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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Cancer Res. Author manuscript; available in PMC 2010 December 2.
Published in final edited form as:
PMCID: PMC2996265
NIHMSID: NIHMS253322

Positive Crosstalk between Estrogen Receptor and NFκB in Breast Cancer

Abstract

Estrogen receptors (ER) and NFκB are known to play important roles in breast cancer but these factors are generally thought to repress each others’ activity. However, we have recently found that ER and NFκB can also act together in a positive manner to synergistically increase gene transcription. To examine the extent of crosstalk between ER and NFκB, a microarray study was conducted in which MCF-7 breast cancer cells were treated with 17β-estradiol (E2), TNFα, or both. Follow-up studies with an ER antagonist and NFκB inhibitors demonstrate that crosstalk between E2 and TNFα is mediated by these two factors. We find that although transrepression between ER and NFκB does occur, positive crosstalk is more prominent with three gene-specific patterns of regulation: 1) TNFα enhances E2 action on ~30% of E2 up-regulated genes, 2) E2 enhances TNFα activity on ~15% of TNFα up-regulated genes, and 3) E2+TNFα causes a more than additive up-regulation of ~60 genes. Consistent with their prosurvival roles, ER and NFκB, and their target gene BIRC3, are involved in protecting breast cancer cells against apoptosis. Furthermore, genes positively regulated by E2+TNFα are clinically relevant since they are enriched in luminal B breast tumors and their expression profiles can distinguish a cohort of patients with poor outcome following endocrine treatment. Taken together, our findings suggest that positive crosstalk between ER and NFκB is more extensive than anticipated and that these factors may act together to promote survival of breast cancer cells and progression to a more aggressive phenotype.

Keywords: Estrogen, NFκB, Cytokine, Breast Cancer, Cell Survival

INTRODUCTION

The estrogen receptor (ER) is expressed in ~75% of breast tumors and is a major prognostic and therapeutic determinant. Women with ER positive tumors have a better prognosis and will likely receive endocrine therapy, such as tamoxifen or an aromatase inhibitor. However, not all ER positive tumors respond to endocrine therapy and frequently de novo or acquired resistance occurs. These ER positive tumors, which tend to retain ER expression but without typical response to tamoxifen, are generally more aggressive with earlier metastatic recurrence (1-3). Gene expression profiling has further delineated the two types of ER positive tumors, referred to as intrinsic subtypes luminal A and luminal B, with the luminal A subtype associated with good patient outcome and the B subtype with a poor survival rate (4, 5). Interestingly, activation of the proinflammatory transcription factor NFκB may play a role in this dichotomy between ER+ tumors. Constitutive activation of NFκB in breast tumors is associated with more aggressive ER+ tumors (6, 7), the development of resistance to endocrine therapy (8, 9), and progression to estrogen-independent growth (10-12).

Two estrogen receptor (ER) subtypes have been identified, ERα and ERβ, that mediate the biological functions of estrogen primarily through their ability to function as ligand-activated transcription factors. Both ERs can stimulate gene transcription by directly binding to DNA at estrogen response elements (EREs) or through tethering to other transcription factors (13, 14). ERs can also negatively regulate or repress transcription in either a direct or indirect manner through interaction with other transcription factors (15, 16). In particular, the ability of ERs to repress the transcriptional activity of NFκB has been well studied. The NFκB pathway is stimulated by a variety of factors, including proinflammatory cytokines. Following cytokine binding to its receptor, activation of the IκB kinase (IKK) complex occurs leading to phosphorylation and subsequent degradation of the inhibitory protein, IκB. This allows release of NFκB family members, p65 and p50, which are sequestered in the cytoplasm by IκB. Once liberated, p65 and p50 can translocate to the nucleus, bind to DNA at cognate NFκB response elements, and regulate target gene transcription. NFκB activation can be repressed by ER through several different mechanisms, including prevention of NFκB binding to DNA (17, 18), recruitment of corepressors into a complex with NFκB (19), competition for coactivators (20, 21), or prevention of NFκB nuclear translocation (22). The basis for these different mechanisms has not been fully elucidated but may be related to different cellular backgrounds or to gene specific mechanisms of crosstalk.

