About GATA3, HNF3A, and XBP1, three genes co-expressed with the oestrogen receptor-alpha gene (ESR1) in breast cancer

Pioneer transcription factors: establishing competence for gene expression

Transcription factors are adaptor molecules that detect regulatory sequences in the DNA and target the assembly of protein complexes that control gene expression. Yet much of the DNA in the eukaryotic cell is in nucleosomes and thereby occluded by histones, and can be further occluded by higher-order chromatin structures and repressor complexes. Indeed, genome-wide location analyses have revealed that, for all transcription factors tested, the vast majority of potential DNA-binding sites are unoccupied, demonstrating the inaccessibility of most of the nuclear DNA. This raises the question of how target sites at silent genes become bound de novo by transcription factors, thereby initiating regulatory events in chromatin. Binding cooperativity can be sufficient for many kinds of factors to simultaneously engage a target site in chromatin and activate gene expression. However, in cases in which the binding of a series of factors is sequential in time and thus not initially cooperative, special "pioneer transcription factors" can be the first to engage target sites in chromatin. Such initial binding can passively enhance transcription by reducing the number of additional factors that are needed to bind the DNA, culminating in activation. In addition, pioneer factor binding can actively open up the local chromatin and directly make it competent for other factors to bind. Passive and active roles for the pioneer factor FoxA occur in embryonic development, steroid hormone induction, and human cancers. Herein we review the field and describe how pioneer factors may enable cellular reprogramming.

Relationships of ESR1 and XBP1 expression in human breast carcinoma and stromal cells isolated by laser capture microdissection compared to intact breast cancer tissue

Results from investigations of human genomics which utilize intact tissue biopsy specimens maybe compromised due to a host of uncontrolled variables including cellular heterogeneity of a sample collected under diverse conditions, then processed and stored using different protocols. To determine the cellular origin and assess relationships of mRNA expression of two genes reported to be co-expressed in human breast carcinoma (estrogen receptor-α, ESR1 and X-box binding protein 1, XBP1), gene expression analyses were performed with intact tissue sections and compared with those of laser capture microdissection (LCM)-procured carcinoma and stromal cells from serial sections of the same tissue. Frozen sections of human breast carcinomas were first evaluated for structural integrity and pathology after hematoxylin and eosin (H&E) staining. Total RNA preparations from intact tissue sections and LCM-procured carcinoma and stromal cells were reverse transcribed for measurements of ESR1 and XBP1 expression by quantitative PCR (qPCR). These results were compared with those obtained from microarray analyses of LCM-procured carcinoma cells. Levels of ESR1 and XBP1 were detected in the intact breast cancer tissue sections suggesting coordinate gene expression. Although coordinate expression of these genes was observed in the LCM-procured carcinoma cells, it was not discerned in LCM-procured stromal cells. The origin of coordinate expression of ESR1 and XBP1 observed in whole tissue sections of human breast cancer biopsies is due principally to their co-expression in carcinoma cells and not in the surrounding stromal cells as substantiated using LCM-procured cells. Collectively, a microgenomic process was established from human tissue preparation to RNA characterization and analysis to identify molecular signatures of specific cell types predicting clinical behavior.

Lrig1 is an estrogen-regulated growth suppressor and correlates with longer relapse-free survival in ERα-positive breast cancer

Lrig1 is the founding member of the Lrig family and has been implicated in the negative regulation of several oncogenic receptor tyrosine kinases including ErbB2. Lrig1 is expressed at low levels in several cancer types but is overexpressed in some prostate and colorectal tumors. Given this heterogeneity, whether Lrig1 functions to suppress or promote tumor growth remains a critical question. Previously, we found that Lrig1 was poorly expressed in ErbB2-positive breast cancer, suggesting that Lrig1 has a growth-inhibitory role in this tumor type. However, breast cancer is a complex disease, with ErbB2-positive tumors accounting for just 25% of all breast cancers. To gain a better understanding of the role of Lrig1 in breast cancer, we examined its expression in estrogen receptor α (ERα)-positive disease which accounts for the majority of breast cancers. We find that Lrig1 is expressed at significantly higher levels in ERα-positive disease than in ERα-negative disease. Our study provides a molecular rationale for Lrig1 enrichment in ERα-positive disease by showing that Lrig1 is a target of ERα. Estrogen stimulates Lrig1 accumulation and disruption of this induction enhances estrogen-dependent tumor cell growth, suggesting that Lrig1 functions as an estrogen-regulated growth suppressor. In addition, we find that Lrig1 expression correlates with prolonged relapse-free survival in ERα-positive breast cancer, identifying Lrig1 as a new prognostic marker in this setting. Finally, we show that ErbB2 activation antagonizes ERα-driven Lrig1 expression, providing a mechanistic explanation for Lrig1 loss in ErbB2-positive breast cancer. This work provides strong evidence for a growth-inhibitory role for Lrig1 in breast cancer.

Targeting androgen receptor in estrogen receptor-negative breast cancer

Endocrine therapies for breast cancer that target the estrogen receptor (ER) are ineffective in the 25%-30% of cases that are ER negative (ER-). Androgen receptor (AR) is expressed in 60%-70% of breast tumors, independent of ER status. How androgens and AR regulate breast cancer growth remains largely unknown. We find that AR is enriched in ER- breast tumors that overexpress HER2. Through analysis of the AR cistrome and androgen-regulated gene expression in ER-/HER2+ breast cancers we find that AR mediates ligand-dependent activation of Wnt and HER2 signaling pathways through direct transcriptional induction of WNT7B and HER3. Specific targeting of AR, Wnt or HER2 signaling impairs androgen-stimulated tumor cell growth suggesting potential therapeutic approaches for ER-/HER2+ breast cancers.

Epigenetic switch involved in activation of pioneer factor FOXA1-dependent enhancers

Transcription factors (TFs) bind specifically to discrete regions of mammalian genomes called cis-regulatory elements. Among those are enhancers, which play key roles in regulation of gene expression during development and differentiation. Despite the recognized central regulatory role exerted by chromatin in control of TF functions, much remains to be learned regarding the chromatin structure of enhancers and how it is established. Here, we have analyzed on a genomic-scale enhancers that recruit FOXA1, a pioneer transcription factor that triggers transcriptional competency of these cis-regulatory sites. Importantly, we found that FOXA1 binds to genomic regions showing local DNA hypomethylation and that its cell-type-specific recruitment to chromatin is linked to differential DNA methylation levels of its binding sites. Using neural differentiation as a model, we showed that induction of FOXA1 expression and its subsequent recruitment to enhancers is associated with DNA demethylation. Concomitantly, histone H3 lysine 4 methylation is induced at these enhancers. These epigenetic changes may both stabilize FOXA1 binding and allow for subsequent recruitment of transcriptional regulatory effectors. Interestingly, when cloned into reporter constructs, FOXA1-dependent enhancers were able to recapitulate their cell type specificity. However, their activities were inhibited by DNA methylation. Hence, these enhancers are intrinsic cell-type-specific regulatory regions of which activities have to be potentiated by FOXA1 through induction of an epigenetic switch that includes notably DNA demethylation.

