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Transketolase Regulates the Metabolic Switch to Control Breast Cancer Cell
Metastasis via the Alpha-ketoglutarate Signaling Pathway
Chien-Wei Tseng1,2
, Wen-Hong Kuo3, Shih-Hsuan Chan
1,2,4, Hong-Lin Chan
5,
King-Jen Chang6, Lu-Hai Wang*
1,2
1Graduate Institute of Integrated Medicine, China Medical University, Taichung, 404,
Taiwan 2Institute of Molecular and Genomic Medicine, National Health Research Institutes,
35 Keyan Road, Zhunan, Miaoli Country 350, Taiwan 3Department of Surgery, National Taiwan University Hospital, Taipei 100, Taiwan
4Institute of Molecular Medicine, National Tsing Hua University, Hsinchu 300,
Taiwan 5Institute of Bioinformatics and Structural Biology, National Tsing Hua University,
Hsinchu 300, Taiwan 6Department of Surgery, Taiwan Adventist Hospital, Taipei 105, Taiwan
*Corresponding author
Running title: TKT regulates breast cancer metastasis via α-KG signaling
Statement of significance: Findings uncover the clinical significance of TKT
in breast cancer progression and metastasis and demonstrate effective
combined therapies against TKT and α-KG.
Abbreviations list: transketolase, TKT; alpha-ketoglutarate, α-KG; succinate
dehydrogenase, SDH; fumarate hydratase, FH; HIF prolyl hydroxylase 2, PHD2;
triple negative breast cancer, TNBC; aldolase A, ALDOA; triose phosphate isomerase,
TPIS; α-enolase, ENOA; pyruvate dehydrogenase E1, ODPB; pentose phosphate
pathway, PPP; differential gel electrophoresis, DIGE; enhanced chemiluminescence,
ECL; Institutional Animal Care and Use Committee, IACUC; Oxygen consumption
rate, OCR; extracellular acidification rate, ECAR; carbonyl
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cyanide-p-trifluoromethoxyphenylhydrazone, FCCP; 2-deoxy glucose, 2-DG;
bioluminescence imaging, BLI; vascular endothelial growth factor, VEGF;
G-protein-coupled receptor, GPCR; L-2HG dehydrogenase, L2HGDH; D-2HG
dehydrogenase, D2HGDH; JmjC domain-containing histone demethylase, KDMs;
glucose-6-phosphate, G6P; hepatocellular carcinoma, HCC; reactive oxygen species,
ROS; pyruvate kinase M2, PKM2; 5-methylcytosine, 5mC; 5-carboxylcytosine, 5caC;
docetaxel, Doc; doxorubicin, Dox; oxythiamine, OT
Address Correspondence to: Lu-Hai Wang, China Medical University, No. 91,
Hsueh-Shih Road, Taichung, 40402, Taiwan, Phone: 886-4-22057153, Fax:
886-4-22060248, E-mail: [email protected] or [email protected] .
Conflict of interest statement
The authors declare no potential conflicts of interest.
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Abstract
Although metabolic reprogramming is recognized as a hallmark of tumorigenesis and
progression, little is known about metabolic enzymes and oncometabolites that
regulate breast cancer metastasis, and very few metabolic molecules have been
identified as potential therapeutic targets. In this study, the transketolase (TKT)
expression correlated with tumor size in the 4T1/BALB/c syngeneic model. In
addition, TKT expression was higher in lymph node metastases compared with
primary tumor or normal tissues of patients, and high TKT levels were associated
with poor survival. Depletion of TKT or addition of alpha-ketoglutarate (α-KG)
enhanced the levels of tumor suppressors succinate dehydrogenase (SDH) and
fumarate hydratase (FH), decreasing oncometabolites succinate and fumarate and
further stabilizing HIF prolyl hydroxylase 2 (PHD2) and decreasing HIF-1α,
ultimately suppressing breast cancer metastasis. Reduced TKT or addition of α-KG
mediated a dynamic switch of glucose metabolism from glycolysis to oxidative
phosphorylation. Various combinations of the TKT inhibitor oxythiamine, docetaxel,
and doxorubicin enhanced cell death in triple-negative breast cancer (TNBC) cells.
Furthermore, oxythiamine treatment led to increased levels of α-KG in TNBC cells.
Together, our study has identified a novel TKT-mediated α-KG signaling pathway that
regulates breast cancer oncogenesis and can be exploited as a modality for improving
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therapy.
Keywords: TNBC, TKT, α-KG, metabolism, metastasis
Introduction
Breast cancer patients have five-year survival rate over 90%; however, for patients
with distant metastasis, their survival rate decreases to only about 25% because of the
lack of effective strategies against breast cancer metastasis and recurrence (1). Tumor
cells with altered metabolic program have high requirements of glucose metabolism
for rapid proliferation. Despite some studies aiming at elucidating the correlation
between aberrant metabolic behavior and tumor progression, how metabolic processes
regulate breast cancer cells growth and metastasis is not fully understood.
A number of studies show that oncogenic signaling in cancers drives metabolic
reprogramming to generate large amounts of biomass during rapid tumor growth (2).
For example, HIF-1α elevates the expression of glycolytic enzymes including aldolase
A, phosphoglycerate kinase 1, and pyruvate kinase (3). In addition, a number of
studies revealed that genetic defects in TCA cycle enzymes, such as SDH and FH,
were also associated with tumor progression (4,5).
In this study, we used proteomic approach to identify certain differentially
expressed metabolic enzymes involved in tumor progression such as aldolase A
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(ALDOA), triose phosphate isomerase (TPIS), α-enolase (ENOA), transketolase
(TKT) and pyruvate dehydrogenase E1 (ODPB). Among them, TKT is a metabolic
enzyme involved in the non-oxidative branch of the pentose phosphate pathway (PPP)
and connects PPP with glycolysis. Previous studies revealed that TKT was associated
with metastasis of ovarian (6) and esophageal (7) cancers, as well as poor patient
survival (6,7). To date, no study has reported the effect of TKT-regulated metabolic
signaling on tumor metastasis in breast cancer.
In this study, we reveal clinical significance and regulatory mechanism of TKT in
progression and metastasis of breast cancer via α-KG signaling. TKT plays important
roles in regulating dynamic switch of glucose metabolism. The combined therapy
based on the new targets TKT or α-KG could be developed as an improved
therapeutic approach for TNBC.
Materials and Methods
Cell culture and transfection
The human breast cancer MDA-MB-231, Hs578T and MCF-7 cells and mouse
breast cancer 4T1 cells were from ATCC (Manassas, VA). The 4T1 is a highly
tumorigenic and invasive cell line capable of metastasizing from the primary
mammary gland tumor to liver, lung, lymph nodes and brain. The highly metastatic
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cell line MDA-MB-231-IV2-3 was previously established and described (8). All cell
lines were cultured in DMEM (Invitrogen) supplemented with 10% fetal bovine
serum (Biological Industries, Israel) at 37oC with 5% CO2. Cell lines were clear of
mycoplasma as determined by the Venor GeM kit (MB Minerva biolabs) and were
further authenticated in 2017 by Taiwan Bioresource Collection and Research Centre
(BCRC) using a short tandem repeat method. For transfection assay, cells were
transfected with 20 μM siTKT or 20 μM siRNA control or TKT/pCMV plasmid (1
μg/μL) using Lipofectamine RNAiMAX transfection reagent (Thermo Fisher
Scientific, Waltham, MA).
Protein extraction
Cell samples were lysed in lysis buffer containing 7M urea, 2M thiourea, 4% w/v
CHAPS, 10 mM Tris-HCl pH 8.3 and 1 mM EDTA. Protein lysates were extracted,
sonicated and centrifuged and the protein concentration was determined using
Coomassie Protein Assay Reagent (BioRad).
2-D DIGE, gel image analysis and protein identification by MALDI-TOF-MS
The protein profiles of tumor tissues with 0.5, 1 and 2 cm in size were analyzed
using 2-D differential gel electrophoresis (DIGE). Protein samples were labeled with
cyanine dyes Cy2, Cy3 and Cy5 and all procedures have been described previously
(9,10). The Cy-Dye-labeled 2-DE gels were visualized according to the previous
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report (10). For protein identification, the peptide mixture was loaded onto a MALDI
plate and samples were analyzed using an Autoflex III mass spectrometer (Bruker
Daltonics) and parameters were described according to the previous report (10).
