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Cancer Research 67, 6725, July 15, 2007. doi: 10.1158/0008-5472.CAN-06-4394
© 2007 American Association for Cancer Research
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Cell, Tumor, and Stem Cell Biology

BEX2 Is Overexpressed in a Subset of Primary Breast Cancers and Mediates Nerve Growth Factor/Nuclear Factor-{kappa}B Inhibition of Apoptosis in Breast Cancer Cell Lines

Ali Naderi1, Andrew E. Teschendorff1, Juergen Beigel1, Massimiliano Cariati1, Ian O. Ellis2, James D. Brenton1 and Carlos Caldas1

1 Cancer Genomics Program, Department of Oncology, University of Cambridge, Hutchison/Medical Research Council Research Center, Cambridge, United Kingdom and 2 Department of Histopathology, Nottingham City Hospital NHS Trust and University of Nottingham, Nottingham, United Kingdom

Requests for reprints: Carlos Caldas or Ali Naderi, Cancer Genomics Program, Department of Oncology, University of Cambridge, Hutchison/MRC Research Center, Hills Road, Cambridge CB2 2XZ, United Kingdom. Phone: 44-1223-404420; Fax: 44-1223-331753; E-mail: cc234{at}cam.ac.uk or an258{at}cam.ac.uk.


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
We have identified a novel subtype of estrogen receptor (ER)-positive breast cancers with improved outcome after tamoxifen treatment and characterized by overexpression of the gene BEX2. BEX2 and its homologue BEX1 have highly correlated expression and are part of a cluster enriched for ER response and apoptosis genes. BEX2 expression is induced after estradiol (E2) treatment with a peak at 3 h, suggesting BEX2 is an estrogen-regulated gene. BEX2 belongs to a family of genes, including BEX1, NGFRAP1 (alias BEX3), BEXL1 (alias BEX4), and NGFRAP1L1 (alias BEX5). Both BEX1 and NGFRAP1 interact with p75NTR and modulate nerve growth factor (NGF) signaling through nuclear factor-{kappa}B (NF-{kappa}B) to regulate cell cycle, apoptosis, and differentiation in neural tissues. In breast cancer cells, NGF inhibits C2-induced apoptosis through binding of p75NTR and NF-{kappa}B activation. Here, we show that BEX2 expression is necessary and sufficient for the NGF-mediated inhibition (through NF-{kappa}B activation) of C2-induced apoptosis. We also show that BEX2 modulates apoptosis of breast cancer cells in response to E2 (50 nmol/L) and tamoxifen (5 and 10 µmol/L). Furthermore, BEX2 overexpression enhances the antiproliferative effect of tamoxifen at pharmacologic dose (1 µmol/L). These data suggest that a NGF/BEX2/NF-{kappa}B pathway is involved in regulating apoptosis in breast ancer cells and in modulating response to tamoxifen in primary tumors. [Cancer es 2007;67(14):6725–36]


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
The heterogeneity of breast cancer poses a significant challenge in the diagnosis, prognostication, and treatment of the disease. Indeed, using expression analysis, breast cancers can be subclassified into at least six subtypes: luminal-like subgroups A, B, and C; basal-like; normal breast-like; and HER-2–like (1–3). Different subclasses of estrogen receptor–positive (ER+) tumors might reflect different cells of origin (4), and importantly, identifying different subgroups of ER+ tumors may have clinical implications: within tamoxifen-treated tumors, those that are ER+/progesterone receptor–negative (PR–) and express HER-1 and HER-2 have worse clinical outcomes than ER+/PR+ tumors (5).

The heterogeneity of ER+ breast cancer is the result of complex interactions between estrogen response and growth factor receptor signaling pathways, including the insulin-like growth factor and epidermal growth factor families (6). The nerve growth factor (NGF) pathway has also been implicated in the survival and proliferation of breast cancer cells (7). NGF treatment of breast cancer cells activates nuclear factor-{kappa}B (NF-{kappa}B), resulting in apoptosis inhibition after treatment with a ceramide homologue, C2 (8, 9). In breast cancer cells, the effects of NGF on apoptosis and proliferation are mediated through different receptors: p75NTR and p140TrkA, respectively (8, 9).

In this study, using expression microarray analysis of 135 primary breast tumors, we identified a subset of ER+ breast cancer with overexpression of BEX2 and BEX1. BEX1 was first identified in blastocytes using differential display analysis, and subsequent database homology searches identified other family members [BEX2, NGFRAP1 (BEX3), BEXL1, and NGFRAP1L1], all mapping to Xq22.1-23 (10, 11). NGFRAP1 (BEX3) encodes NADE, which interacts with the death domain of p75NTR and mediates apoptosis in neural cells in response to NGF (12). BEX1 also encodes a small adaptor-like protein that interacts with p75NTR and inhibits NF-{kappa}B activation in PC12 cells to regulate cell cycle arrest (13). BEX1 and BEX2 have been reported to be silenced by promoter methylation in malignant gliomas (14). We therefore investigated whether BEX2 and BEX1 could also be involved in NGF signaling in breast cancer cells.


   Materials and Methods
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 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Expression Microarray Experiments
The samples used were from a cohort of 135 frozen breast tumors collected at Nottingham City Hospital NHS Trust between 1986 and 1992. The institution research ethics committee approved this study. Total RNA extraction, RNA amplification, and indirect labeling were carried out as described before (15–17). Oligonucleotide microarrays containing 22,575 features were used (Agilent Human 1A 60-mer Oligo Microarray, Agilent Technologies). Hybridization, scanning, feature extraction, and data normalization were done as previously published (15).

