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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Cancer Lett. Author manuscript; available in PMC Dec 26, 2012.
Published in final edited form as:
PMCID: PMC3214732
NIHMSID: NIHMS325067

Differential expression of microRNA expression in tamoxifen-sensitive MCF-7 versus tamoxifen-resistant LY2 human breast cancer cells

Abstract

Microarrays identified miRNAs differentially expressed and 4-hydroxytamoxifen (4-OHT) regulated in MCF-7 endocrine- sensitive versus resistant LY2 human breast cancer cells. 97 miRNAs were differentially expressed in MCF-7 versus LY2 cells. Opposite expression of miRs- 10a, 21, 22, 29a, 93, 125b, 181, 200a, 200b, 200c, 205, and 222 was confirmed. Bioinformatic analyses to impute the biological significance of these miRNAs identified 36 predicted gene targets from those regulated by 4-OHT in MCF-7 cells. Agreement in the direction of anticipated regulation was detected for 12 putative targets. These miRNAs with opposite expression between the two cell lines may be involved in endocrine resistance.

Keywords: microRNA, breast cancer, tamoxifen-resistance, endocrine-resistance, SERMs

1. Introduction

The ability of selective estrogen receptor modulators (SERMs, e.g., tamoxifen and raloxifene) and aromatase inhibitors (AI) to prevent disease recurrence in patients whose initial breast tumors expressed estrogen receptor alpha (ERα) provides compelling data supporting the role of ERα in the pathogenesis of breast cancer [1]. Unfortunately, approximately 40% of patients relapse after tamoxifen (TAM) or other endocrine therapies [2]. The mechanisms for the acquired resistance to endocrine therapies is complex and, even in the presence of continued ERα expression, includes amplification of growth factor signaling pathways, e.g., epidermal growth factor receptor (EGFR), MAPK, PI3K/AKT, JNK, and p38 MAPK [2; 3; 4], but the role of microRNAs in endocrine-resistance remains to be fully elucidated.

MicroRNAs are short, non-coding RNAs that regulate gene expression at the post-transcriptional level by direct binding to the 3′UTR of mRNA targets within the ribonucleoprotein RNA-induced silencing (RISC) complex, causing translational repression usually accompanied by mRNA decay [5; 6]. miRNAs regulate diverse cellular processes including differentiation, replication, migration, and apoptosis [7]. Microarray technology has been used to generate miRNA profiles and demonstrate aberrant miRNA expression in a variety of cancers including breast tumors and cell lines [8; 9; 10; 11; 12; 13]. These miRNA expression profiles correlate with classification of tumor grade and patient prognosis [8; 9; 14]. Altered miRNA expression in cancer may result from chromosomal rearrangements, deletions or epigenetic modifications in DNA or chromatin structure [14]. Bioinformatic analyses are used to identify putative mRNA targets of miRNAs, thus linking miRNAs to the regulation of complex protein networks involved in a variety of cellular functions [15]. miRNAs in breast cancer cells function as tumor suppressors, e.g., Let-7 family members, miR-125a and miR-125b, and miR-200; or as oncogenes, i.e., ‘oncomirs’, e.g., miR-21, miR-10b, miR-155, and the miR-17-92 cluster [13; 16].

miRNAs are processed from longer transcripts called precursor (pre)-miRNAs by Dicer within the cytoplasm. Pre-miRNAs are, in turn, the products of the processing, within the nucleus by DROSHA, of the initial miRNA gene transcripts called primary (pri)-miRNAs [17]. Recent studies have identified miRNAs regulated by estradiol (E2) in breast cancer cells and other cells and tissues (reviewed in [18]). For example, we and others reported that miR-21 and the Let-7 family of miRNAs are downregulated by E2 in breast cancer cells [11; 12; 18; 19]. Interestingly, E2 upregulates transcription of miR-17-92 and its paralog miR-106a-363 clusters in MCF-7 human breast cancer cells, but appears to delay processing of the miR-17-92 gene product into its final miRNAs, including miR-18a and miR-20a [20], although the mechanism remains to be identified.

There are only a few studies of miRNA in TAM/endocrine-resistant breast cancer cells. Cell-based studies found that miRNA-221/222 are overexpressed in TAM-, fulvestrant-, and tumor necrosis factor (TNF)- resistant derivative of MCF-7 cells [21; 22; 23]. However, no one has examined the effect of TAM on the expression of miRNAs in TAM-sensitive versus resistant breast cancer cells.

To investigate whether antiestrogen-resistance correlates with changes in miRNA expression, we profiled miRNA expression in TAM- sensitive MCF-7 and TAM/endocrine-resistant LY2 human breast cancer cells. LY2 cells were derived from MCF-7 by serial passage in the antiestrogen LY 117018, a precursor to Raloxifene (RAL) [24], and express wild-type ERα mRNA levels similar to MCF-7 cells [25], but are resistant to TAM, RAL, and Fulvestrant (ICI 182,780) [26]. We hypothesized that differences in miRNA expression with TAM treatment between the TAM-sensitive MCF-7 versus TAM-resistant LY2 cells would identify miRNAs and their mRNA gene targets contributing to antiestrogen-sensitivity and resistance, respectively. miRNA microarrays were used to identify TAM-regulated miRNAs in these two cell lines. We identified 97 miRNAs that were differentially expressed between the two cell lines and focused on 12 miRNAs that showed the greatest difference in expression between the two cell lines. Quantitative real time polymerase chain reaction (Q-PCR) was used to confirm the results obtained by microarray. In addition to miRNAs differentially regulated in the two cell lines, eight endogenous controls, including 6 miRNAs, 5S rRNA, and SNORD38B, were identified from the microarray data and their expression confirmed by Q-PCR.

A search of the Sloan-Kettering Targets and Expression (http://www.microrna.org/microrna/getDownloads.do) dataset was used to identify 36 putative gene targets of these miRNAs from amongst those that were reported to be regulated by 4-OHT in MCF-7 cells [27]. Q-PCR was used to examine the expression of 8 miRNAs. Q-PCR and Western analyses were used to examine the expression of gene/protein targets of the miRs- 21, 125b, 200a, 200b, 200c, 221 and 222: PDCD4/Pdcd4, BCL2/Bcl-2, CYP1B1, ERBB3/ErbB3, ESR1/ERα, and ZEB-1. Our studies show opposite regulation of select miRNAs and target proteins between the two cell lines, thus indicating a putative role of these miRNAs in TAM/endocrine resistance.

2. Materials and Methods

2.1 Cells and treatments

MCF-7 human breast cancer cells were purchased from ATCC (Manassas, VA, USA) and maintained in IMEM supplemented with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin (Invitrogen, Carlsbad, CA, USA). LY2 tamoxifen/fulvestrant-resistant human breast cancer cells were provided by Dr. Robert Clarke, Georgetown University, and were used at P<16 from this source. LY2 cells were originally derived from MCF-7 cells by selection in increasing concentrations of LY 117018 [24]. LY2, selected for resistance to LY 117018, are cross-resistant to TAM, raloxifene, Fulvestrant (ICI 182,780), and are ERα positive, although ERα protein expression is lower than MCF-7 cells [24; 28]. LCC1, LCC2, LCC9 are also derivatives of MCF-7 cell lines that are E2, tamoxifen, and multiple SERM-independent, respectively [29], and were provided by Dr. Robert Clarke, Georgetown University, and were, like LY2, used at P<16 from this source. MDA-MB-231 ‘triple negative’ breast cancer cells were purchased from ATCC. E2 and 4-OHT were purchased from Sigma (St. Louis, MO, USA). ICI 182,780 was from Tocris (Ellisville, MO, USA). Prior to treatment, the medium was replaced with phenol red-free IMEM supplemented with 5% dextran charcoal-stripped FBS (DCC-FBS) and 1% penicillin/streptomycin (stripped medium) for 48 h (referred to as ‘serum-starving’ or ‘serum starved’ cells). Cells were treated with ethanol (EtOH, the vehicle control, 0.01% final volume), 10 nM E2 or 100 nM 4-OHT for 6 h. For the microarray profiling, 4 separate experiments (biological replicates) were performed at different times over a 6 month period for each cell line. Note: Referrals in the text to ER and not specifically to ERα or ERβ indicated that either ERα or ERβ or both may be involved in the response tested.