Western blotting
Cells were lysed in the lysis buffer containing 7M urea, 2M thiourea, 4% w/v
CHAPS, 10 mM Tris-HCl pH 8.3, 1 mM EDTA, phosphate and protease inhibitors
(Roche). Protein lysates were sonicated and centrifuged and the protein concentration
was determined using protein assay kit (Thermo). The defined amount of final lysates
was resolved in 8-12% SDS-polyacrylamide gels, transferred onto PVDF membrane
and probed with appropriate antibodies. Antibodies include rabbit polyclonal
anti-LDHA (GTX101416, Genetex), rabbit polyclonal anti-α-KG dehydrogenase
(clone C2C3, GTX105124, Genetex), rabbit polyclonal anti-SDH (GTX113833,
Genetex), rabbit polyclonal anti-FH (clone N2C2, GTX110128, Genetex), rabbit
polyclonal anti-MDM2 (GTX100531, Genetex), mouse monoclonal anti-TKT (clone
7H1AA1, ab112997. abcam), mouse monoclonal anti-PHD2 (clone 366G/76/3,
ThermoFisher). Mouse monoclonal anti-β-actin (clone SPM161, Santa Cruz
Biotechnology) was used as the internal control and protein expression levels were
visualized with the enhanced chemiluminescence (ECL) detection kit (Pierce, Boston
Technology, Woburn, MA) and exposed to X-ray film. All experiments were repeated
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three times.
Immunohistochemistry
Paraffin-embedded matched normal, primary tumor and lymph node metastatic
tissue sections of breast cancer specimens (n = 11) were provided by Dr. Wen-Hung
Kuo, National Taiwan University Hospital. Other samples were from commercial
tissue arrays (US Biomax, MD; SuperBioChips, Korea), including 19 normal, 90
tumors and 50 lymph node metastatic tissues. The slides were stained with mouse
monoclonal anti-TKT antibody (clone 7H1AA1, ab112997. abcam) using an
automatic slide stainer BenchMark XT (Ventana Medical Systems). The staining
intensities were evaluated and quantified by one pathologist (Pathology Core Lab.,
National Health Research Institutes) and 2 independent investigators. The IHC scores
of TKT for each specimen were graded as follows: no expression, weak (+); moderate
(++); strong (+++).The expression levels of TKT in tumor cells were quantified as
percentage. Paraffin-embedded sections of tumor cells with TKTL1 overexpression
(Origene, RG205218) were stained with mouse monoclonal anti-TKT antibody (1
mg/mL, 1:75 dilution) (clone 7H1AA1, ab112997. abcam) or rabbit polyclonal
anti-TKTL1 antibody (1 mg/mL, 1:75 dilution) (clone N1C1, GTX109459, Genetex).
We first used D’Agostino and Pearson omnibus normality test to reveal that the
quantitative results of IHC TKT expression were not Gaussian distribution (P =
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0.0015). Thus, we used non-parametric Mann-Whitney test to analyze the quantitative
results.
Proliferation assay
Cell proliferation was detected using CellTiter 96 Aqueous One Solution cell
proliferation assay (Promega). Assay was performed according to manufacturer’s
protocol. 1.4 x 104 cells were cultured in a 24-well plate and incubated for different
times. CellTiter 96 Aqueous One Solution reagent was added and incubated for 1h at
37 oC. The quantity of formazan product, proportional to living cell numbers, was
measured at 490 nm using 96-well plate reader. Each experiment was performed in
triplicate and the shown data were mean ± S.D.
Cell invasion and migration assays
MDA-MB-231 and Hs578T cells were treated with 20 μM siTKT or 1 mM α-KG.
or TKT/pCMV plasmid (1 μg/μL). After 48h, these cells (1 x 105 cells) were seeded
on Boyden chamber, incubated for 8h and then stained with 0.5% crystal violet dye.
Cell invasion and migration were assayed in 8 μm Falcon Cell Culture Inserts with or
without Matrigel (BD Biosciences), respectively. All experiments were performed in
triplicate.
Soft agar colony formation assay
MDA-MB-231 or MCF-7 cells at densities of 1 x 105 cells were seeded in 6-well
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plate containing top layer of 0.4% agarose and bottom layer of 0.4% agarose medium.
Treatment group was transfected with 20 μM of siTKT for 48h. After one month,
colonies were stained with p-Iodonitrotetrazolium violet (1 mg/ml) for 48h and then
counted. Data represent mean ± S.D and experiment was performed in triplicate.
Tail vein injection and orthotopic metastasis assays in mouse models (8)
To study the effects of α-KG on tumor progression, MDA-MB-231 cells (1 x 106)
re-suspended in 100 μL PBS were implanted orthotopically in 4th
mammary fat pads
of eight-week-old female CB17-SCID mice. After implantation of MDA-MB-231
cells for 24h, α-KG reagent was intraperitoneally injected three times a week until 3
months. α-KG dissolved in PBS was used for injection of 10 mg/kg each time. Tumor
volume was calculated by the formula: tumor volume [cm3] = [length (cm) × width
(cm)2
× 0.5]. To study the effects of TKT knockdown on tumor metastasis,
MDA-MB-231-IV2-3 cells were treated with 20 μM siTKT. After 48h,
MDA-MB-231-IV2-3 cells (1 x 106) re-suspended in 100 μL PBS were injected per
mouse intravenously via tail veins into six to eight-week-old female CB17-SCID mice
(BioLASCO, Taiwan). Tumor growth and metastasis to individual organs were
observed using live animal BLI (Caliper IVIS system, PerkinElmer). Tumor volume
and weight were also measured at the end point. Cell metastases were quantified by
BLI signals of each mouse at the end point. Animal experiments were approved by the
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Institutional Animal Care and Use Committee (IACUC).
Orthotopic injection of stable TKT knockdown cells in mouse model
MDA-MB-231 cells were respectively transfected with two independent
GFP-TKT/pCMV plasmid (Origene, NM001064, Derwood, MD, USA). After 48h,
these cells were selected by flow cytometry and transfection efficiency was confirmed
by Western blot. Stable shTKT cells were orthotopically injected at 1 x 106 cells per
mouse into 4th
mammary fat pads of CB17-SCID mice (n = 7) and tumor volumes
were recorded once a week during the 70 days period. Tumor volume = 4/3∏R3, R =
[length (cm) + width (cm)]/2. Animal experiments were approved by IACUC.
TKT activity
MDA-MB-231 cells were transfected with 20 μM siTKT. After 48h, these cells
were lysed with 0.1 M Tris-HC1 buffer (pH 7.6), centrifuged and the supernatant was
collected (34). 50 μL supernatant was mixed with 200 μL reaction mixture including
14.4 mM/L ribose-5-phosphate, 190 μM/L NADH, 380 μM/L TP, > 250U/L
glycerol-3-phosphate dehydrogenase and > 6500 U/L triose phosphate isomerase (11).
Enzyme activity was detected at 340 nm. One unit of enzyme activity indicates the
amount of enzyme catalyzing the oxidation of 1 μmol o NADH per min
Metabolic assay
Oxygen consumption rate (OCR) is an indicator of mitochondrial oxidation and
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extracellular acidification rate (ECAR) is an indicator of lactate production which is
equated to the glycolytic rate. OCR and ECAR were detected by XFe24 extracellular
flux analyzer (Seahorse Bioscience). MDA-MB-231 cells (7 x 103 cells) were cultured
in X24 culture plate (Seahorse Bioscience). OCR and ECAR were measured in XF
base medium (Seahorse Bioscience). OCR was analyzed over time following injection
of 1 μM oligomycin, 2 μM carbonyl cyanide-p-trifluoromethoxyphenylhydrazone
(FCCP) and 0.5 μM rotenone/antimycin. ECAR was measured over time following
injection of 10 mM glucose, 1 μM oligomycin and 50 mM 2-deoxy glucose (2-DG).