In contrast, very few reports have indicated that positive transcriptional crosstalk can occur between ER and NFκB (23-26). In each case, the mechanisms for positive crosstalk appears to involve a complex formation containing the ER and NFκB family members at either an ERE or an NFκB-RE. Previously, we have found that activation of ER and NFκB in breast cancer cells, via treatment with estradiol (E2) and the proinflammatory cytokine TNFα, leads to enhanced transcription of the prostaglandin E2 synthase (PTGES) gene (24). However, the extent to which this positive crosstalk between ER and NFκB occurs in breast cancer cells is not known. This lack of information prompted us to examine the genome-wide transcriptional crosstalk between ER and NFκB and, interestingly, we found that positive crosstalk is predominant compared to repression. We identified a large subset of genes that are synergistically up-regulated by the combination of E2 and TNFα in an ER and NFκB dependent manner. This subset of genes is highly enriched in Luminal B tumors and may contribute to ER and NFκB dependent breast cancer cell survival. Furthermore, this subset of genes demonstrates a unique expression pattern in breast tumors of women with poor response to tamoxifen and reduced disease-free and overall survival.

MATERIALS AND METHODS

Materials

17β-estradiol (E2) was obtained from Sigma. The cytokines TNFα, IL-1β and IL-6 were obtained from R&D Systems. IKK Inhibitor VII, which inhibits both IKKα and IKKβ, was obtained from Calbiochem. ICI 182,780 was obtained from Tocris. Adenoviral vectors for GFP and a dominant negative form of IκBα (IκBα-DN) were very kindly given to us by Dr. Ruxana Sadikot (UIC). The IAP antagonist (SMAC mimetic) was very generously provided by Dr. Xiadong Wang (University of Texas Southwestern Medical Center).

Cell Culture

MCF-7 cells were obtained from Dr. Benita Katzenellenbogen (UIUC) and cultured in MEM containing 5% calf serum as previously described (24). ZR75-1 and T47D cells were obtained from Dr. Debra Tonetti (UIC) and cultured in RPMI containing 10% fetal bovine serum. All three cell lines express ERα but not ERβ (unpublished observation); hence references to ER in these cell lines indicate ERα. Prior to E2 treatments, cells were cultured in phenol-red free media containing 5% charcoal-dextran (CD) stripped serum for at least 3 days. Expression of GFP or IκBα-DN was carried out using adenoviral vectors as previously described (24, 27, 28).

Gene Expression Profiling and Analysis

Total RNA was harvested for cRNA labeling and hybridization to Affymetrix HGU133A GeneChips was carried out as described previously (27, 29, 30), with three replicates for each treatment. Arrays were scanned and analyzed using the GeneChip Operating Software (Affymetrix, Santa Clara, CA). CEL files were processed and normalized using “gcrma” function in the R/Bioconductor package (31). Normalized data were further analyzed using GeneSpring software and significantly regulated genes were identified by the following criteria: ≥ 2.0 fold-change and P<0.05 for at least one treatment condition (E2, TNFα or E2+TNFα) compared to untreated control, as previously described (30, 32). After identification of regulated genes, modulation of gene regulation was considered “enhanced” if the fold change by E2+TNFα was greater than 1.5x the fold-change seen with either E2 or TNFα alone. Similarly, gene regulation was considered “reversed” if the fold change by E2+TNFα was less than 0.67x the fold change seen with E2 or TNFα alone. All microarray data are publicly available through GEO (accession number GSE11467).