Microarray Data Analysis
A total of 307 slides was compared for correlations between dye reversal pairs using Spotfire DecisionSite 8.0, and for each biological specimen, only those genes with a positive correlation were selected for further analysis. We further removed those genes with >20% missing data across all samples and this resulted in a matrix of 1,203 genes. Missing data points were imputed by the k-means nearest neighbor method as described before (18). Microarray data are deposited in ArrayExpress database (accession number E-UCON-1).

Independent component analysis (ICA; ref. 19) was implemented using the R package mlica.3 Supervised analysis by t test/ANOVA and similarity ranking were done by Spotfire DecisionSite 8.0. Significance analysis of microarrays (SAM)4 and prediction analysis of microarrays (PAM)5 were done following the instructions of the software. The significance analysis of Pearson's correlations using Monte-Carlo simulations was done applying the R statistical language.6 Analysis of the BEX expression signature function was done using Ingenuity Pathways Analysis software (Ingenuity Systems). Biostatistical analysis was done with Statistical Package for the Social Sciences version 12.0.1 (SPSS). Single sample prediction (SSP) classifier was derived as described before (20).

Real-Time PCR Analysis on Tumors
Reverse transcription-PCR (RT-PCR) to assess the expression levels of BEX1 and BEX2 on tumor samples was done using gene-specific Taqman assays (Applied Biosystems). Housekeeping genes HPRT1 and RPLP0 were used as controls. Experimental procedures were done following the manufacturer's instruction (Applied Biosystems). Relative gene expressions were calculated as described before (21).

Analysis of Apoptosis with C2 and NGF Treatments
Cell culture and apoptotic assays with MCF-7 and MDA-MB-231 cells were done as described in refs. 8, 9. Briefly, cells were grown and treated in the following groups (in triplicate): (a) control group (C2–/NGF–), no treatment; (b) C2–/NGF+, treatment with 200 ng/mL ß-NGF (R&D Systems); (c) C2+/NGF–, treatment with ceramide analogue C2 (Sigma) at 20 µmol/L; and (d) C2+/NGF+, treatments with both ß-NGF and C2. Apoptosis was scored after staining with Hoechst 33258 (Sigma) as described in refs. 8, 9.

RT-PCR Analysis of BEX Expression in Cell Lines with Different Treatments
Expression levels for BEX1 and BEX2 genes were measured using gene-specific Taqman assays. BEX relative expression is equal to BEX expression in the treated group/average BEX expression in the control group.

NGF/C2 treatments. The MCF-7 cell line was treated with C2 and NGF in four groups as described above. After 24 h of incubation, cells were harvested. Experiments were carried out in four replicates.

Estradiol treatment. MCF-7 cells grown in medium containing phenol red–free DMEM (Invitrogen) and 10% charcoal/dextran-treated serum (HyClone) were incubated with 17-ß-estradiol (Sigma) at 1 nmol/L concentration. Cells were harvested at 0, 1, 3, 6, and 12 h for RT-PCR measurement of BEX1 and BEX2 expression. Four replicate experiments were carried out for each treatment condition.

NF-{kappa}B inhibition. MCF-7 cells were serum deprived for 24 h and then treated separately with 18 µmol/L SN50 NF-{kappa}B inhibitor peptide (Tebu-Bio) in the presence or absence of C2/NGF. Untreated MCF-7 cells and treatment with C2/NGF were used as controls. After another 6, 12, and 18 h of incubation, cells were harvested.

Experiments with BEX2-Transfected Cells
BEX2 transfection. The BEX2 construct in pDream2.1/LIC expression vector (cytomegalovirus promoter and a Flag tag) was obtained from GenScript Corp. Transfection of MCF-7 and MDA-MB-231 cells was carried out in four replicates using ExGen 500 reagent (Fermentas Life Sciences) as instructed by the manufacturer. Cells were cotransfected with 1.2 µg of green fluorescent protein (GFP)-carrying vector with either 1.6 µg of the empty or BEX2-carrying pDream2.1/LIC vector (BEX2+). RT-PCR and Western blotting with anti-FLAG antibody (Sigma) at 1:500 dilution of primary antibody were used to confirm overexpression.

C2/NGF experiments. Cells were grown for 24 h and then incubated with C2 and NGF for the apoptotic assays described above.

Tamoxifen treatment. MCF-7 cells were grown on coverslips. Tamoxifen (Sigma) treatment was carried out at 1, 5, and 10 µmol/L concentrations in serum-free medium for 24 h and untreated cells were used as controls. To assess the effect of BEX2 overexpression, either BEX2+ or empty vector was transfected in four replicates followed by tamoxifen treatment at 5 and 10 µmol/L. Apoptosis was measured using Hoechst and Annexin V-FITC staining. Annexin V-FITC assay was done using Annexin V-FITC fluorescence microscopy kit (BD Biosciences) following the manufacturer's instructions.

Experiments with BEX2 Gene Knockdown Cells
Generation of BEX2 knockdown cells. BEX2 knockdown (BEX2-KD) in MCF-7 and MDA-MB-231 cell lines was carried using SMARTpool small interfering RNA (siRNA; four oligonucleotides) reagents following the manufacturer's instructions (Dharmacon, Inc.). Cells transfected with siCONTROL Non-Targeting siRNA (Dharmacon) and grown under the same conditions were used as controls. All siRNA silencing experiments were done in four replicates.

C2/NGF experiments. After transfection, MCF-7 and MDA-MB-231 cells (knockdown and controls) were incubated at 37°C for 24 h followed by treatments with C2 and NGF as above.

Estradiol treatment. MCF-7 cells were treated in the following four groups for 48 h: (a) serum starvation, (b) serum starvation and 17-ß-estradiol at 50 nmol/L, (c) serum starvation in BEX2-KD cells, and (d) serum starvation in BEX2-silenced cells and 17-ß-estradiol at 50 nmol/L. After 48 h of incubation, cells were harvested, fixed in 4% formaldehyde, and then stained with Hoechst to score apoptosis (percentage).