For ECAR, glucose (10 mM), oligomycin (1 μM) and 2-DG (50 mM) were used to
estimate glycolytic metabolism. Glucose treatment could increase glycolytic
metabolism in cells. 2-DG, a synthetic glucose analog, acted as a competitor for
glucose and interfered with glucose metabolism. For OCR, oligomycin (1 μM),
carbonyl cyanide-4-(trifluoromethoxy)phenylhydrazone (FCCP) (1μM) and
rotenone/antimycin (0.5 μM) were used to estimate oxidative respiration. For
mitochondrial respiration, oligomycin treatment inhibited ATP synthase in
mitochondria. FCCP, a proton ionophore in mitochondria, transported protons across
cell membranes to disrupt ATP synthesis. Finally, rotenone and antimycin were
inhibitors for electric transport chain in mitochondria.
Statistical analysis
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Kaplan-Meier method (logrank test) was used to analyze survival data. Data were
presented as mean ± SD. Student’s t test was used to compare the differences between
two experimental groups and one-way ANOVA was used to compare the differences
between multiple groups using Tukey test in GraphPad. χ2 test was used to analyze
the correlation between TKT levels and clinical factors; *P < 0.05, ** P < 0.01, *** P
< 0.001. OCR and ECAR data were calculated by paired t-test.
Results
Identification of metabolic proteins potentially involved in breast cancer
progression using proteomic analysis
Using proteomic approach and examining tumors of varying sizes, we attempted to
identify differentially expressed proteins associated with breast cancer progression.
We used syngeneic orthotopic implantation of 4T1 cells in BALB/c mice, and tumors
with 0.5, 1 and 2 cm in size were collected for further proteomic analyses. The protein
profiles from the tumor with 0.5 cm in size were compared with those tumors with 1
and 2 cm in size by two dimensional protein gel analysis (Supplementary Fig.
S1A-S1C). After spot detection and quantification from the 2-D gel images, a total of
21 differentially expressed proteins (P < 0.05) with 1.5-fold changes were chosen for
further identification (Supplementary Fig. S1A-S1C) by using MALDI-TOF-MS and
MASCOT database (Supplementary Table S1). Three proteins related to glycolysis
were up-regulated in the bigger tumors; they included ALDOA, TPIS and ENOA.
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Other metabolic enzymes included the up-regulated TKT involved in PPP and the
down-regulated ODPB involved in pyruvate oxidation (Supplementary Table S1,
Supplementary Fig. S1D). Tumors with 1 and 2 cm in size had 1.5 and 2 fold,
respectively, increased expression of TKT when compared with the 0.5 cm tumor
(Supplementary Table S1, Supplementary Fig. S1D).
TKT displays higher expression in metastatic lymph node tissues and breast
cancer patients with high TKT expression have poor overall survival
We analyzed TKT expression in normal and tumor tissues according to gene
expression arrays from Oncomine database (Bild data). As compared with normal
tissues, TKT displayed significantly higher expression in tumor tissues (Fig. 1A,
non-parametric Mann-Whitney test, P = 0.03). We also found that the levels of TKT in
TNBC patients were significantly higher than those in non-TNBC patients (Fig. 1B, P
< 0.001). Kaplan-Meier survival curve (logrank test) from Curtis 5-year overall
survival data showed that patients with higher TKT levels had poorer 5-year survival
than those with lower TKT levels (n = 637, Fig. 1C) (P = 0.019, Chi-square = 5.502,
HR = 1.3298). The similar result is also observed in different clinical database (n =
158, Fig. 1D) (P = 0.003, Chi-square =8.7476, HR = 2.3131), suggesting that TKT has
a prognostic potential. TNBC is the breast cancer subtype with the poorest outcome;
however, very few metabolic enzymes as prognostic indicators for TNBC patients are
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known. The role of TKT in TNBC patients has not been reported, thus we further
analyzed the correlation between TKT expression levels and TNBC patients’ 5-year
overall survival. Among the 637 cases, there were a total of 106 TNBC patients. Our
analysis showed that TNBC patients with higher TKT levels had poorer 5-year overall
survival than those with lower TKT levels (n = 106, Fig. 1E) (P = 0.0006, Chi-square
=11.7166, HR = 2.3758), showing that TKT might have a prognostic potential in
TNBC patients, and it could play a role in TNBC progression. The clinicopathologic
features of TKT in breast cancer patients from Curtis data showed that TKT levels
were significantly associated with some clinical factors, including stage, age, grade,
type, TNBC and tumor size (Supplementary Table S2). We also analyzed TKT
expression in normal, primary tumor and lymph node metastatic tissues by using
immunohistochemistry. First, we checked whether TKT antibody used in the IHC
staining cross-reacted with TKTL-1. To address this, we used TKTL1/pCMV plasmid
to overexpress TKTL1 in MDA-MB-231 cells. The overexpression efficiency was
verified (Supplementary Fig. S2A). The paraffin-embedded sections of tumor cells
with TKTL1 overexpression were stained with anti-TKT or anti-TKTL1 antibody.
Our results displayed high staining intensity of TKTL1 in tumor cells overexpressing
TKTL1 using anti-TKTL1, whereas staining intensity using TKT antibody was
insignificant (Supplementary Fig. S2B). These results suggest that TKT antibody used
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in the IHC staining does not cross-react with TKTL1.
The staining intensity of TKT was evaluated and quantified as no expression to
the highest expression by a pathologist and two independent investigators of our team.
As summarized in Supplementary Fig. S2C, a high percentage of normal tissues
displayed insignificant TKT intensities (60%) or low intensities of TKT (30%) when
compared with those of tumor tissues (P < 0.001). Moreover, metastatic lymph node
tissues displayed a higher percentage of high intensities of TKT (56%) when
compared with primary tumor (25%, P < 0.001). The representative staining
photographs are shown in Fig. 1F. The percentage of TKT expression in tumor cells,
not including stroma cells, from primary tumor and lymph node metastatic tissue
sections were further quantified. Metastatic lymph node tissues displayed a higher
percentage of TKT expression in tumor cells when compared with the primary tumor
(Supplementary Fig. S2D, P < 0.001). These results showed that TKT expression
levels were the highest in lymph node metastases, suggesting that a possible
correlation of TKT levels with progression of metastasis in breast cancer.
Downregulation of TKT suppresses metastatic functions and affects cell cycle
distribution
To further elucidate the functional role of TKT, we manipulated TKT expression by
siRNA depletion of TKT in MDA-MB-231 and Hs578T TNBC cells (Fig. 2A). The
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downregulation of TKT in MDA-MB-231 cells resulted in significantly decreased cell
proliferation (Fig. 2B-2D). This phenomenon was also observed in Hs578T cells (Fig.
2E-2G). The inhibition by TKT knockdown in both cell lines was significantly
rescued by TKT/pCMV overexpression (Fig. 2B-2G). Cell migration and invasion
were carried out by transwell Boyden chamber assays. Downregulation of TKT led to
a significant inhibition of invasion (Fig. 2H) and migration (Fig. 2I) of MDA-MB-231
and Hs578T cells, whereas the inhibitory effects were almost completely rescued by
TKT overexpression. MDA-MB-231 cells with the inhibited TKT expression
displayed reduced ability of colony formation (Fig. 2J). TKT knockdown increased
the percentage of cells in the G2/M phase in MDA-MB-231 and Hs578T cells (Fig.
2K). Taken together, these data suggested that the depletion of TKT impaired tumor
cell growth and metastasis-related abilities.
Knockdown of TKT suppresses lung metastasis of breast cancer cells
To evaluate whether depletion of TKT suppressed cancer cell metastasis in vivo, we
used tail vein injection of the highly invasive MDA-MB-231-IV2-3 cells (1x106 cells)
in CB17-SCID mice (n=8). The highly metastatic MDA-MB-231-IV2-3 sublines
derived from the MDA-MB-231 parental line was established and described
previously (8). The MDA-MB-231-IV2-3 cells exhibited dramatically higher
invasiveness than the MDA-MB-231 parental cells in vitro and they also exhibited
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more aggressive lung and lymph node metastasis in vivo (8). The data from tail vein
injection model showed that knockdown of TKT resulted in greatly decreased lung
metastasis of the MDA-MB-231-IV2-3 cells (Fig. 3A, P = 0.005, Fig. 3B, P = 0.002)
by bioluminescence imaging (BLI) as also reflected in H&E staining (Fig. 3C). These
findings indicated that knockdown of TKT inhibited lung metastasis of the highly
invasive breast cancer cells (Supplementary Fig. S3A-S3F).