Gene Ontology (GO) term enrichment was carried out using the Functional Annotation Clustering tool in DAVID (http://david.abcc.ncifcrf.gov/), as previously described (33). Enrichment of gene expression patterns in human breast tumors was determined using data from a breast tumor compendium and Genomica software as previously described (34). Survival analysis was carried out using gene expression profiles from the Uppsala patient population, as previously described with some modifications (27, 35). A total of 81 ER positive tumors from patients who subsequently underwent endocrine therapy with tamoxifen only were used to assess the role of E2+TNFα regulated genes in patient outcome. Expression profiles of E2+TNFα regulated genes were used to cluster patients using average linkage hierarchical clustering. Kaplan-Meier estimates were used to compute survival curves for disease-free survival, distant metastases-free survival, and disease-specific survival, and the significance of the hazard ratios between the four major patient clusters was determined by the P of the likelihood ratio test, as was described previously (35).

RNA Isolation and QPCR

RNA isolation was carried out using Trizol according to the manufacturer's instructions (Invitrogen). 0.5 μg of total RNA was reverse transcribed using MMLV-reverse transcriptase (Invitrogen). The resulting product was diluted to 100 μl with ddH2O and 2 μl were used for each subsequent QPCR reaction. QPCR was carried out and analyzed as previously described using 36B4 as an internal control (30). Primer sequences are available upon request.

Cell Survival and Apoptosis Assays

Cell viability was assessed in MCF-7 cells seeded in 96-well plates using the CellTiter 96® AQueous One Solution (Promega) according to manufacturer's instructions. Annexin V-FITC labeling was performed following the manufacturer's instruction (BD Biosciences) and the percentage of positively stained cells was assessed by flow cytometry.

Statistical Analysis

QPCR, survival and apoptosis data were analyzed by one-way or two-way ANOVA followed by post-hoc Tukey or Bonferroni tests, as appropriate. Significance for all statistical tests was set at P<0.05. Data shown are the mean +/- SEM from three to six independent determinations.

RESULTS

To examine genome-wide crosstalk between ER and NFκB, a microarray study was carried out using RNA from ER positive MCF-7 breast cancer cells that were treated with E2, TNFα or both for 2 hr. A total of 395 genes were identified as significantly up- or down-regulated by at least one of the three treatments (Supplemental Table 1, fold change ≥2.0, P<0.05). Hierarchical clustering analysis revealed several distinct patterns of regulation (Fig. 1). As previously demonstrated, a large number of genes are down-regulated by E2 treatment [Cluster A and (30)]. Interestingly, three distinct subsets of up-regulated genes were also identified: genes that are up-regulated by E2 (Cluster B), genes that are up-regulated by TNFα (Cluster C), and genes that are up-regulated by E2+TNFα (Cluster D). These three subsets of up-regulated genes were utilized to examine crosstalk between E2 and TNFα in more detail.

Figure 1
Characterization of Gene Expression Profile in Response to E2 and TNFα Treatment in Breast Cancer Cells

TNFα Modulates Gene Regulation by E2

To examine how the presence of TNFα influences E2 action, we compared the effect of E2 and E2+TNFα on the subset of genes that are up-regulated by E2 (n=46). Unexpectedly, we found that TNFα enhances E2 activity on ~30% of these genes (Fig. 2A), which partially accounts for the genes in Cluster D (Fig. 1). The ability of TNFα to enhance E2 activity is exemplified by pS2, which is robustly up-regulated by E2, not affected by TNFα alone, and up-regulated to a greater extent by the combination of E2+TNFα when compared to E2 alone (Fig. 2B). The ability of TNFα to enhance E2 regulation of pS2 is mediated by the NFκB pathway since an inhibitor of the IKK complex prevents TNFα action (Fig. 2C).