2.2 MicroRNA microarray analyses

RNA was isolated from MCF-7 and LY2 cells, treated as above, using the mirVana miRNA Isolation Kit from Ambion (Austin, TX, USA) and sent to Exiqon (http://exiqon.com//) where the RNA samples were labeled with either Hy3 or Hy5 fluorescent labels and hybridized into the miRCURY LNA microarray (miRbase 11.0 human array). This microarray featured 1275 bone fide and putative human miRNAs plus additional controls. Four separate experiments (biological replicates) were performed. Data analysis was performed by Exiqon as follows: clustering of miRNAs was performed using log2 (Hy3/Hy5) ratios which passed the filtering criteria on variation across sample groups using a two tailed T-test p-value < 0.001. The Hy3 signals were normalized using the single color approach ‘Quantile’ followed by a background correction. The data were deposited in GEO as GSE28267 http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28267. The subset of miRNAs showing the highest variation among the 1275 miRNAs were used for clustering which provided a subset of 50 miRNAs that showed maximum variation between the two cell lines. The heat map (Figure 1) shows the result of clustering of miRNAs. The miRNA clustering tree is shown on the left and top. Each column represents a treatment and each row an miRNA.

Figure 1
Heat map (hierarchical clusters) of significant differences in miRNA expression between MCF-7 and LY2 cells

2.3 RNA isolation and quantitative Real-Time-PCR (Q-PCR) for miRNA expression

miRNA-enriched total RNA was extracted from MCF-7 and LY2 cells treated as above using the miRNA isolation kit (Exiqon). The quality and quantity of the isolated RNA was analyzed using a NanoDrop spectrophotometer and Agilent Bioanalyzer. cDNA was synthesized using the miRCURY LNA first strand cDNA synthesis kit (Exiqon) and Q-PCR was performed using the miRCURY LNA SYBR Green master mix (Exiqon) using the miRNA primer sets for miR-10a, -21, -22, -125b, -181a, -200a, -221 and -222 (Exiqon). SNORD38B and 5SRNA were used for normalization of miRNA expression. Analysis and fold change was determined using the comparative threshold cycle (Ct) method. The change in miRNA expression was calculated as fold-change, i.e., relative to EtOH-treated (control).

2.4 RNA Isolation, RT-PCR and Q-PCR for mRNA expression

RNA was extracted from cells using Trizol (Invitrogen) or RNeasy (Qiagen). The High Capacity cDNA Reverse Transcription kit (PE Applied Biosystems) was used to reverse transcribe total RNA using random hexamers. Q-PCR for BCL2, CYP1B1, ERBB3, ESR1, PDCD4, and 18S using Taqman primers and probes as Assays-on-Demand was performed in the ABI PRISM 7900 SDS 2.1 (PE Applied Biosystems) using relative quantification. Analysis and fold differences were determined using the comparative CT method. Fold change was calculated from the ΔΔCT values with the formula 2−ΔΔCT and data are relative to EtOH-treated cells.

2.5 Whole cell and nuclear lysate preparation for western blotting

Whole cell lysates were prepared and western blots were performed as described [28]. Nuclear extracts (NE) were prepared using the NE-PER kit from Thermo Scientific (Rockford, IL, USA). Antibodies were purchased as follows: ERα (Santa Cruz Biotechnology, Santa Cruz, CA, USA), ERβ (H150, Santa Cruz, CA, USA), Argonaute 2 (Anti-Ago2, clone 9E8.2, #04-642, Millipore, Billerica, MA, USA), Pdcd4 (GeneTex,Irvine, CA ), Bcl-2 (Assay Designs, Plymouth Meeting, PA), E-cadherin (Cell Signaling, Danvers, MA, USA),α-tubulin (Thermo Scientific, Rockford, IL, USA), β-actin (Sigma, St. Louis, MO, USA). The ZEB-1 antibody was generously provided by Dr. Douglas Darling, University of Louisville. Chemiluminescent bands on the PVDF membranes were visualized on a Kodak Carestream Imager using Carestream Molecular Imaging software (New Haven, CT, USA).

2.6 Statistical analysis

Data preprocessing was performed on two sets of samples sent to Exiqon at different times (sample set 1 and 2 contained 6 and 14 cell treatments, respectively; different miRNA chips were utilized for the 2 sets of samples) separately before combining them for further analysis. Two-step filtering (1) excluding empty and blank spots and (2) keeping only those spots for which foreground intensities were greater than 1.1 x background intensities for 2 or more samples in the 6-sample group and 10 or more samples in the 14-sample group was done before normalization. For the remaining spots, background intensities were subtracted from the foreground intensities. Since even after the filtering step, some spots had backgrounds larger than foregrounds; we treated those as missing and imputed them using the k-nearest neighbor algorithm. Normalization within-arrays was performed using the loess method [30], while for between-arrays the quantile method was applied. The two sets of samples were then matched by their miRNA names and combined for further analysis.

In order to identify miRNAs which are expressed by MCF-7 and LY2 cells treated with EtOH and 4-OHT and by MCF-7 cells treated with E2, the four technical replicates on each chip and the four arrays (biological replicates) corresponding to each of the five treatment groups (n=20) were averaged. All expression values were represented as log2 ratios of Hy3 (experimental) versus Hy5 (universal reference). Differential expression of miRNAs between different TAM-sensitive and TAM-resistant cell lines treated with either 4-OHT or EtOH were determined by fitting a hierarchical linear model using the limma package [31] and testing the corresponding contrasts of interest, e.g., MCF-7 vs. LY2 treated with 4-OHT, MCF-7 vs. LY2 treated with EtOH, and E2 vs. 4-OHT treated MCF-7 cells, for each miRNA. Fold change, adjusted t-statistic, unadjusted and false discovery rate (FDR) adjusted p-values were calculated for each miRNA for each comparison. Of the 225 miRNAs that passed the filter for analysis, only those miRNAs with adjusted p-values below 0.10, i.e., FDR of 10%, were considered as differentially expressed.

2.7 Gene pathway analysis

Functional and network analyses of differentially expressed miRNAs gene expression changes were performed using Ingenuity Pathways Analysis (IPA) 8.8 (Ingenuity® Systems, http://www.ingenuity.com). Networks were generated using 12 differentially expressed miRNAs (Figure 3) that were uploaded into IPA. Analysis considered all genes from the dataset that met the 2-fold (p-value < 0.05) change cut-off and that were associated with biological functions in the Ingenuity Pathways Knowledge Base. For all IPA analyses, Fisher’s exact test was used to determine the probability that each biological function assigned to the genes within the data set was due to chance alone.

Figure 3
Selected miRNAs are differentially expressed in MCF-7 (TAM-S) and LY2 (TAM-R) breast cancer cells

3. Results and Discussion

3.1 Identification of miRNAs differentially expressed in MCF-7 and LY2 cells

To identify miRNAs that might be involved in TAM- resistance, we compared the miRNA transcription profiles between MCF-7 TAM-sensitive and LY2 TAM-resistant cells in response to 4-OHT using ethanol as the vehicle control. The cells were treated for 6 h, a time point selected as that at which maximal primary ERα-gene target transcription occurs [32]. Since serum levels of 4-OHT in breast cancer patients on oral TAM-citrate are 8-18 nM and breast tumors concentrate 4-OHT to 74 nM – 1.5 μM [33], the 100 nM 4-OHT concentration used in our experiments is at the lower range of that found in women on TAM therapy. In addition, MCF-7 cells were treated with 10 nM E2, as per previous investigations of miRNA transcriptional responses [11; 12; 19; 20; 34]. Four separate experiments were performed for each treatment group and cell line.

