Introduction
Most breast tumors in both premenopausal and postmenopausal women express estrogen receptor type alpha (ER). Tamoxifen is a Selective Estrogen Receptor Modulator (SERM) widely used for adjuvant therapy in the treatment of ER+ breast cancer. In the hormone-sensitive tumors, tamoxifen acts as a partial antagonist, impairing ER function by competing with estrogen for binding to the receptor [
1]; however, more than three years of tamoxifen treatment only results in approximately 50% reduction in the incidence of invasive breast cancer in women at high risk, whereas about a third of ER+ breast tumors are intrinsically resistant to tamoxifen [
2,
3].
Third generation aromatase inhibitors (AI) present a valuable alternative to tamoxifen adjuvant therapy in postmenopausal women with ER+ breast cancer [
4‐
6]. Aromatase activity is essential for catalyzing the conversion to estrogen of steroid precursors in peripheral tissues, the major source of estrogen production in postmenopausal women. Upon treatment with AI, aromatase activity is reduced by at least 96% and circulating estrogen is virtually absent, inhibiting hormone-dependent tumor growth [
7]. In spite of the sensitivity of tamoxifen-resistant tumors to AI, breast tumors also acquire resistance to AI after long term treatment, resulting in disease recurrence and aggressive tumor growth [
8,
9]. Clinical trials are underway to assess the possibility of delaying the onset of resistance by administering AI for two to three years following two to three years of tamoxifen treatment [
10,
11]. The mechanistic basis underlying breast tumor resistance to either hormone depletion or to tamoxifen is still inadequately understood. In the vast majority of cases, resistance must occur through hormone-independent ER signaling events [
12,
13]. Accordingly, Selective Estrogen Receptor Downregulators (SERDs, for example, Faslodex) have been found to be effective inhibitors of ER+ breast tumor growth but their utility is limited to their use as second or third line therapeutics in postmenopausal women with metastatic disease due to their broader impact on physiological ER signaling pathways in normal tissues [
14,
15]. Therefore, it is imperative to continue to identify critical downstream events of ER signaling in breast cancer.
Breast cancer therapy trials have also been designed to explore the effect of retinoid compounds either alone or in combination with tamoxifen [
16]. In
in vitro and pre-clinical models of breast cancer using MCF-7 cell xenografts,
all-trans- retinoic acid (ATRA) alone or in combination with tamoxifen induced cell cycle arrest and apoptosis, leading to tumor regression through activation of multiple signal transduction pathways [
17‐
19]. Synergistic anti-tumor effects have been noted
in vitro for the combination of retinoid and tamoxifen and multiple molecular mechanisms for the ligand effects have been reported [
20,
21]. However, toxicity issues due to ATRA treatment was a challenge in patients with advanced breast cancer during phaseI/II clinical trials [
22]. Fenretinide, a synthetic amide of retinoic acid, has a better toxicological profile acting on both ER+ and ER- breast tumors principally by inducing apoptosis by both retinoic acid receptor (RAR) -dependent and -independent mechanisms; this drug showed a modest chemopreventive effect only in younger premenopausal women [
23].
Hormonal adjuvant therapy of breast cancer is overall tumoristatic with cell death balancing a basal level of cell proliferation [
24]. From a fundamental mechanistic standpoint, for resistance to develop in the long term during either hormone depletion or tamoxifen adjuvant therapy, the latent tumors must sustain a basal level of cell cycling to enable the generation and/or progression of genetic or epigenetic changes [
25] leading to resistance. It is the premise of this study that understanding the mechanisms that support the persistence of a small fraction of cells in S-phase throughout the course of hormonal adjuvant therapy in breast cancer will shed light on this critical precondition for the eventual development of resistance to the treatments. Since estrogen-independent ER signaling has been implicated in the development of resistance to adjuvant therapy, it was the goal of this study to examine the relationship between hormone-independent actions of ER and the basal cycling state of estrogen deprived breast cancer cells. Further, the ER-RAR axis has only been investigated in the context of ligand-dependent effects [
26]; it was therefore of additional interest to explore a possible interplay between the apo- forms of ER and RAR and its impact on basal proliferation, that is, under conditions of hormone depletion or tamoxifen antagonism.