Figure 2
TNFα Modulates Gene Regulation by E2 in a Gene-Specific Manner

In addition, we found that TNFα reverses or represses E2 action on <10% of E2 up-regulated genes (Fig. 2A), as demonstrated by c-Fos, which is up-regulated to a greater extent by E2 alone compared to E2+TNFα (Fig. 2B). As is the case for enhanced pS2 regulation, the repression of c-Fos by E2+TNFα is also mediated by the NFκB pathway since the IKK inhibitor prevented repression of this gene by TNFα (Fig. 2C). In addition, the effect of E2+TNFα on both pS2 and c-Fos is completely blocked by the ER antagonist, ICI 182,780 indicating that the different effects of TNFα on E2 action require ER activity (Fig. 2C).

On the remaining 60% of the E2 up-regulated genes, TNFα appears to have no effect (Fig. 2A), as shown for Cluster B (Fig. 1) and demonstrated by the up-regulation of IGFBP4, which is not different between E2 and E2+TNFα at either the 2 or 3 hr time points (Fig. 2B). However, a slight reduction in E2 activity with the addition of TNFα was seen after 4 hr. ICI 182,780 completely blocked regulation of IGFBP4 by E2 or E2+TNFα whereas the IKK inhibitor had no effect (Fig. 2C). Taken together, these findings indicate that the proinflammatory cytokine, TNFα, acting through the NFκB pathway can influence E2 activity, either positively or negatively, in a gene-dependent manner. Furthermore, it appears that at the early time points chosen for study, enhancement of E2 activity by TNFα is ~3x more common than repression.

E2 Modulates Gene Regulation by TNFα

We next examined how the presence of E2 influences TNFα activity on genes up-regulated by TNFα (n=39). We found that E2 represses or reverses TNFα activity on ~ 41% of these genes (Fig. 3A). This finding is expected because the ability of ER to repress NFκB is well documented. Regulation of the NFκB target gene, ICAM1, demonstrates the ability of E2 to repress gene regulation by TNFα (Fig. 3B) and that this effect is mediated by the ER, as evidenced by the reversal of repression by ICI 182,780 (Fig. 3C). In addition, we found that E2 has no effect on the regulation of ~44% of TNFα up-regulated genes (Fig. 3A), as demonstrated by Cluster C (Fig. 1). However, this subset contains several NFκB target genes that are known to be repressed by ER. For example, our microarray data indicates that E2 treatment has no effect on TNFα up-regulation of its own gene but this is in contrast to several reports in the literature, which demonstrate that E2 can repress TNFα auto-regulation (19, 36, 37). This conflict was resolved by a time-course experiment, which revealed that E2 can repress regulation of TNFα mRNA but only at the earlier time points examined and that repression by E2 is lost at 2 hr, the time point at which the microarray was carried out (Fig. 3B). Treatment with ICI at the 2 hr time point had no effect on the auto-regulation of TNFα (Fig. 3C). These findings suggest that our microarray data may have under-estimated the ability of E2 to repress TNFα activity and that E2 repression of some TNFα regulated genes may be time-dependent.

Figure 3
E2 Modulates Gene Regulation by TNFα in a Gene-Specific and Time-Dependent Manner

One particularly unanticipated finding from our study is that E2 can enhance TNFα activity on ~15% of TNFα up-regulated genes (Fig. 3A and some genes in Cluster D of Fig. 1). This enhancement is demonstrated for BIRC3 (c-IAP2), which is an important anti-apoptotic gene of the Inhibitor of Apoptosis (IAP) family and is known to be up-regulated by NFκB (38). The up-regulation of BIRC3 is greatly enhanced by E2+TNFα as compared to TNFα alone (Fig. 3B). The effect of E2 on TNFα regulation of BIRC3 is completely prevented by ICI 182,780, indicating an essential role for the ER in enhancing NFκB activity on this gene (Fig. 3C). These findings indicate that although ER represses NFκB activity on many genes, ER can also enhance NFκB activity in a gene-specific manner.