Tamoxifen treatment. MCF-7 cells (controls and knockdown) were treated with NGF and tamoxifen (5 and 10 µmol/L). Apoptosis was assessed after 24 h using Annexin V-FITC assay as described above.

Assessment of Proliferation in Tamoxifen-Treated Cells
MCF-7 and MDA-MB-231 cells were grown in 96-well plates to 50% confluence. Both cell lines were then transfected and treated in the following groups: (a) siCONTROL transfection followed by NGF and (b) BEX2-KD followed by NGF. MCF-7 cells were further studied in the following groups: (a) empty vector transfection followed by tamoxifen at 1 µmol/L and (b) BEX2 transfection followed by tamoxifen at 1 µmol/L. siCONTROL or empty vector–transfected cells without any treatment were used as controls. Proliferation was measured 24 and 72 h after the treatments using Vybrant 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) proliferation assay kit (Invitrogen) following the manufacturer's instructions. All experiments were done in eight biological replicates.

NF-{kappa}B Activity Assays
p50 NF-{kappa}B. MCF-7 cells were cultured in the following five groups: (a) untreated cells (control), (b) C2/NGF treatment (overnight), (c) BEX2 silencing followed by C2/NGF treatment, (d) transfection with empty vector (control), and (e) transfection with BEX2 vector. Nuclear extraction was carried out using Nuclear Extraction kit (Panomics, Inc.), and NF-{kappa}B DNA-binding activity was measured by ELISA in 10 µg of starting nuclear extract (TransBinding NF-{kappa}B Assay kit, Panomics). The assays were done in four biological replicates following the manufacturer's instructions. The binding of p50 NF-{kappa}B to DNA was measured for each treatment group, and ratios were calculated relative to the untreated control for C2/NGF and silencing experiments or empty vector control for the overexpression experiments.

Phosphorylated p65 NF-{kappa}B. MCF-7 cells were cultured in 96-well plates in five groups: (a) untreated cells (control), (b) transfection with siCONTROL siRNA followed by NGF treatment (overnight), (c) BEX2 silencing followed by NGF treatment, (d) transfection with empty vector (control), and (e) transfection with BEX2 vector. The amounts of phosphorylated p65 and total p65 NF-{kappa}B proteins were measured using ELISA (SuperArray CASE NF-{kappa}B p65 S468 kit, Tebu-Bio). Assays were done in eight biological replicates following the manufacturer's instructions. For each experimental group, the ratio of phosphorylated p65/total p65 was obtained and relative ratios were calculated as treatment group/control group.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
BEX1 and BEX2 are classifiers of ER+ breast cancer. Expression microarray analysis revealed that BEX2 was the gene with the highest frequency of significant log2 ratios (P < 0.05) across the cohort: >98% of the samples showed differential expression relative to the common reference pool (Supplementary Fig. S1). This indicated that the expression of BEX2 varied significantly across most samples. Cancer outlier profile analysis (COPA), a methodology recently proposed to identify biologically relevant genes (22), showed that BEX2 and its close homologue, BEX1, ranked among the top genes (Fig. 1A ). The mutual presence of these two genes in COPA analysis was striking and led us to further investigate their expression profiles.


Figure 1
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  		Figure 1. Expression pattern of BEX genes in primary breast cancers and ICA of breast cancer expression data reveals a BEX mode. A, results of COPA showing top 10 ranked genes. Range of COPA scores for the top 10 genes in each centile and scores of BEX genes. B, correlation of BEX2 log ratios between dye reversal experiments [sample/reference (LogS/R) and reference/sample (LogR/S) are log10 based]. P value is calculated using t test/ANOVA. C, heat map showing the expression of BEX1 and BEX2 across the 135 samples (log10 ratio scales: –1.5 to 1.5). Columns, ER status of the samples. D, graphic showing relative weights of genes in BEX ICA mode. Bold italic, BEX1, BEX2, and known estrogen response genes.

 
BEX2 expression relative to the common reference pool separated the breast tumors in two significantly different (P < 1 x 10–5; Fig. 1B) groups with overexpression (n = 20) and underexpression (n = 115) of the gene. BEX1 expression also varied significantly between the two groups (P < 1 x 10–5), reflecting the strong correlation (Pearson's correlation coefficient = 0.94) in expression patterns of both genes (Fig. 1C). Most interestingly, all samples with BEX overexpression were ER+ (P < 0.001; Fig. 1C).

To validate the expression microarray results, RT-PCR was used to confirm the expression levels of BEX1 and BEX2 in a subset of samples from the original cohort. The correlation coefficients between RT-PCR results and expression microarray ratios were 0.87 (BEX2; n = 40) and 0.6 (BEX1; n = 40; P < 0.001; Supplementary Fig. S2). BEX1 expression was very low in BEX– samples, explaining the wide difference in log ratios between BEX+ and BEX– groups in the microarray data.

BEX1 and BEX2 genes are associated with an estrogen response expression mode. To gain insight into the possible biological role and function of the BEX– genes, we applied ICA. ICA decomposes the expression matrix into a set of expression modes, which have been shown to provide better representations of underlying biological processes or pathways than other dimensional reduction methods, such as principal component analysis (PCA; refs. 19, 23). The explanation for this is that ICA infers expression modes that are as mutually statistically independent as possible. As such modes provide closer approximations to the underlying biologically relevant processes that gave rise to the data in the first place. In other words, ICA approximates the expression matrix as a linear superposition of independent biological processes that are inferred using the criterion of statistical independence through a nonlinear decorrelation step. In contrast, PCA only does a linear decorrelation and so does not decompose the expression matrix into the independent biological processes that generated the data. Our ICA analysis identified an expression mode with strong representation of BEX1 and BEX2 (Fig. 1D; Supplementary Table S1). BEX1 showed the highest weight in this mode, and BEX2 was represented as one of the top 20 genes. Known estrogen response genes, such as GATA3, TFF1, LIV-1, and AREG (24, 25), as well as genes previously shown to be expressed in breast cancers, such as LACRT (26), DCD (27), and BMP7 (28), were also highly activated. Not surprisingly, using the SSP classifier (20), 60% (n = 12) of BEX overexpressers were luminal subtype A, 30% (n = 6) were luminal subtype B, and 10% (n = 2) were normal subtype.