Estrogen-sensitive breast cancer cell lines (MCF-7, T47 D and ZR-75-1) have proven to be exceptionally reliable predictive models both
in vitro and
in vivo for clinical drug response and the development of clinical drug resistance in breast cancer [
27‐
30]. We have observed that the expected basal proliferating state of hormone-depleted or tamoxifen treated breast cancer cells may be reproduced
in vitro in established cell lines for an indefinite period by avoiding the common practice of intermittently replenishing the culture media, thus avoiding depletion of autocrine growth factors. We, therefore, used
in vitro models to investigate the potential impact of hormone-independent actions of ER on the survival or proliferation of hormone-sensitive breast cancer cells and the related mechanisms under conditions that mimic hormonal adjuvant therapy, that is, estrogen-depletion and tamoxifen treatment.
Materials and methods
Chemicals and reagents
Dulbecco's minimum essential medium (DMEM), glutamine and penicillin/streptomycin/glutamine stock mix were purchased from Life Technologies, Inc. (Carlsbad, CA, USA). Fetal bovine serum (FBS) and charcoal-stripped FBS were from Invitrogen (Carlsbad, CA, USA). Fugene 6 and Dharmafect 1 were from Roche Diagnostics (Indianapolis, IN, USA) and Dharmacon (Thermo Scientific Dharmacon, Inc., Lafayette, CO, USA), respectively. ERα (J-003401-12), RARα (J-003437-07) and control (D-001810-02) small interfering RNA (siRNA) were purchased from Dharmacon (Thermo Scientific Dharmacon, Inc.). Affinity purified rabbit and mouse antibodies to human ERα (sc-543), RARα (sc-551), RARβ (sc-552), RARγ (sc-550) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH; sc-47724) were from Santa Cruz Biotechnologies (Santa Cruz, CA, USA). Peroxidase-conjugated secondary antibody was from Vector Laboratories (Burlingame, CA, USA). For standard PCR, HotStart Taq Plus DNA Polymerase was used (Qiagen, Germantown, MD, USA). Reagents for real time PCR, primers and TaqMan probes were purchased from Applied Biosystems (Branchburg, NJ, USA). PI/RNase staining buffer was from BD Pharmigen (San Diego, CA, USA). The Guava Nexin Reagent was purchased from Guava Technologies (Guava Technologies, Inc., Hayward, CA, USA). The protease inhibitor cocktail kit was obtained from Pierce Biotechnology (Thermo Scientific, Rockford, IL, USA). 17β-estradiol (E2), 4-hydroxytamoxifen (OH-Tam), all-trans-Retinoic acid (ATRA) and fulvestrant were purchased from Sigma Aldrich (Saint Louis, MO USA). ATRA stock solution (5 mmol/L) was made in a mixture of 50% ethanol and 50% DMSO (Fisher Chemical, Fair Lawn, NJ, USA). First strand cDNA from human peripheral blood leukocytes (PBL), thymus and spleen were obtained from Biochain Institute (Biochain Institute Inc., Hayward, CA, USA). Total RNA from normal human breast and human breast tumors were obtained from Biochain Institute Institute and Clonetech (Clonetech Laboratories Inc., Mountain View, CA, USA).
