmitate (mM)
70
60
50
40
30
20
10
0
1.00
0.75
0.50
0.25
42 kDa
Actin
rl
s
ctrl shRNA
CPT1a 1
CPT1a 2
80
60
40
20
0
125
250
375
Relative mitoROS
G
100
0
CPT1a
ct
un
tra
Growth & Viability (%)
F
86 kDa
uc
ed
hR
N
A
C
PT
1a
C
PT 1
1a
2
0.00
ns
d
Relative CPT1a expression
E
1.25
500
10
8
6
4
2
0
ctrl shRNA
CPT1a 1
CPT1a 2
0
Growth & Viability (%)
1.0
0.8
0.6
0.4
0.2
ct
rl
du
ce
d
sh
R
N
A
PP
AR
a
PP
1
AR
a
2
0.0
un
tra
ns
J
1.2
120
ctrl shRNA
PPARa 1
100
80
60
40
20
0
0
125 250 375 500
0
0
100 200 300 400 500
palmitate (mM)
Figure 6.
Relative mitoROS
% Annexin V Positive
10
80
60
40
20
0
ctrl shRNA
PPARa 1
PPARa 2
0
25
50
0
125 250 375 500
palmitate (mM)
PPARa
7
6
5
4
3
2
1
0
ctrl shRNA
PPARa 2
100
palmitate (mM)
untransduced
ctrl shRNA
PPARa 1
PPARa 2
20
120
K
PPARa
30
Growth & Viability (%)
I
Relative PPARa expression
H
25 50 100 200
palmitate (mM)
palmitate (mM)
100
palmitate (mM)
- NAC
+ NAC
**
*
250
375
500
palmitate (m M)
palmitate (mM)
D
**
80
60
AML
40
20
0
Normal
0
20 40 60 80 100
palmitate (m M)
150
Clonogenic growth (% control)
Clonogenic growth (% control)
B
Dead cells (% control)
A
CFU-GM
BFU-E
125
100
75
50
25
0
Normal
150
125
100
75
50
25
0
AML
D
4
2
0
0
25 50 100
palmitate (mM)
10
8
6
4
2
0
0
25 50 100
palmitate (mM)
6
4
2
0
0
AML
% of CD45+ CD33+ CD19-
6
12
Relative mitochondrial ROS
8
Relative mitochondrial ROS
AML
Relative mitochondrial ROS
C
25 50 100
palmitate (mM)
80
60
20
0
25 50 100
palmitate (mM)
6
4
2
0
0
25 50 100
palmitate (mM)
4
2
0
0
25 50 100
palmitate (mM)
20
15
10
5
0
control palmitate
control
1200
AML (secondary)
AML (primary)
900
palmitate
300
0
1400
1200
1000
800
600
400
200
0
Figure 7.
3
9 12
6
Time (days)
***
15
18
100
100
**
75
50
25
0
***
75
50
25
0
Control
control palmitate
% CD45+CD33+CD19-
600
Tumour mass (mg)
6
F
1500
0
% of CD45+ CD33+ CD19-
0
Relative mitochondrial ROS
0
Relative mitochondrial ROS
2
control palmitate
Normal
% CD45+CD33+CD19-
Tumour volume (mm )
Relative mitochondrial ROS
3
E
4
***
40
Normal
6
CFU-L
Palmitate
Control
Palmitate
From www.bloodjournal.org by guest on July 31, 2017. For personal use only.
Prepublished online January 28, 2015;
doi:10.1182/blood-2014-08-594408
AML cells have low spare reserve capacity in their respiratory chain that
renders them susceptible to oxidative metabolic stress
Shrivani Sriskanthadevan, Danny V. Jeyaraju, Timothy E. Chung, Swayam Prabha, Wei Xu, Marko Skrtic,
Bozhena Jhas, Rose Hurren, Marcela Gronda, Xiaoming Wang, Yulia Jitkova, Mahadeo A. Sukhai,
Feng-Hsu Lin, Neil Maclean, Rob Laister, Carolyn A. Goard, Peter J. Mullen, Stephanie Xie, Linda Z.
Penn, Ian M. Rogers, John E. Dick, Mark D. Minden and Aaron D. Schimmer
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