A total of 97 miRNAs exhibited differential expression between TAM-sensitive MCF-7 and TAM-resistant LY2 cells with either EtOH or 4-OHT treatment (Figure 1, Tables 1 and and2).2). Forty-seven miRNAs were exclusively differentially expressed between the two cell lines in the presence of EtOH and 21 miRNAs were exclusively differentially expressed between the two cell lines in the presence of 4-OHT. Twenty-nine miRNAs were commonly differentially expressed between the two cell lines both with treatment by EtOH or 4-OHT. A Venn diagram is provided to schematically represent these results (Figure 2, left hand side). We represent the same data by separating up-regulated and down-regulated miRNAs on the right hand side of Figure 2. For example, 53 miRNAs demonstrated enhanced and 23 miRNAs demonstrated reduced expression in MCF-7 cells when compared to LY2 cells treated with the vehicle control EtOH (Table 1). Twenty-nine miRNAs demonstrated increased and 21 miRNAs demonstrated decreased expression in MCF-7 cells when compared to LY2 cells treated with 4-OHT (Table 2). Differentially expressed miRNAs for EtOH-treated MCF-7 versus LY2 are shown in Table 1, 4-OHT-treated MCF-7 versus LY2 are shown in Table 2, and E2 versus 4-OHT-treated MCF-7 are shown in Table 3. Of the total 225 miRNAs analyzed, 128 miRNAs were not differentially expressed between MCF-7 and LY2 in cells treated with EtOH or 4-OHT (data not shown). One miRNA, miR-423-5p demonstrated higher and miR-181a, demonstrated lower expression in MCF-7 cells treated with E2 compared to MCF-7 cells treated with 4-OHT (Table 3).

Figure 2
Venn diagrams summarizing differentially expressed (DE) miRNAs
Table 1
MicroRNAs Differentially Expressed in MCF-7/EtOH vs. LY2/EtOH in human breast cancer cells
Table 2
MicroRNAs Differentially Expressed in MCF-7/4-OHT vs. LY2/4-OHT in human breast cancer cells
Table 3
MicroRNAs Differentially Expressed in MCF-7/E2 vs. MCF-7/4-OHT in human breast cancer cells

From that list of 76 miRNAs showing opposite direction of expression in MCF-7 versus LY2 cells (Figure 2, Tables 1 and and2),2), 12 miRNAs showing opposite direction of expression in MCF-7 versus LY2 cells were selected for further study (Figure 3A and B). The microarray expression data show that miR- 10a, miR-22, miR-29a, miR-125b, miR-181a, and miR-222 were lower in EtOH-treated MCF-7 than in LY2 cells. In contrast, miR-21, miR-93, and miR-200a,b, and c were lower in EtOH-treated LY2 than MCF-7. Of these miRNAs, only miR-21 and miR-181a were E2 regulated, i.e., inhibited by E2, in MCF-7 cells. Of these miRNAs exhibiting opposite expression in MCF-7 and LY2 cells, miR-10a, miR-21, miR-22, miR-125b, miR-181a, miR-200a and miR-222 were selected for Q-PCR validation. In addition, we included miR-221 for analysis because of its reported role in TAM/endocrine resistance [21], although its expression was not significantly different between MCF-7 and LY2 cells in the microarray. A literature review of the relationship between these miRNAs and breast cancer is summarized in Supplementary Table 1.

3.2 Selection of endogenous control genes for Q-PCR normalization and validation of select miRNAs by Q-PCR

Prior to performing Q-PCR to confirm the miRNA microarray data it was necessary to identify endogenous control genes (ECG) for normalization of miRNA transcript expression. First, we compared the expression of U6 (RNU6-1) and U48 (RNU48) RNA genes, traditionally used as controls for miRNA expression [35; 36; 37], in MCF-7 and LY2 cells after 6 h of 4-OHT or EtOH treatment (Figure 4A and 4B). U6 expression was increased by 4-OHT in MCF-7 and reduced by 4-OHT in LY2 cells. U48 expression was comparable between the two cell lines and unaffected by 4-OHT.

Figure 4
Selection of endogenous control genes for analysis of miRNA expression by Q-PCR

Eight additional candidate ECG were identified as showing low variation in expression in the miRNA microarray: high signal: miR-16, Let-7f, and 5SrRNA; medium signal: SNORD38D (U38B), Let-7d, and miR-340; low signal: miR-765, miR-744, miR-887, miR-92b. Eight of these ECG were screened for their expression in MCF-7 and LY2 cells after 6 h or vehicle (EtOH) or 100 nM 4-OHT treatment (Figure 4A and 4B). Two general conclusions can be made from these data: 1) ECG expression differs between the two cell lines; 2) 4-OHT affects ECG expression more in MCF-7 than LY2 cells. Expression of Let-7f was reduced by 4-OHT in both cell lines. miR-744 was reduced by 4-OHT whereas Let-7d and miR-340 were increased by 4-OHT in MCF-7 cells. Overall, the best ECG in MCF-7 and LY2 cells are U48, 5S rRNA, U38B, and miR-765 for high, medium, and low expression miRNAs, respectively. Because of the low expression of miR-765, we selected 5S rRNA, U48, and U38B to normalize miRNA expression in the rest of the studies in this manuscript.

Although Let-7a was reported to be an ECG for miRNA [36], Let-7a expression was increased by E2 and reduced by 4-OHT in MCF-7 cells (Figure 4C). Let-7 family members are highly conserved in sequence and function across species [38]. Misregulation of Let-7 leads to a less differentiated cellular state and the development of cancer; hence, Let-7 family members are considered as tumor-suppressor miRNAs [39; 40]. We observed that 4-OHT repressed the expression of all eight Let-7 family members in MCF-7 cells and none of the Let-7 family members in LY2, commensurate with a less differentiated cellular state. Let-7b, Let-7c, Let-7g, and Let-7i showed opposite expression between MCF-7 and LY2 cells. Since Let-7a [41] and Let-7g [42] downregulate Myc and high Myc expression results in a negative feedback loop inhibiting Let-7a expression [38], we examined Myc mRNA in MCF-7 and LY2 cells (Figure 4D). Based on the higher Let-7 expression in LY2, we expected lower Myc in LY2 and our data confirmed significantly lower Myc expression in LY2 compared with MCF-7 cells (Figure 4D). In agreement with an earlier report [43], E2 increased and 4-OHT inhibited Myc transcription in MCF-7 cells (Figure 4E). Since transient overexpression of Let-7a, Let-7b, and Let-7i was reported to inhibit ERα expression in MCF-7 cells [44], we examined ESR1 mRNA and protein levels in MCF-7 and LY2 cells. As expected, ESR1 mRNA and ERα protein were lower in endocrine-resistant LY2 compared to endocrine-sensitive MCF-7 cells (Figure 4F). The reduced expression of ERα in LY2 also reflects higher expression of miR-221 and miR-222 that have been reported to suppress ERα expression [45; 46; 47].

To validate the changes in miRNA expression detected in the miRNA microarrays, Q-PCR was performed on 7 of the 12 miRNAs in Figure 3: miR-10a, miR-21, miR-22, miR-125b. miR-181a, miR-200a and miR-222 in MCF-7 and LY2 cells treated with EtOH or 100 nM 4-OHT for 6 h, and MCF-7 cells treated with 10 nM E2 for 6 h (Figure 5A). In addition, miR-221 was analyzed because it, along with miR-222, has been reported to be overexpressed and involved in endocrine-resistance in breast cancer cells [21; 34; 48].

Figure 5
Q-PCR analysis of the miRNA expression in MCF-7 and LY2 cells

For comparison between the two cell lines, miRNA expression was normalized to the value in EtOH treated MCF-7 cells. There was general agreement in the direction (up- or down-regulation) of miRNA expression in MCF-7 and LY2 cells between the Q-PCR and microarray data. The exception is that 4-OHT increased miR-200a in MCF-7 cells in Q-PCR. In agreement with other recent results examining E2-regulation of miRNA expression in MCF-7 cells [11; 12; 19; 20], the miRNA expression changes in response to E2 or 4-OHT were less than five-fold. E2 decreased miR-21 expression in MCF-7 cells, as observed in our earlier experiments [19] and as reported by others [12]. 4-OHT increased miR-21 expression in MCF-7 cells. LY2 cells had lower expression of miR-21 and miR-200a, in agreement with the data in the microarray (Figure 3). A recent analysis of miRNA expression in breast tumors by deep sequencing showed upregulation of miR-21 in ER+ breast tumors relative to normal breast tissue and triple negative breast tumors [49].