Cell culture and treatment with fulvestrant or ATRA
MCF-7 and T47 D (American Type Culture Collection) cells were cultured in DMEM supplemented with FBS (10%), penicillin (100 unit/ml), streptomycin (100 μg/ml) and L-glutamine (2 mM). ZR-75-1 (American Type Culture Collection) cells were cultured in RPMI 1640 supplemented with FBS (10%), penicillin (100 unit/ml), streptomycin (100 μg/ml) and L-glutamine (2 mM). Hormone depleted cells were grown in low glucose phenol-red free media supplemented with 5% charcoal-stripped FBS (v/v) and L-glutamine (2 mM) for 48 hours before the experiments. Hormone-depleted MCF-7 cells were grown to 60 to 70% confluency in six-well plates and treated with vehicle or ATRA (1 μM) for 24 hours. After 24 hours, the cells were harvested for total RNA isolation and mRNA profiling. Hormone-depleted MCF-7 cells were grown to 30 to 40% confluency in six-well plates and treated with vehicle or fulvestrant (100 nM) for up to 4 days. After 72 hours to 96 hours, the cells were harvested for isolation of total RNA and protein.
Transfection and gene silencing
Cells were plated at 20% confluence in low glucose phenol red free medium supplemented with 5% charcoal stripped FBS and glutamine 24 hours to 48 hours prior to transfection. Treatment with vehicle (ethanol), E2 (1 nM) or OH-Tam (100 nM) was begun an additional 24 hours later. Cells were transfected with control siRNA, ERα siRNA or RARα siRNA (100 pmol/mL) in 24-well microplates or 25 cm2 flasks using 2 μl and 12.5 μl of Dharmafect 1 (Thermo Scientific Dharmacon Inc.), respectively, according to the vendor's protocol. The cell culture medium was not replenished for the duration of the experiment. In the RARα1 rescue experiments, 2 × 106 cells were co-transfected with 2 μg of either the vector plasmid or RARα1 expression plasmid and with control siRNA or ERα siRNA by nucleofection using the Kit V Amaxa Nucleofection System (Amaxa Biosystems, Allendale, NJ, USA) according to the vendor's instructions. In the RARα1 rescue of fulvestrant- treated cells and RARα1 overexpression experiments, 2 μg RARα1 expression plasmid was introduced at a cell density of 2.5 × 105 cells per well in six-well plates using Fugene 6 according to the manufacturer's protocol.
Cell growth assay
Cells were seeded in 24-well microplates at 20% confluence in phenol-red free media supplemented with 5% charcoal-stripped FBS (v/v) and incubated at 37°C with 5% CO2 for 24 h. Cells were transfected with either control siRNA or siRNA targeting ERα using Dharmafect 1. Twenty-four hours after transfection the media was replaced with fresh phenol-red free media supplemented with 5% charcoal-stripped FBS (v/v) and the cells were treated with vehicle (ethanol), E2 (1 nM) or OH-Tam (100 nM) for the following five days; the culture media was not changed during this period but E2 and OH-Tam were replenished every 48 h. Viable cell counts were monitored using the trypan blue dye exclusion assay at intervals of 24 h.
Cell cycle analysis
Cells were trypsinized and harvested in phenol red free medium supplemented with charcoal stripped FBS. Cells (1 × 106) were washed and resuspended in 500 μl PBS. The cells were fixed by adding 500 μl 100% ice cold ethanol, drop-wise with agitation and incubated on ice for 20 minutes. The cells were sedimented by brief centrifugation at 200 xg for five minutes and the excess ethanol decanted. After the remaining ethanol was dried off, the cells were resuspended in 500 μl of PI/RNase solution. The cells were incubated in the dark at room temperature for 20 minutes and the cell cycle distribution determined by flow cytometric analysis using a FACSCalibur cell analyzer (BD Biosciences, San Jose, CA, USA). The data were acquired with BD CellQuest Pro software and analyzed using ModFit LT software.
Apoptosis assay
Early stage apoptosis of cells was measured by Guava Nexin analysis using the Guava Nexin Reagent staining kit according to the manufacturer's instructions. Briefly, 8 × 104 cells were incubated for 20 minutes at room temperature with the Guava Nexin Reagent and 2,000 cells per sample were analyzed using the Guava System.