Common E2 and TNFα Target Genes

Previous work from our lab demonstrated that the PTGES gene is up-regulated independently by E2 and TNFα and in a more than additive manner by the combination of E2+TNFα (24). Our microarray data suggest that a similar regulation occurs on a large subset of common E2 and TNFα target genes (n=63), which make up the majority of Cluster D (Fig. 1). These genes, as represented by PHLDA1 and IL17RB (Fig. 4A), are significantly up-regulated by E2+TNFα compared to either E2 or TNFα alone across a 4 hr time course.

Figure 4
Common E2 and TNFα Target Gene Regulation in MCF-7 Cells

To examine regulation of PHLDA1 in more detail, additional studies were carried out using different proinflammatory cytokines and different ER positive breast cancer cell lines. The combination of E2+TNFα or E2+IL1β, but not E2+IL6, led to a significantly greater up-regulation of PHLDA1 in MCF-7 cells compared to E2 or cytokine alone (Fig. 4B). A significant up-regulation of PHLDA1 by E2+TNFα was also observed in two other ER positive breast cancer cell lines, ZR75-1 and T47D (Fig. 4B). The ER is required for regulation of PHLDA1 by E2+TNFα since the ER antagonist, ICI 182,780, completely blocked regulation (Fig. 4C). The fact that both TNFα and IL-1β but not IL-6 can regulate this gene suggests an important role for the NFκB pathway in the regulation of PHLDA1. Expression of IκBα–DN, which cannot be phosphorylated or degraded and thereby blocks NFκB activity, confirms that the NFκB pathway is also required for the enhanced up-regulation of PHLDA1 by E2+TNFα (Fig. 4C). These findings indicate that the scope of positive crosstalk between ER and NFκB in breast cancer may be broader than expected, rather than being limited to one particular cytokine in a single cell line.

ER and NFκB Target Genes in Breast Cancer Cell Survival and Human Breast Tumors

In total, 80 genes were identified as being up-regulated to a greater extent than by E2+TNFα than by E2 or TNFα alone based on three different patterns of regulation: 1) TNFα enhanced E2 activity, 2) E2 enhanced TNFα activity, and 3) up-regulation by E2+TNFα. The top three biological functions associated with these 80 genes were transcriptional regulation, metabolism, and apoptosis/cell death, as identified using functional annotation clustering of enriched GO terms. The overall enrichment score for each cluster ranged from 2.63 to 1.49 but only the transcriptional regulation cluster reached significance (Benjamini Hochberg corrected p-value = 0.01). The identification of apoptosis-related function for these genes is consistent with the prosurvival roles for both ER and NFκB. To investigate this further, we took advantage of the fact that treatment of some breast cancer cell lines, including the MCF-7 cells used in these studies, with higher doses of TNFα can induce apoptosis through prolonged activation of the JNK pathway (39-41). Treatment of MCF-7 cells with TNFα for 30-48 hr caused a greater than 50% reduction in cell viability and a 4-fold increase in the number of apoptotic cells (Fig. 5A and 5B). The effect of TNFα on cell viability and apoptosis is completely reversed by the combination of E2+TNFα, indicating that E2 prevents TNFα induced apoptosis. We find that the ability of E2 to prevent TNFα induced cell death is blocked by ICI 182,780, as well as an inhibitor of the IKK complex (Fig. 5C), indicating that both ER and NFκB are required for E2 to promote cell survival in the presence of TNFα. To examine whether BIRC3, an antiapoptotic factor that is highly up-regulated by the combination of E2+TNFα (Fig. 3B), may be an important effector of ER and NFkB mediated cell survival, we used an IAP antagonist that blocks activity of BIRC3 (42, 43). We found that the IAP antagonist completely prevented an increase in cell survival by E2+TNFα, which suggests that the ER and NFκB dependent up-regulation of BIRC3 plays an essential role in breast cancer cell survival (Fig. 5C).