To determine if the effects of E2 and 4-OHT on miRNA expression were ER-mediated, MCF-7 cells were pretreated with 100 nM ICI 182,780 (ICI, Fulvestrant) for 6 h, a time that reduces ERα protein and activity [50]. For each of the eight miRNAs, ICI increased expression relative to EtOH in MCF-7 cells (Figure 5B). These data suggest that unliganded ER may suppress transcription of these miRNAs or that some component regulating miRNA expression or processing is inhibited by unliganded ER. Alternatively, since ICI is an agonist for GPER/GPR30 [51; 52], it is possible that ICI activates intracellular signaling pathways, e.g., MAPK, that increase miRNA expression. For example, MAPK increases miRNA expression by phosphorylating TRBP, a component of the Dicer complex that processes pre-miRNA into mature miRNA [53]. Testing GPER/GPR30 is beyond the scope of the current study. ICI ablated the inhibition of miR-10a, miR-21, miR-22, miR-200a, miR-221, and miR-222 by E2 in MCF-7 cells. These data indicate that E2-occupied ER suppresses the transcription of these miRNAs. The combination of ICI and 4-OHT did not further increase miRNA expression in MCF-7 cells with the exception of miR-10a, a result seen in both MCF-7 and LY2. While the mechanism involved for the increase in miR-10a appears to be, at least in part, ER-mediated, future studies are needed to address this mechanism in greater detail. There is only one report about miR-10a regulation [54]. That report found that miR-10a expression increased as mouse embryonic stem cells differentiated into smooth muscle cells [54]. Others reported that miR-10a associates with the 5′ UTR of mRNAs encoding ribosomal proteins, enhances their translation, increases global protein synthesis, and thus contribute to oncogenesis [55]. For miR-21, miR-125b, and miR-181a, 4-OHT inhibited the stimulation over basal expression detected with ICI treatment in MCF-7 cells.

For LY2 cells, ICI had no significant effect on basal miRNA expression (Figure 5C). These data indicate that, unlike MCF-7 cells, the regulation of miRNA expression in LY2 cells is independent of ER. These data are in agreement with the estrogen-independent, endocrine-resistant phenotype of LY2 cells [24; 56]. As discussed above, ICI and 4-OHT synergistically increased miR-10a transcription. ICI reduced 4-OHT-stimulated miR-125b and miR-222 expression (Figure 5C), a result implicating ER involvement in 4-OHT-regulating the expression of these miRNAs, a result commensurate with higher miR-125b in ERα/PR-positive than ERα/PR-negative breast tumors [57]. The apparent synergy of ICI and 4-OHT in upregulating miR-10a transcription may be mediated by GPR30/GPER, for which both ICI and 4-OHT are agonists [58]. However, others have reported that an ERα variant called ERα36, and not GPR30, mediates non-genomic ER signaling, including ICI agonist activity [59]. ERα36 arises from a promoter in the first exon of ERα, but lacks both the N- and C terminal transcription activation domains, AF-1 and AF-2, respectively, of full-length wild type ERα66 [60; 61]. Further studies would be required to examine ERα36 expression in LY2 cells. However, ERα36 was not detected using an antibody that recognizes epitopes conserved in ERα66 and ERα36 [61; 62] (Supplementary Fig 1).

3.3 Time course of miRNA expression in MCF-7 cells

Time-dependent changes in the expression of 8 miRNAs were detected after 1, 4, 6, and 8 h treatment with EtOH, E2, or 4-OHT (Figure 6). E2 repressed the expression of miR-22, miR-125b, miR-181a, miR-200a (except at the 6 h time point), and miR-221 (except at the 6 h time point) relative to EtOH. 4-OHT increased expression of miR-21a, miR-22, miR-181a, and miR-200a relative to EtOH at the 6 h time point. 4-OHT inhibited miR-221 expression, although the difference was not statistically significant at the 6 h time point. To our knowledge, there are only two reports examining the effect of E2 on miRNA at various times (0, 1, 3, 4, 6, and 12 h) of treatment in MCF-7 cells [11; 20]. The time-course of miR-21 expression does not agree with a previous report showing E2 increased miR-21 over time [11]. This difference is likely the result of differences in the MCF-7 cells used since Bhat-Nakshatri et al. used MCF-7 cells stably transformed with a bicistronic vector control [11] whereas we used MCF-7 cells at passages less than 9 from ATCC.

Figure 6
Time course analysis of miRNA expression

3.4 Time course of E2 and 4-OHT regulation of ERα, ERβ, and Argonaute-2 (Ago2)

To determine if changes in miRNA expression with time reflect changes in ERα, ERβ, or Ago 2 expression, MCF-7 cells were treated with EtOH, E2, or 4-OHT for 1, 4, 6, or 8 h prior to western blot for ERα, ERβ, and Ago2 protein expression (Figure 7A). These data show that ERα was increased after 4 h of treatment with EtOH and remained increased through the 8 h time course in MCF-7 cells. Consistent with previous investigations [63], E2 reduced ERα and 4-OHT stablized ERα in MCF-7 cells. ERβ was increased with EtOH, E2, and 4-OHT treatment for 1 h, but at 4 h, E2 and 4-OHT reudced ERβ. At 6 h, only 4-OHT reduced ERβ. At 8 h, ERβ was increased and this increase was inhibited by E2 and 4-OHT. Ago2 was unaffected by EtOH until 8 h when there was an increase in Ago2. Ago2 was decreased by E2 and 4-OHT with time and the increase in Ago2 with EtOH at 8 h was further increased by 4-OHT. This is the first examination of the effect of E2 or 4-OHT on Ago2 expression. The changes in miR-21 expression with time and treatment correspond to the expression of ERα protein and at some time points/treatments appear to inversely correspond to ERβ protein expression (Figure 7B). These data confirm the role of ERα and ligand in regulating miR-21 expression.

Figure 7
Time-dependent changes in ERα, ERβ, and Ago2 expression in E2- or 4-OHT-treated MCF-7 cells

3.5 Computational identification of miRNA target mRNA genes in 4-OHT-treated MCF-7 cells

mRNA targets of the 12 miRNAs that were differentially expressed between MCF-7 and LY2 cells (Figure 2) were identified in silico using target identification software:, Target Scan 5.1 (http://www.targetscan.org/), PicTar (http://pictar.mdc-berlin.de/), miRanda (http://www.microrna.org/microrna/getGeneForm.do), and miR Base Release 15 (http://www.mirbase.org/). This data was integrated with mRNA targets regulated by 4-OHT after 4, 8, 24 and 48 h treatment of MCF-7 cells [27]. The gene symbols were transcribed from [27] and were searched against the miRanda predicted Human Target Site Predictions data contained in the file named human_predictions_aug2008.txt, downloaded from http://www.microrna.org/microrna/home.do. It was necessary to update several of the HUGO gene symbols presented in [27] in order to be consistent with the current HUGO identifiers for these transcripts in the human predictions dataset. Examples include updating C1 orf 24 to FAM129A, and RENT1 to UPF1. All genes listed in [27] were found the predicted target of at least one miRNA in the human_predictions_aug2008.txt dataset with the exception of SNCG, SLC16A5, RAP140, LOC441453, ELF3, LSS, CLIC3, EHD4,SERPINA1, EGFL5, SRD5A1, and KRT13. This analysis identified 36 genes that were regulated by 4-OHT in MCF-7 cells and which are putative targets of the 12 miRNAs identified in miRNA microarray analyses (Figure 8, Supplementary Table 2). Supplementary Table 2 also lists the putative miRNA target mRNA genes, their mRNA expression in 4-OHT treated cells at 8 and 48 h from [64], and whether these data agree with the data on miRNA expression in response to 4-OHT (Figure 5). In general, the predicated gene targets agree with the direction of miRNA expression in 4-OHT treated MCF-7 cells. In order to identify gene networks involving 12 miRNAs that were differentially expressed in LY2 and MCF-7 cells (Figure 3), Ingenuity Pathway Analysis (IPA) was performed. Networks created by IPA are groups of proteins that interact directly or indirectly with genes or proteins in a dataset. As expected, IPA identified cancer as the top category followed by reproductive system disease and cellular development as significantly associated with the miRNAs in the data set (Supplementary Figure 3). Core analysis using IPA generated 2 networks containing the 12 differentially expressed miRNAs and key proteins involved in breast cancer (Supplementary Figure 4A and 4B). Network 1 and 2 shows 35 and 9 molecules respectively (Supplementary Figures 4A and 4B). The identity and cellular location of these molecules are provided in Supplementary Table 3. Functional analysis with IPA tools identified 14 molecules in network 1 and 5 in network 2 as having roles in breast cancer (indicated by red lines in Supplementary Figure 4A and 4B). Network 1 identified Myc as a central node, although none of the miRNAs directly connect to Myc. miR-10a mapped to a number of gene targets in Network 1 while miR-200b mapped to only one target, VIM. However, recent studies show that downregulation of the miR-200bc/429 cluster is associated with breast tumor progression through upregulation of phospholipase C gamma 1 (PLCG1) which, in turn, regulates cell mobility, proliferation, and viability [65]. APC, MYC, CYRB, CASP3, CSF1, UNCX, NPTX1, miR-10a, miR-22, miR-29a, miR-93, miR-200a, miR-205 and miR-222 are the genes associated with breast cancer in this network. Network 2 centers on estrogen receptor in breast cancer and supports our observation that the expression of miR-21 in MCF-7 cells is regulated by ER (Figure 4B).

