Optimized dosing schedule based on circadian dynamics of ... · 5/5/2018 · circadian alter. ations, the role of cancer stem cells (CSC) in defining this circadian change . remains

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.).

Research. on October 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 May 7, 2018; DOI: 10.1158/0008-5472.CAN-17-4034

http://cancerres.aacrjournals.org/

1

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]




2

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) =




7

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




12

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




13

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




15

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




16

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




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




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




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




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.




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




27

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




28

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




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.



















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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http://cancerres.aacrjournals.org/cgi/alerts

mailto:[email protected]

http://cancerres.aacrjournals.org/content/early/2018/05/05/0008-5472.CAN-17-4034


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Optimized dosing schedule based on circadian dynamics of ... · 5/5/2018 · circadian alter. ations, the role of cancer stem cells (CSC) in defining this circadian change . remains