Optimized dosing schedule based on circadian dynamics of mouse
breast cancer stem cells improves the anti-tumor effects of aldehyde
dehydrogenase
Naoya Matsunaga1,2, Takashi Ogino1, Yukinori Hara1, Takahiro Tanaka1, Satoru Koyanagi1,2,
Shigehiro Ohdo1
1Department of Pharmaceutics, Faculty of Pharmaceutical Sciences, Kyushu University, 3-1-1
Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
2Department of Glocal Healthcare Science, Faculty of Pharmaceutical Sciences, Kyushu
University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
Running title: Importance of circadianity in CSCs for TNBC therapy
Keywords: WNT;; β-catenin; cancer stem-like cells; N,N-diethylaminobenzaldehyde;
chronotherapy
FINANCIAL SUPPORT
This work was supported in part by a Grant-in-Aid for Scientific Research A (16H02636 to S.
Ohdo), Grant-in-Aid for Challenging Exploratory Research (17H06262 to S. Ohdo) and
Scientific Research C (15K08098 to N. Matsunaga) from Japan for the Promotion of Science.
This research was supported by Platform Project for Supporting Drug Discovery and Life
Science Research (Basis for Supporting Innovative Drug Discovery and Life Science
Research (BINDS)) from AMED under Grant Number JP18am0101091. VECELL 3D plates
were a gift from Makoto Kodama, PhD (VECELL, Inc.).
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COMPETING FINANCIAL INTERESTS
The authors declare no competing financial interests.
CORRESPONDING AUTHOR
Shigehiro Ohdo
Department of Pharmaceutics, Faculty of Pharmaceutical Sciences, Kyushu University
Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
Phone: +81-92-642-6610
E-mail: [email protected]
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ABSTRACT
Although malignant phenotypes of triple-negative breast cancer (TNBC) are subject to
circadian alterations, the role of cancer stem cells (CSC) in defining this circadian change
remains unclear. CSC are often characterized by high aldehyde dehydrogenase (ALDH)
activity, which is associated with the malignancy of cancer cells and used for identification and
isolation of CSC. Here we show that the popultation of ALDH-positive cells in a mouse 4T1
breast tumor model exhibits pronounced circadian alterations. Alterations in the number of
ALDH-positive cells was generated by time-dependent increases and decreases in the
expression of Aldh3a1. Importantly, circadian clock genes were rhythmically expressed in
ALDH-negative cells, but not in ALDH-positive cells. Circadian expression of Aldh3a1 in
ALDH-positive cells was dependent on the time-dependent release of Wingless-type mmtv
integration site family 10a (WNT10a) from ALDH-negative cells. Furthermore, anti-tumor and
anti-metastatic effects of ALDH inhibitor N,N-diethylaminobenzaldehyde were enhanced by
administration at the time of day when ALDH activity was increased in 4T1 tumor cells. Our
findings reveal a new role for the circadian clock within the tumor microenvironment in
regulating the circadian dynamics of CSC. These results should enable the development of
novel therapeutic strategies for treatment of TNBC with ALDH inhibitors.
Significance: This seminal report reveals circadian dynamics of cancer stem cells are
regulated by the tumor microenvironment, and provides a proof of principle of its implication
for chronotherapy in TNBC.
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INTRODUCTION
According to the World Health Organization, breast cancer is the most common cancer
in patients worldwide (1). However, current treatment strategies cannot eliminate the majority
of breast cancers. In particular, triple-negative breast cancer (TNBC) is highly aggressive (2).
TNBC is usually resistant to chemotherapeutic drugs and has also been incriminated in
recurrence after chemotherapy, radiation treatment, and resection surgery (3).
One approach for increasing the efficacy of pharmacotherapy is to administer drugs at
the time of day when they are most effective and/or best tolerated. A chronopharmacological
strategy can enhance the effects of drugs and/or attenuate their toxicity (4,5). Circadian
variations in biological functions, such as gene expression and protein synthesis, are thought
to be important factors affecting the efficacy of drugs. Experimental chronopharmacology
studies have successfully guided the development of chronotherapy schedules with
5-fluorouracil, leucovorin, and oxaliplatin in human colorectal cancer. Chronomodulated
chemotherapy regimens have also produced the highest tumor response rates and the
longest survival reported in multicenter randomized trials (6-9). The circadian rhythm in the
tolerability and the efficacy of docetaxel and doxorubicin in mice bearing syngeneic mammary
cancer tumors derived from MA13/C cells is investigated as a prerequisite for the
development of chronotherapy schedules with these drugs in human breast cancer (10) .
However, there is no previous study evaluating chronotherapy for treatment of TNBC.
Tumor masses are composed of heterogeneous cells, and this heterogeneity is relevant
to resistance to chemotherapy and a high risk of recurrence. Cancer stem-like cells (CSCs)
represent a distinct proportion in cancer cells, but they play a key role in driving tumor growth,
progression, and metastasis owing to their self-renewal and differentiation capacities. CSCs
in TNBC tumor mass are also considered to be responsible for metastasis, recurrence, and
resistance against chemotherapy and radiation treatment (11,12). Because CSCs are
characterized by specific cell surface markers (13,14), this subpopulation of cells can be
isolated from mixed tumorigenic and nontumorigenic cells using different immune selection
methods (15). However, a limitation of surface marker recognition approaches is that the
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results are ascribed to the specific studied population (16). In addition, because the
characteristics of CSCs are complex, general studies of CSCs should be more thorough and
provide more data to confirm the population as CSCs (17,18). Therefore, a more useful
method involving detection of the activity of a specific protein in CSCs has been developed to
identify and/or isolate CSCs in both basic research and the clinical setting (19). High aldehyde
dehydrogenase (ALDH) activity is often detected in cells with stem-like properties, suggesting
that this enzyme can be used as a marker to isolate CSCs (20); the ALDEFLUOR assay
measures ALDH enzyme activity via cleavage of a fluorescent substrate,
BODIPY-aminoacetaldehyde, and is a commonly used method to identify and isolate CSCs
(21,22) .