To further assess whether decreased lung metastasis by the depletion of TKT
resulted from decreased targeting of the tumor cells to lung, the cells transfected with
the control or TKT siRNA were injected into CB17-SCID mice through tail vein (n=8)
and after 24h, the lung was perfused with PBS to flush out intravascular tumor cells
and subsequently the expression levels of human GAPDH reflecting the injected cells
in lung tissues were measured. BLI analysis exhibited about equivalent signals in the
lungs of siCon or siTKT transfected cells 30 mins after injection (Fig. 3D, P = 0.294).
The qPCR data confirmed the result (Fig. 3E, P = 0.222). To confirm the inhibitory
effects of transient TKT knockdown on tumor growth, two different knockdown
stable lines, MDA-MB-231-shTKT1 and MDA-MB-231-shTKT2, as well as
MDA-MB-231-shNC line were established, and each (1 x 106 cells) were implanted
orthotopically into the 4th
mammary fat pad of CB17-SCID mouse (n = 7). The
knockdown efficiency of shTKT was verified (Fig. 3F) and the result showed that
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tumor sizes in both TKT knockdown groups were significantly smaller than those in
the control group (Fig. 3G-3H, Supplementary Fig. S3G-S3I). These findings
indicated that knockdown of TKT did not inhibit lung targeting (Supplementary Fig.
S4A-S4D), but inhibited the subsequent lung colonization ability of the tumor cells.
Identification of TKT-regulated metabolites in breast cancer cells
Recent reports indicated the involvement of Warburg effect in tumor metastasis and
suggested that molecules participating in metabolic modulation were potential targets
for anti-metastasis therapy (12). To address TKT-regulated metabolic pathways in
breast cancer cells, we manipulated TKT expression by siRNA treatment of
MDA-MB-231 cells for 48h and then cell lysates were harvested for identifying
altered metabolites by LC/MS-MS (Waters, Massachusetts, USA). The differentially
expressed metabolites in siTKT-treated cells were identified when comparing with the
siRNA control cells. Knockdown of TKT increased some TCA cycle intermediates
including α-KG (Fig. 4A) and malate, while decreased succinate and fumurate (P <
0.05). Reports indicated that the alternation of metabolites in the TCA cycle was
associated with tumor formation (4). For example, succinate and fumarate
accumulated in the mitochondria leaked out to the cytosol because of inactivation of
the tumor suppressors SDH and FH resulting in promoting cancer formation (13). At
present, the potential role of α-KG and the relationship between TKT and α-KG in
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triple negative breast cancer are still unclear. Our findings that TKT might play an
important role in metastasis and its knockdown led to increased α-kG prompted us to
further investigate the potential effect of α-KG in oncogenic behavior of cancer cells.
α-KG suppresses tumor cell growth, migration and invasion
We further found that TKT overexpression attenuated α-KG levels (Fig. 4B, P <
0.001), which was consistent with the result from TKT knockdown. The physiological
concentration of α-KG in healthy brain tissues ranges from 1 to 3 mM, whereas its
concentration is decreased to 100 to 300 μM in gliomas (14). IDH1 mutated tumor
cells exhibited decreased α-KG, leading to increased HIF-1α levels (15). The similar
results were observed in α-KG derivatives treatments in IDH1 mutated gliomas (16)
or SDH-deficient tumor cells (17). Despite its tumor suppressor role of artificial
α–KG derivative in cancers, many studies revealed that non-α-KG derivative could
attenuate cell proliferation of colon cancer (18) and reduce the levels of vascular
endothelial growth factor (VEGF) and erythropoietin through decreasing HIF-1α,
thereby inhibiting angiogenesis ability of the Hep3B hepatoma cells (19). These
findings suggested the potential tumor suppressing role of α-KG. Furthermore,
G-protein-coupled receptor (GPCR) GPR99 was reported to function as a receptor for
the TCA cycle intermediate α-KG (20). Although previous studies indicated that
α-KG-dependent dioxygenases signaling pathways functioned as tumor suppressors
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(21), the regulatory role of α-KG in breast cancer is unclear. Treatment of α-KG
resulted in significantly decreased MDA-MB-231 cell growth when compared with
the control (Fig. 4C). Furthermore, treatment of α-KG led to a significant inhibition of
cell invasion (Fig. 4D) and migration (Fig. 4E). MCF-7 cells with the inhibited TKT
expression displayed reduced ability of colony formation (Supplementary Fig. S4E).
TKT overexpression promoted cell proliferation in MDA-MB-231 (Fig. 4F-4H) and
Hs578T (Supplementary Fig. S4F-S4H) cells, whereas its effect was substantially
reversed by α-KG treatment. These findings indicate that α-KG can impair
metastatic-related abilities of breast cancer cells. We further verified that the
promotion of TKT on invasion (Fig. 4I) and migration (Fig. 4J) in MDA-MB-231 and
Hs578T cells were substantially reversed by α-KG treatment, suggesting that TKT
regulated invasion and migration of tumor cells via α-KG signaling. In our study, we
observed the cellular levels of α-KG were increased after the treatment of α-KG
(Supplementary Fig. S5A-S5B).
α-KG suppresses lung metastasis of breast cancer cells
We next assessed the effect of this metabolic pathway on tumor growth and
metastasis using a mouse model. 1 x 106 MDA-MB-213 cells were implanted
orthotopically into mammary fat pads of CB17-SCID mice (n=10). One day after
implantation, intraperitoneal α-KG (10 mg/kg) administration was started three times
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a week for 3 months. BLI data revealed that α-KG treatment led to a significant
reduction of primary tumor growth (Fig. 4K, P < 0.001). There were significant
differences in the weights (Fig. 4L, P = 0.024) and sizes (Fig. 4M, P = 0.004) of
primary tumors between control and the α-KG treated groups after 3 months.
Individual organ metastases were also examined, and we found that α-KG treatment
significantly diminished lung and lymph node metastases (Fig. 4N, P < 0.05). Overall,
our data for the first time demonstrated that TKT-mediated α-KG signaling suppressed
growth and metastases of breast cancer.
TKT regulates breast cancer metastasis via the α-KG signaling pathway
To further explore TKT-regulated downstream pathways in breast cancer metastasis,
the effects of TKT on the α-KG and TCA cycle enzymes were examined. Previous
studies indicated that accumulation of α-KG enhanced the activity of PHD and
subsequent destabilization of its downstream target HIF-1α (22). To assess the
relationship between TKT and HIF-1α in MDA-MB-231 cells, the impact of TKT on
PHD2 was investigated. Results revealed that downregulation of TKT enhanced
PHD2 expression (Fig. 5A) and this phenomenon was also observed in the
α-KG-treated cells (Fig. 5B). Moreover, knockdown of TKT reduced HIF-1α
expression (Fig. 5A), suggesting that TKT affected HIF-1α expression via the PHD2
signaling pathway. HIF-1α has been reported to be associated with tumor metastasis
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(23) and is known to be a transcription factor regulating the expression of LDHA (24).
Other studies revealed that knockdown of LDHA inhibited breast cancer metastasis
(25). At present, the relationship between TKT and LDHA is not known, thus we
further assess the effect of TKT on LDHA expression. Our data showed that
knockdown of TKT inhibited LDHA expression (Fig. 5A) and this phenomenon was
also observed in α-KG-treated cells (Fig. 5B). These results suggested that TKT
decreased LDHA expression and promoted HIF-1α degradation through the α-KG
signaling pathway, leading to the inhibition of breast cancer metastasis. Our data
suggest that a regulatory network of those metabolites and their corresponding
catalyzing enzymes are involved in the regulation of involved in breast cancer
metastasis.