Figure 5
ER and NFκB-dependent Breast Cancer Cell Survival

To further examine the significance of the 80 gene signature resulting from positive crosstalk by E2+TNFα in breast tumor biology, we utilized a recently described breast tumor compendium that contains gene expression profiles for ~1200 well-annotated breast tumors (34). We first identified tumors in the compendium that significantly over-express or under-express genes from the positive crosstalk gene set by 1.8-fold or more (Fig. 6A). We next examined whether this gene expression profile was enriched in tumors with certain attributes or characteristics, including ER status, intrinsic subtype [luminal A, luminal B, Her2, Basal, or Normal (4)] or grade. As expected, we find that the positive crosstalk gene set is significantly over-expressed in ER+ tumors and under-expressed in ER- tumors (Fig. 6A). In addition, tumors of the Luminal B intrinsic subtype, but not the Luminal A subtype, also significantly overexpress the E2+TNFα positive crosstalk genes. Luminal B tumors have previously been shown to be more aggressive ER+ tumors associated with a worse patient outcome whereas Luminal A tumors are also ER+ but associated with a better patient outcome (5). These findings suggest that the combination of E2 and proinflammatory cytokines, acting through ER and NFκB, may coordinately regulate specific genes associated with more aggressive ER+ tumors. In contrast, Grade 3 and Basal subtype tumors under-express the positive crosstalk gene set. This most likely is related to the fact that the majority of Basal and Grade 3 tumors are ER negative.

Figure 6
Genes Regulated by E2+TNFα are Enriched in ER+ and Luminal B Breast Tumors and are Associated with Response to Tamoxifen Therapy

The association of the 80 positive cross-talk genes with key clinical parameters suggests that they may be involved in response to endocrine treatments and patient survival. To investigate whether expression of the 80 gene signature is prognostic of patient outcome, we examined the expression of these genes in a cohort of women with ER-positive breast tumors (n = 81) who had been treated with tamoxifen and followed over time. Hierarchical clustering of patients using expression levels of the 80 genes grouped them into four clusters with distinct expression profiles (Fig. 6B). Survival analysis of the four patient clusters indicated distinct outcomes for disease recurrence (disease-free survival; Fig. 6C), metastases (distant metastases-free survival; Fig. 6C), and death from breast cancer (disease-specific survival; Fig. 6C) following tamoxifen treatment. Expression profiles of the 80 genes clearly distinguished patients with good outcomes (Figs. 6B and 6C, green cluster and curves) from those with poor outcomes (Figs. 6B and 6C, red cluster and curves). Survival differences between the four patient clusters were statistically significant for disease-free (p=0.0128) and distant metastases-free (p=0.0138) survival and nearly significant for disease-specific survival (p=0.0782). These findings suggest that the interactions between ER and NFκB pathways and their downstream target genes may alter the genetic programming of ER-positive tumors and subsequently impact response to endocrine therapy and patient survival.

DISCUSSION

The major mechanism of crosstalk between ER and NFκB that has been described is transrepression, whereby ER represses NFκB activity and NFκB represses ER activity (44, 45). Our microarray results confirm that transrepression does occur between these two factors in breast cancer cells and that ER repression of NFκB activity is more common than NFκB repression of ER activity. Because NFκB activation is associated with tumor invasiveness, metastasis, and drug resistance (46), the fact that ER represses NFκB activity on numerous genes may represent one mechanism by which ER positive breast tumors are actually less aggressive than ER negative tumors. This concept has been previously suggested for ER repression of RelB, a member of the NFκB family, in breast cancer (47). However, results from our microarray analysis clearly demonstrate that transrepression is only one of many mechanisms of crosstalk that occurs between these two pleiotropic transcription factors.