In this study, we used the ALDEFLUOR assay to investigate the ALDH activity in mice
implanted with murine TNBC 4T1 cells. The number of ALDH-positive cells (high ALDH
activity cells) in a mouse breast tumour model exhibited pronounced circadian alterations,
which was caused by the time-dependent release of Wingless-type mmtv integration site
family 10a (WNT10a) from ALDH-negative cells. Therefore, we investigated whether
anti-tumor and anti-metastatic effects of ALDH inhibitor were improved by changing the
dosing schedule.
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MATERIALS AND METHODS
Cells and treatments
4T1 mouse breast cancer cells were purchased from American Type Culture Collection.
Cells were cultured under a 5% CO2 environment at 37°C in roswell park memorial institute
(RPMI)-1640 medium supplemented with 10% fetal bovine serum and 1%
penicillin/streptomycin in two-dimensional (2D) CELLSTAR cell culture flasks (Greiner
Bio-One, Monroe, NC) or synthetic three-dimensional (3D) scaffold biomaterials (VECELL
3D-inserts; VECELL Inc., Kitakyusyu, Japan). We confirmed that there was no microbial in
this cell lines using TaKaRa PCR Mycoplasma Detection Set. We confirmed that cell lines
were authenticated by each cell bank using short tandem repeat-polymerase chain reaction
(PCR) analysis, and these cell lines were used in less than 3 months from frozen stocks. We
confirmed that there was no microbial growth in both cell lines using fluorochrome staining. To
downregulate the Aldh3a1 gene, 4T1 cells were infected with lentiviral vectors expressing
small hairpin (sh) ribonucleic acid (RNA) against the mouse Aldh3a1 gene
(pGFP-C-shAldh3a1 Lenti Vector; Origene Technologies, Inc., Rockville, MD). After infection
of cells with lentiviral vectors, cells were maintained in medium containing 2 µg/mL puromycin.
Green fluorescent protein (GFP)-expressing cells were selected by sorting using fluorescence
activated cell sorting (FACS) (BD Biosciences, Franklin Lakes, NJ). Downregulation of the
Aldh3a1 gene was confirmed by reverse transcription (RT)-PCR. Aldh3a1::Luc-expressing
4T1 cells were prepared using luciferase reporter vectors under the control of the mouse
Aldh3a1 promoter. The mouse Aldh3a1 promoter region spanning from 660 to 675 bp (the
distance in base pairs from the putative transcription start site, +1) was amplified by PCR, and
the product was ligated into the pGL4.18 luciferase reporter vector (Promega, Madison, WI).
The primer sequences used for amplification of the mouse Aldh3a1 promoter region were as
follows: forward primer, 5ʹ-ATACTCGAGACTGGCTAAACATACAGAAAGGG-3ʹ; reverse
primer, 5ʹ- ATAAGATCTTGGAACTCCTGGAATAAGCAAG-3ʹ. After transfection of
Aldh3a1::Luc vectors into 4T1 cells, transgene-expressing cells were selected with G418
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(Wako Chemicals, Osaka, Japan). Individual colonies were expanded and maintained in
medium containing 1 µg/mL G418. The activity of Aldh3a1::Luc was assessed using
luciferase assays. To prepare Wnt10a-downregulated Aldh3a1::Luc-expressing 4T1 cells,
Aldh3a1::Luc-expressing 4T1 cells were infected with lentiviral vectors expressing shRNA
against the mouse Wnt10a gene (pGFP-C-shWnt10a Lenti Vector; Origene Technologies,
Inc.). After infection of cells with lentiviral vectors, cells were maintained in medium containing
2 µg/mL puromycin. GFP-expressing cells were selected by sorting using FACS (BD
Biosciences). Downregulation of the Wnt10a gene was confirmed by RT-PCR.
ALDEFLUOR assay
ALDH-positive (ALDH-high activity) and ALDH-negative (ALDH-low activity) cells were
gated based on the ALDEFLUOR assay (StemCell Technologies, Vancouver, BC, Canada)
according to the manufacturer’s instructions. Briefly, dissociated single cells from cell lines or
tumor specimens were suspended in ALDEFLUOR assay buffer containing an ALDH
substrate, BODIPY-aminoacetaldehyde at 1.5 µM; this was followed by incubation for 40 min
at 37°C. A specific inhibitor of ALDH, DEAB, was used at a 10-fold molar excess as a
negative control. FACS (BD Biosciences) was performed on more than 1 × 106 cells under low
pressure in the absence of ultraviolet light. The data were analyzed using BD FACSDiva
software V6.1.3 (BD Biosciences).
Animals and treatments
Five-week-old female BALB/c mice (Kyudo Co., Ltd., Saga, Japan) were housed under a
standardized light-dark cycle at 24 ± 1°C and 60% ± 10% humidity with food and water ad
libitum. Thirty microliters medium containing 5 × 104 native 4T1 cells, Aldh3a1-downregulated
4T1 cells, Aldh3a1::Luc-expressing 4T1 cells, or Wnt10a-downregulated
Aldh3a1::Luc-expressing 4T1 cells was injected into the right hind footpads of the mice.
Tumor volume was estimated according to the following formula: tumor volume (mm3) =
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4π(XYZ)/3, where 2X, 2Y, and 2Z are the three perpendicular diameters of the tumor. After the
tumor size reached 300 mm3, experiments were performed. On day 21 after implantation of
4T1 tumor cells into the mice (day 3 after the last DEAB injection), the lungs were removed,
rinsed, and fixed in Bouin solution to heighten the contrast between tumor nodules and
normal lung parenchyma. The numbers and sizes of metastatic tumor cells were determined
under a dissecting microscope. A solution of DEAB (Sigma-Aldrich, St. Louis, MO) and
Wnt-C59 (Cellagen Technology, San Diego, CA) was prepared by dissolving in 5% dimethyl
sulfoxide (DMSO) in 95% olive oil. The drugs were injected using a 30-gauge needle. All
experimental procedures were performed under the approval and guidelines of Kyushu
University.