Previous study indicates that L-2HG dehydrogenase (L2HGDH) and D-2HG
dehydrogenase (D2HGDH) prevent oncometabolites L-2HG and D-2HG from
accumulating in normal cells, respectively, by converting them back to α-KG (21). We
have found that TKT depletion enhanced the levels of L2HGDH and D2HGDH (Fig.
5A). Overall, these results indicate that TKT depletion enhances L2HGDH and
D2HGDH levels, resulting in the increase of α-KG and PHD2 levels and thereby
promoting HIF-1α degradation.
TKT regulates tumor suppressors SDH and FH signaling pathway
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Our data showed that knockdown of TKT decreased the expression levels of
metabolites succinate and fumarate (Fig. 5C). Previous studies indicated that the
inactivation mutations in SDH and FH led to abnormal accumulation of metabolites
succinate and fumarate in TCA cycle, which in turn inhibited PHD and induced
HIF-1α in tumors (4,5). The correlation between TKT and SDH and FH in breast
cancer is still unclear; thus, we investigated the effects of TKT knockdown on the
expression levels of SDH and FH. We found that knockdown of TKT increased the
levels of SDH and FH (Fig. 5A), leading to decreased levels of succinate and
fumarate and thus stabilizing the PHD2-regulated signaling pathway.
Previous studies report α-KG-dependent dioxygenases signaling pathways
functioned as tumor suppressors (21). Additionally, SDH and FH have been reported
to be targets of α-KG-dependent dioxygenases, including JmjC domain-containing
histone demethylase (KDMs) and DNA demethylases (26). These studies suggest that
TKT may control transcriptional regulation of SDH and FH via α-KG-dependent
dioxygenases. To elucidate the potential underlying mechanism, we detected the
effects of TKT depletion or α-KG treatment on RNA levels of SDH and FH. Our
results showed that TKT depletion (Fig. 5D, P < 0.001) or α-KG treatment (Fig. 5E, P
< 0.01) indeed increased RNA levels of SDH and FH suggesting regulation at the
transcriptional level. Overall, the regulatory mechanism of TKT via α-KG signaling in
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breast cancer metastasis is depicted in Fig. 5F.
Reduced TKT or α-KG treatment regulates glucose metabolism and
mitochondrial oxygen consumption
Tumor cells predominantly metabolize glucose through glycolysis instead of
oxidative phosphorylation in TCA cycle to rapidly produce ATPs and nucleic acid
building stones for supporting their high rate of growth (27). The effect of TKT on
metabolic activities in cancers was unclear; thus, we examined the relationship among
glycolysis, mitochondrial metabolism and oncogenic TKT signaling. The knockdown
efficiency of TKT in MDA-MB-231 cells was initially estimated (Fig. 6A). TKT
knockdown (Fig. 6B, P < 0.001) or α-KG treatment (Fig. 6C, P < 0.001) exhibited
decreased ECAR. TKT knockdown (Fig. 6D, P < 0.001) or α-KG treatment (Fig. 6E,
P < 0.001) elevated OCR. These results demonstrated that reduced TKT led to switch
of glucose metabolism from glycolysis to mitochondrial respiration via the α-KG
signaling pathway.
To further confirm whether knockdown of TKT drove the switch of glucose
metabolism from glycolysis to TCA cycle, we used mass spectrometry to measure
expression levels of metabolites in glycolysis and TCA cycle. Reduction of TKT
diminished the levels of glycolytic metabolites including glucose-6-phosphate (G6P),
pyruvate and lactic acid, while increased the TCA cycle metabolites including α-KG
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and malate (Supplementary Fig. S5A). We treated the cancer cells with α-KG and
observed a similar result like TKT knockdown (Supplementary Fig. S5B), suggesting
that reduction of TKT drove the switch of glucose metabolism from glycolysis to
mitochondrial metabolism at least in part through the α-KG signaling pathway.
To further verify this, the effect of decreased TKT on the expression levels of
metabolic enzymes in TCA cycle was evaluated. We found that the depletion of TKT
resulted in increased expression levels of metabolic enzymes in TCA cycle including
aconitase, α-KG dehydrogenase, SDH, FH, and malate dehydrogenase
(Supplementary Fig. S6A). The similar result was obtained in α-KG-treated cells
(Supplementary Fig. S6B). By contrast, the depletion of TKT resulted in decreased
levels of glycolytic enzymes including PKM2, HK, and PFK (Supplementary Fig.
S6C) and the similar results were also observed in α-KG-treated cells (Supplementary
Fig. S6C). Taken together, these results indicate that reduced TKT leads to the
alteration of glucose metabolism by switching from glycolytic activity to
mitochondrial metabolism via the elevation of metabolic enzymes in TCA cycle
through the α-KG signaling pathway. Since tumor cells depend on glycolysis for their
rapid growth, inhibition of TKT or addition of α-KG could be used as a modality for
developing cancer therapeutics not only for breast cancer including triple negative
breast cancer as shown in this study, but for other types of cancer as well.
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27
Oxythiamine in combination with docetaxel and/or doxorubicin enhances
inhibitory effects of TNBC cells
Docetaxel and doxorubicin are commonly used drugs for TNBC, but their
efficiencies are limited as a result of the development of drug resistance. Oxythiamine
inhibits TKT and thus could lead to downregulation of glycolysis, not targeted by the
two drugs. Thus combinatory treatment of oxythiamine together with the two drugs
may enhance the killing effect of cancer cells. Oxythiamine, an anti-metabolite
thiamine analogue, induces cell apoptosis and suppresses tumor cell growth in cancers
by targeting TKT (28,29). Although some studies indicate that oxythiamine can
suppress tumor progression, the effects of oxythiamine in breast cancer are unclear. In
this study, we first assessed the effect of oxythiamine on TKT activity according to
previous study (11). Tumor cells were treated with 5 mM oxythiamine for 48h. Our
results revealed that TKT activity was significantly reduced by oxythiamine treatment
(Fig. 7A, P < 0.01). In addition, we found oxythiamine treatment elevated the levels
of α-KG in MDA-MB-231 (Fig. 7B, P < 0.001) and Hs578T (Fig. 7C, P < 0.001) cells
as expected, suggesting that oxythiamine suppressed tumor growth could in part
through the α-KG signaling pathway. Then we analyzed whether oxythiamine
treatment affected growth of breast normal cells. The results showed that cell
viabilities of non-tumorigenic human breast epithelial cell line H184 for 24 (P = 0.16),
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48 (P = 0.08) and 72h (P = 0.07) were not significantly decreased by 5 mM
oxythiamine treatment when compared with those without oxythiamine treatment (Fig.
7D), meaning there was no significant side effects of oxythiamine in human breast
normal cells. We observed that docetaxel or doxorubicin treatment increased α-KG
levels (Fig. 7E, P < 0.001). Moreover, previous studies report that docetaxel or
doxorubicin treatment attenuates HIF-1α levels (30,31), further supporting our
findings that TKT affects HIF-1α expression via α-KG signaling. Thus, we tested the
inhibitory effects of oxythiamine in combination with docetaxel and/or doxorubicin
on cell proliferation. We treated TNBC cell lines MDA-MB-231 (Fig. 7F-7H) and
Hs578T (Fig. 7I-7K) with 5 mM oxythiamine, 1 μM docetaxel, 1 μM doxorubicin and
oxythiamine in combination with docetaxel and/or doxorubicin for 24, 48 and 72
hours. Treatment of oxythiamine had significant inhibitory effects for 24 (Fig. 7F, 7I)
and 48h (Fig. 7G, 7J) in both cell lines. Although treatment of docetaxel or
doxorubicin had inhibitory effects of TNBC cells, the killing effects of oxythiamine
combining with docetaxel or doxorubicin could be strengthened in TNBC cells, In
addition, combining of the three drugs had maximum killing effects (> 90% decrease)
for 72h in both TNBC cell lines (Fig. 7H, 7K). These findings indicate that
oxythiamine could enhance drug sensitivities of TNBC cells.
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29
Discussion
Increasing evidence suggests that some pivotal genes, such as HIF-1α, which is
able to regulate certain enzymes to induce metabolic reprogramming in cancers.