Projection of the sample expression values along the BEX mode showed significant differential activation between ER+ and ER– samples (P = 6.4 x 10–9; Supplementary Fig. S3). Thus, we concluded that this ICA mode and the genes highly activated in this mode, including the BEX genes, are associated with ER status. We verified that the BEX ICA mode and its association with estrogen response were robust under repeated runs of the algorithm as well as under variations in the number of inferred modes (data not shown). Analysis of publicly available data sets also showed a majority of the genes in this mode to be differentially expressed in ER+ versus ER– breast cancers (data not shown).7

A distinct BEX+ cluster of genes in breast cancer. Having established the significance of the expression of BEX genes in breast cancer using both COPA and ICA, we asked whether there were genes significantly correlating with BEX1 and BEX2 (hereafter designated "BEX+ cluster"). To investigate this, we used Pearson's correlation coefficients and tested significance of the coefficients by comparison with null distributions obtained using Monte-Carlo simulation. The gene correlations were computed to the average expression profile of BEX1 and BEX2 because both genes were highly correlated (>0.9). The correlation analysis and Monte-Carlo simulation identified 35 genes (Fig. 2A ) with significant correlations to the expression of BEX1 and BEX2 (BEX+ cluster), with absolute correlation values ranging from approximately 0.25 to 0.4 (P < 0.0025, q < 0.06). There were nine of these genes also present in the BEX ICA mode. To validate the BEX+ cluster, a similar analysis was done in an independent data set (29). BEX1, together with 23 other genes from the cluster, was present in the external data set. Sixteen of the overlapping genes (~70%) had significant correlations with BEX1 (P < 0.04; Fig. 2B) and showed the same direction of expression changes. Considering the differences in methodology and variation in the platform used, this overlap supports the existence of a distinct BEX+ cluster.


Figure 2
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  		Figure 2. BEX cluster and expression signature in breast cancer. A, bar plot of BEX cluster 35 genes identified by correlation analysis. Each column identifies a gene and the direction of the column and its height reflect the nature of the correlation (P and q values of Pearson's correlation and Monte-Carlo simulation). B, bar plot of overlapping BEX cluster genes with significant correlations to BEX1 (P < 0.04) in van 't Veer et al.'s study. C, centroid of BEX expression signature by PAM. Weights for the up-regulated and down-regulated genes. Red, genes that overlap with ICA BEX mode. D, graphic of BEX2 relative expression ratios in response to E2 (at 1 nmol/L) in MCF-7 cell line. *, P < 0.01, compared with untreated cells using Mann-Whitney U test.

 
Supervised analysis defines a developmental/apoptosis/cell proliferation BEX expression signature in breast cancer. To identify genes that could differentiate between tumors expressing high levels of BEX genes (BEX+; n = 20) from the remainder of tumors (BEX–; n = 115), the samples were divided in two groups based on the expression ratios of BEX2 (BEX+ log2 > 0; BEX– log2 < 0). This subdivision was validated using an unsupervised k-means algorithm (k = 2; data not shown).

The first supervised analysis used a class prediction algorithm based on the nearest shrunken centroid method5 (30). This algorithm generated an optimal classifier consisting of 37 genes with a correct classification rate of 85% (Fig. 2C; Supplementary Fig. S4). Notably, 60% of the genes from the BEX+ cluster were also members of the optimal classifier.

To validate these results, further supervised analysis using t test/ANOVA and SAM were conducted (Supplementary Excel Files S1 and S2). The results showed that approximately 2/3 of the genes overlap among all supervised methods and with the BEX+ cluster.

The expression patterns in comparison with BEX2 of the 68 genes from the ANOVA-derived signature were analyzed using similarity ranking of correlation coefficients (Supplementary Fig. S5; Supplementary Excel File S3) within the expression matrix of 1,203 genes filtered for analysis (see Materials and Methods). BEX1 ranked closest to BEX2 with 0.9 similarity and the other 31 with positive correlation ranked ordered 3 to 33 of 1,203. Likewise, the 36 genes with negative correlation with BEX genes ranked the most distant (e.g., C10orf81 ranked 1,203 and TNFSF7 ranked 1,201 with –0.28 and –0.27 similarities, respectively).

These findings show that there is a distinct expression signature differentiating BEX+ and BEX– samples, which is reproducible using different supervised methods.

To gain further insights into the potential functional significance of the BEX expression signature, the Ingenuity Pathways Analysis software was used. The stability of results was tested by analyzing signatures obtained using SAM, ANOVA, and PAM. Significant associations (P < 0.001) were detected between the BEX signature and development, apoptosis, and cell proliferation functions (Supplementary Table S2).

BEX2 expression in MCF-7 breast cancer cells increases with estrogen treatment. Given that BEX1 and BEX2 expression are significantly higher in a subset of ER+ breast cancers, we investigated the effect of estrogen on the expression of both genes in the ER+ cell line MCF-7. MCF-7 cells were treated with estradiol (E2) at 1 nmol/L over 12 h. Cells were harvested at 1, 3, 6, and 12 h time points, and BEX1 and BEX2 expression ratios relative to baseline untreated cells were measured using RT-PCR (Fig. 2D). BEX2 expression was induced at 60 min, peaked at 3 h (4.1 ± 0.2), and returned to baseline by 12 h. In contrast, E2 did not have any effect on the expression of BEX1, which was not expressed at baseline in MCF-7 cells (data not shown). These findings indicate that BEX2 expression increases in response to E2 treatment in the breast cancer cell line MCF-7.