Quantitative RT-PCR analysis
Total RNA was extracted using RNAiso (Takara Bio Co., Ltd., Shiga, Japan) or a QIAGEN
RNeasy Mini Kit (Qiagen, Hilden, Germany). cDNA was synthesized using a ReverTra Ace
qPCR RT Kit (Toyobo, Osaka, Japan) and amplified by PCR. Real-time PCR analysis was
performed on diluted cDNA samples using the THUNDERBIRD SYBR qPCR Mix (Toyobo)
with the 7500 Real-time PCR system (Applied Biosystems, Foster City, CA). Data were
normalized using 18s and β-actin mRNAs as controls because spinal expression of these
MRAs is constant throughout the day. Primer sequences are listed in Supplementary Table
1.
Western blot analysis
Protein samples were prepared from ALDH-positive and ALDH-negative 4T1 cells using
CelLytic MT Cell Lysis Reagent (Sigma-Aldrich) supplemented with protease inhibitor cocktail,
which contained 2 μg/mL aprotinin, 2 μg/mL leupeptin, and 100 μM phenylmethylsulfonyl
fluoride (PMSF). Then, 20 µg of the protein lysate was resolved by sodium dodecyl sulfate
polyacrylamide gel electrophoresis on 10% or 12% gels, transferred to polyvinylidene
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difluoride membranes, and probed with antibodies against ALDH3A1 (ab76976; Abcam,
Cambridge, MA), WNT10a (SAB3500393; Sigma-Aldrich), and β-ACTIN (sc-1616; Santa
Cruz Biotechnology, Santa Cruz, CA). Specific antigen-antibody complexes were visualized
using horseradish peroxidase-conjugated secondary antibodies and a chemiluminescence
reagent.
Microarray analysis
ALDH-positive and ALDH-negative 4T1 cells were prepared from 4T1 tumor-implanted
mice at zeitgeber time (ZT)0 and ZT12 (ZT0, lights on; ZT12, lights off). Total RNA was
extracted from cells using a QIAGEN RNeasy Mini Kit (Qiagen). The quality of the total RNA
was checked using an Agilent 2200 TapeStation (Agilent Technologies, Santa Clara, CA).
Then, 50 ng total RNA for each gene was used for the labeling reaction with the one-color
protocol of an Agilent Low-Input QuickAmp Labeling Kit (Agilent Technologies). Labeled RNA
was hybridized to a 60K Agilent 60-mer SurePrint technology (SurePrint G3 Mouse Gene
Expression 8 × 60K Microarray Kit version 2.0) according to the manufacturer's protocol. All
hybridized microarray slides were washed and scanned using an Agilent scanner. Relative
hybridization intensities and background hybridization values were calculated using Agilent
Feature Extraction software (version 9.5.1.1). Raw signal intensities and flags for each probe
were calculated from hybridization intensities and spot information according to procedures
recommended by Agilent. The raw signal intensities of two samples were log2-transformed
and normalized using a quantile algorithm in the ‘preprocessCore’ library package of the
Bioconductor software (www.bioconductor.org). This produced a gene expression matrix
consisting of 55,681 probe sets; differentially expressed genes between samples were
selected using a Z-score of 2.0 or more and a ratio of 1.5-fold or more. For downregulated
genes, a Z-score of -2.0 or less and a ratio of 0.75 or less were used. Functional analysis of
the differentially expressed genes was performed using the kyoto encyclopedia of genes and
genomes (KEGG) database on the DAVID system (23). The full data has been deposited in
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national center for biotechnology information (NCBI) gene expression omnibus (GEO)
( Accession#:GSE103598).
Chromatin immunoprecipitation analysis
Cross-linked chromatin extracted from cells of the spinal cord was sonicated on ice,
and nuclear fractions were obtained by centrifugation at 10,000 × g for 5 min. Supernatants
were incubated with antibodies against β-catenin (#8480; Cell Signaling Technology, Beverly,
MA), Transcription factor 7-like 2 (TCF7L2) (#2569; Cell Signaling Technology), or rabbit IgG
(sc66931; Santa Cruz Biotechnology). DNA was purified using a DNA purification kit
(Promega) and amplified by PCR for the surrounding β-catenin/TCF binding site in the
upstream region of the Aldh3a1 gene. The primer sequences for the amplification of the
surrounding β-catenin/TCF binding site were as follows: 5ʹ-CCTGGGTGATACAGAGAGGA-3ʹ
and 5ʹ- CACAACCTACTGGTTGGAGA-3ʹ. The quantitative reliability of PCR was evaluated
through kinetic analysis of the amplified products to ensure that signals were only derived
from the exponential phase of amplification. This analysis was also performed in the absence
of an antibody or in the presence of rabbit IgG as negative controls; no PCR products were
detected with ethidium bromide staining in any samples.
In vivo bioluminescence monitoring
An in vivo imaging system (IVIS Spectrum; Caliper Life Sciences Inc., Hopkinton, MA)
was used for in vivo bioluminescence monitoring (24). Mice implanted with
Aldh3a1::Luc-expressing 4T1 cells or Wnt10a-downregulated Aldh3a1::Luc-expressing 4T1
cells were subcutaneously injected with 15 mg/kg D-luciferin potassium salt (Wako
Chemicals) dissolved in phosphate-buffered saline. Cells were injected into the back near the
neck, under isoflurane anesthesia with concentrated oxygen and a gas anesthesia system
(BleaseDatum Vaporizer; Spacelabs Healthcare, Inc., Snoqualmie, WA). Images were
acquired 6 and 12 min after D-luciferin injection (5-s exposure time). The duration under
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isoflurane anesthesia was approximately 20 min for each experiment. After data were
obtained, mice recovered from isoflurane anesthesia within 1 to 2 min.
In vitro bioluminescence monitoring
The bioluminescence of cultured Aldh3a1::Luc- expressing 4T1 cells was recorded
using a real-time monitoring system (Lumicycle; Actimetrics, Wilmette, IL). The ALDH-positive
populations of Aldh3a1::Luc-expressing 4T1 cells were cultured on VECELL 3D inserts. The
3D inserts were placed in 35-mm dishes, in which ALDH-negative 4T1 cells were seeded and
stimulated with 100 nM dexamethasone for synchronization of their circadian clocks. The
amplitude of bioluminescence derived from Aldh3a1::Luc was calculated using Lumicycle
analysis software (Actimetrics). Bioluminescence images at the cellular level were acquired
using the LV200 LuminoView microscope system (Olympus, Tokyo, Japan).