HIF-1 has been reported to induce glycolytic enzymes, including aldolase A,
phosphoglycerate kinase 1, and pyruvate kinase (3). HIF-1α regulates dynamic switch
from oxidative to glycolytic metabolism by activating glucose transporters and
glycolytic enzymes (32). Certain metabolic enzymes involved in glucose transport,
glycolysis and lipid metabolism are targets of HIF-1α (33). In our study, we found that
TKT depletion promoted HIF-1α degradation via α-KG signaling. These results
suggest that TKT mediated signaling pathways may collaborate to regulate dynamic
switch of glucose metabolism. Xu et al (34) reported that TKT reduced oxidative
stress and played important roles in glycolysis and glutathione synthesis in
hepatocellular carcinoma (HCC) cells. TKT knockdown attenuated NADPH
production and led to the increase of reactive oxygen species (ROS) (34). TKT
knockdown decreased glucose flux, and purine metabolites including AMP, ADP, ATP
and GTP (34). Together, these results provide evidence that TKT may play an
important role in metabolic reprogramming in tumors.
The emerging evidence demonstrates that several TCA cycle enzymes are tumor
suppressors, such as SDH and FH, and their genetic defects are associated with
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30
tumorigenesis. The inactivation mutations in SDH and FH leads to abnormal
accumulation of metabolites succinate and fumarate in TCA cycle, and the subsequent
inhibition of PHD and enhancement of HIF-1α pathways in tumors (4,5). Here, we
have demonstrated that reduction of TKT augments levels of SDH, FH and PHD2, but
decreased levels of HIF-1α. In addition, levels of oncometabolites succinate and
fumarate are significantly reduced by TKT knockdown, which is likely due to
increased levels of SDH and FH, which in turn affects PHD2 stabilization and HIF-1α
degradation. HIF-1α is a transcription factor regulating the expression of LDHA (24)
and its knockdown inhibits breast cancer metastasis (25). We have also noticed that
knockdown of TKT decreases levels of LDHA, suggesting that reduction of TKT
resulted in decreased HIF-1α and LDHA via elevated levels of SDH and FH, leading
to the inhibition of tumor metastasis.
Previous reports indicate that a glycolytic enzyme pyruvate kinase M2 (PKM2) is a
transcriptional coactivator for HIF-1, amplifying HIF-1 activity via a positive
feedback regulation, and thereby promoting cancer progression (35). To date, the
underlying mechanism of TKT-mediated regulation of PKM2 via α-KG signaling is
unclear. We found that TKT depletion or α-KG treatment reduced PKM2 levels
(Supplementary Fig. S6C) and promoted HIF-1α degradation. A significant positive
correlation existed between TKT and PKM2 (r = 0.4635, P < 0.0001, Supplementary
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Fig. S6D). Breast cancer patients (N = 3951, P < 0.001, Supplementary Fig. S6E)
including TNBC patients (N = 255, P = 0.045, Supplementary Fig. S6F) with higher
TKT and PKM2 levels had poorer recurrence-free survival (RFS) than those with
lower TKT and PKM2. We also observed that breast cancer patients (N = 3951, P <
0.001, Supplementary Fig. S6G) including TNBC patients (N = 255, P = 0.0049,
Supplementary Fig. S6H) with higher TKT, PKM2 and HIF-1α levels had poorer RFS
than those lower TKT, PKM2 and HIF-1α. On the other hand, a study indicated that
p53 induced tumor suppressor MDM2 E3-ubiuitin-mediated degradation of HIF-1α
(36). To date, the underlying mechanism of TKT-mediated regulation of MDM2 via
α-KG signaling is not known. We found that TKT depletion or α-KG treatment
enhanced MDM2 levels (Supplementary Fig. S6I) and promoted HIF-1α degradation.
A significant negative correlation existed between TKT and MDM2 (r = -0.2618, P <
0.0001, Supplementary Fig. S6J). Breast cancer patients with higher MDM2 levels
had better RFS than those with lower MDM2 (N = 3951, P = 0.0019, Supplementary
Fig. S6K). Since both PKM2 and MDM2 could regulate HIF-1α stability, our results
suggest aside from the TKT/α-KG–mediated regulation of PHD2 and HIF-1α
degradation, PKM2 and MDM2 could also play a role in TKT-mediate control of
HIF-1α stability.
α-KG functions as a co-substrate for Fe (II)/ α-KG-dependent dioxygenases,
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32
including KDMs and the TET (ten-eleven translocation) family of DNA hydroxylases
(26). They catalyze hydroxylation in diverse substrates including proteins, alkylated
DNA/RNA and 5-methylcytosine (5mC) of genomic DNA (26). TET family of DNA
hydroxylases catalyzes a three-step oxidation reaction to convert 5mC to
5-carboxylcytosine (5caC), and subsequent decarboxylation of. 5caC leading to DNA
demethylation (26). Succinate dehydrogenase (SDH) and fumarate hydratase (FH)
have been reported to be the targets of α-KG-dependent dioxygenases, including
KDMs and DNA demethylases (26). Our results showed that TKT depletion or α-KG
treatment increased RNA levels of SDH and FH. Together, these studies suggest that
TKT may control transcription of SDH and FH via α-KG-dependent dioxygenases
signaling.
TKT inhibitor oxythiamine had been reported to have anti-cancer activity (28,29).
For example, Oxythiamine in combination with Sorafenib had enhanced effects on
HCC cell growth by in vivo assay (34). Despite its potential therapeutic development,
at present, the targeted therapy of TKT against TNBC cells has not been reported. Our
results showed that the combinations of oxythiamine with docetaxel and doxorubicin
had maximum inhibitory effects in TNBC cells, suggesting the combining drugs as a
novel therapy against TNBC. Our study for the first time revealed that oxythiamine
treatment elevated the levels of α-KG in TNBC cells, meaning that oxythiamine
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33
suppressed tumor cell growth via α-KG signaling pathway. Together, it is important to
develop effective targeted therapy in combination with the conventional therapeutic
drugs to maximize therapeutic benefits for TNBC.
Acknowledgments
We thank the Protein Chemistry Core Lab, Pathology Core Lab and Cell Sorter
Core Lab of the National Health Research Institutes for mass spectrometric analysis,
H&E and IHC staining and technical assistance of cell cycle, respectively. All authors
received Ministry of Science and Technology (MOST), Taiwan (MOST
104-2320-B-039-055-MY3, MOST 104-2320-B-039-054-MY3, MOST
106-2811-B-039-004) and National Health Research Institutes (NHRI) (NHRI
06A1-MGPP09-014) grants.
References
1. Ci Y, Qiao J, Han M. Molecular Mechanisms and Metabolomics of Natural
Polyphenols Interfering with Breast Cancer Metastasis. Molecules 2016;21,pii:
E1634.
2. Schulze A, Harris AL. How cancer metabolism is tuned for proliferation and
vulnerable to disruption. Nature 2012;491:364-73.
3. Semenza GL, Roth PH, Fang HM, Wang GL. Transcriptional regulation of
genes encoding glycolytic enzymes by hypoxia-inducible factor 1. J Biol
Research. on June 18, 2020. © 2018 American Association for Cancercancerres.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on March 29, 2018; DOI: 10.1158/0008-5472.CAN-17-2906
34
Chem 1994;269:23757-63.
4. Selak MA, Armour SM, MacKenzie ED, Boulahbel H, Watson DG, Mansfield
KD, et al. Succinate links TCA cycle dysfunction to oncogenesis by inhibiting
HIF-alpha prolyl hydroxylase. Cancer Cell 2005;7:77-85.
5. Yang M, Soga T, Pollard PJ. Oncometabolites: linking altered metabolism
with cancer. J Clin Invest 2013;123:3652-8.
6. Ricciardelli C, Lokman NA, Cheruvu S, Tan IA, Ween MP, Pyragius CE, et al.
Transketolase is upregulated in metastatic peritoneal implants and promotes
ovarian cancer cell proliferation. Clin Exp Metastasis 2015;32:441-55.
7. Chao YK, Peng TL, Chuang WY, Yeh CJ, Li YL, Lu YC, et al. Transketolase
Serves a Poor Prognosticator in Esophageal Cancer by Promoting Cell
Invasion via Epithelial-Mesenchymal Transition. J Cancer 2016;7:1804-11.