Antiestrogens and their therapeutic applications in breast cancer and other diseases

The identification of the link between breast cancer and estrogens has led to the development of antiestrogens, in particular tamoxifen, to inhibit the activities of estrogen receptors (ERs) in breast cancer cells. The clinical use of tamoxifen has played a major part in decreasing breast cancer mortality over the past 30 years. Though antiestrogenic in the breast, some antiestrogens have estrogen-like actions in other tissues, acting to promote bone density and protect against cardiovascular disease, thus raising the possibility of their use in counteracting the effects of estrogen loss following menopause. Moreover, antiestrogens show efficacy as chemopreventive agents in women at high risk of developing breast cancer. Thus, antiestrogens define an important and well-understood class of cancer drug, which continue to be a mainstay in breast cancer treatment.

Multi-gene biomarker panel for reference free prostate cancer diagnosis: determination and independent validation

Identification of biomarkers that can accurately and reliably diagnose prostate cancer is clinically highly desirable. A novel classification method, K-closest resemblance was applied to several high-quality transcriptomic datasets of prostate cancer leading to the discovery of a panel of eight gene biomarkers that can detect prostate cancer with over 96% specificity and sensitivity in leave-one-out cross-validation. Independent validation on clinical samples confirmed the discriminatory power of this gene panel, yielding over 95% accuracy of diagnosis based on receiver-operating characteristic curve analyses. Different levels of validation of the proposed biomarker panel have shown that it allows extremely accurate diagnosis of prostate cancer. Application of this panel can possibly add a fast and objective tool to the pathologist's arsenal following further clinical testing.

IRE1alpha controls cyclin A1 expression and promotes cell proliferation through XBP-1

IRE1 is a conserved dual endoribonuclease/protein kinase that is indispensable for directing the endoplasmic reticulum (ER) stress response in yeast, flies, and worms. In mammalian systems, however, the precise biological activities carried out by IRE1alpha are unclear. Here, molecular and chemical genetic approaches were used to control IRE1 activity in a number of prostate cancer cell lines and the resulting impact on gene transcription, cell survival, and proliferation was examined. Modulating IRE1alpha activity had no transcriptional effect on the induction of genes classically associated with the ER stress response (Grp78 and CHOP) or cell survival when confronted with ER stress agents. Rather, IRE1alpha activity was positively correlated to proliferation. Since Xbp-1 mRNA is the sole known substrate for IRE1 endoribonuclease activity, the role of this transcription factor in mediating proliferation was examined. Repressing total Xbp-1 levels by siRNA techniques effectively slowed proliferation. In an effort to identify IRE1/XBP-1 targets responsible for the cell cycle response, genome-wide differential mRNA expression analysis was performed. Consistent with its ability to sense ER stress, IRE1alpha induction led to an enrichment of ER-Golgi, plasma membrane, and secretory gene products. An increase in cyclin A1 expression was the only differentially expressed cell cycle regulatory gene found. Greater cyclin A protein levels were consistently observed in cells with active IRE1alpha and were dependent on XBP-1. We conclude that IRE1alpha activity controls a subset of the ER stress response and mediates proliferation through tight control of Xbp-1 splicing.

Orphan nuclear receptors in breast cancer pathogenesis and therapeutic response

Nuclear receptors comprise a large family of highly conserved transcription factors that regulate many key processes in normal and neoplastic tissues. Most nuclear receptors share a common, highly conserved domain structure that includes a carboxy-terminal ligand-binding domain. However, a subgroup of this gene family is known as the orphan nuclear receptors because to date there are no known natural ligands that regulate their activity. Many of the 25 nuclear receptors classified as orphan play critical roles in embryonic development, metabolism, and the regulation of circadian rhythm. Here, we review the emerging role(s) of orphan nuclear receptors in breast cancer, with a particular focus on two of the estrogen-related receptors (ERRalpha and ERRgamma) and several others implicated in clinical outcome and response or resistance to cytotoxic or endocrine therapies, including the chicken ovalbumin upstream promoter transcription factors, nerve growth factor-induced B, DAX-1, liver receptor homolog-1, and retinoic acid-related orphan receptor alpha. We also propose that a clearer understanding of the function of orphan nuclear receptors in mammary gland development and normal mammary tissues could significantly improve our ability to diagnose, treat, and prevent breast cancer.

Estrogen regulation of X-box binding protein-1 and its role in estrogen induced growth of breast and endometrial cancer cells

BACKGROUND: X-box binding protein 1 (XBP1), a transcription factor involved in unfolded protein response, is also an estrogen-regulated gene and strongly correlates with estrogen receptor alpha (ERα) expression in breast cancers. We investigated the functional role of XBP1 in estrogen responsive breast and endometrial cancer cells as its functions are not fully understood. MATERIALS AND METHODS: ERα positive breast (MCF7) and endometrial (ECC1) cancer cells were used to study XBP1 gene regulation by 17-β-estradiol (E2) and to investigate the role of XBP1 in E2-mediated growth using short interfering RNA. Quantitative real-time PCR and Western blot were used to assess RNA and protein levels. Recruitment of ERα and other cofactors at the promoter and enhancer region of the XBP1 gene was investigated by chromatin immunoprecipitation. Estrogen responsive element (ERE)-mediated transcriptional activity was evaluated by a luciferase reporter assay. RESULTS: E2 induced the transcription of XBP1 in both MCF7 and ECC1 cells. E2-dependent recruitment of ERα, steroid receptor coactivator (SRC)-1 and SRC-3, and RNA polymerase II were observed at the promoter and/or enhancer region of the XBP1 gene. Depletion of XBP1 markedly inhibited the E2-induced growth in MCF7 and ECC1 cells. However, ERE-mediated transcription was not altered in XBP1-overexpressing or XBP1-depleted MCF7 cells. CONCLUSION: Our results confirm E2-induced transcription of XBP1 and demonstrate the crucial role of XBP1 in E2-induced growth of ERα positive breast and endometrial cancer cells without modulating the classical ERE-mediated transcription by ER. This knowledge creates new opportunities for therapeutic interventions.