Western blot
Cells were harvested by trypsinization, lysed in a high salt-detergent buffer (400 nM NaCl; 10 nM Tris, pH 8.0; 1 mM EDTA; 1 mM EGTA; β-mercaptoethanol; and 0.1% Triton x-100) containing a protease inhibitor cocktail kit and incubated on ice for 30 minutes. Cell lysates were heated to 95°C for five minutes. Protein samples (10 to 20 μg) were resolved by electrophoresis on 8% sodium dodecylsulfate-polyacrylamide gels and electrophoretically transferred to PVDF membranes (Millipore Corporation, Bedford, MA, USA). The blots were probed with the appropriate primary antibody and the appropriate horseradish peroxidase conjugated secondary antibody and the protein bands visualized using enhanced chemiluminescence as described [
31]. The chemiluminescent signals were quantified using the FluorChem HD2 imaging system (Alpha Innotech/Cell Biosciences, Inc., Santa Clara, CA, USA) and normalized to GAPDH.
RNA isolation, reverse transcription PCR and Real time PCR
Total RNA from cells was isolated using the RNeasy mini kit (Qiagen, Georgetown, MD, USA). Reverse transcription PCR reactions were performed using 500 ng of total RNA and the high capacity complementary DNA Archive kit (Applied Biosystems) according to the vendor's protocol. cDNAs of RARα1 and RARα2 were amplified by competitive PCR. The upstream and downstream primers used for amplification of RARα1 and RARα2 were as follows: RARα1, 5'-GCCAGGCGCTCTGACCACTC-3' and 5'-AGCCCTTGCAGCCCTCACAG-3'; RARα2, 5'-ACTCCGCTTTGGAATGGCTCAAAC-3' and 5'-AGCCCTTGCAGCCCTCACAG-3'. The cDNA for the house keeping gene glyceraldehyde-3- phosphate dehydrogenase (GAPDH) was amplified and the primer sequences used were as follows: 5'-TGGTCACCAGGGCTGCTTTT-3' and 5'-GGTGAAGACGCCAGTGGACT-3'. The cycling parameters were: 95°C for 15 minutes; 94°C for 30 sec; 60°C for 30 sec; 72°C for 30 sec and 72°C for 10 minutes. RARα1 and RARα2 cDNAs were amplified in the same reaction, yielding products of 222 bp and 182 bp, respectively. PCR products were separated in ethidium bromide-stained 2% agarose gels by electrophoresis. cDNA was also measured by quantitative real time PCR in the 7500 StepOne Plus Real time PCR System (Applied Biosystems). Primers and TaqMan probes for the human ERα, CCNA, CDKN1, ERBB2, ERBB3, MUC20, LYPD1, RARα and GAPDH genes were obtained from the Applied Biosystems inventory. All samples were measured in triplicate and normalized to GAPDH values.
mRNA profiling
The Affymetrix chips were purchased from Affymetrix (Santa Clara, CA, USA) DNA microarray analysis using Affymetrix was performed as a full service global gene expression study at the transcriptional profiling core facility of the Cancer Institute of New Jersey. Total RNA samples were used to generate labeled cRNAs, which were hybridized to human U133 Plus2.0 Affymetrix microarrays. The expression data were analysed initially using Affymetrix GeneChip Operating Software to create CEL files. The CEL files were imported into the Bioconductor program affylmGUI [
32]. The probe set level intensities were quantified and normalized using robust multiarray averaging and quantile normalization. Differential expression between treatments was determined using the limma linear modeling method, and the significance of differences was ranked by the moderated
t-statistic. The values for signal intensities were corrected for siRNA transfection efficiencies determined using a Green Fluorescent Protein (GFP) reporter expression plasmid. To identify genes differentially expressed under the different treatments, the fold-changes were calculated by dividing the average signal of the treatment by the control, and genes with a fold-change greater or lesser than a given threshold were chosen. The advantage of this approach is that rejection of many false negatives is avoided, compared to requiring a statistically significant difference in expression, but has the potential drawback of including false positives. When we limited the genes in Tables
1 and
2 to those showing significant differential expression at the
P = 0.05 level by the linear modeling method, 25/54 genes in Table
1 and 24/68 genes in Table
2 were retained. In the reduced sets of genes, similar percentages of genes showed RARα peaks as in the larger gene set, confirming the generality of our result. The Affymetrix data are deposited in GEO (Accession number: [GEO:GSE26298]).