Three different types of positive crosstalk between ER and NFκB were identified in our study. First, TNFα can enhance E2 activity on ~30% of E2 up-regulated genes, as demonstrated by pS2. Second, E2 can enhance TNFα activity on ~15% of TNFα up-regulated genes, such as BIRC3. And third, E2+TNFα acting together cause a more than additive up-regulation of a specific subset of genes, including PHLDA1 and IL17RB. Although repression between ER and NFκB has been well documented, few instances of a positive interaction between ER and NFκB have been reported (23-26). For example, ER and NFκB act together to up-regulate prostaglandin E synthase (24), the serotonin 1A receptor (26), prolactin in pituitary cells (23), and cyclin D1 in mammary cells (25). Thus, our study adds significant new information to the field by highlighting the extensive degree of positive crosstalk that occurs between ER and NFκB in breast cancer cells.

The concept that ER and NFκB can work together to positively up-regulate expression of particular genes could have important implications in breast cancer disease progression. Recent evidence indicates that ER positive breast tumors with constitutively active NFκB are more aggressive and less responsive to tamoxifen (7). Our findings suggest that the positive transcriptional crosstalk between ER and NFκB may enhance expression of genes involved in the promotion of more aggressive tumors. This is supported by the observation that these genes are enriched in luminal B tumors, a more aggressive subtype of ER+ breast tumors (5), but not in luminal A tumors, which are also ER+ but have a better patient outcome. Furthermore, the gene expression profile of tumors from women who failed to respond to tamoxifen and had poor disease-free and overall survival indicate that the expression levels of these genes, including some that are highly expressed in poor outcome patients, are associated with response to endocrine therapy.

One potential reason why these tumors are more aggressive is that both ER and NFκB are transcription factors with well characterized pro-survival or anti-apoptotic activities. While ER and NFκB can act individually to up-regulate cell survival genes, we find that they can also act together to enhance expression of additional cell survival genes, including PHLDA1 and BIRC3. PHLDA1 has been shown to be required for survival of cells following serum starvation (48). Furthermore, PHLDA1 has been detected in breast tumors and appears to correlate with better patient outcome in ER negative tumors and worse outcome in ER positive tumors (49). The function and expression of BIRC3, in contrast, has not been well examined in breast tumors. However, the IAP family of apoptosis inhibitors does play an anti-apoptotic function in different cancer cells and may contribute to tumor resistance to therapeutic drugs (43, 50, 51). Our findings demonstrate that inhibition of BIRC3 using an IAP antagonist (also known as a SMAC mimetic), which can bind and inhibit activity of IAP proteins, completely prevented cell survival in response to E2 and TNFα. We propose that while both ER and NFκB have individual pro-survival functions, they may also act together to regulate the expression of additional anti-apoptotic genes, such as BIRC3, which can further contribute to the enhanced survival of breast cancer cells. In addition to BIRC3, other genes may contribute to more aggressive breast tumors. For example, IL17RB has recently been observed to have a prognostic function in breast tumors when its expression is compared to the level of another gene, HOXB13 (52). The ratio of these two genes may also be predictive of tumor responsiveness to tamoxifen (53). Intriguingly, activation of NFκB is associated with anti-estrogen resistance (6, 8, 9) but whether NFκB activation can alter the HOXB13 to IL17RB ratio and how this influences response to tamoxifen requires further investigation.

In summary, our findings indicate that a spectrum of crosstalk between ER and NFκB can be observed in breast cancer cells and, in particular, that these two factors act together to enhance the expression of numerous genes. It is possible that the coordinated actions of ER and NFκB lead to enhanced cell survival, reduced response to therapeutic agents, such as tamoxifen, and the development of more aggressive breast tumors. Thus, transcriptional crosstalk between ER and NFκB represents a potential therapeutic target for breast cancer treatment and further investigation into this possibility is warranted.

Supplementary Material

Acknowledgements

This work was supported by R01CA130932 to JF. We are very grateful to Benita Katzenellenbogen for her support in initiating this project (R01CA18119 from the National Cancer Institute to BSK).

Financial Support: R01CA130932 (JF)

Footnotes

Disclosure Statement: The authors have nothing to disclose.

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