Estrogen-induced aurora kinase-A (AURKA) gene expression is activated by GATA-3 in estrogen receptor-positive breast cancer cells

Aurora-A is a proto-oncogenic mitotic kinase that is frequently overexpressed in human epithelial malignancies including in breast and ovarian cancers. The mechanism of transcriptional upregulation of Aurora-A in human breast cancer is not yet elucidated. We report herein that Aurora-A transcription is positively regulated by GATA-3 in response to estrogen in estrogen receptor α (ERα)-positive cells. Transient expression of aurora-A promoter deletion mutants in luciferase constructs identified a GATA binding sequence motif as a functional regulatory element in ERα-positive breast cancer cells. Electrophoretic mobility shift assay identified the binding of regulatory proteins to the GATA element. Anti-GATA-3 antibody generated a supershifted complex. Recruitment of GATA-3 to the aurora-A promoter was verified by chromatin immunoprecipitation analysis with GATA-3 antibody. Ectopic expression of GATA-3 resulted in elevated expression of Aurora-A in both ERα-positive and negative cells while siRNA-mediated silencing led to downregulation of endogenous Aurora-A in ERα-positive cells. Estrogen treatment of ERα-positive cells induced increased Aurora-A expression with enhanced recruitment of GATA-3 to the aurora-A promoter. Finally, in the ACI rat model of estrogen-induced breast cancer, known to be associated with elevated Aurora-A expression, we observed increased expression of GATA-3 in preinvasive and invasive mammary epithelial cells exposed to prolonged estrogen treatment and in developing breast tumors. These results demonstrate a direct positive role of estrogen in regulating Aurora-A expression through activation of the ERα-GATA-3 signaling cascade and suggest that this pathway may be critical in the origin of estrogen-stimulated sporadic breast cancer.

Prognosis of hormone-dependent breast cancers: implications of the presence of dysfunctional transcriptional networks activated by insulin via the immune transcription factor T-bet

Estrogen receptor alpha (ERalpha)-positive breast cancers that co-express transcription factors GATA-3 and FOXA1 have a favorable prognosis. These transcription factors form an autoregulatory hormonal network that influences estrogen responsiveness and sensitivity to hormonal therapy. Disruption of this network may be a mechanism whereby ERalpha-positive breast cancers become resistant to therapy. The transcription factor T-bet is a negative regulator of GATA-3 in the immune system. In this study, we report that insulin increases the expression of T-bet in breast cancer cells, which correlates with reduced expression of GATA-3, FOXA1, and the ERalpha:FOXA1:GATA-3 target gene GREB-1. The effects of insulin on GATA-3 and FOXA1 could be recapitulated through overexpression of T-bet in MCF-7 cells (MCF-7-T-bet). Chromatin immunoprecipitation assays revealed reduced ERalpha binding to GREB-1 enhancer regions in MCF-7-T-bet cells and in insulin-treated MCF-7 cells. MCF-7-T-bet cells were resistant to tamoxifen in the presence of insulin and displayed prolonged extracellular signal-regulated kinase and AKT activation in response to epidermal growth factor treatment. ERalpha-positive cells with intrinsic tamoxifen resistance as well as MCF-7 cells with acquired tamoxifen and fulvestrant resistance expressed elevated levels of T-bet and/or reduced levels of FOXA1 and GATA-3. Analysis of publicly available databases revealed ERalpha-positive/T-bet-positive breast cancers expressing lower levels of FOXA1 (P = 0.0137) and GATA-3 (P = 0.0063) compared with ERalpha-positive/T-bet-negative breast cancers. Thus, T-bet expression in primary tumors and circulating insulin levels may serve as surrogate biomarkers to identify ERalpha-positive breast cancers with a dysfunctional hormonal network, enhanced growth factor signaling, and resistance to hormonal therapy.

Emerging roles for XBP1, a sUPeR transcription factor

X-box binding protein 1 (XBP1) is a unique basic region leucine zipper (bZIP) transcription factor whose active form is generated by a nonconventional splicing reaction upon disruption of homeostasis in the endoplasmic reticulum (ER) and activation of the unfolded protein response (UPR). XBP1, first identified as a key regulator of major histocompatibility complex (MHC) class II gene expression in B cells, represents the most conserved signaling component of UPR and is critical for cell fate determination in response to ER stress. Here we review recent advances in our understanding of this multifaceted transcription factor in health and diseases.

The role of X-box binding protein-1 in tumorigenicity

Rapid growth of a tumor can overwhelm the vasculature that supplies it with nutrients and oxygen. Inside such tumors, cells undergo endoplasmic reticulum stress but can survive such adverse microenvironments by an adaptive mechanism called the unfolded protein response (UPR). X-box binding protein-1 (XBP-1) is a critical transcriptional activator of the UPR and is responsible for regulating the function of genes in cell survival. An unconventional splicing of the XBP-1(U) messenger RNA (mRNA) results in two proteins: XBP-1(S) that is often increased in a variety of human cancers and any translated proteins from the unspliced XBP-1(U) mRNA that acts as a dominant negative of endogenous XBP-1(S) action. In cancer cells, overexpression of XBP-1 can confer drug resistance by preventing drug-induced cell-cycle arrest and mitochondrial permeability and apoptosis, while downregulation of XBP-1 increases the sensitivity to killing by hypoxia. XBP-1 is also implicated in cellular de-differentiation, oncovirus infection and the epithelial-to-mesenchymal transition. Given that XBP-1 mediates a wide range of responses in tumorigenesis, it is logical to focus on XBP-1 as an anticancer therapeutic target. Furthermore, combining inhibitors of XBP-1 with other anti-UPR drugs may enhance the activity of some antineoplastic therapies.

Alternatively activated macrophages in infection and autoimmunity

Macrophages are innate immune cells that play an important role in activation of the immune response and wound healing. Pathogens that require T helper-type 2 (Th2) responses for effective clearance, such as parasitic worms, are strong inducers of alternatively activated or M2 macrophages. However, infections such as bacteria and viruses that require Th1-type responses may induce M2 as a strategy to evade the immune system. M2 are particularly efficient at scavenging self tissues following injury through receptors like the mannose receptor and scavenger receptor-A. Thus, M2 may increase autoimmune disease by presenting self tissue to T cells. M2 may also exacerbate immune complex (IC)-mediated pathology and fibrosis, a hallmark of autoimmune disease in women, due to the release of profibrotic factors such as interleukin-1beta, transforming growth factor-beta, fibronectin and matrix metalloproteinases. We have found that M2 comprise anywhere from 30% to 70% of the infiltrate during acute viral or experimental autoimmune myocarditis, and shifts in M2 populations correlate with increased IC deposition, fibrosis and chronic autoimmune pathology. Thus, women may be at an increased risk of M2-mediated autoimmunity due to estrogen's ability to increase Th2 responses.