Statistical and data analyses
The values presented are expressed as means ± standard errors of the means. The
significance of the 24-h variations in each parameter was tested by one-way analysis of
variance (ANOVA). The statistical significance of differences between groups was analyzed
by one-way or two-way ANOVA, followed by Tukey-Kramer post-hoc tests and Dunnett's test.
Equal variances were not formally tested. A 5% level of probability was considered significant.
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RESULTS
Circadian variations in the number of ALDH-positive cells in a mouse 4T1 breast tumor
model.
To investigate the malignancy of ALDH-positive cells, which indicated high activity of
ALDH, isolated from mouse 4T1 breast cancer cell lines, we implanted ALDH-positive cells
into the hind footpads of female BALB/c mice (Supplementary Fig. 1A). The ALDH-positive
cells exhibited profound tumor formation as well as enhanced pulmonary metastasis
(Supplementary Fig. 1B). Furthermore, the expression levels known CSC biomarkers,
SRY-related HMG-box-2 (Sox-2), POU domain, class 5, transcription factor 1 (Pou5f1), and
Nanog (25-27) in ALDH-positive cells were significantly higher than those in ALDH-negative
cells (Supplementary Fig. 1C), confirming that ALDH-positive cells have stem-like
properties.
Next, we elucidated whether ALDH-positive cells, which indicated high activity of ALDH,
in 4T1 tumor exhibited circadian characteristics. To achieve this, we assessed the number of
ALDH-positive cells in 4T1 breast cancer tumor-bearing mice kept under a 12-h light-dark
cycle. After the tumor size reached 300 mm3, tumor masses were removed at six different
time points and prepared as single-cell suspensions. The absence of necrosis in the
suspensions was confirmed by microscopic observation. The results of ALDEFLUOR assay
and FACS analysis revealed that a proportion of ALDH-positive cells in 4T1 tumor masses
exhibited significant circadian variations (F5,12 = 6.534, P = 0.004, one-way ANOVA; Fig. 1A).
The number of ALDH-positive 4T1 cells increased from the late light phase to the early dark
phase. Since seventeen Aldh genes have been identified in mammals (28), we attempted to
identify the Aldh gene responsible for the circadian alterations in ALDH activity in 4T1 tumor
cells implanted in mice. The mRNA expression of Aldh3a1 and Aldh6a1, which showed high
expression in cultured ALDH-positive cells by microarray analysis, was detected in 4T1 tumor
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masses. The mRNA levels for Aldh3a1, but not for Aldh6a1, in 4T1 cell-implanted mice
showed a significant circadian oscillation (F5,30 = 2.836, P = 0.033; one-way ANOVA; Fig. 1B
left panel, Supplementary Fig. 2). A similar rhythmic variation was also detected in the
protein levels of ALDH3a1 (F5,12 = 7.355, P = 0.002; one-way ANOVA, Fig. 1B right panel),
suggesting that the rhythmic expression of the Aldh3a1 gene was related to circadian
alterations in ALDH activity in 4T1 tumor masses.
To investigate this possibility, we prepared Aldh3a1-downregulated 4T1 cells via
introduction of lentivirus vectors expressing a specific shRNA (Supplementary Fig. 3A). The
growth and pulmonary metastasis of tumors formed by Aldh3a1-downregulated 4T1 cells was
significantly slower than those observed in mice implanted with control shRNA-expressing
4T1 cells (Supplementary Fig. 3B and C). Furthermore, the proportion of ALDH-positive
cells in Aldh3a1-downregulated 4T1 tumors did not show significant circadian alterations (Fig.
1C). These data suggest that the Aldh3a1 gene is responsible for generating circadian
alterations in ALDH activity in 4T1 tumor masses. This circadian alteration in ALDH activity
appeared to be reflected in the time-dependent changes in the number of ALDH-positive cells
in 4T1 tumor masses.
Circadian regulation of Aldh3a1 expression in 4T1 tumors by Wnt/β-catenin signaling
Next, we investigated the mechanism through which Aldh3a1 was expressed in a
circadian manner in 4T1 tumor cells. In mammalian cells, circadian rhythms in gene
expression are generated by a molecular oscillator driven by a transcriptional-translational
feedback loop consisting of clock genes (29). Therefore, we assessed the temporal
expression profiles of clock genes in both ALDH-positive and ALDH-negative (ALDH-low
activity) populations of 4T1 tumors. The number of ALDH-positive cells in 4T1 tumors varied
with the time of day; accordingly, we collected at least 10,000 ALDH-positive cells at six
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different time points and extracted their RNA. Although the mRNA levels of the main
components of the circadian clock, i.e., Clock, Bmal1, Period2 (Per2), Cryptochome1 (Cry1),
and Rev-erbα did not exhibit significant circadian oscillations in ALDH-positive populations of
4T1 cells, their expression exhibited significant circadian oscillations in ALDH-negative 4T1
cells (F5,12 = 6.278, P = 0.004 for Clock; F5,12 = 21.714, P < 0.001 for Bmal1; F5,12 = 5.034, P =
0.010 for Per2; F5,12 = 5.522, P = 0.007 for Cry1; F5,12 = 5.621, P = 0.007 for Rev-erbα;
one-way ANOVA; Fig. 2A). Because ALDH-negative cells constituted the microenvironment,
these findings suggest that the circadian oscillator functions in microenvironmental cells
rather than CSCs in 4T1 tumors.
Considering the dysfunction of circadian machinery in CSCs, we hypothesized that the
circadian expression of Aldh3a1 in ALDH-positive 4T1 cells was regulated by soluble factors
released from surrounding microenvironmental cells. To identify the factors responsible for
regulating the diurnal expression of Aldh3a1 in 4T1 tumor cells, we performed oligonucleotide
microarray analyses using RNA isolated from ALDH-positive and ALDH-negative populations
from 4T1 tumors implanted in mice at ZT0 and ZT12; at these time points, the expression of
Aldh3a1 in 4T1 tumors decreased and increased, respectively (Fig. 1C). Three criteria were
applied to select circadian cycle-dependent genes that regulate Aldh3a1 expression: (1) the
expression of genes in ALDH-negative cells being greater than that in ALDH-positive cells, (2)
the expression of genes in ALDH-negative cells at ZT0 being greater than that in
ALDH-negative cells at ZT12, (3) the expression of genes in ALDH-negative cells at ZT12
being greater than that in ALDH-negative cells at ZT0. From this analysis, we identified 618
candidate circadian time-dependent genes in ALDH-negative cells (Supplementary Table 2).