Table 1
Tamoxifen Insensitive genes supported by the Apo-ER -> Apo-RARα Axis
LGALS1
| ↓ | - | 0.31 | 0.46 | CASC5 | - | - | 0.47 | 0.51 |
METTL7A
| ↓ | - | 0.37 | 0.53 | BIRC5 | - | - | 0.53 | 0.48 |
CDKN3
| ↓ | - | 0.44 | 0.60 | PTTG1 | - | - | 0.57 | 0.54 |
XK
| ↓ | - | 0.46 | 0.54 | PLK4 | - | - | 0.56 | 0.49 |
GHR
| ↓ | - | 0.41 | 0.57 | CENPA | - | - | 0.58 | 0.56 |
YPEL1
| ↓ | - | 0.58 | 0.54 | TMSB15A | - | - | 0.42 | 0.41 |
SHANK2
| ↑ | ++
| 0.58 | 0.57 | C5 | - | - | 0.38 | 0.48 |
ENY2
| - | ++
| 0.54 | 0.45 | CDC2 | - | - | 0.56 | 0.59 |
ONECUT2
| - | ++
| 0.50 | 0.58 | CCNA2 | - | - | 0.59 | 0.52 |
HIST1H4C
| - | ++
| 0.21 | 0.31 | LOC150759 | - | - | 0.49 | 0.59 |
NCAPH
| - | ++
| 0.47 | 0.53 | NCAPG | - | - | 0.50 | 0.51 |
CENPN
| - | ++
| 0.56 | 0.55 | CENPM | - | - | 0.57 | 0.50 |
UBE2T
| - | ++
| 0.53 | 0.60 | FAM64A | - | - | 0.55 | 0.58 |
PHF19
| - | ++
| 0.50 | 0.50 | MND1 | - | - | 0.51 | 0.55 |
ZNF367
| - | ++
| 0.52 | 0.51 | FGFR1 | - | - | 0.56 | 0.53 |
SNORA72
| - | ++
| 0.43 | 0.58 | HELLS | - | - | 0.58 | 0.55 |
KIF23
| - | +
| 0.58 | 0.56 | TNFAIP8L1 | - | - | 0.47 | 0.55 |
ENAH
| - | +
| 0.54 | 0.50 | OVOS2 | - | - | 0.40 | 0.58 |
MAD2L1
| - | +
| 0.40 | 0.55 | ZNF141 | - | - | 0.55 | 0.52 |
SMC4
| - | +
| 0.54 | 0.60 | LOC100129673 | - | - | 0.39 | 0.48 |
SEC31A
| - | +
| 0.55 | 0.57 | ASPM | - | - | 0.45 | 0.45 |
SFPQ
| - | +
| 0.60 | 0.49 | EPHX4 | - | - | 0.51 | 0.55 |
CENPF
| - | +
| 0.51 | 0.58 | HNRPD | - | - | 0.36 | 0.55 |
COBL
| - | - | 0.54 | 0.52 | ARPC5L | - | - | 0.59 | 0.52 |
PBK
| - | - | 0.56 | 0.56 | RGS3 | - | - | 0.57 | 0.45 |
MLF1IP
| - | - | 0.44 | 0.58 | SIPA1L1 | - | - | 0.55 | 0.58 |
SAMHD1
| - | - | 0.60 | 0.53 | | | | | |
Table 2
Tamoxifen Insensitive genes Repressed by the Apo-ER -> Apo-RARα Axis
IFI44L
| ↓ | +
| 1.69 | 2.22 | UBL3
| - | ++
| 1.61 | 1.58 |
IFI44
| ↓ | - | 2.09 | 2.28 | SLC7A11
| - | ++
| 1.71 | 2.03 |
CCPG1
| ↓ | - | 1.67 | 1.56 | KIAA0652
| - | ++
| 1.57 | 1.63 |
SLC25A36
| ↓ | - | 1.66 | 1.73 | PHLDB1
| - | ++
| 1.64 | 1.55 |
SETD5
| ↓ | ++
| 1.52 | 2.11 | CCNT2