8. Chan SH, Huang WC, Chang JW, Chang KJ, Kuo WH, Wang MY, et al.
MicroRNA-149 targets GIT1 to suppress integrin signaling and breast cancer
metastasis. Oncogene 2014;33:4496-507.
9. Lai TC, Chou HC, Chen YW, Lee TR, Chan HT, Shen HH, et al. Secretomic
and proteomic analysis of potential breast cancer markers by two-dimensional
differential gel electrophoresis. J Proteome Res 2010;9:1302-22.
10. Chou HC, Lu YC, Cheng CS, Chen YW, Lyu PC, Lin CW, et al. Proteomic
Research. on June 18, 2020. © 2018 American Association for Cancercancerres.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on March 29, 2018; DOI: 10.1158/0008-5472.CAN-17-2906
35
and redox-proteomic analysis of berberine-induced cytotoxicity in breast
cancer cells. J Proteomics 2012;75:3158-76.
11. Zhao Y, Wu Y, Hu H, Cai J, Ning M, Ni X, et al. Downregulation of
transketolase activity is related to inhibition of hippocampal progenitor cell
proliferation induced by thiamine deficiency. BioMed Res Int
2014;2014:572915.
12. Doppler H, Storz P. Differences in Metabolic Programming Define the Site of
Breast Cancer Cell Metastasis. Cell Metab 2015;22:536-7.
13. King A, Selak MA, Gottlieb E. Succinate dehydrogenase and fumarate
hydratase: linking mitochondrial dysfunction and cancer. Oncogene
2006;25:4675-82.
14. Thirstrup K, Christensen S, Moller HA, Ritzen A, Bergstrom AL, Sager TN, et
al. Endogenous 2-oxoglutarate levels impact potencies of competitive HIF
prolyl hydroxylase inhibitors. Pharmacol Res 2011;64:268-73.
15. Xu W, Yang H, Liu Y, Yang Y, Wang P, Kim SH, et al. Oncometabolite
2-hydroxyglutarate is a competitive inhibitor of alpha-ketoglutarate-dependent
dioxygenases. Cancer Cell 2011;19:17-30.
16. Zhao S, Lin Y, Xu W, Jiang W, Zha Z, Wang P, et al. Glioma-derived
mutations in IDH1 dominantly inhibit IDH1 catalytic activity and induce
Research. on June 18, 2020. © 2018 American Association for Cancercancerres.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on March 29, 2018; DOI: 10.1158/0008-5472.CAN-17-2906
36
HIF-1alpha. Science 2009;324:261-5.
17. MacKenzie ED, Selak MA, Tennant DA, Payne LJ, Crosby S, Frederiksen CM,
et al. Cell-permeating alpha-ketoglutarate derivatives alleviate pseudohypoxia
in succinate dehydrogenase-deficient cells. Mol Cell Biol 2007;27:3282-9.
18. Rzeski W, Walczak K, Juszczak M, Langner E, Pozarowski P,
Kandefer-Szerszen M, et al. Alpha-ketoglutarate (AKG) inhibits proliferation
of colon adenocarcinoma cells in normoxic conditions. Scand J Gastroenterol
2012;47:565-71.
19. Matsumoto K, Imagawa S, Obara N, Suzuki N, Takahashi S, Nagasawa T, et
al. 2-Oxoglutarate downregulates expression of vascular endothelial growth
factor and erythropoietin through decreasing hypoxia-inducible factor-1alpha
and inhibits angiogenesis. J Cell Physiol 2006;209:333-40.
20. He W, Miao FJ, Lin DC, Schwandner RT, Wang Z, Gao J, et al. Citric acid
cycle intermediates as ligands for orphan G-protein-coupled receptors. Nature
2004;429:188-93.
21. Losman JA, Kaelin WG, Jr. What a difference a hydroxyl makes: mutant IDH,
(R)-2-hydroxyglutarate, and cancer. Genes Dev 2013;27:836-52.
22. Vatrinet R, Leone G, De Luise M, Girolimetti G, Vidone M, Gasparre G, et al.
The alpha-ketoglutarate dehydrogenase complex in cancer metabolic plasticity.
Research. on June 18, 2020. © 2018 American Association for Cancercancerres.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on March 29, 2018; DOI: 10.1158/0008-5472.CAN-17-2906
37
Cancer Metab 2017;5:3.
23. Zhao T, Zhu Y, Morinibu A, Kobayashi M, Shinomiya K, Itasaka S, et al.
HIF-1-mediated metabolic reprogramming reduces ROS levels and facilitates
the metastatic colonization of cancers in lungs. Sci Rep 2014;4:3793
24. Miao P, Sheng S, Sun X, Liu J, Huang G. Lactate dehydrogenase A in cancer: a
promising target for diagnosis and therapy. IUBMB life 2013;65:904-10.
25. Rizwan A, Serganova I, Khanin R, Karabeber H, Ni X, Thakur S, et al.
Relationships between LDH-A, lactate, and metastases in 4T1 breast tumors.
Clin Cancer Res 2013;19:5158-69.
26. Xiao M, Yang H, Xu W, Ma S, Lin H, Zhu H, et al. Inhibition of
alpha-KG-dependent histone and DNA demethylases by fumarate and
succinate that are accumulated in mutations of FH and SDH tumor suppressors.
Genes Dev 2012;26:1326-38.
27. Soga T. Cancer metabolism: key players in metabolic reprogramming. Cancer
Sci 2013;104:275-81.
28. Wang J, Zhang X, Ma D, Lee WP, Xiao J, Zhao Y, et al. Inhibition of
transketolase by oxythiamine altered dynamics of protein signals in pancreatic
cancer cells. Exp Hematol Oncol 2013;2:18.
29. Zhao F, Mancuso A, Bui TV, Tong X, Gruber JJ, Swider CR, et al. Imatinib
Research. on June 18, 2020. © 2018 American Association for Cancercancerres.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on March 29, 2018; DOI: 10.1158/0008-5472.CAN-17-2906
38
resistance associated with BCR-ABL upregulation is dependent on
HIF-1alpha-induced metabolic reprograming. Oncogene 2010;29:2962-72.
30. Oh ET, Kim CW, Kim SJ, Lee JS, Hong SS, Park HJ. Docetaxel
induced-JNK2/PHD1 signaling pathway increases degradation of HIF-1alpha
and causes cancer cell death under hypoxia. Sci Rep 2016;6:27382.
31. Blagosklonny MV, An WG, Romanova LY, Trepel J, Fojo T, Neckers L. p53
inhibits hypoxia-inducible factor-stimulated transcription. J Biol Chem
1998;273:11995-8.
32. Semenza GL. HIF-1: upstream and downstream of cancer metabolism. Curr
Opin Genet Dev 2010;20:51-6.
33. Keith B, Johnson RS, Simon MC. HIF1alpha and HIF2alpha: sibling rivalry in
hypoxic tumour growth and progression. Nat Rev Cancer 2011;12:9-22.
34. Xu IM, Lai RK, Lin SH, Tse AP, Chiu DK, Koh HY, et al. Transketolase
counteracts oxidative stress to drive cancer development. Proc Natl Acad Sci
USA 2016;113:E725-34.
35. Luo W, Semenza GL. Pyruvate kinase M2 regulates glucose metabolism by
functioning as a coactivator for hypoxia-inducible factor 1 in cancer cells.
Oncotarget 2011;2:551-6.
36. Ravi R, Mookerjee B, Bhujwalla ZM, Sutter CH, Artemov D, Zeng Q, et al.
Research. on June 18, 2020. © 2018 American Association for Cancercancerres.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on March 29, 2018; DOI: 10.1158/0008-5472.CAN-17-2906
39
Regulation of tumor angiogenesis by p53-induced degradation of
hypoxia-inducible factor 1alpha. Genes Dev 2000;14:34-44.
Figure Legends
Figure 1 Clinical significance of TKT in TNBC patients.