Functional analysis of these genes using the Kyoto Encyclopedia of Genes and Genomes
(KEGG) database (23) revealed that 19 biological pathways were enriched in a statistically
significant manner (P < 0.05; Supplementary Table 3).
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Among the genes involved in pathways related to cancer progression, we focused on
those that encode WNT proteins, because WNT proteins are secreted molecules that act on
cell-surface receptors, and also WNT signal transduction has been implicated in sustaining
the stemness of CSCs (30). To determine whether WNT signaling is involved in the circadian
regulation of Aldh3a1, the mRNA levels of Aldh3a1 were assessed in 4T1 tumor cells
implanted in mice after the intratumoral injection of a canonical WNT signal inhibitor, Wnt-C59,
at ZT2 and ZT14. Four hours after the injection of Wnt-C59 at each time point, the mRNA
levels of Aldh3a1 did not exhibit a significant time-dependent variation (Fig. 2B), suggesting
that WNT signaling is involved in the circadian regulation of Aldh3a1 expression in 4T1 tumor
cells.
Extracellular WNT stimulates several intracellular signal transduction cascades,
resulting in the activation or repression of a variety of genes (31). The major effector of these
transduction cascades is a bipartite transcription factor formed by β-catenin and a member of
the TCF protein family, such as TCF7L2 (32). A consensus DNA sequence of the
β-catenin/TCF binding site CTTTGA is located between 532 and 538 bp from the transcription
start site of the mouse Aldh3a1 gene (Fig. 2C left panel). The DNA sequence of the
β-catenin/TCF binding site has also been found at a similar location in all mammals examined,
including mice, rats, monkeys, and humans (Supplementary Fig. 4A). Thus, the luciferase
reporter of the mouse Aldh3a1 promoter containing the motif CTTTGA (Aldh3a1::Luc)
responded to β-catenin and TCF7L2 (Supplementary Fig. 4B). The results of chromatin
immunoprecipitation also revealed that both β-catenin and TCF7L2 bound to the promoter
region of the Aldh3a1 gene in 4T1 tumors, and the amount of bound protein was increased at
ZT14 compared with that at ZT2 (Fig. 2C right panel).
To determine whether the upstream region containing the β-catenin/TCF binding site
was responsible for the circadian expression of Aldh3a1, we prepared 4T1 cells that stably
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expressed Aldh3a1::Luc (Supplementary Fig. 5A). After confirming that the luciferase
activity of the Aldh3a1::Luc-expressing cells was mainly driven by ALDH-positive populations
(Supplementary Fig. 5B), we implanted these cells into the hind footpads of mice. In vivo
imaging analysis results revealed that the bioluminescence from tumors formed by
Aldh3a1::Luc-expressing 4T1 cells also showed significant circadian oscillation, with peak
levels during the early dark phase (F5,34 = 15.427, P < 0.001, one-way ANOVA; Fig. 2D). The
rhythmic pattern of the bioluminescence from Aldh3a1::Luc-expressing 4T1 tumors
resembled the overall rhythm of the expression of ALHD3a1 (Fig. 1C).
Circadian oscillation of Aldh3a1 expression in ALDH-positive cells by temporal
enhancement of WNT10a release from microenvironmental cells
Several genes encoding WNT ligands were highly expressed in ALDH-negative 4T1
cells (Supplementary Fig. 6). Among these, the expression of Wnt10a mRNA exhibited
profound circadian oscillation only in ALDH-negative cells (F5,12 = 17.117, P < 0.001, one-way
ANOVA; Fig. 3A). In vitro promoter analysis revealed that the transcription of Wnt10a was
controlled by the main components of the circadian clock (Supplementary Fig. 7). The
CLOCK/BMAL1-mediated transactivation of Wnt10a was repressed by PER2 and CRY1,
suggesting that PER and CRY proteins periodically repress the CLOCK/BMAL1-mediated
transactivation of the Wnt10a gene. Positive and negative regulation by the products of
circadian clock genes appeared to generate a circadian rhythm in the mRNA and protein
expression of Wnt10a. Although the expression of the WNT10a protein in ALDH-positive 4T1
cells was not detected by western blot analysis, its protein levels in ALDH-negative
populations of 4T1 tumors exhibited a significant time-dependent variation (F1.14 = 9.699, P =
0.036, two-way ANOVA; Fig. 3B). In contrast, the ALDH3a1 protein was difficult to detect in
ALDH-negative populations of 4T1 tumors; however, the protein levels showed a significant
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time-dependent variation in ALDH-positive 4T1 cells (F1,4 = 20.415, P = 0.011, two-way
ANOVA; Fig. 3B). These results suggest the possibility that extracellularly produced WNT10a
from microenvironmental cells act on ALDH-positive CSCs to induce Aldh3a1 expression.
To investigate this possibility, we prepared Wnt10a-downregulated
Aldh3a1::Luc-expressing 4T1 cells (Supplementary Fig. 8A and B, Supplementary Fig. 9)
and implanted them into the hind footpads of mice. The bioluminescence from tumors formed
by control Aldh3a1::Luc-expressing 4T1 cells (expressing the control shRNA) showed a
significant time-dependent variation (P < 0.01, Fig. 3C). However, the variation in the
bioluminescence from Aldh3a1::Luc-expressing 4T1 tumors was dampened by the
downregulation of Wnt10a. The intensity of the bioluminescence from Wnt10a-downregulated
4T1 tumors remained low at both the light and dark phases. Consistent with these
observations, the downregulation of Wnt10a in 4T1 cells decreased the number of
ALDH-positive cells and dampened their circadian oscillation (Fig. 3D), supporting the notion
that WNT10a is a major regulator of the circadian expression of the Aldh3a1 gene in 4T1
tumor cells.