| - | - | 1.53 | 1.63 |
MALL
| ↓ | - | 1.67 | 1.81 | STX3
| - | - | 1.52 | 1.59 |
LYPD1
| ↓ | - | 1.66 | 1.59 | CLN8
| - | - | 1.71 | 1.72 |
FAM186A
| ↓ | - | 1.64 | 1.75 | UBXN10
| - | - | 1.73 | 1.64 |
GPR158
| ↓ | - | 1.81 | 1.54 | PVR
| - | - | 1.63 | 2.39 |
CDKN1A
| ↓ | - | 1.70 | 1.51 | TNFRSF10A
| - | - | 1.54 | 1.62 |
CEACAM6
| ↑ | +
| 2.35 | 1.63 | FLJ31958
| - | - | 1.71 | 1.52 |
LGALS3BP
| ↑ | - | 1.98 | 1.92 | C18orf25
| - | - | 1.50 | 1.61 |
CTSS
| ↑ | - | 1.50 | 1.86 | TAPBP
| - | - | 1.62 | 1.51 |
SELL
| ↑ | - | 1.75 | 1.71 | ADAM17
| - | - | 1.58 | 1.63 |
SHROOM1
| ↑ | - | 1.68 | 1.59 | HCP5
| - | - | 1.59 | 2.52 |
CP
| ↑ | ++
| 1.71 | 1.75 | DISC1
| - | - | 1.80 | 1.74 |
ABHD2
| ↑ | ++
| 1.56 | 1.57 | SP100
| - | - | 1.77 | 1.61 |
ABLIM1
| ↑ | ++
| 1.56 | 1.55 | AASS
| - | - | 1.53 | 2.17 |
ALOX5
| ↑ | - | 1.72 | 2.09 | HLA-G
| - | - | 1.50 | 2.33 |
HLA-C
| ↑ | - | 1.51 | 2.51 | HLA-B
| - | - | 1.61 | 2.08 |
MAP1B
| ↑ | - | 2.12 | 1.51 | RSAD2
| - | - | 1.84 | 3.19 |
ARHGAP1
| ↑ | - | 1.58 | 1.55 | SGSM3
| - | - | 1.72 | 1.50 |
SP110
| ↑ | - | 1.58 | 1.63 | HLA-J
| - | - | 1.52 | 2.04 |
RTP4
| ↑ | - | 1.60 | 1.81 | SESN1
| - | - | 1.53 | 1.60 |
MUC20
| ↑ | - | 1.75 | 1.91 | ANO10
| - | - | 1.51 | 1.64 |
RNF38
| - | +
| 1.80 | 1.69 | SAMD9
| - | - | 1.68 | 1.56 |
C9orf80
| - | +
| 1.64 | 1.53 | FLJ13197
| - | - | 1.68 | 1.57 |
CEACAM5
| - | - | 2.35 | 1.70 | PGLS
| - | - | 1.54 | 1.81 |
CNOT4
| - | - | 1.79 | 1.92 | LMO3
| - | - | 1.61 | 1.58 |
PLXNA2
| - | - | 1.65 | 1.86 | DNAJC21
| - | - | 1.68 | 1.61 |
TTC9
| - | - | 1.76 | 1.51 | SETD2
| - | - | 1.52 | 2.11 |
EIF5A2
| - | - | 1.90 | 1.67 | ZNF24
| - | - | 2.10 | 1.68 |
FLCN
| - | ++
| 1.51 | 1.53 | TTLL11
| - | - | 1.72 | 1.51 |
BAZ2A
| - | ++
| 1.53 | 1.58 | ZNF544
| - | - | 1.58 | 1.71 |
Statistical analyses
Experimental values are presented as mean ± standard deviation (s.d.). The statistical significance of differences (P-value) between values being compared was determined using analysis of variance. In all cases, the differences noted in the text are reflected by a P-value of <0.001.