Figure 8
Computational identification of mRNA gene targets of 12 miRNAs oppositely expressed in MCF-7 and LY2 cells

3.6 PDCD4, BCL2, CYP1B1, and ERBB3 are differentially expressed in MCF-7 and LY2 cells

Among the 36 putative gene targets in Supplemental Table 2, we focused first on the PDCD4 tumor suppressor because we had previously identified PDCD4 tumor suppressor as a bone fide mRNA target downregulated by miR-21 in MCF-7 cells [19]. Since miR-21 expression was significantly lower in LY2 than MCF-7 cells, we anticipated that PDCD4 mRNA and protein expression would be higher in LY2 than in MCF-7 cells. However, PDCD4 mRNA was undetectable in EtOH-treated LY2 cells. With 4-OHT treatment, PDCD4 mRNA was detected at low levels in LY2 cells (Figure 9A). Neither E2 nor 4-OHT affected GADPH expression and GADPH CT values were similar in MCF-7 and LY2 cells, indicating that the quality of the RNA was not an issue in the lack of PDCD4 expression in control (EtOH)-treated LY2 cells (Supplemental Fig 2). 4-OHT reduced PDCD4 mRNA in MCF-7 cells (Figure 8A and 8B), consistent with the increase in miR-21 induced by 4-OHT. As reported previously, E2 increased PDCD4 mRNA (Figure 9A and 9B). We did not detect Pdcd4 protein expression in LY2, although Pdcd4 was expressed in MCF-7 (Figure 8C).

Figure 9
miR-21 target genes expression in MCF-7 and LY2 cells

The anti-apoptotic, pro-survival BCL2 is also a target of miR-21 [19]. Again, since miR-21 expression was lower in LY2, we expected higher BCL2 expression in LY2 than MCF-7 cells. However, we did not detect BCL2 mRNA in LY2 cells, whether EtOH or 4-OHT treated (data not shown). As expected based on our previous data and the work of others [19; 66], E2 increased BCL2 mRNA in MCF-7 cells. 4-OHT had no significant effect on BCL2 mRNA expression in MCF-7 cells. We did not detect Bcl-2 protein expression in LY2, although Bcl-2 was expressed in MCF-7 cells (Figure 9C). Others reported that 1 μM 4-OHT suppressed Bcl-2 expression in MCF-7 cells after 7 d of treatment [67].

CYP1B1 is a cytochrome P450 enzyme implicated in the metabolism of exogenous and endogenous substrates, including E2, and CYP1B1 polymorphisms are associated with breast cancer risk [68]. CYP1B1 was stimulated by 8 h treatment with 1 μM 4-OHT in MCF-7 cells [64] and is a putative target of regulation by miR-200 family members that are reduced in LY2 compared to MCF-7 cells. Because 4-OHT increased miR-200a expression, we examined CYP1B1 expression after 6 h treatment with 4-OHT or EtOH in MCF-7 and LY2 cells. CYP1B1 mRNA expression was very low (CT ~ 39) in LY2 cells and 4-OHT did not affect CYP1B1 expression (Figure 10A). These results are in contrast to a previous report showing 2–6-fold higher CYP1B1 in TAM- and fulvestrant- resistant cell lines derived from of MCF-7 cells [69]. The reason for this difference in CYP1B1 expression may be cell line- or cell culture- condition mediated. As another possible difference, we noticed that the endocrine resistant cell lines used in the previous report were supplemented with insulin [69], whereas we do not supplement our cell culture media with insulin. Although studies in diabetic rats indicate that insulin represses hepatic CYP1B1 [70], the regulation of CYP1B1 by insulin in breast cancer cells has not, to our knowledge, been examined. CYP1B1 mRNA expression was higher in MCF-7 than LY2 cells, but was not significantly regulated by E2 or 4-OHT with 6 h treatment in MCF-7 cells. These data reflect previous findings regarding detection of CYP1B1 expression in MCF-7 cells [71]. We did not detect an increase in CYP1B1 with 6 h of treatment, as reported for 12 h of E2 treatment in MCF- 7 cells [72]. The reduction of miR-200b and miR-200c detected with 4-OHT treatment in MCF-7 cells in microarray (Figure 3) would be expected to increase targets of these miRNAs, including CYP1B1. Indeed, CYP1B1 mRNA was increased in the microarray study with 8 h of 1 μM 4-OHT treatment (Supplementary Table 2) [64]; but after 6 h of treatment, no reduction in CYP1B1 was detected.

Figure 10
CYP1B1, ERBB3, and ESR1 gene expression in MCF-7 and LY2 cells

ERBB3 is an oncogene that is a member of the epidermal growth factor receptor (EGFR) family of transmembrane tyrosine kinases that is bound by heregulin and is involved in the pathogenesis and progression of breast cancer [73]. ERBB3 is frequently over-expressed in breast cancer and increased in TAM resistance [73; 74]. ERBB3 is a putative target of miR-22, miR-125b, miR-221, miR-222, miR-93 according to our bioinformatic analyses and is a bone fide target of miR-125b [75]. Increased expression of these miRNAs in LY2 cells would be expected to reduce the expression of ERBB3 in LY2 cells. In agreement with this idea, we did not detect ERBB3 mRNA in LY2 cells, even when treated with 4-OHT (Figure 10B and data not shown). We did not detect regulation of ERBB3 mRNA by E2 or 4-OHT with 6 h treatment in MCF-7 cells. Others reported that ERBB3 mRNA was inhibited by 48 h treatment of MCF-7 cells with 1 nM E2 and this inhibition blocked by 1 μM TAM in MCF-7 cells [76]. The difference in time of treatment is likely responsible for differences in ERBB3 regulation.

3.7 ESR1 and ERα protein expression is lower in LY2 than MCF-7 cells

MiR-221 and miR-222 expression was higher in LY2 compared to MCF-7 cells. miR-221 and miR-222 are overexpressed in ERα-negative and TAM-resistant breast cancer cell lines [21; 47]. Knockdown of miR-221 and miR-222 in MDA-MB-468 breast cancer cells partially restored ERα expression and TAM-sensitivity [47]. ESR1 mRNA expression is lower in LY2 than MCF-7 cells (Figure 10C). Western confirmed lower ERα protein expression in LY2 cells when compared to MCF-7 cells (Figure 4F). These data agree with reports that miR-221/222 is overexpressed in TAM-resistant breast cancer cell lines and suppresses ERα expression.

3.8 miR-200-regulated ZEB1 is reduced in LY2 cells

miR-200 family members suppress expression of the transcription factor ZEB1 that initiates epithelial to mesenchymal transition (EMT) by repressing transcription of E-cadherin and other genes regulating cell polarity [77; 78; 79; 80; 81; 82; 83]. Because all three miR-200 family members were expressed at significantly lower levels in LY2 than MCF-7 cells, we examined ZEB1 as a miR-200 target in MCF-7, LCC1, LCC2, LCC9, LY2, and MDA-MB-231 breast cancer cells by western blot (Figure 11A). LCC1 are estrogen-independent derivatives of MCF-7 cells and LCC2 and LCC9 are also endocrine-resistant derivatives of MCF-7 cells ( do we have to mention this again.it is already explained in M&M) [29]. MDA-MB-231 serve as a positive control since ZEB1 expression is higher in MDA-MB-231, but not in MCF-7 [84]. As expected, ZEB1 was not expressed in MCF-7, but was expressed in MDA-MB-231 (Figure 11A). LY2 cells express ZEB1, indicating that this cell line has undergone EMT. However, LCC1, LCC2, and LCC9 cells do not express ZEB1, indicating that these estrogen-independent (LCC1) and tamoxifen/endocrine-resistant (LCC2 and LCC9) cell lines have not undergone EMT. Because E-cadherin is inversely correlated with ZEB1 expression and inversely correlated with miR-200c [79], we examined E-cadherin in MCF-7, LY2, and MDA-MB-231 cells (Figure 11B). E-cadherin was not expressed in LY2 or MDA-MB-231 cells, indicating that LY2 cells have undergone EMT. This is, to our knowledge, the first demonstration of EMT in the LY2 endocrine-resistant breast cancer cell line.