In addition to analysis of the 4T1 tumor mass, we also detected significant circadian
accumulation of the WNT10a protein in the culture medium of ALDH-negative 4T1 cells after
synchronizing their circadian clocks by dexamethasone treatment (F13,28 = 6.325, P < 0.001,
one-way ANOVA; Fig. 4A). This finding suggests that tumor microenvironmental cells
enhance the release of WNT10a in a circadian fashion. The rapid degradation of WNT protein
has been reported previously (33). The half-life of the WNT10a protein in the medium was
approximately 4 h (Fig. 4B). Consequently, circadian accumulation of WNT10a in the culture
medium of ALDH-negative 4T1 cells may be associated with both its time-dependent
synthesis and rapid degradation.
To determine whether the time-dependent release of WNT10a from tumor
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17
microenvironmental cells causes circadian expression of Aldh3a1 in ALDH-positive 4T1 cells,
dexamethasone-treated ALDH-negative 4T1 cells was spatially co-cultured with
ALDH-positive cells that were isolated from Aldh3a1::Luc-expressing 4T1 tumors. Because
CSC stemness decreases under normal culture conditions, Aldh3a1::Luc-expressing
ALDH-positive 4T1 cells were maintained in transwell inserts (chambers) containing a 3D
scaffold (34). The 3D scaffold chambers were inserted into wells in which ALDH-negative 4T1
cells were seeded on the bottom (Fig. 4C left panel). Aldh3a1::Luc-expressing
ALDH-positive 4T1 cells showed a significant time-dependent oscillation of bioluminescence
when co-cultured with dexamethasone-treated ALDH-negative 4T1 cells (Fig. 4C right panel,
Supplementary Movie 1); however, this oscillation did not occur when they were co-cultured
with dexamethasone-untreated ALDH-negative 4T1 cells (Supplementary Movie 2). These
results suggest that the time-dependent enhancement of Wnt10a released from tumor
microenvironmental cells regulates the circadian expression of the Aldh3a1 gene in
ALDH-positive 4T1 cells.
Dosing time-dependent change in the anti-tumor and anti-metastatic effects of ALDH
inhibitor DEAB on 4T1 tumor-bearing mice
Since the number of ALDH-positive cells showed significant circadian variation in 4T1
tumor-bearing mice (Fig. 1), we investigated whether anti-tumor and anti-metastatic effects of
ab ALDH inhibitor were changed by optimizing dosing schedule. DEAB is commonly used as
a selective inhibitor of ALDH in CSCs (35). The intraperitoneal administration of DEAB (50
mg/kg) at ZT14, when the number of ALDH-positive cells was abundant, significantly
suppressed the growth and pulmonary metastasis of 4T1 tumor cells in mice (Fig. 5A and B).
In contrast, administration of the same dosage of DEAB at ZT2 did not result in significant
anti-tumor as well as anti-metastatic activity. These data reveal a significant relationship
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18
between the circadian alterations in the number of ALDH-positive 4T1 cells and their
malignant characteristics. Choosing the most appropriate dosing time can improve the
anti-tumor and anti-metastatic effects of ALDH inhibitor on malignant TNBC.
DISCUSSION
Although hormone replacement therapy is effective in patients with predominantly
estrogen receptor-positive breast cancers, patients with TNBC have poor prognosis (2). The
intratumoral heterogeneity consisting of CSCs and their environment cells could be explained
for malignancies and high recurrence of TNBC. Our results suggest that circadian variation in
the number of ALDH-positive cells in 4T1-tumor bearing mice plays an important role affecting
the anti-tumor and anti-metastatic effects of ALDH inhibitor. The activity of ALDH was
regulated by time-dependent variations in WNT10A released from ALDH-negative cells (Fig.
5C). This circadian interaction between ALDH-positive and ALDH-negative cells suggested a
potential therapeutic targets as chronotherapy for treatment of TNBC.
ALDHs exhibit a wide taxonomic distribution from bacteria to humans. They catalyze the
conversion of aldehydes to corresponding acids via an NAD(P)+-dependent irreversible
reaction (36). The family of ALDH contributes to sustain the stemness of cancer cells;
therefore their activity is used as a marker for CSCs (20). Implantation of ALDH-negative cells
to mice showed slow tumor growth and poor metastasis. Furthermore, inhibition of ALDH
activity resulted not only in the disruption of circadian variations in the number of
ALDH-positive cells, but also in the prevention of tumor growth and metastasis. ALDH has the
ability to ameliorate oxidative stress in tumor cells (37). Therefore, development of method
selectively inhibiting ALDH activity in CSCs would be useful for treatment of malignant
cancers including TNBC.
The circadian clock machinery in immature cells, e.g., ES cells and stem-like cells, is
functional after differentiation (38,39). Low level expression of clock genes in those immature
cells is thought to be important for sustaining their stemness (11). The expressions of clock
gene in ALDH-positive cells were lower than those in ALDH-negative cells, suggesting that
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19
dysfunction of circadian machinery is also required for sustaining the stemness of CSCs in
4T1 tumors. Overexpression of Aldh3a1 in 4T1 cells slightly increased the mRNA levels of
Bmal1 and Rev-Erbα, but in contrary decreased the expression of Clock (Supplementary Fig.
10). Although we were unable to clarify whether ALDH was indispensable for suppression of
circadian clock machinery in CSCs, low level expression of these clock genes in
ALDH-positive cells was unlikely due to the elevation of ALDH enzymatic activity. Recent
study has demonstrated that pharmacological activation of REV-ERBs is specifically lethal in
cancer cells (40). However, such strategy may be ineffective to CSCs in 4T1 tumors because
of low expression of clock genes including Rev-erbα.
Circadian expression of Aldh3a1 in ALDH-positive cells was dependent on
Wnt/β-catenin signaling. The expression of WNT10a in ALDH-negative cells was controlled
by the components of circadian clock. The results of co-culture experiment supported the
notion that the time-dependent enhancement of WNT10a release from ALDH-negative cells
caused the circadian expression of Aldh3a1 in the ALDH-positive CSCs. In mammals,
WNT/β-catenin signaling is prominent in stem cells and cancer cells (41). WNT proteins act as
critical microenvironmental factors for sustaining the stem cells in a self-renewing state. In
4T1 tumor masses, ALDH-negative cells were distinct from ALDH-positive cells, confirming by
the difference in the expression levels of typical CSC markers. Although ALDH-positive and
ALDH-negative cells were somewhat identical to each other, there were obvious genetic
differences between those cell populations.