Gene expression meta-analysis supports existence of molecular apocrine breast cancer with a role for androgen receptor and implies interactions with ErbB family

Background

Pathway discovery from gene expression data can provide important insight into the relationship between signaling networks and cancer biology. Oncogenic signaling pathways are commonly inferred by comparison with signatures derived from cell lines. We use the Molecular Apocrine subtype of breast cancer to demonstrate our ability to infer pathways directly from patients' gene expression data with pattern analysis algorithms.

Methods

We combine data from two studies that propose the existence of the Molecular Apocrine phenotype. We use quantile normalization and XPN to minimize institutional bias in the data. We use hierarchical clustering, principal components analysis, and comparison of gene signatures derived from Significance Analysis of Microarrays to establish the existence of the Molecular Apocrine subtype and the equivalence of its molecular phenotype across both institutions. Statistical significance was computed using the Fasano & Franceschini test for separation of principal components and the hypergeometric probability formula for significance of overlap in gene signatures. We perform pathway analysis using LeFEminer and Backward Chaining Rule Induction to identify a signaling network that differentiates the subset. We identify a larger cohort of samples in the public domain, and use Gene Shaving and Robust Bayesian Network Analysis to detect pathways that interact with the defining signal.

Results

We demonstrate that the two separately introduced ER^- breast cancer subsets represent the same tumor type, called Molecular Apocrine breast cancer. LeFEminer and Backward Chaining Rule Induction support a role for AR signaling as a pathway that differentiates this subset from others. Gene Shaving and Robust Bayesian Network Analysis detect interactions between the AR pathway, EGFR trafficking signals, and ErbB2.

Conclusion

We propose criteria for meta-analysis that are able to demonstrate statistical significance in establishing molecular equivalence of subsets across institutions. Data mining strategies used here provide an alternative method to comparison with cell lines for discovering seminal pathways and interactions between signaling networks. Analysis of Molecular Apocrine breast cancer implies that therapies targeting AR might be hampered if interactions with ErbB family members are not addressed.

The -9247 T/C polymorphism in the SOST upstream regulatory region that potentially affects C/EBPalpha and FOXA1 binding is associated with osteoporosis

Accumulating evidence shows that genes that cause monogenic diseases also contribute to similar complex disease in the general population. We sought to determine whether the allelic variation in seven monogenic bone disease genes (CLCN7, TCIRGI, SOST, CA2, CSTK, TGFB1 and SLC26A2) contributes to osteoporosis/bone mineral density (BMD) variation in the normal Chinese population. We conducted a gene-wide tag SNP-based association study in 1243 Chinese subjects with low BMD (Z-scores < or = -1.28, equivalent to the lowest 10% of the population) and high BMD (Z-score > or = +1.0). Twenty-two tag SNPs were selected and genotyped by using the high-throughput Sequenom genotyping platform. Allelic and haplotype association tests were conducted by Haploview and binary logistic regression analyses. The -9247 polymorphism rs1230399 in the upstream regulatory region of the sclerostin gene showed significant genotypic/allelic associations with spine, femoral neck, trochanter and total hip BMD (P=0.03-0.004). The T-allele of rs1230399 increased the risk of osteoporosis (OR=1.52, P=0.005). Computational analysis showed that rs1230399 is located at the core consensus recognition site of two cooperating transcription factors C/EBPalpha and FOXA1 that modulate estrogen receptor function. T-->C polymorphism abolishes the binding of both C/EBPalpha and FOXA1 to the sclerostin gene. Our data suggest a mechanistic link between rs1230399 and BMD through estrogen ERalpha/FOXA1 signaling pathways driven by long-distance enhancers.

Profile of estrogen-responsive genes in an estrogen-specific mammary gland outgrowth model

Both ovarian and pituitary hormones are required for the pubertal development of the mouse mammary gland. Estradiol directs ductal elongation and branching, while progesterone leads to tertiary branching and alveolar development. The purpose of this investigation was to identify estrogen-responsive genes associated with pubertal ductal growth in the mouse mammary gland in the absence of other ovarian hormones and at different stages of development. We hypothesized that the estrogen-induced genes and their associated functions at early stages of ductal elongation would be distinct from those induced after significant ductal elongation had occurred. Therefore, ovariectomized prepubertal mice were exposed to 17beta-estradiol from two to 28 days, and mammary gland global gene expression analyzed by microarray analysis at various times during this period. We found that: (a) gene expression changes in our estrogen-only model mimic those changes that occur in normal pubertal development in intact mice, (b) both distinct and overlapping gene profiles were observed at varying extents of ductal elongation, and (c) cell proliferation, the immune response, and metabolism/catabolism were the most common functional categories associated with mammary ductal growth. Particularly striking was the novel observation that genes active during carbohydrate metabolism were rapidly and robustly decreased in response to estradiol. Lastly, we identified mammary estradiol-responsive genes that are also co-expressed with estrogen receptor alpha in human breast cancer. In conclusion, our genomic data support the physiological observation that estradiol is one of the primary hormonal signals driving ductal elongation during pubertal mammary development.

Genomic antagonism between retinoic acid and estrogen signaling in breast cancer

Retinoic acid (RA) triggers antiproliferative effects in tumor cells, and therefore RA and its synthetic analogs have great potential as anticarcinogenic agents. Retinoic acid receptors (RARs) mediate RA effects by directly regulating gene expression. To define the genetic network regulated by RARs in breast cancer, we identified RAR genomic targets using chromatin immunoprecipitation and expression analysis. We found that RAR binding throughout the genome is highly coincident with estrogen receptor alpha (ERalpha) binding, resulting in a widespread crosstalk of RA and estrogen signaling to antagonistically regulate breast cancer-associated genes. ERalpha- and RAR-binding sites appear to be coevolved on a large scale throughout the human genome, often resulting in competitive binding activity at nearby or overlapping cis-regulatory elements. The highly coordinated intersection between these two critical nuclear hormone receptor signaling pathways provides a global mechanism for balancing gene expression output via local regulatory interactions dispersed throughout the genome.