Figure 11
ZEB1 and E-cadherin expression

Supplementary Material

Acknowledgments

This work was supported by NIH R21 CA124811 and NIH R01 CA138410 to CMK and in part by P30ES01443 for Bioinformatic analysis by TSK. We thank Dr. Nalinie S. Wickramasinghe for performing the cell treatments and isolating the RNA sent to Exiqon. We thank Dr. Barbara J. Clark for her review of our manuscript.

Footnotes

Conflict of interest

The authors declare that they have no conflict of interest.

References

1. Peng J, Sengupta S, Jordan VC. Potential of selective estrogen receptor modulators as treatments and preventives of breast cancer. Anticancer Agents Med Chem. 2009;9:481–499. [PMC free article] [PubMed]
2. Ring A, Dowsett M. Mechanisms of tamoxifen resistance. Endocr Relat Cancer. 2004;11:643–658. [PubMed]
3. Arpino G, Wiechmann L, Osborne CK, Schiff R. Crosstalk between the Estrogen Receptor and the HER Tyrosine Kinase Receptor Family: Molecular Mechanism and Clinical Implications for Endocrine Therapy Resistance. Endocr Rev. 2008;29:217–233. [PMC free article] [PubMed]
4. Clarke R, Liu MC, Bouker KB, Gu Z, Lee RY, Zhu Y, Skaar TC, Gomez B, O’Brien K, Wang Y, Hilakivi-Clarke LA. Antiestrogen resistance in breast cancer and the role of estrogen receptor signaling. Oncogene. 2003;22:7316–7339. [PubMed]
5. Friedman RC, Farh KK, Burge CB, Bartel DP. Most mammalian mRNAs are conserved targets of microRNAs. Genome Res. 2009;19:92–105. [PMC free article] [PubMed]
6. Djuranovic S, Nahvi A, Green R. A parsimonious model for gene regulation by miRNAs. Science. 2011;331:550–553. [PMC free article] [PubMed]
7. Nelson KM, Weiss GJ. MicroRNAs and cancer: past, present, and potential future. Mol Cancer Ther. 2008;7:3655–3660. [PubMed]
8. Iorio MV, Ferracin M, Liu CG, Veronese A, Spizzo R, Sabbioni S, Magri E, Pedriali M, Fabbri M, Campiglio M, Menard S, Palazzo JP, Rosenberg A, Musiani P, Volinia S, Nenci I, Calin GA, Querzoli P, Negrini M, Croce CM. MicroRNA Gene Expression Deregulation in Human Breast Cancer. Cancer Res. 2005;65:7065–7070. [PubMed]
9. Volinia S, Calin GA, Liu CG, Ambs S, Cimmino A, Petrocca F, Visone R, Iorio M, Roldo C, Ferracin M, Prueitt RL, Yanaihara N, Lanza G, Scarpa A, Vecchione A, Negrini M, Harris CC, Croce CM. A microRNA expression signature of human solid tumors defines cancer gene targets. Proceedings of the National Academy of Sciences. 2006;103:2257–2261. [PMC free article] [PubMed]
10. Yang N, Kaur S, Volinia S, Greshock J, Lassus H, Hasegawa K, Liang S, Leminen A, Deng S, Smith L, Johnstone CN, Chen XM, Liu CG, Huang Q, Katsaros D, Calin GA, Weber BL, Butzow R, Croce CM, Coukos G, Zhang L. MicroRNA Microarray Identifies Let-7i as a Novel Biomarker and Therapeutic Target in Human Epithelial Ovarian Cancer. Cancer Res. 2008;68:10307–10314. [PMC free article] [PubMed]
11. Bhat-Nakshatri P, Wang G, Collins NR, Thomson MJ, Geistlinger TR, Carroll JS, Brown M, Hammond S, Srour EF, Liu Y, Nakshatri H. Estradiol-regulated microRNAs control estradiol response in breast cancer cells. Nucl Acids Res. 2009;37:4850–4861. [PMC free article] [PubMed]
12. Maillot G, Lacroix-Triki M, Pierredon S, Gratadou L, Schmidt S, Benes V, Roche H, Dalenc F, Auboeuf D, Millevoi S, Vagner S. Widespread Estrogen-Dependent Repression of microRNAs Involved in Breast Tumor Cell Growth. Cancer Res. 2009;69:8332–8340. [PubMed]
13. O’Day E, Lal A. MicroRNAs and their target gene networks in breast cancer. Breast Cancer Res. 2010;12:201. [PMC free article] [PubMed]
14. Calin GA, Ferracin M, Cimmino A, Di Leva G, Shimizu M, Wojcik SE, Iorio MV, Visone R, Sever NI, Fabbri M, Iuliano R, Palumbo T, Pichiorri F, Roldo C, Garzon R, Sevignani C, Rassenti L, Alder H, Volinia S, Liu C-g, Kipps TJ, Negrini M, Croce CM. A MicroRNA Signature Associated with Prognosis and Progression in Chronic Lymphocytic Leukemia. N Engl J Med. 2005;353:1793–1801. [PubMed]
15. Drakaki A, Iliopoulos D. MicroRNA Gene Networks in Oncogenesis. Curr Genomics. 2009;10:35–41. [PMC free article] [PubMed]
16. Mocellin S, Pasquali S, Pilati P. Oncomirs: From Tumor Biology to Molecularly Targeted Anticancer Strategies. Mini Reviews in Medicinal Chemistry. 2009;9:70–80. [PubMed]
17. Verghese ET, Hanby AM, Speirs V, Hughes TA. Small is beautiful: microRNAs and breast cancer-where are we now? J Pathol. 2008;215:214–221. [PubMed]
18. Klinge CM. Estrogen Regulation of MicroRNA Expression. Current Genomics. 2009;10:169–183. [PMC free article] [PubMed]
19. Wickramasinghe N, Manavalan T, Dougherty S, Riggs K, Li Y, Klinge C. Estradiol downregulates miR-21 expression and increases miR-21 target gene expression in MCF-7 breast cancer cells. Nucleic Acids Res. 2009;37:2584–2595. [PMC free article] [PubMed]
20. Castellano L, Giamas G, Jacob J, Coombes RC, Lucchesi W, Thiruchelvam P, Barton G, Jiao LR, Wait R, Waxman J, Hannon GJ, Stebbing J. The estrogen receptor-alpha induced microRNA signature regulates itself and its transcriptional response. Proceedings of the National Academy of Sciences. 2009;106:15732–15737. [PMC free article] [PubMed]
21. Miller TE, Ghoshal K, Ramaswamy B, Roy S, Datta J, Shapiro CL, Jacob S, Majumder S. MicroRNA-221/222 confers tamoxifen resistance in breast cancer by targeting p27(Kip1) J Biol Chem. 2008;283:29897–29903. [PMC free article] [PubMed]
22. Rao X, Di Leva G, Li M, Fang F, Devlin C, Hartman-Frey C, Burow ME, Ivan M, Croce CM, Nephew KP. MicroRNA-221/222 confers breast cancer fulvestrant resistance by regulating multiple signaling pathways. Oncogene. 2011 in press. [PMC free article] [PubMed]
23. Xin F, Li M, Balch C, Thomson M, Fan M, Liu Y, Hammond SM, Kim S, Nephew KP. Computational analysis of microRNA profiles and their target genes suggests significant involvement in breast cancer antiestrogen resistance. Bioinformatics. 2009;25:430–434. [PMC free article] [PubMed]
24. Bronzert DA, Greene GL, Lippman ME. Selection and characterization of a breast cancer cell line resistant to the antiestrogen LY 117018. Endocrinology. 1985;117:1409–1417. [PubMed]
25. Mullick A, Chambon P. Characterization of the estrogen receptor in two antiestrogen-resistant cell lines, LY2 and T47D. Cancer Res. 1990;50:333–338. [PubMed]
26. Crawford AC, Riggins RB, Shajahan AN, Zwart A, Clarke R. Co-Inhibition of BCL-W and BCL2 Restores Antiestrogen Sensitivity through BECN1 and Promotes an Autophagy-Associated Necrosis. PLoS ONE. 2010;5:e8604. [PMC free article] [PubMed]