It has been well known that microenvironment surrounding CSCs is composed by
tumor-associated fibroblasts, macrophages, myeloid-derived suppressor cells, and/or
regulatory T-cells (42). In addition, stromal fibroblasts are also involved in microenvironmental
constitutive cells, which is capable of releasing WNT proteins (43,44). Because gain of
β-catenin activity allows stem cell overpopulation and cancer development (45), disruption of
the circadian machinery in microenvironment cells may lead to arrhythmic expression of
WNT10a therefore enhancing malignancies of TNBC. This notion is also supported by
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20
previous findings that circadian host disruption accelerates the progression of many types of
cancer, including those without any clock or barely detectable Bmal1 expression and shorten
survival (46,47). Disruption of circadian rhythms in host animal also accelerates tumor growth
and angiogenesis/stromagenesis through the mediation of Wnt signaling pathway (48). In
contrast, the reinforcement of the host circadian clock or that of cancer tissues slows
proliferation of tumor cells in relation to the timing of meals or kinase inhibitor administration
(49,50). Consequently, the maintenance of circadian clock function in microenvironment may
be important to suppress overpopulation of CSCs.
Our present findings suggest that the effectiveness of anti-cancer drugs vary with the
circadian dynamics of CSCs, which are regulated by the tumor microenvironmental factors.
However, many drugs are still administered without regard to the time of day. Identification of
rhythmic markers for detection of the circadian dynamics of CSCs in tumors should enable
their use in chronotherapy, in which chemoradiation and/or high-dosage treatments are
administered at a time of day when CSCs are most vulnerable. Furthermore, circadian
machinery in tumor microenvironment may be a therapeutic target of TNBC, because the
machinery was participated in the regulation of tumor malignancies.
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21
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FIGURE LEGENDS
Figure 1 Circadian variations in the proportion of ALDH-positive cells in 4T1 tumors
implanted in mice. (A) Temporal profiles of the proportion of ALDH-positive cells in 4T1
tumor-bearing mice: left panels show the flow cytometric profiles of ALDH-positive (P4) and
ALDH-negative (P2) cells in 4T1 tumor masses. The right panel shows the temporal profile of
the proportion of ALDH-positive cells. The horizontal bar at the bottom indicates the light and
dark cycles. Values are means ± SEMs (n = 3). There were significant time-dependent
variations in the proportion of ALDH-positive cells (F5,12 = 6.534, P = 0.004; one-way ANOVA).
(B) Temporal expression profiles of Aldh3a1 mRNA (left) and its protein (right) in 4T1
tumor-implanted mice. Data were normalized to Gapdh mRNA levels. Values are means ±
SEMs (n = 3−6). There were significant time-dependent variations in both mRNA and protein
levels (F5, 30 = 2.836, P = 0.033 for mRNA; F5,12 = 7.355, P = 0.023 for protein; one-way
ANOVA). (C) Downregulation of the Aldh3a1 gene suppresses the circadian alterations in the
number of ALDH-positive cells in 4T1 tumor-implanted mice. Values are means ± SEMs (n =
6). **P < 0.01, significant difference between the two time points (F1,10 = 259.937, P < 0.001;
two-way ANOVA with Tukey-Kramer post-hoc tests).
Figure 2 Role of Wnt/β-catenin signaling in the circadian regulation of Aldh3a1
expression in 4T1 tumors. (A) The temporal mRNA expression profiles of clock genes in
ALDH-positive and ALDH-negative cells isolated from 4T1 tumor-implanted mice. Data were
normalized to Gapdh mRNA levels. Values are means ± SEMs (n = 3). There were significant
time-dependent variations in the mRNA levels of Clock, Bmal1, Per2, Cry1, and Rev-erbα in
ALDH-negative cells (F5,12 = 6.278, P = 0.004 for Clock; F5,12 = 21.714, P < 0.001 for Bmal1;
F5,12 = 5.034, P = 0.010 for Per2; F5,12 = 5.522, P = 0.007 for Cry1; F5,12 = 5.621, P = 0.007 for
Rev-erbα; one-way ANOVA). (B) Temporal expression profiles of Aldh3a1 mRNA in 4T1
tumor-implanted mice after intratumoral (i.t.) injection of Wnt-C59 (1 µg/mouse). The mRNA
levels were assessed 4 h after Wnt-C59 injection. Data were normalized to the levels of 18S
rRNA. Values are means ± SEMs (n = 5). *P < 0.05, significant difference between the two
time points (F1,8 = 12.485, P = 0.008; two-way ANOVA with Tukey-Kramer post-hoc tests). (C)
The temporal binding profiles of β-catenin and TCF7L2 to the upstream region of the mouse
Aldh3a1 gene in 4T1 tumor-implanted mice. Solid arrows in the schematic diagram represent
the area amplified by PCR. The signals of the amplified PCR products of immunoprecipitated
DNA together with antibodies against β-catenin and TCF7L2 were normalized to those of the
input DNA. Values are means ± SEMs (n = 3). **P < 0.01, significant difference between the
two time points (t4 = 5.417, P = 0.006 for β-catenin; t4 = 8.742, P = 0.001 for TCF7L2; unpaired
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t-test, two-sided). (D) The temporal profiles of bioluminescence from Aldh3a1::Luc-expressing
4T1 cell-implanted mice. Left panels show representative images of in vivo bioluminescence
imaging of tumors formed by Aldh3a1::Luc-expressing 4T1 cells. The right panel shows the
quantification of the intensity of bioluminescence from tumors formed by
Aldh3a1::Luc-expressing 4T1 cells. Values are means ± SEMs (n = 5−10). There was a
significant time-dependent variation in bioluminescence intensity (F5,34 = 15.427, P < 0.001;
one-way ANOVA).