Expression of FOXA1 and GATA-3 in breast cancer: the prognostic significance in hormone receptor-negative tumours

Introduction

The expression of additional genes, other than oestrogen receptor (ER), may be important to the hormone-responsive phenotype of breast cancer. Microarray analyses have revealed that forkhead box A1 (FOXA1) and GATA binding protein 3 (GATA-3) are expressed in close association with ERα, both encoding for transcription factors with a potential involvement in the ERα-mediated action in breast cancer. The purpose of this study was to explore if the expression of FOXA1 and GATA-3 may provide an opportunity to stratify subsets of patients that could have better outcome, among the ERα-negative/poor prognosis breast cancer group.

Methods

We evaluate FOXA1 and GATA-3 expression in 249 breast carcinomas by immunohistochemistry, associating it with breast cancer molecular markers, clinicopathological features and patient's survival. The clinicopathological features and immunohistochemical markers of the tumours were compared using the chi-square test and ANOVA. Disease-free survival was analysed through Kaplan–Meier survival curves and Cox regression.

Results

FOXA1 expression was demonstrated in 42% of invasive carcinomas, while GATA-3 was detected in 48% of the cases. FOXA1 expression was inversely associated with tumour size, Nottingham Prognostic Index, histological grade, lymph vascular invasion, lymph node stage and human epidermal growth factor receptor-2 (HER-2) overexpression, while GATA-3 expression showed inverse association with histological grade and HER-2. Both FOXA1 and GATA-3 were directly associated with ERα and progesterone receptor. Among FOXA1-positive tumours, 83.1% are comprised in the luminal A subtype, similar to GATA-3 where 87.7% of positive tumours were classified within this molecular subtype. In the subset of ERα-negative patients, those who were FOXA1-negative had a 3.61-fold increased risk of breast cancer recurrence when compared with the FOXA1-positive.

Conclusions

FOXA1 was a significant predictor of good outcome in breast cancer, whereas GATA-3 was an important luminal marker. The expression of FOXA1 may be used for risk stratification among ERα-negative patients.

Genetic ablation of caveolin-1 drives estrogen-hypersensitivity and the development of DCIS-like mammary lesions

Caveolin-1 (Cav-1) loss-of-function mutations are exclusively associated with estrogen receptor-positive (ER(+)) human breast cancers. To dissect the role of Cav-1 loss-of-function in the pathogenesis of human breast cancers, we used Cav-1(-/-) null mice as a model system. First, we demonstrated that Cav-1(-/-) mammary epithelia overexpress two well-established ER co-activator genes, CAPER and Foxa1, in addition to ER-alpha. Thus, the functional loss of Cav-1 may be sufficient to confer estrogen-hypersensitivity in the mammary gland. To test this hypothesis directly, we subjected Cav-1(-/-) mice to ovariectomy and estrogen supplementation. As predicted, Cav-1(-/-) mammary glands were hyper-responsive to estrogen and developed dysplastic mammary lesions with adjacent stromal angiogenesis that resemble human ductal carcinoma in situ. Based on an extensive biomarker analysis, these Cav-1(-/-) mammary lesions contain cells that are hyperproliferative and stain positively with nucleolar (B23/nucleophosmin) and stem/progenitor cell markers (SPRR1A and beta-catenin). Genome-wide transcriptional profiling identified many estrogen-related genes that were over-expressed in Cav-1(-/-) mammary glands, including CAPER--an ER co-activator gene and putative stem/progenitor cell marker. Analysis of human breast cancer samples revealed that CAPER is overexpressed and undergoes a cytoplasmic-to-nuclear shift during the transition from pre-malignancy to ductal carcinoma in situ. Thus, Cav-1(-/-) null mice are a new preclinical model for studying the molecular paradigm of estrogen hypersensitivity and the development of estrogen-dependent ductal carcinoma in situ lesions.

Log-Linear Models for Gene Association

We describe a class of log-linear models for the detection of interactions in high-dimensional genomic data. This class of models leads to a Bayesian model selection algorithm that can be applied to data that have been reduced to contingency tables using ranks of observations within subjects, and discretization of these ranks within gene/network components. Many normalization issues associated with the analysis of genomic data are thereby avoided. A prior density based on Ewens' sampling distribution is used to restrict the number of interacting components assigned high posterior probability, and the calculation of posterior model probabilities is expedited by approximations based on the likelihood ratio statistic. Simulation studies are used to evaluate the efficiency of the resulting algorithm for known interaction structures. Finally, the algorithm is validated in a microarray study for which it was possible to obtain biological confirmation of detected interactions.

TranscriptomeBrowser: a powerful and flexible toolbox to explore productively the transcriptional landscape of the Gene Expression Omnibus database

Background

As public microarray repositories are constantly growing, we are facing the challenge of designing strategies to provide productive access to the available data.

Methodology

We used a modified version of the Markov clustering algorithm to systematically extract clusters of co-regulated genes from hundreds of microarray datasets stored in the Gene Expression Omnibus database (n = 1,484). This approach led to the definition of 18,250 transcriptional signatures (TS) that were tested for functional enrichment using the DAVID knowledgebase. Over-representation of functional terms was found in a large proportion of these TS (84%). We developed a JAVA application, TBrowser that comes with an open plug-in architecture and whose interface implements a highly sophisticated search engine supporting several Boolean operators (http://tagc.univ-mrs.fr/tbrowser/). User can search and analyze TS containing a list of identifiers (gene symbols or AffyIDs) or associated with a set of functional terms.

Conclusions/Significance

As proof of principle, TBrowser was used to define breast cancer cell specific genes and to detect chromosomal abnormalities in tumors. Finally, taking advantage of our large collection of transcriptional signatures, we constructed a comprehensive map that summarizes gene-gene co-regulations observed through all the experiments performed on HGU133A Affymetrix platform. We provide evidences that this map can extend our knowledge of cellular signaling pathways.

Identification of gene transcript signatures predictive for estrogen receptor and lymph node status using a stepwise forward selection artificial neural network modelling approach

OBJECTIVE

The advent of microarrays has attracted considerable interest from biologists due to the potential for high throughput analysis of hundreds of thousands of gene transcripts. Subsequent analysis of the data may identify specific features which correspond to characteristics of interest within the population, for example, analysis of gene expression profiles in cancer patients to identify molecular signatures corresponding with prognostic outcome. These high throughput technologies have resulted in an unprecedented rate of data generation, often of high complexity, highlighting the need for novel data analysis methodologies that will cope with data of this nature.

METHODS

Stepwise methods using artificial neural networks (ANNs) have been developed to identify an optimal subset of predictive gene transcripts from highly dimensional microarray data. Here these methods have been applied to a gene microarray dataset to identify and validate gene signatures corresponding with estrogen receptor and lymph node status in breast cancer.