Discussion
ER is known to regulate genes in a ligand-independent manner [
40,
41]. Hormone-independent actions of ER play an important role in supporting the growth of hormone-refractory breast tumors [
12]. On the other hand, studies of gene regulation by ER in estrogen-sensitive breast cancer cells have mostly focused on estrogen-responsive genes that have profound roles in tumor growth and development and the effects of tamoxifen on gene regulation by estrogen [
42]. The findings of this study, however, highlight a potentially significant mechanism of hormone-independent transcriptional action of ER in hormone-sensitive breast cancer cells. This action of ER is clearly a major contributor to the ability of hormone-sensitive breast cancer cells to maintain a basal level of proliferation under conditions of hormone-depletion. This effect of apo-ER occurred primarily through supporting the cell division cycle. Remarkably, the action of apo-ER was also rather insensitive to tamoxifen at a dose that is clinically relevant to circulating concentrations of the drug that induce all of the surrogate biomarkers of clinical response [
43,
44]. Similar to clinical breast tumors, breast cancer cell lines are heterogeneous and can yield clonal populations of inherently tamoxifen resistant cells that are variably ER-dependent [
45]; nevertheless, the fraction of S-phase cells in hormone-depleted or tamoxifen-treated cells under the
in vitro conditions in this study was much higher than the frequency of emergence of aggressively growing colonies in tamoxifen-treated cultures [
45]. Therefore, it is likely that the basal level of S-phase cells observed in hormone-depleted or tamoxifen treated cultures represent a substantial proportion of cells in which the cell cycle progression is slowed. In a tumor environment, however, this slow proliferation must be offset by cell death, resulting in an overall tumoristatic effect. Since a basal level of cell division is an essential pre-condition for progressive events leading to the eventual development of resistance of breast tumors to hormonal adjuvant therapy, understanding the mechanism of the hormone-independent effects of ER in hormone-sensitive cells is important.
In hormone-sensitive breast cancer cells, the well-established ER-RAR axis has been best characterized in the context of ligand effects (estrogen, retinoids, tamoxifen + retinoids) [
20,
46]. The results of this study however establish that in hormone-sensitive cells that are depleted of hormone or treated with tamoxifen, a major mechanism by which ER supports the cell cycle is by supporting the basal expression of RARα1. The role of RARα1 in mediating the action of apo-ER is strongly evident from the following observations: (i) In hormone-depleted cells, apo-ER maintained the basal expression level of RARα1 but was not itself regulated by RARα1; (ii) The regulation of RARα1 by apo-ER was insensitive to tamoxifen; (iii) Knocking down RARα1 negatively impacted the basal cell cycle progression and restoring basal apo-RARα1 levels rescued basal level cell division following depletion of ER; (iv) Apo-RARα1 independently regulated a complement of genes in a manner that strongly favored cell division similar to their regulation by apo-ER. This mechanism was remarkable for the following reasons. First, apo-ER regulated the α1 subtype of RAR but not RARs -β or - γ. Second, most of the common target genes of apo-ER and apo-RARα1 including all of the genes involved in the cell division cycle were insensitive to ATRA. These findings suggest that a major molecular mechanism by which apo-ER supports basal cell division in hormone-sensitive breast cancer cells may not be sensitive to conventional RAR ligands (agonists), but would be predictably opposed by specific inactivators or down-regulators of RARα1.
The cell cycle regulation, which occurs through the apo-ER/apo-RARα1 axis, could theoretically exclude a subpopulation(s) of cells; such a subpopulation(s) could represent tumor cells that are either inherently resistant to hormonal adjuvants or that undergo progressive changes leading to resistance. Whereas the findings in this study do not preclude this possibility, we found no evidence for residual cycling cells following depletion of apo-ER or apo-RARα1 that were characterized by ErbB2 or ErbB3 overexpression, common features associated with a resistant phenotype [
47,
48].