27. Frasor J, Chang EC, Komm B, Lin CY, Vega VB, Liu ET, Miller LD, Smeds J, Bergh J, Katzenellenbogen BS. Gene Expression Preferentially Regulated by Tamoxifen in Breast Cancer Cells and Correlations with Clinical Outcome. Cancer Res. 2006;66:7334–7340. [PubMed]
28. Riggs KA, Wickramasinghe NS, Cochrum RK, Watts MB, Klinge CM. Decreased Chicken Ovalbumin Upstream Promoter Transcription Factor II Expression in Tamoxifen-Resistant Breast Cancer Cells. Cancer Res. 2006;66:10188–10198. [PubMed]
29. Brunner N, Boysen B, Jirus S, Skaar TC, Holst-Hansen C, Lippman J, Frandsen T, Spang-Thomsen M, Fuqua SA, Clarke R. MCF7/LCC9: an antiestrogen-resistant MCF-7 variant in which acquired resistance to the steroidal antiestrogen ICI 182,780 confers an early cross-resistance to the nonsteroidal antiestrogen tamoxifen. Cancer Res. 1997;57:3486–3493. [PubMed]
30. Smyth GK, Speed TP. Normalization of cDNA microarray data. Methods. 2003;31:265–273. [PubMed]
31. Smyth GK. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol. 2004;3:Article3. [PubMed]
32. Shang Y, Hu X, DiRenzo J, Lazar MA, Brown M. Cofactor dynamics and sufficiency in estrogen receptor-regulated transcription. Cell. 2000;103:843–852. [PubMed]
33. Kisanga ER, Gjerde J, Guerrieri-Gonzaga A, Pigatto F, Pesci-Feltri A, Robertson C, Serrano D, Pelosi G, Decensi A, Lien EA. Tamoxifen and Metabolite Concentrations in Serum and Breast Cancer Tissue during Three Dose Regimens in a Randomized Preoperative Trial. Clin Cancer Res. 2004;10:2336–2343. [PubMed]
34. Rao X, Di Leva G, Li M, Fang F, Devlin C, Hartman-Frey C, Burow ME, Ivan M, Croce CM, Nephew KP. MicroRNA-221/222 confers breast cancer fulvestrant resistance by regulating multiple signaling pathways. Oncogene. 2010 [PMC free article] [PubMed]
35. Jiang J, Lee EJ, Gusev Y, Schmittgen TD. Real-time expression profiling of microRNA precursors in human cancer cell lines. Nucl Acids Res. 2005;33:5394–5403. [PMC free article] [PubMed]
36. Davoren PA, McNeill RE, Lowery AJ, Kerin MJ, Miller N. Identification of suitable endogenous control genes for microRNA gene expression analysis in human breast cancer. BMC Mol Biol. 2008;9:76. [PMC free article] [PubMed]
37. Peltier HJ, Latham GJ. Normalization of microRNA expression levels in quantitative RT-PCR assays: identification of suitable reference RNA targets in normal and cancerous human solid tissues. RNA. 2008;14:844–852. [PMC free article] [PubMed]
38. Roush S, Slack FJ. The let-7 family of microRNAs. Trends in Cell Biology. 2008;18:505–516. [PubMed]
39. Boyerinas B, Park SM, Hau A, Murmann AE, Peter ME. The role of let-7 in cell differentiation and cancer. Endocr Relat Cancer. 2010;17:F19–36. [PubMed]
40. Bader AG, Brown D, Winkler M. The Promise of MicroRNA Replacement Therapy. Cancer Research. 2010;70:7027–7030. [PMC free article] [PubMed]
41. Sampson VB, Rong NH, Han J, Yang Q, Aris V, Soteropoulos P, Petrelli NJ, Dunn SP, Krueger LJ. MicroRNA Let-7a Down-regulates MYC and Reverts MYC-Induced Growth in Burkitt Lymphoma Cells. Cancer Res. 2007;67:9762–9770. [PubMed]
42. Lan FF, Wang H, Chen YC, Chan CY, Ng SS, Li K, Xie D, He ML, Lin MC, Kung HF. Hsa-let-7g inhibits proliferation of hepatocellular carcinoma cells by downregulation of c-Myc and upregulation of p16INK4A. International Journal of Cancer. 2010;128:319–331. [PubMed]
43. Dubik D, Dembinski TC, Shiu RPC. Stimulation of c-myc oncogene expression associated with estrogen-induced proliferation of human breast cancer cells. Cancer Res. 1987;47:6517–6521. [PubMed]
44. Zhao Y, Deng C, Wang J, Xiao J, Gatalica Z, Recker RR, Xiao GG. Let-7 family miRNAs regulate estrogen receptor alpha signaling in estrogen receptor positive breast cancer. Breast Cancer Res Treat. 2011 in press. [PubMed]
45. Chen JQ, Russo J. ER[alpha]-negative and triple negative breast cancer: Molecular features and potential therapeutic approaches. Biochimica et Biophysica Acta (BBA) -Reviews on Cancer. 2009;1796:162–175. [PMC free article] [PubMed]
46. Di Leva G, Gasparini P, Piovan C, Ngankeu A, Garofalo M, Taccioli C, Iorio MV, Li M, Volinia S, Alder H, Nakamura T, Nuovo G, Liu Y, Nephew KP, Croce CM. MicroRNA Cluster 221–222 and Estrogen Receptor {alpha} Interactions in Breast Cancer. J Natl Cancer Inst. 2010;102:706–721. [PMC free article] [PubMed]
47. Zhao JJ, Lin J, Yang H, Kong W, He L, Ma X, Coppola D, Cheng JQ. MicroRNA-221/222 negatively regulates ERalpha and associates with tamoxifen resistance in breast cancer. J Biol Chem. 2008;283:31079–31086. [PMC free article] [PubMed]
48. Wu H, Zhu S, Mo YY. Suppression of cell growth and invasion by miR-205 in breast cancer. Cell Res. 2009;19:439–448. [PMC free article] [PubMed]
49. Farazi TA, Horlings HM, ten Hoeve JJ, Mihailovic A, Halfwerk H, Morozov P, Brown M, Hafner M, Reyal F, van Kouwenhove M, Kreike B, Sie D, Hovestadt V, Wessels LFA, van de Vijver MJ, Tuschl T. Sequence and Expression Analysis in Breast Tumors by Deep Sequencing MicroRNA. Cancer Research. 2011;71:4443–4453. [PMC free article] [PubMed]
50. Wijayaratne AL, Nagel SC, Paige LA, Christensen DJ, Norris JD, Fowlkes DM, McDonnell DP. Comparative analyses of mechanistic differences among antiestrogens. Endocrinology. 1999;140:5828–5840. [PubMed]
51. Filardo EJ, Quinn JA, Bland KI, Frackelton AR., Jr Estrogen-induced activation of Erk-1 and Erk-2 requires the G protein-coupled receptor homolog, GPR30, and occurs via trans-activation of the epidermal growth factor receptor through release of HB-EGF. Mol Endocrinol. 2000;14:1649–1660. [PubMed]
52. Prossnitz ER, Maggiolini M. Mechanisms of estrogen signaling and gene expression via GPR30. Molecular and Cellular Endocrinology. 2009;308:32–38. [PMC free article] [PubMed]
53. Paroo Z, Ye X, Chen S, Liu Q. Phosphorylation of the Human MicroRNA-Generating Complex Mediates MAPK/Erk Signaling. Cell. 2009;139:112–122. [PMC free article] [PubMed]
54. Huang H, Xie C, Sun X, Ritchie RP, Zhang J, Chen YE. miR-10a Contributes to Retinoid Acid-induced Smooth Muscle Cell Differentiation. Journal of Biological Chemistry. 2010;285:9383–9389. [PMC free article] [PubMed]
55. Ørom UA, Nielsen FC, Lund AH. MicroRNA-10a Binds the 5′UTR of Ribosomal Protein mRNAs and Enhances Their Translation. Molecular Cell. 2008;30:460–471. [PubMed]
56. Davidson NE, Bronzert DA, Chambon P, Gelmann EP, Lippman ME. Use of two MCF-7 cell variants to evaluate the growth regulatory potential of estrogen-induced products. Cancer Res. 1986;46:1904–1908. [PubMed]