BEX2 expression in MCF-7 breast cancer cells increases with C2-induced apoptosis and with NGF treatment. The expression data suggested a potential link between BEX2 and BEX1 with ER response and apoptosis. We therefore asked whether the expression of BEX genes in the MCF-7 ER+ breast cancer cell line is modulated in response to C2 and NGF using RT-PCR (Fig. 3A ). MCF-7 cells were previously shown to express p75NTR (9).


Figure 3
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  		Figure 3. BEX2 and regulation of apoptosis. A, BEX2 relative expression ratios by RT-PCR in MCF-7 cell line. Columns, BEX2 expression ratios. C2–/NGF+, NGF treatment alone; C2+/NGF–, C2 treatment alone; C2+/NGF+, C2 and NGF treatments. *, P < 0.001, compared with untreated cells using Mann-Whitney U test. B, RT-PCR and Western blot to confirm BEX2 expression in MCF-7 and MDA-MB-231 cells. For RT-PCR experiments, transfection with BEX2 vector (left) and knockdown using siRNA (right) are shown. Four replicate experiments were done for each condition and –{Delta}{Delta}CT measurements are shown for each set of experiments. Western blot was done using BEX2-transfected MCF-7 (MCF-BEX2) and MDA-MB-231 (MDA-BEX2) cells. Empty vector control cells (MDA-EV and MCF-EV). Anti-FLAG antibody (Sigma) at 1:500 dilution was used (BEX2 construct carries a FLAG tag at the 5'-end). C, apoptosis in MCF-7 and MDA-MB-231 cells overexpressing BEX2. Columns, percentage of apoptosis. EV, cells transfected with empty vector; BEX2+, cells transfected with BEX2 vector; MDA, MDA-MB-231. D, apoptosis in MCF-7 and MDA-MB-231 cells with BEX2-KD. CT, control siRNA.

 
Apoptosis in MCF-7 cells were analyzed in four groups as described in Materials and Methods. We confirmed the previously published results: no significant change compared with controls in the C2–/NGF+ group, gross apoptosis in the C2+/NGF– group, and rescue from apoptosis in the C2+/NGF+ group (Supplementary Fig. S6).

The BEX2 expression ratios relative to control cells were as follows: (a) 2.62 ± 0.44 in response to NGF, (b) 4.4 ± 0.80 in response to C2, and (c) 8.9 ± 1.61 in response to C2 + NGF treatments (significantly higher than other groups; P < 0.001; Fig. 3A). BEX1 expression was not detected in MCF-7 either at baseline or in response to the treatments (data not shown).

These data show that, in MCF-7 cells, BEX2 expression increases slightly with NGF stimulation, increases significantly with C2 treatment (which induces apoptosis), and increases further with rescue from C2-induced apoptosis by NGF treatment. In contrast, BEX1 was not expressed either at baseline or with any of the treatments used. We therefore manipulated BEX2 expression levels in breast cancer cells and analyzed its effects on apoptosis.

BEX2 overexpression rescues breast cancer cells from C2-induced apoptosis mimicking NGF treatment. We asked whether BEX2 overexpression could rescue breast cancer cells (MCF-7 and MDA-MB-231) from C2-induced apoptosis in the absence of NGF. Despite being ER–, MDA-MB-231 is also rescued from C2-induced apoptosis by NGF (9).

Both cell lines were cotransfected with a BEX2-FLAG expression vector and a GFP expression vector to assess transfection efficiency. As a negative control, similar experiments used cotransfection with an empty vector and GFP. Overexpression of BEX2 in transfected cells was confirmed using RT-PCR and Western blot with anti-FLAG antibody because none of the commercially available BEX2 antibodies worked in our hands (Fig. 3B). BEX2 overexpression significantly reduced the C2-induced apoptosis in both cell lines (P = 0.0001; Fig. 3C; Supplementary Fig. S7). These data show that BEX2 overexpression rescues cells from C2-induced apoptosis in two different breast cancer cell lines and is sufficient to produce an antiapoptotic effect similar to that observed with NGF treatment.

Knockdown of BEX2 inhibits the NGF antiapoptotic response in breast cancer cells. We next asked whether the expression of BEX2 is necessary for the NGF antiapoptotic effect. siRNA was used to knock down BEX2 in MCF-7 and MDA-MB-231 cell lines, and in parallel experiments, nontargeted siRNA (controls) was used as a control. RT-PCR confirmed that BEX2 transcript levels were suppressed by ~90% in BEX2 siRNA-treated cells compared with controls (Fig. 3B). BEX2-KD significantly inhibited the antiapoptotic effect of NGF after C2 treatment (P = 0.001) in both cell lines (Fig. 3D) compared with controls. These results show that BEX2 expression is required for NGF-mediated antiapoptotic response in two different breast cancer cell lines.

BEX2 modulates the apoptotic responses of MCF-7 cells to estrogen and tamoxifen. Ceramide is a physiologic mediator of programmed cell death. Although C2 "mimics" the proapoptotic activity of cytokines known to interact with the ER response, the direct relevance of the "NGF/BEX2 pathway" to apoptosis in response to estrogen modulation was not addressed in the experiments described above. Indeed, tamoxifen treatment in addition to its antiproliferative effects induces apoptosis in breast cancer cells (31), and E2 has an antiapoptotic activity in breast cancer cell lines in response to various stressors (32, 33). We therefore treated MCF-7 cells with tamoxifen or E2, using doses previously shown to modulate apoptosis, and compared responses with and without manipulation of BEX2 expression.