(A) The expression levels of TKT in tumor (n= 40) and normal (n= 7) tissues were
analyzed according to gene expression arrays in Oncomine database (non-parametric
Mann-Whitney test, P = 0.03). (B) The levels of TKT in non-TNBC (n = 1725) and
TNBC (n = 250) patients from Curtis data were compared (***P < 0.001). (C)
Kaplan-Meier curve for TKT expression in association with 5-year survival of 637
breast cancer patients. Patients were divided into high (blue line) and low (red line)
TKT expression groups based on the mean + SD levels among the patients analyzed
(log-rank test, P = 0.019). (D) Kaplan-Meier curve for TKT expression in association
with overall survival (n = 158). Patients were divided into high (blue line) and low
(red line) TKT expression groups based on the median levels among the patients
analyzed (log-rank test, P = 0.003). (E) Kaplan-Meier curve for TKT expression in
association with 5-year survival of 106 TNBC patients among the 637 breast cancer
patients. Patients were divided into high (blue line) and low (red line) TKT expression
groups based on the mean + SD levels among the patients analyzed (log-rank test, P =
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40
0.0006). (F) Representative pictures of TKT IHC from normal, primary tumor and
lymph node metastatic tissues (scale bar: 1 mm, Supplementary Fig. S2 shows
quantitative results).
Figure 2 Downregulation of TKT suppresses growth, invasion/migration and
colony formation and affects cell cycle distribution of breast cancer cells.
(A) 20 μM siTKT reduced TKT expression in MDA-MB-231 and Hs578T cells,
whereas its inhibitory effects were rescued by TKT/pCMV overexpression (1 μg/μL).
The effects of TKT expression on cell proliferation in MDA-MB-231 (B-D) and
Hs578T cells (E-G) were measured after siTKT or siTKT and TKT/pCMV
co-treatment for 24, 48 and 72h (*P < 0.05, **P < 0.01, ***P < 0.001). For invasion
(H) and migration (I) assays, MDA-MB-231 and Hs578T cells were treated with
siTKT or siTKT and TKT/pCMV co-treatment for 48h (***P < 0.001) and then
incubated on Boyden chamber for 8h. (J) For colony assay, 1 x 105 cells
MDA-MB-231 or MCF-7 (Supplementary Fig. S4E) cells were transfected with
siTKT. (K) MDA-MB-231 and Hs578T cells were transfected with siTKT. 48h later,
tumor cells were harvested for analysis of cell cycle distribution after PI staining. The
percentage of cells was quantified by FlowJo 7.6 (*P < 0.05, ***P < 0.001).
Figure 3 Knockdown of TKT does not inhibit early targeting to lung but
suppresses lung metastasis of breast cancer cells.
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41
(A) MDA-MB-231-IV2-3 cells (1 x 106 cells) were transfected with 20 μM of siCon
or siTKT. After 48h, 1 x 106 cells per mouse were injected intravenously into
CB17-SCID mice via tail veins (n = 8). Lung metastases as reflected by amount of
cancer cells in lung in vivo (A) and ex vivo (B) were quantified using BLI signal (n=8).
(C) Images show H&E staining of lung metastases. More detailed data are shown in
Supplementary Fig. S3A-S3F. Scale bar: 1mm. T represents tumor cells in the lung.
(D) MDA-MB-231-IV2-3 cells (1 x 106 cells) transiently transfected with siCon or
siTKT were injected at 1 x 106 cells per mouse into CB17-SCID mice via tail veins
(n=8). BLI images showed lung metastasis of tumor cells in siCon and siTKT-treated
mice 30 mins after injection (P = 0.294). (E) 24h after injection, the mice were
perfused with PBS to rid of blood and lung tissues were harvested. Specific qPCR
primers for human GAPDH were used to detect injected cells in lung tissues and
mouse actin mRNA was used as the internal control (P = 0.222). (F) Knockdown
efficiency of shTKT in the two independent stable lines, MDA-MB231-shTKT-1 and
MDA-MB231-shTKT-2 was confirmed when compared with the control group (stable
MDA-MB-231-shNC cells). (G) Stable shTKT cells were orthotopically injected at 1
x 106 cells per mouse into 4
th mammary fat pads of CB17-SCID mice (n = 7) and
tumor volumes (H) were recorded once a week during the 70 days period (***P <
0.001).
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42
Figure 4 α-KG inhibits growth, lymph node and lung metastases of breast cancer
cells in CB17-SCID mice.
MDA-MB-231 cells were treated with siTKT (A) or TKT/pCMV (B). After 48h, their
effects on α-KG levels were measured by LC-MS. (C) MDA-MB-231 cells were
treated with or without 100 or 1000 μM α-KG for 18, 24 and 48h and cell growth was
measured using MTS assay (*P < 0.05, **P < 0.01, ***P < 0.001). For invasion (D)
and migration (E) assays, MDA-MB-231 cells were treated with 1 mM α-KG
(treatment) for 48h and then incubated on Boyden chamber for 8h. Each experiment
was repeated three times. TKT overexpression promoted cell proliferation of
MDA-MB-231 (F-H) and Hs578T (Supplementary Fig. S4F-S4H). 1 mM α-KG
treatment decreased the phenomenon. TKT overexpression promoted cell invasion (I)
and migration (J), whereas its effects were decreased by α-KG treatment (*P < 0.05,
**P < 0.01, ***P < 0.001). MDA-MB-231 cells were orthotopically injected at 1 x
106 cells per mouse into 4
th mammary fat pads of CB17-SCID mice. Starting the next
day, the mice were intraperitoneal injected with α-KG (10 mg/kg) or PBS control
three times per week. The images of tumor cells in tumors (K) and various organs,
including spleen, lung, liver and lymph node (N) from individual mice (n=10) were
monitored by BLI signal. Representative BL1 images were shown after 3 months of
continuous treatment with PBS or α-KG. Tumor weight (L) and tumor volume (M)
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43
quantification in α-KG or PBS control were measured (*P < 0.05,**P < 0.01, ***P <
0.001).
Figure 5 TKT and α-KG reversely regulate glucose metabolic enzymes.
Knockdown of TKT (A) or α-KG treatment (B) significantly altered the expression of
TCA cycle enzymes. (C) LC-MS data showed reduction of TKT decreased the levels
of succinate and fumarate. The effects of TKT knockdown (D) or α-KG treatment (E)
on RNA levels of SDH and FH were measured by qPCR. GAPDH was served as the
internal control (**P < 0.01, ***P < 0.001). (F) Model of breast cancer cell metastasis
suppressed by downregulation of TKT via α-KG and SDH and FH commonly
mediated signaling pathways.
Figure 6 Knockdown of TKT or α-KG addition affects glucose metabolism and
mitochondrial oxygen consumption.
(A) Knockdown efficiency of siTKT in MDA-MB-231 cells was confirmed. Reduced
TKT or α-KG addition decreased glycolytic metabolism (ECAR) (B, C, P < 0.001)
while increased oxygen consumption rate (OCR) (D, E, P < 0.001). The ECAR and
OCR values were normalized with 7 x 104 MDA-MB-231cells per well.
Figure 7 Oxythiamine in combination with docetaxel and/or doxorubicin
enhances inhibitory effects on TNBC cell viability.
(A) MDA-MB-231 cells were treated with 5 mM oxythiamine. After 48h, the effect of
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44
oxythiamine on TKT activity was measured. The effects of 5 mM oxythiamine (OT)
treatment on the levels of α-KG for 24h in MDA-MB-231 (B) and Hs578T (C) cells.
(D) The effects of OT treatment on viabilities of non-tumorigenic human normal
breast cell line H184 for 24h (P = 0.16), 48h (P = 0.08) and 72h (P = 0.07) were
assessed. (E) The effects of docetaxel (Doc) or doxorubicin (Dox) on the levels of
α-KG were measured by LC-MS (***P < 0.001). The effects of OT in combination
with Doc and/or Dox on cell viabilities of MDA-MB-231 (F-H) and Hs578T (I-K)
were assessed. Cell viabilities for 24h (F, I), 48h (G, J) and 72h (H, K) were measured.
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Published OnlineFirst March 29, 2018.Cancer Res Chien-Wei Tseng, Wen-Hung Kuo, Shih-Hsuan Chan, et al. signaling pathwaybreast cancer cell metastasis via the alpha-ketoglutarate Transketolase regulates the metabolic switch to control
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