Figure 3 WNT10a regulates the circadian alterations in the number of ALDH-positive
cells in 4T1 tumors. (A) The temporal mRNA expression profiles of Wnt10a in ALDH-positive
or ALDH-negative cells in tumor-implanted mice. Data were normalized to Gapdh mRNA
levels. Values are means ± SEMs (n = 3). There was a significant time-dependent variation in
Wnt10a mRNA levels in ALDH-negative cells (F5,12 = 17.117, P < 0.001; one-way ANOVA).
(B) Temporal protein expression profiles of WNT10a and ALDH3a1 in ALDH-positive or
ALDH-negative cells in tumor-implanted mice. Full-sized images of the western blotting
results are presented in Supplementary Fig. 11. Values of protein levels were normalized to
β-actin levels. Values are means ± SEMs (n = 3). **P < 0.01, *P < 0.05, significant differences
between the two time points (F1,4 = 9.699, P = 0.036 for Wnt10a; F1,4 = 20.415, P = 0.011 for
ALDH3a1; two-way ANOVA with Tukey-Kramer post-hoc tests). (C) Downregulation of
Wnt10a abrogated the circadian alterations in bioluminescence driven by
Aldh3a1::Luc-expressing cells in 4T1 tumor-implanted mice. Left panels show representative
in vivo bioluminescence images of Aldh3a1::Luc-expressing 4T1 tumors, which were
introduced with lentiviral vectors expressing control shRNA (upper) or shRNA against Wnt10a
(lower). The right panel shows quantification of the intensity of bioluminescence from tumors
formed by Aldh3a1::Luc-expressing 4T1 cells. Values are means ± SEMs (n = 5). **P < 0.01,
significant difference between the two time points (t8 = 3.712, P = 0.006; unpaired t-test,
two-sided). (D) Downregulation of Wnt10a diminished the circadian alterations in the number
of ALDH-positive cells in 4T1 tumor-implanted mice. Values are means ± SEMs (n = 4). **P <
0.01, significant difference between the two time points (F1,6 = 751.527, P < 0.001 for Control
shRNA; F1,6 = 340.149, P < 0.001 for Wnt10a shRNA; two-way ANOVA with Tukey-Kramer
post-hoc tests). ## P < 0.01, significant difference between the two groups (F1,6 = 306.436, P <
0.001 for ZT14; two-way ANOVA with Tukey-Kramer post-hoc tests).
Figure 4 Temporal enhancement of WNT10a release from microenvironmental cells in
4T1 tumor masses causes circadian oscillation of Aldh3a1 expression in
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ALDH-positive cells. (A) Temporal expression profiles of WNT10a proteins in the culture
medium of ALDH-negative cells whose circadian clocks were synchronized by treatment with
100 nM dexamethasone (DEX) or vehicle (0.1% ethanol). Fifty microliters of medium collected
at the indicated time points was used for western blot analysis. Full-sized western blotting
images are presented in Supplementary Fig. 12. Lower panel shows the quantification of
WNT10a protein levels. Values are means ± SEMs (n = 3). There was a significant
time-dependent variation in WNT10a protein levels in the DEX-treated group (F13,28 = 6.595, P
< 0.001, one-way ANOVA). (B) The half-life of WNT10a protein in the medium. Medium
incubated with ALDH-negative cells was collected and then incubated at 37°C for 6 h.
Full-sized western blotting images are presented in Supplementary Fig. 13. (C) Temporal
profiles of bioluminescence driven by Aldh3a1::Luc in ALDH-positive cells, which were
spatially co-cultured with ALDH-negative cells after treatment with 100 nM DEX or vehicle
(0.1% ethanol) for 2 h. Left panel presents the experimental procedure for the real-time
bioluminescent assay.
Right panel shows the temporal profiles of bioluminescence activity driven by Aldh3a1::Luc in
ALDH-positive cells which cultured 3D scaffold chamber (VECELL 3D) . Values are means ±
SEMs (n = 6). There was a significant time-dependent variation in the intensity of
bioluminescence in the DEX-treated group (F52, 265 = 109.272, P < 0.001; one-way ANOVA).
Figure 5 Dosing time-dependent change in the anti-tumor and anti-metastatic effects of
DEAB in 4T1 tumor-bearing mice. (A) Influence of dosing time on the ability of DEAB to
suppress the growth of 4T1 tumor cells implanted in mice. Solid arrows indicate the injection
of saline or DEAB (50 mg/kg, i.p.). Values are means ± SEMs (n = 5). Tumor volume on one
day before the initiation of DEAB treatment was set at 1.0. **P < 0.01, significantly different
from that of other groups (F3, 48 = 443.300, P < 0.001; two-way ANOVA with Tukey-Kramer
post-hoc tests). (B) Influence of dosing time on the ability of DEAB to suppress the metastasis
of 4T1 cells in the lungs. After treatment with DEAB for 21 days, pulmonary metastatic tumors
were counted. The left panel shows representative photographs of lungs prepared from 4T1
cell-implanted mice after treatment with DEAB (50 mg/kg, i.p.) at ZT2 or ZT14. Blue arrows
indicate metastatic tumor cells. The right panel shows the quantification of the number of
metastatic tumor cells and their sizes in the lungs of mice treated with DEAB (50 mg/kg, i.p.)
at ZT2 or ZT14. Values are means ± SEM (n = 4). *P < 0.05, significant difference in the total
number of metastatic tumor cells between groups (F3,12 = 4.962, P = 0.018; two-way ANOVA
with Tukey-Kramer post-hoc tests). (C) Schematic diagrams indicating the mechanism
underlying the circadian alterations in the number of ALDH-positive cells in 4T1 breast cancer
tumors. Microenvironmental cells in 4T1 tumors enhanced the release of WNT10a in a
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29
time-dependent manner, and these cells were under the control of the circadian clock. The
extracellular release of WNT10a stimulated ALDH-positive CSCs at a certain time of day,
thereby inducing the WNT/β-catenin signal-mediated transactivation of the Aldh3a1 gene.
This time-dependent enhancement of ALDH3a1 expression caused circadian alterations in
the number of ALDH-positive cells in 4T1 tumors.
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Published OnlineFirst May 7, 2018.Cancer Res Naoya Matsunaga, Takashi Ogino, Yukinori Hara, et al. effects of aldehyde dehydrogenasemouse breast cancer stem cells improves the anti-tumor Optimized dosing schedule based on circadian dynamics of
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