Treatment of MCF-7 cells with tamoxifen at 5 and 10 µmol/L resulted in significant apoptosis (P < 0.01), which was not seen at 1 µmol/L (Fig. 4A and B ; Supplementary Fig. S8). Apoptosis was significantly reduced by both NGF treatment and BEX2 overexpression (P < 0.03; Fig. 4A and B). Treatment with the NF-{kappa}B inhibitor SN50 and BEX2-KD removed the protective effects of BEX2 overexpression and NGF, respectively (P < 0.01; Fig. 4A and B). These data indicate that activation of the NGF/BEX2 pathway inhibits tamoxifen-induced apoptosis and this effect of BEX2 is mediated through NF-{kappa}B.


Figure 4
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  		Figure 4. BEX2 modulation of tamoxifen/E2 induced apoptosis and tamoxifen antiproliferative effect. A, apoptosis of MCF-7 in response to tamoxifen using Hoechst staining. TAM, tamoxifen at 10 µmol/L for 24 h; NGF, at 200 ng/mL for 24 h; BEX2 (+), BEX2 transfection. *, P < 0.01 for NGF and TAM versus TAM, BEX2 transfection and TAM versus empty vector and TAM, and BEX2 transfection and TAM + SN50 versus empty vector and TAM. Columns, mean; bars, SE. B, apoptosis of MCF-7 in response to tamoxifen using Annexin V-FITC assay. TAM, tamoxifen at 0, 1, 5, and 10 µmol/L concentrations for 24 h; NGF, at 200 ng/mL. *, P < 0.03 for TAM versus TAM-5 and BEX2 transfection; **, P < 0.01 for all other experimental conditions. All P values are calculated using Mann-Whitney U test. C, apoptosis of MCF-7 in response to serum starvation and E2. Percentage of apoptotic MCF-7 cells is shown in each treatment group. SS, serum starvation for 48 h; E2, at 50 nmol/L; *, P = 0.01 for E2 treatment versus no treatment. D, effect of BEX2 on proliferation changes mediated by NGF and tamoxifen using MTT assay. BEX2 transfection, BEX2 overexpression; TAM, tamoxifen at 1 µmol/L; MCF, MCF-7. Incubation was done for 1 and 3 d. {Delta}OD measured as absorbance difference at 520 nm between the treatment groups and untreated controls. *, P value is for TAM versus TAM/BEX2 overexpression after 1-d incubation using Mann-Whitney U test.

 
MCF-7 cells subjected to serum starvation (48 h) and treated with E2 (50 nmol/L) showed a significant reduction of apoptosis compared with untreated cells (P = 0.01; Fig. 4C). In contrast, in BEX2-KD MCF-7 cells, E2 was not as effective as an antiapoptotic agent (Fig. 4C). These results show that BEX2 is necessary for the E2 antiapoptotic activity in serum-starved MCF-7 cells.

BEX2 modulation of cell proliferation. Having shown that BEX2 plays a role in modulating apoptosis in breast cancer cells in response to NGF and tamoxifen, we next analyzed whether it could also play a role in modulating cell proliferation using the MTT assay.

As previously described (34), NGF significantly (P < 0.01) increased cell proliferation after 1 and 3 days of treatment. This was not significantly altered by BEX2-KD (P > 0.3; Fig. 4D). In addition, BEX2-KD and BEX2 overexpression had no measurable effect in the proliferation of these two breast cancer cell lines (P > 0.3; data not shown). These data indicate that BEX2 is not involved in NGF-mediated proliferation.

MCF-7 cells treated with tamoxifen at 1 µmol/L (pharmacologic dose) for 1 or 3 days showed significantly impaired proliferation (Fig. 4D). BEX2 overexpression further reduced proliferation rate in cells tamoxifen treated for 24 h (P = 0.01; Fig. 4D) but not in cells tamoxifen treated for 72 h (P > 0.3). These data indicate that BEX2 modulates the antiproliferative activity of tamoxifen in the MCF-7 breast cancer cell line but this effect seems to depend on the duration of tamoxifen exposure.

BEX2 mediates NF-{kappa}B activation in the NGF antiapoptotic pathway. The antiapoptotic effect of NGF in breast cancer cell lines treated with C2 is mediated through the activation of NF-{kappa}B (9). To determine whether BEX2 is directly involved in this pathway in MCF-7 cells, we measured the binding of p50 NF-{kappa}B to DNA and the phosphorylation of p65 NF-{kappa}B using ELISA assays. NGF treatment had no effect on p50 NF-{kappa}B binding (Fig. 5A ) and increased ratio of phosphorylated p65 NF-{kappa}B/total p65 NF-{kappa}B (P < 0.01; Fig. 5B). BEX2 overexpression significantly increased both p50 NF-{kappa}B DNA binding and ratio of phosphorylated p65 NF-{kappa}B/total p65 NF-{kappa}B (P = 0.01; Fig. 5A and B). Treatment with C2/NGF also significantly increased p50 NF-{kappa}B DNA binding (P < 0.01; Fig. 5A), but BEX2-KD, which reverts apoptosis rescue (see Fig. 3D), dramatically reduced p50 NF-{kappa}B binding (1 ± 0.18; P = 0.01; Fig. 5A) after C2/NGF treatment. The rise in the ratio of phosphorylated p65 NF-{kappa}B/total p65 NF-{kappa}B after NGF treatment is also significantly reduced in BEX2-KD cells (P = 0.03; Fig. 5B). These data show that BEX2 expression is both necessary and sufficient for NGF-mediated NF-{kappa}B activation.