57. Mattie MD, Benz CC, Bowers J, Sensinger K, Wong L, Scott GK, Fedele V, Ginzinger D, Getts R, Haqq C. Optimized high-throughput microRNA expression profiling provides novel biomarker assessment of clinical prostate and breast cancer biopsies. Mol Cancer. 2006;5:24. [PMC free article] [PubMed]
58. Thomas P, Pang Y, Filardo EJ, Dong J. Identity of an Estrogen Membrane Receptor Coupled to a G Protein in Human Breast Cancer Cells. Endocrinology. 2005;146:624–632. [PubMed]
59. Kang L, Zhang X, Xie Y, Tu Y, Wang D, Liu Z, Wang ZY. Involvement of Estrogen Receptor Variant ER-{alpha}36, Not GPR30, in Nongenomic Estrogen Signaling. Mol Endocrinol. 2010;24:709–721. [PMC free article] [PubMed]
60. Wang Z, Zhang X, Shen P, Loggie BW, Chang Y, Deuel TF. Identification, cloning, and expression of human estrogen receptor-[alpha]36, a novel variant of human estrogen receptor-[alpha]66. Biochemical and Biophysical Research Communications. 2005;336:1023–1027. [PubMed]
61. Wang Z, Zhang X, Shen P, Loggie BW, Chang Y, Deuel TF. A variant of estrogen receptor-{alpha}, hER-{alpha}36: Transduction of estrogen- and antiestrogen-dependent membrane-initiated mitogenic signaling. PNAS. 2006;103:9063–9068. [PMC free article] [PubMed]
62. Lee LMJ, Cao J, Deng H, Chen P, Gatalica Z, Wang Z-Y. ERalpha36, a Novel Variant of ERalpha, is Expressed in ER-positive and -negative Human Breast Carcinomas. Anticancer Research. 2008;28:479–483. [PMC free article] [PubMed]
63. Wijayaratne AL, McDonnell DP. The human estrogen receptor-alpha is a ubiquitinated protein whose stability is affected differentially by agonists, antagonists, and selective estrogen receptor modulators. J Biol Chem. 2001;276:35684–35692. [PubMed]
64. Frasor J, Stossi F, Danes JM, Komm B, Lyttle CR, Katzenellenbogen BS. Selective estrogen receptor modulators: discrimination of agonistic versus antagonistic activities by gene expression profiling in breast cancer cells. Cancer Res. 2004;64:1522–1533. [PubMed]
65. Uhlmann S, Zhang JD, Schwager A, Mannsperger H, Riazalhosseini Y, Burmester S, Ward A, Korf U, Wiemann S, Sahin O. miR-200bc/429 cluster targets PLC[gamma]1 and differentially regulates proliferation and EGF-driven invasion than miR-200a/141 in breast cancer. Oncogene. 2010;29:4297–4306. [PubMed]
66. Lim KB, Ng CY, Ong CK, Ong CS, Tran E, Nguyen TT, Chan GM, Huynh H. Induction of apoptosis in mammary gland by a pure anti-estrogen ICI 182780. Breast Cancer Res Treat. 2001;68:127–138. [PubMed]
67. El Etreby MF, Liang Y, Wrenn RW, Schoenlein PV. Additive effect of mifepristone and tamoxifen on apoptotic pathways in MCF-7 human breast cancer cells. Breast Cancer Research and Treatment. 1998;51:149–168. [PubMed]
68. Economopoulos K, Sergentanis T. Three polymorphisms in cytochrome P450 1B1 (CYP1B1) gene and breast cancer risk: a meta-analysis. Breast Cancer Research and Treatment. 2010;122:545–551. [PubMed]
69. Brockdorff BL, Skouv J, Reiter BE, Lykkesfeldt AE. Increased expression of cytochrome p450 1A1 and 1B1 genes in anti-estrogen-resistant human breast cancer cell lines. Int J Cancer. 2000;88:902–906. [PubMed]
70. Sindhu RK, Koo JR, Sindhu KK, Ehdaie A, Farmand F, Roberts CK. Differential regulation of hepatic cytochrome P450 monooxygenases in streptozotocin-induced diabetic rats. Free Radic Res. 2006;40:921–928. [PubMed]
71. Spink DC, Spink BC, Cao JQ, DePasquale JA, Pentecost BT, Fasco MJ, Li Y, Sutter TR. Differential expression of CYP1A1 and CYP1B1 in human breast epithelial cells and breast tumor cells. Carcinogenesis. 1998;19:291–298. [PubMed]
72. Tsuchiya Y, Nakajima M, Kyo S, Kanaya T, Inoue M, Yokoi T. Human CYP1B1 Is Regulated by Estradiol via Estrogen Receptor. Cancer Res. 2004;64:3119–3125. [PubMed]
73. Hamburger AW. The role of ErbB3 and its binding partners in breast cancer progression and resistance to hormone and tyrosine kinase directed therapies. J Mammary Gland Biol Neoplasia. 2008;13:225–233. [PMC free article] [PubMed]
74. Liu B, Ordonez-Ercan D, Fan Z, Edgerton SM, Yang X, Thor AD. Downregulation of erbB3 abrogates erbB2-mediated tamoxifen resistance in breast cancer cells. International Journal of Cancer. 2007;120:1874–1882. [PubMed]
75. Scott GK, Goga A, Bhaumik D, Berger CE, Sullivan CS, Benz CC. Coordinate Suppression of ERBB2 and ERBB3 by Enforced Expression of Micro-RNA miR-125a or miR-125b. J Biol Chem. 2007;282:1479–1486. [PubMed]
76. Revillion F, Pawlowski V, Lhotellier V, Louchez MM, Peyrat JP. mRNA expression of the type I growth factor receptors in the human breast cancer cells MCF-7: regulation by estradiol and tamoxifen. Anticancer Res. 2003;23:1455–1460. [PubMed]
77. Cochrane DR, Howe EN, Spoelstra NS, Richer JK. Loss of miR-200c: A Marker of Aggressiveness and Chemoresistance in Female Reproductive Cancers. J Oncol. 2010;2010:821717. [PMC free article] [PubMed]
78. Cochrane DR, Spoelstra NS, Howe EN, Nordeen SK, Richer JK. MicroRNA-200c mitigates invasiveness and restores sensitivity to microtubule-targeting chemotherapeutic agents. Molecular Cancer Therapeutics. 2009;8:1055–1066. [PubMed]
79. Hurteau GJ, Carlson JA, Spivack SD, Brock GJ. Overexpression of the MicroRNA hsa-miR-200c Leads to Reduced Expression of Transcription Factor 8 and Increased Expression of E-Cadherin. Cancer Res. 2007;67:7972–7976. [PubMed]
80. Bracken CP, Gregory PA, Kolesnikoff N, Bert AG, Wang J, Shannon MF, Goodall GJ. A Double-Negative Feedback Loop between ZEB1-SIP1 and the microRNA-200 Family Regulates Epithelial-Mesenchymal Transition. Cancer Res. 2008;68:7846–7854. [PubMed]
81. Burk U, Schubert J, Wellner U, Schmalhofer O, Vincan E, Spaderna S, Brabletz T. A reciprocal repression between ZEB1 and members of the miR-200 family promotes EMT and invasion in cancer cells. EMBO Rep. 2008;9:582–589. [PMC free article] [PubMed]
82. Gregory PA, Bert AG, Paterson EL, Barry SC, Tsykin A, Farshid G, Vadas MA, Khew-Goodall Y, Goodall GJ. The miR-200 family and miR-205 regulate epithelial to mesenchymal transition by targeting ZEB1 and SIP1. Nat Cell Biol. 2008;10:593–601. [PubMed]
83. Korpal M, Lee ES, Hu G, Kang Y. The miR-200 Family Inhibits Epithelial-Mesenchymal Transition and Cancer Cell Migration by Direct Targeting of E-cadherin Transcriptional Repressors ZEB1 and ZEB2. J Biol Chem. 2008;283:14910–14914. [PMC free article] [PubMed]
84. Kirschmann DA, Seftor EA, Nieva DR, Mariano EA, Hendrix MJ. Differentially expressed genes associated with the metastatic phenotype in breast cancer. Breast Cancer Res Treat. 1999;55:127–136. [PubMed]
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