It is well established that the RARα gene is activated by estrogen; however, there is evidence in the literature that ER associates at a basal level with the core promoter of the RARα gene by tethering to DNA bound Sp1 [
49]. Apo-ER may thus directly regulate the RARα gene to maintain the basal expression level of RARα1. The observation that the RARα1 protein level decreased more dramatically than its mRNA upon knocking down ER suggests that apo-ER also regulates RARα1 by additional posttranscriptional mechanisms.
The results of this study further indicate that multiple molecular mechanisms must underlie the downstream action of apo-RARα1 on target genes in the context of mediating the effects of apo-ER. The apo-ER/apo-RARα1 axis regulates genes in both a positive and a negative manner to support cell division; both sets of target genes were enriched for associated chromatin sites of RAR binding, suggesting that RARα1 must act on these target genes by direct as well as indirect mechanisms. RAR belongs to the Class II subfamily of nuclear receptors, which typically, in their ligand-free (apoprotein) form, maintain a transcriptionally repressed state of target genes activated by the corresponding agonists [
38]. However, only a small fraction of genes regulated by the apo-ER-RARα1 axis appeared to be regulated by this classical mechanism of action of RARα1, since (i) the genes repressed by apo-RARα1 were largely insensitive to ATRA and (ii) most genes activated by apo-RARα1 were ATRA-insensitive. Therefore, apo-RARα1 must act by non-classical mechanisms on most of the target genes, including those with associated RAR binding sites.
RARα is consistently present in the nucleus in breast tumors and its expression levels correlate with that of the proliferation marker, ki-67 [
50]. The functional RARα isoform in different hormone-sensitive breast cancer cell lines and that identified in a limited number of breast tumors was almost exclusively of type 1, an isoform that is believed to be genetically redundant [
51]. The findings reported here would predict that agents that selectively target the α1 subtype of RAR for functional inhibition or degradation would significantly enhance hormone ablation therapy in breast cancer since this would further decrease cycling cells. Since the effect of depleting RARα1 occurs through a different gene regulatory program compared with retinoid agonists, and since RARα1 is genetically redundant and could be the major or only RARα subtype in breast cancer cells, this new approach (rather than the use of RAR agonists) to enhancing hormonal adjuvant therapy in breast cancer may be clinically more acceptable. The structural divergence of the two RARα isoforms arising from alternative promoter usage and alternative splicing includes differences in functional sub-domains [
34] which may enable their differential targeting with pharmacological agents. This approach may have fewer side effects than SERDs due to a redundancy of RAR subtypes in other tissues. Studies are underway to test this concept in pre-clinical models of hormone-sensitive breast cancer.
Conclusions
We have observed that in hormone-sensitive breast cancer cells, there is a hormone-independent component through which ER supports proliferation and that apo-RARα1 is a major mediator of this effect. The data also show that the majority of genes regulated by apo-RARα1 do not confirm to the classical model of gene regulation by Class II nuclear receptors since they are not regulated by ATRA. Further, selectively down-regulating RARα1 might significantly enhance hormone ablation therapy in breast cancer since this would further decrease cycling cells. Since the effect of depleting RARα1 occurs through a different gene regulatory program compared with retinoid agonists, and since RARα1 is genetically redundant and appears to be the only RARα subtype in breast tumor cell lines and possibly the major subtype in clinical tumors, this new approach (rather than the use of RAR agonists) to enhancing hormonal adjuvant therapy in breast cancer may be clinically more acceptable. RARα1 is also structurally divergent from RARα2, which is expressed in normal tissues, so that it should be possible to develop selective down-regulators of RARα1.
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Competing interests
The authors declare that they have no competing interests.
Authors' contributions
MDS conducted most of the experiments and contributed to the planning and analysis. MR, MP and IK contributed to the execution of some of the experiments. RT contributed to the bioinformatics analysis. IM contributed with an intellectual clinical perspective to the studies. MR was responsible for the overall direction of the project.