Figure 5
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  		Figure 5. BEX2 and NF-{kappa}B activation. A, measurement of p50 NF-{kappa}B DNA binding in MCF-7 cells using ELISA. Fold p50 NF-{kappa}B DNA binding is compared with untreated cells (C2/NGF and silencing experiments) or empty vector–transfected cells (transfection experiment). C2, 10 µmol/L; NGF, 200 ng/mL. *, P = 0.01 for C2/NGF versus BEX2-KD and C2/NGF and for BEX2 overexpression versus empty vector transfection. B, measurement of phosphorylated p65 NF-{kappa}B in MCF-7 cells using ELISA. Relative ratio for phosphorylated p65 NF-{kappa}B/total p65 NF-{kappa}B is compared with untreated cells (NGF and silencing experiments) or empty vector–transfected cells (transfection experiment). *, P = 0.03 for NGF versus BEX2-KD and NGF; **, P = 0.01 for BEX2 overexpression versus empty vector transfection. C, BEX2 fold expression by RT-PCR in MCF-7 cells treated with C2+/NGF+ and inhibition of NF-{kappa}B with SN50 treatment. *, P < 0.001 for C2+/NGF+/SN50+ versus C2+/NGF+. Expression ratios are relative to the average BEX2 expression in untreated MCF-7 cells. All P values are calculated using Mann-Whitney U test. Columns, mean; bars, SE.

 
Notably, total p65 protein level by ELISA (and REL-A/p65 gene by RT-PCR) did not significantly change after either NGF treatment or BEX2 overexpression (data not shown). This indicates that the effect of NGF/BEX2 on p65 NF-{kappa}B is mediated through an increase in phosphorylation, not a change of protein/gene expression.

BEX2 expression is increased by NF-{kappa}B inactivation. The ELISA experiments showed that NF-{kappa}B activation in C2/NGF treated cells is extremely sensitive to and dependent on BEX2 expression. This suggested that modulation of BEX2 expression is a regulator of the pathway. We therefore analyzed whether BEX2 expression levels change when NF-{kappa}B is prevented from relocating to the nucleus despite stimulation of the pathway. MCF-7 cells were treated with SN50, a cell-permeable polypeptide that inhibits translocation of the NF-{kappa}B active complex into the nucleus, and this inhibited the antiapoptotic effect of NGF in C2-exposed cells (data not shown). SN50 treatment alone did not change BEX2 expression (Fig. 5C). Overnight treatment with C2/NGF/SN50 for 18 h led to a 21-fold ± 3.3 increase (P < 0.001; Fig. 5C) in BEX2 expression. Similar results were obtained after 6 and 12 h of SN50 treatment: relative expressions of 18 ± 2.5–fold and 20 ± 3–fold, respectively (data not shown). This shows that, upon simultaneous activation of the pathway with NGF/C2 treatment and inhibition of NF-{kappa}B DNA binding using SN50, there is a significant further increase of BEX2 expression compared with activation of the pathway alone.

Increased BEX2 expression was not observed with other proapoptotic stimuli, such as tamoxifen treatment (10 µmol/L) or serum starvation (data not shown), indicating that the effect of NGF/NF-{kappa}B modulation (e.g., with C2 and SN50) on BEX2 expression is not the result of a nonspecific apoptotic response.

BEX2+/ER+ breast cancers have a better response to tamoxifen therapy. Having established that in our cohort all BEX+ cases were ER+ breast cancers, we asked whether there was any influence of BEX2 status on outcome among patients treated with tamoxifen therapy. We first divided the cases (n = 34) into BEX2 overexpression or BEX2 underexpression using one of two criteria: (a) log2 ratios normalized to the median value on the microarrays, showing at least 2-fold expression difference (n = 24), and (b) RT-PCR of samples with <2-fold expression difference by microarray analysis (n = 10), showing {Delta}CT < –1 SD or {Delta}CT > +1 SD of the mean (n = 6). Using these criteria, a total of 30 cases was available for survival analysis and this showed a significantly better (P = 0.03; Fig. 6A ; Supplementary Table S3) disease-free interval in patients with BEX2 overexpression [n = 16; 95% confidence interval (95% CI), 121–161 months] versus those with BEX2 underexpression (n = 14; 95% CI, 63–123 months).


Figure 6
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  		Figure 6. Outcome with tamoxifen therapy and proposed NGF/BEX2/NF-{kappa}B apoptotic pathway. A, Kaplan-Meier disease-free survival curve in tamoxifen-treated cases with high versus low BEX2 expression. Cum Survival, cumulative survival; DFI, disease-free interval in months; N, number of events/number of cases in each group. B, schematic presentation of NGF/BEX2/NF-{kappa}B pathway. +, stimulatory effect; –, inhibitory effect; dashed line, hypothetical feedback loop.

 

   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
The evidence for the involvement of BEX1 and BEX2 genes in human cancer has emerged with the report that both genes are silenced by promoter methylation in human gliomas (14). BEXL1, another BEX family member, is epigenetically silenced in ovarian cancer (35). The data presented here reveal overexpression of BEX1 and BEX2 in a subset of ER+ breast cancers. We could not detect any correlation in our breast cancers between BEX2 methylation and expression (data not shown). We also reviewed array comparative genomic hybridization data available for the tumors with BEX overexpression and found no alterations at the genomic DNA level (data not shown). BEX2 and BEX1 were also highlighted by outlier analysis (COPA), which recently was used to identify significant cancer genes (22). We noted that BEX1 was also significantly overexpressed in ER+ versus ER– tumors in two publicly available data sets, and interestingly, in both data sets BEX1 ranks among the top genes in COPA analysis7 (36, 37). ICA, a completely unsupervised algorithm, identified a mode that included BEX1 and BEX2. This mode correlated strongly with ER+ status (P = 6.4 x 10–9) and included several well-known estrogen response genes. The correlation of BEX1 and BEX2 with estrogen response genes was further supported using supervised analysis. One of these genes, GATA3, is a transcription factor with known correlation to ER expression (24). Other estrogen response genes included LIV-1, TFF1, and AREG (24, 38, 39). Interestingly, several BEX-associated genes (GATA3, LIV-1, TFF1, SCUBE2, and KIAA0882) are present in the luminal subtype A cluster, which is associated with estrogen response (2), and indeed, 60% of BEX overexpressers were luminal A. The pattern of BEX2 increased expression in response to E2 treatment (Fig. 2D) is compatible with that of other estrogen early up-regulated genes (40).