RESULTS

Many gene transcripts were identified whose expression could differentiate patients to very high accuracies based upon firstly whether they were positive or negative for estrogen receptor, and secondly whether metastasis to the axillary lymph node had occurred. A number of these genes had been previously reported to have a role in cancer. Significantly fewer genes were used compared to other previous studies. The models using the optimal gene subsets were internally validated using an extensive random sample cross-validation procedure and externally validated using a follow up dataset from a different cohort of patients on a newer array chip containing the same and additional probe sets. Here, the models retained high accuracies, emphasising the potential power of this approach in analysing complex systems. These findings show how the proposed method allows for the rapid analysis and subsequent detailed interrogation of gene expression signatures to provide a further understanding of the underlying molecular mechanisms that could be important in determining novel prognostic markers associated with cancer.

Genomic analysis of estrogen cascade reveals histone variant H2A.Z associated with breast cancer progression

We demonstrate an integrated approach to the study of a transcriptional regulatory cascade involved in the progression of breast cancer and we identify a protein associated with disease progression. Using chromatin immunoprecipitation and genome tiling arrays, whole genome mapping of transcription factor-binding sites was combined with gene expression profiling to identify genes involved in the proliferative response to estrogen (E2). Using RNA interference, selected ERα and c-MYC gene targets were knocked down to identify mediators of E2-stimulated cell proliferation. Tissue microarray screening revealed that high expression of an epigenetic factor, the E2-inducible histone variant H2A.Z, is significantly associated with lymph node metastasis and decreased breast cancer survival. Detection of H2A.Z levels independently increased the prognostic power of biomarkers currently in clinical use. This integrated approach has accelerated the identification of a molecule linked to breast cancer progression, has implications for diagnostic and therapeutic interventions, and can be applied to a wide range of cancers.

Comparison and identification of estrogen-receptor related gene expression profiles in breast cancer of different ethnic origins

The interactions between genetic variants in estrogen receptor (ER) have been identified to be associated with an increased risk of breast cancer. Available evidence indicates that genetic variance within a population plays a crucial role in the occurrence of breast cancer. Thus, the comparison and identification of ER-related gene expression profiles in breast cancer of different ethnic origins could be useful for the development of genetic variant cancer therapy. In this study, we performed microarray experiment to measure the gene expression profiles of 59 Taiwanese breast cancer patients; and through comparative bioinformatics analysis against published U.K. datasets, we revealed estrogen-receptor (ER) related gene expression between Taiwanese and British patients. In addition, SNP databases and statistical analysis were used to elucidate the SNPs associated with ER status. Our microarray results indicate that the expression pattern of the 65 genes in ER+ patients was dissimilar from that of the ER- patients. Seventeen mutually exclusive genes in ER-related breast cancer of the two populations with more than one statistically significant SNP in genotype and allele frequency were identified. These 17 genes and their related SNPs may be important in population-specific ER regulation of breast cancer. This study provides a global and feasible approach to study population-unique SNPs in breast cancer of different ethnic origins.

FoxA1 translates epigenetic signatures into enhancer-driven lineage-specific transcription

Complex organisms require tissue-specific transcriptional programs, yet little is known about how these are established. The transcription factor FoxA1 is thought to contribute to gene regulation through its ability to act as a pioneer factor binding to nucleosomal DNA. Through genome-wide positional analyses, we demonstrate that FoxA1 cell type-specific functions rely primarily on differential recruitment to chromatin predominantly at distant enhancers rather than proximal promoters. This differential recruitment leads to cell type-specific changes in chromatin structure and functional collaboration with lineage-specific transcription factors. Despite the ability of FoxA1 to bind nucleosomes, its differential binding to chromatin sites is dependent on the distribution of histone H3 lysine 4 dimethylation. Together, our results suggest that methylation of histone H3 lysine 4 is part of the epigenetic signature that defines lineage-specific FoxA1 recruitment sites in chromatin. FoxA1 translates this epigenetic signature into changes in chromatin structure thereby establishing lineage-specific transcriptional enhancers and programs.

Forkhead box A1 expression in breast cancer is associated with luminal subtype and good prognosis

AIMS

Forkhead box A1 (FOXA1) is a forkhead family transcription factor expressed in breast cancer cells. It is essential for optimal expression of approximately 50% of oestrogen receptor (ER)-related genes. This study explored the FOXA1 relationship with luminal and basal breast cancer subtypes, proliferation markers, and survival in breast cancer patients who had received similar treatment.

METHODS

A tissue microarray comprising tumours from 245 invasive breast cancer patients with 67 months of median follow-up was analysed for FOXA1 expression by immunohistochemistry. Interpretable FOXA1 expression, obtained in 184 patients, was analysed along with other variables such as tumour grade, size, nodal status, ER, progesterone receptor, HER2/neu, proliferation and basal markers.

RESULTS

FOXA1 expression (score >3) was seen in 139 of 184 breast cancers. It correlated positively with ERalpha (p<0.0001), progesterone receptor (p<0.0001), and luminal subtype (p<0.0001); negatively with basal subtype (p<0.0001), proliferation markers and high histological grade (p = 0.0327). Univariate analysis showed nodal status, tumour grade, ER, progesterone receptor, FOXA1, basal markers and p53 as significant predictors of overall survival. Multivariate analysis showed that only nodal status (p = 0.0006) and ER (p = 0.0017) were significant predictors of OS. In luminal subtype patient subgroup, FOXA1 expression was associated with better survival (p = 0.0284) on univariate analysis.

CONCLUSION

Based on this study in patients treated with surgery followed by adjuvant anthracycline-based chemotherapy, FOXA1 expression is associated with good prognosis. It correlates with luminal subtype breast cancer, and could possibly serve as a clinical marker for luminal subtype A. Prognostic ability of FOXA1 in these low-risk breast cancers may prove to be useful in treatment decision making.

Unconventional splicing of XBP-1 mRNA in the unfolded protein response

Cytoplasmic splicing is one of the major regulatory mechanisms of the unfolded protein response (UPR). The molecular mechanism of cytoplasmic splicing is unique and completely different from that of conventional nuclear splicing. The mammalian substrate of cytoplasmic splicing is XBP1 pre-mRNA, which is converted to spliced mRNA in response to UPR, leading to the production of an active transcription factor [pXBP1(S)] responsible for UPR. Interestingly, XBP1 pre-mRNA is also translated into a functional protein [pXBP1(U)] that negatively regulates the UPR. Thus, mammalian cells can quickly adapt to a change in conditions in the endoplasmic reticulum by switching proteins encoded in the mRNA from a negative regulator to an activator. This elaborate system contributes to various cellular functions, including plasma cell differentiation, viral infections, and carcinogenesis. In this short review, I briefly summarize research on cytoplasmic splicing and focus on current hot topics.