BEX2 interacts with LMO2 and this interaction may regulate the transcriptional activity of LMO2 through its binding to NSCL2 (41). NGFRAP1 encodes NADE, which interacts with p75NTR (12, 42–44). More recently, BEX1 was also shown to interact with p75NTR and the data from this group suggest that NGF uses BEX1 to regulate cell cycle arrest (13). The results from these published experiments showing that BEX1 and NGFRAP1 encode small adaptor proteins that interact with p75NTR constitute a link between these genes, NGF signaling, and regulation of apoptosis and differentiation in neural cells. This provided us with a clue about a possible mechanism for involvement of the BEX gene family in breast cancer in light of the published data showing that NGF inhibits the apoptotic response to C2 in cell lines through p75NTR and NF-{kappa}B. C2 is a ceramide analogue that induces massive apoptosis of breast cancer cells (45, 46). For these studies, we analyzed BEX2 because BEX1 is not expressed in the breast cancer cell lines used. Our experiments show that BEX2 is necessary for the antiapoptotic function of NGF in C2-treated breast cancer cells (Fig. 3D) and BEX2 overexpression produces an antiapoptotic effect similar to that observed with NGF treatment (Fig. 3C). Interestingly, in neuronal cells, ceramide is generated as a second messenger of sphingomyelin cycle activation by NGF, downstream of p75NTR (47). This probably explains the moderate rise in BEX2 expression we observed in breast cancer cells treated with C2 alone (Fig. 3A). BEX2-KD inhibited and BEX2 overexpression enhanced NF-{kappa}B activation (both p50 and p65 components; Fig. 5A and B), indicating that BEX2 is in the NGF/NF-{kappa}B pathway upstream of NF-{kappa}B in the modulation of apoptosis. In contrast, BEX2 seems not to be involved in NGF-mediated proliferation (Fig. 4D), which is not surprising because this effect is mediated through a separate receptor (p140TrkA) and downstream pathway (mitogen-activated protein kinase) in breast cancer cells (8, 9).

Our data indicate that BEX2 is also important for apoptosis in response to ER modulation by E2 and tamoxifen by modulating NF-{kappa}B. NF-{kappa}B activity has been shown to play a role in hormone independence and resistance to tamoxifen and raloxifene in breast cancer (48–50). NF-{kappa}B is also activated in anti–estrogen (Fulvestrant)-resistant breast cancer cells, and this resistance can be reversed using NF-{kappa}B inhibitors (51). Our experiments with MCF-7 cells provide further evidence for this role and suggest direct BEX2 involvement: NF-{kappa}B activation by NGF treatment or BEX2 overexpression resulted in reduced tamoxifen-induced apoptosis and the protective effect of BEX2 overexpression was removed with NF-{kappa}B inhibition (Fig. 4A and B).

We propose a possible explanation to reconcile the cell line results with the observed better prognosis of tamoxifen-treated patients who were also BEX2 overexpressers. We consistently observed higher BEX2 expression on simultaneous activation of the pathway (with NGF/C2) and inhibition of NF-{kappa}B DNA binding (with SN50) compared with pathway activation alone (Fig. 5C). This shows that NF-{kappa}B DNA binding is upstream of BEX2 expression, possibly creating a feedback loop. Others have shown that nuclear extracts from ER+ tumors with better response to tamoxifen have much lower NF-{kappa}B DNA-binding activity and ER stimulation results in direct inhibition of NF-{kappa}B DNA binding (52–54). We also observed that BEX2 overexpression enhanced the antiproliferative effect of tamoxifen after 24 h of treatment (Fig. 4D). It is therefore conceivable that the better prognosis in tamoxifen-treated BEX2+ patients is the combined result of relative NF-{kappa}B inactivation leading to BEX2 overexpression, which in turn enhances the tamoxifen antiproliferative effect.

In summary, overexpression of BEX genes is a novel classifier of ER+ breast tumors, and potentially, BEX2 overexpression could serve as a marker to identify tumors with better response to tamoxifen therapy. We propose a model where BEX2 is part of both the NGF/NF-{kappa}B and estrogen response pathways, which regulate apoptosis in breast cancer cells (Fig. 6B). In addition, BEX2 cooperates in inhibiting proliferation of breast cancer cells treated with tamoxifen at pharmacologic dose. These findings suggest the tantalizing possibility of the NGF/BEX2/NF-{kappa}B pathway being a therapeutic target in breast cancer.


   Acknowledgments
 
Grant support: Cancer Research UK.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.


   Footnotes
 
Note: Supplementary data for this article are available at Cancer Research Online (http://cancerres.aacrjournals.org/).

Current address for A.E. Teschendorff, J. Beigel, J.D. Brenton, and C. Caldas: Cancer Research UK Cambridge Research Institute, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, United Kingdom.

3 http://cran.us.r-project.org Back

4 http://www-stat.stanford.edu/~tibs/SAM/ Back

5 http://www-stat.stanford.edu/~tibs/PAM/ Back

6 http://www.R-project.org Back

7 http://www.oncomine.org/main/index.jsp Back

Received 11/29/06. Revised 4/30/07. Accepted 5/11/07.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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