A mouse model for luminal epithelial like ER positive subtype of human breast cancer

Background

Generation of novel spontaneous ER positive mammary tumor animal model from heterozygous NIH nude mice.

Methods

Using brother-sister mating with pedigree expansion system, we derived a colony of heterozygous breeding females showing ER-Positive tumors around the age of 6 months. Complete blood picture, differential leukocyte count, and serum levels of Estrogen, Alanine amino transferase (SGPT), Aspartate amino transferase (SGOT), total protein and albumin were estimated. Aspiration biopsies and microbiology were carried out. Gross pathology of the tumors and their metastatic potential were assessed. The tumors were excised and further characterized using histopathology, cytology, electron microscopy (EM), molecular markers and Mouse mammary Tumor Virus – Long Terminal Repeats (MMTV LTR) specific RT-PCR.

Results

The tumors originated from 2^ndor 5^thor both the mammary glands and were multi-nodulated with variable central necrosis accompanied with an accumulation of inflammatory exudate. Significant increases in estrogen, SGPT, SGOT and neutrophils levels were noticed. Histopathologically, invasive nodular masses of pleomorphic tubular neoplastic epithelial cells invaded fibro-vascular stroma, adjacent dermis and subcutaneous tissue. Metastatic spread through hematogenous and regional lymph nodes, into liver, lungs, spleen, heart and dermal lymphatics was observed. EM picture revealed no viral particles and MMTV-negativity was confirmed through MMTV LTR-specific RT-PCR. High expression of ER α, moderate to high expression of proliferating cell nuclear antigen (PCNA), moderate expression of vimentin and Cytokeratin 19 (K19) and low expression of p53 were observed in tumor sections, when compared with that of the normal mammary gland.

Conclusion

Since 75% of human breast cancer were classified ER-positive and as our model mimics (in most of the characteristics, such as histopathology, metastasis, high estrogen levels) the ER-positive luminal epithelial-like human breast cancer, this model will be an attractive tool to understand the biology of estrogen-dependant breast cancer in women. To our knowledge, this is the first report of a spontaneous mammary model displaying regional lymph node involvement with both hematogenous and lymphatic spread to liver, lung, heart, spleen and lymph nodes.

BEX2 is overexpressed in a subset of primary breast cancers and mediates nerve growth factor/nuclear factor-kappaB inhibition of apoptosis in breast cancer cell lines

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-kappaB (NF-kappaB) 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-kappaB activation. Here, we show that BEX2 expression is necessary and sufficient for the NGF-mediated inhibition (through NF-kappaB 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 micromol/L). Furthermore, BEX2 overexpression enhances the antiproliferative effect of tamoxifen at pharmacologic dose (1 micromol/L). These data suggest that a NGF/BEX2/NF-kappaB pathway is involved in regulating apoptosis in breast cancer cells and in modulating response to tamoxifen in primary tumors.

FOXA1 expression in breast cancer--correlation with luminal subtype A and survival

PURPOSE

FOXA1, a forkhead family transcription factor, is essential for optimum expression of approximately 50% of estrogen receptor alpha (ERalpha):estrogen responsive genes. FOXA1 is expressed in breast cancer cells. It segregates with genes that characterize the luminal subtypes in DNA microarray analyses. The utility of FOXA1 as a possible independent prognostic factor has not been determined in breast cancers.

MATERIALS AND METHODS

A tissue microarray comprising tumors from 438 patients with 15.4 years median follow-up was analyzed for FOXA1 expression by immunohistochemistry. Interpretable FOXA1 expression obtained in 404 patients was analyzed along with other prognostic factors like tumor grade, size, nodal status, ER, progesterone receptor (PR), and HER2/neu.

RESULTS

FOXA1 expression (score >3) was seen in 300 of 404 breast cancers and it correlated with ER (P = 0.000001), PR (P = 0.00001), and luminal A subtype (P = 0.000001). Loss of expression was noted with worsening tumor grade (P = 0.001). Univariate analysis showed nodal status (P = 0.0000012), tumor size (P = 0.00001), FOXA1 (P = 0.0004), and ER (P = 0.012) to be predictors of breast cancer-specific survival. Multivariate analysis showed only nodal status (P = 0.001) and tumor size (P = 0.039) to be significant prognostic factors, whereas FOXA1 (P = 0.060) and ER (P = 0.131) were not significant. In luminal subtype A patient subgroup, FOXA1 expression was associated with better cancer-specific survival (P = 0.024) and in ER-positive subgroup, it was better predictor of cancer-specific survival (P = 0.009) than PR (P = 0.213).

CONCLUSION

FOXA1 expression correlates with luminal subtype A breast cancer and it is significant predictor of cancer-specific survival in patients with ER-positive tumors. Prognostic ability of FOXA1 in these low-risk breast cancers may prove to be useful in clinical treatment decisions.

Positive Cross-Regulatory Loop Ties GATA-3 to Estrogen Receptor α Expression in Breast Cancer

The transcription factor GATA-3 is required for normal mammary gland development, and its expression is highly correlated with estrogen receptor alpha (ER alpha) in human breast tumors. However, the functional role of GATA-3 in ER alpha-positive breast cancers is yet to be established. Here, we show that GATA-3 is required for estradiol stimulation of cell cycle progression in breast cancer cells. The role of GATA-3 in estradiol signaling requires the direct positive regulation of the expression of the ER alpha gene itself by GATA-3. GATA-3 binds to two cis-regulatory elements located within the ER alpha gene, and this is required for RNA polymerase II recruitment to ER alpha promoters. Reciprocally, ER alpha directly stimulates the transcription of the GATA-3 gene, indicating that these two factors are involved in a positive cross-regulatory loop. Moreover, GATA-3 and ER alpha regulate their own expression in breast cancer cells. Hence, this transcriptional coregulatory mechanism accounts for the robust coexpression of GATA-3 and ER alpha in human breast cancers. In addition, these results highlight the crucial role of GATA-3 for the response of ER alpha-positive breast cancers to estradiol. Moreover, they identify GATA-3 as a critical component of the master cell-type-specific transcriptional network including ER alpha and FoxA1 that dictates the phenotype of hormone-dependent breast cancer.

Estrogen limits ischemic cell death by modulating caspase-12-mediated apoptotic pathways following middle cerebral artery occlusion

Estrogen has received considerable attention as a potential therapeutic agent against various forms of neurodegenerative diseases including stroke. Experimental data in animal models of stroke have provided exhaustive evidence of the neuroprotective properties of this steroid hormone. Our laboratory in particular has demonstrated that acute estrogen treatment in male rats significantly reduced (approximately 50%) ischemic cell death within 4 h following permanent occlusion of the middle cerebral artery occlusion (MCAO). However, the cellular and molecular mechanisms implicated in the protective actions of estrogen in this experimental model have yet to be elucidated. Accumulating evidence suggests that in various in vivo and in vitro models, estrogen can be pro-apoptotic and that this effect may be mediated by an estrogen-induced up-regulation of the Fas/FasL system and the subsequent activation of caspase-12. We therefore hypothesized that under ischemic conditions following MCAO, estrogen would up-regulate protective endoplasmic reticulum (ER) stress pathways leading to caspase-12 activation, thus limiting infarct volume. Our results showed that estrogen significantly increased activated caspase-12 at 2, 3 and 4 h post-MCAO. Immunostaining of brain sections showed a significantly higher number of terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate nick end-labeling positive cells in estrogen-treated animals at 4 h, but not at 2 h, post-MCAO. These findings correlate with previous observations that differences in infarct volume between saline and estrogen-treated animals are not seen until 3 and 4 h post-MCAO. A decrease in m-calpain expression was observed in the infarct region only at 4 h post-MCAO following estrogen pre-treatment, suggesting m-calpain may not be involved in regulating estrogen-induced caspase-12 activation. Based on these cellular changes correlated to estrogen pretreatment, we conclude that estrogen may up-regulate ER-specific apoptotic pathways, thus limiting the extent of necrotic cell death which is responsible for the spreading depression and growth of the infarct volume following MCAO.

Identifying estrogen receptor target genes

The estrogen receptor (ER) is a ligand inducible transcription factor that regulates a large number of target genes. These targets are particularly relevant in breast cancer, where the sensitivity of the tumor to estrogens determines whether the patients can be treated with endocrine therapy such as tamoxifen. Identifying genomic ER targets is a daunting task. Quantifying expression levels of suspected target genes after estradiol stimulation or, more recently, using expression microarrays to this effect will reveal which genes are regulated by estradiol, however, without discriminating between direct and indirect targets. The identification of the palindromic sequence that defines the estrogen responsive element (ERE) allows for the in silico discovery of putative ER targets in the genome. However the ER can also bind imperfect EREs and half sites, and can bind indirectly via other factors. Chromatin immunoprecipitation (ChIP) can yield all ER genomic target sites. Coupling of ChIP with genome-wide tiling arrays allows for the genome-wide unbiased identification of direct ER target sequences.

FOXA1 as a therapeutic target for breast cancer

Gene expression profiling studies have classified breast cancer into five intrinsic subtypes with distinct prognostic significance: luminal type A, luminal type B, normal-like, HER-2-positive and basal type. These studies have also uncovered novel diagnostic markers and molecular targets. FOXA1, a winged-helix transcription factor belonging to the forkhead family, is one among them as it is expressed predominantly in luminal type A breast cancer, which is characterized by the presence of estrogen receptor-alpha (ERalpha) with favorable prognosis. FOXA1 is a 'pioneer' factor that binds to chromatinized DNA, opens the chromatin and enhances binding of ERalpha to its target genes. It is essential for the expression of approximately 50% of ERalpha:estrogen-regulated genes. Thus, a network comprising FOXA1, ERalpha and estrogen constitutes a major proliferation and survival signal for luminal type A breast cancer. However, by controlling differentiation and by regulating the expression of cell cycle inhibitor p27kip1 and the cell adhesion molecule E-cadherin, FOXA1 may prevent metastatic progression of luminal type A breast cancer. This article reviews possible roles of FOXA family transcription factors in breast cancer initiation, hormone dependency and speculates on the potential of FOXA1 as a therapeutic target.

Fog2 excision in mice leads to premature mammary gland involution and reduced Esr1 gene expression

The critical role for GATA family proteins in maintaining the normal (non-transformed) cell state is corroborated by the recent findings of mutations or methylation in GATA genes both in primary cancers and tumor lines including breast. Previously, microarray profiling studies determined that the highest expression of both GATA3 and ESR1 (estrogen receptor alpha) is seen in tumors associated with the most favorable survival outcomes, whereas the lowest expression of GATA3 is detected in tumor subtypes showing the worst outcomes. At this time, genes and pathways that are regulated by GATA3 in the mammary gland are not well defined. We have previously established a requirement for FOG (Friend Of GATA) cofactors during mouse development. Here we report that in the murine mammary gland Fog2 gene expression is upregulated upon pregnancy and lactation with prominent expression in the epithelial cells of the gland during post-lactational regression. Mammary-specific deletion of Fog2 identified a role for this gene during gland involution; excision of the Fog2 gene leads to the accelerated involution of the gland despite diminished levels of the remodeling enzymes. Importantly, the levels of several genes linked to the control of cancerous transformation in the breast (Esr1, Prg and Foxa1) are significantly reduced upon Fog2 excision. This implicates FOG2 in the maintenance of epithelial cell differentiation in the mammary gland and in performing a protective role in breast cancer.

Identification and meta-analysis of a small gene expression signature for the diagnosis of estrogen receptor status in invasive ductal breast cancer

In breast cancer, the determination of estrogen receptor (ER) expression is crucial for the decision on therapeutic strategies. Current ER expression analysis is based on immunohistochemical (IHC) staining of ER on formalin fixed tissue sections. However, low levels of ER expression frequently escape detection because of varying sensitivities of routine histopathological laboratories. Moreover, in estimating ER by IHC the receptor protein only is tested instead of the complex underlying ER pathway, which reflects its biological activity. To overcome this limitation, we have used the microarray technology to study 56 samples of invasive ductal carcinoma. We infer a robust and reliable signature of 10 genes, which is associated with ER expression and presumably therapeutically relevant biological processes. In a meta-analysis, the signature was tested on 3 further independent microarray gene expression data sets, covering different laboratories, array platforms, and clinics. The classification based on the signature showed a very low misclassification rate. In summary, the expression of few genes is sufficient to determine ER status. Future decisions on antiestrogen based therapy in breast cancer could be based on this signature rather than on immunostaining alone.

FOXA1: Growth inhibitor and a favorable prognostic factor in human breast cancer

The transcription factor Forkhead-box A1 (Foxa1), a member of the FOX class of transcription factors, has been implicated in the pathogenesis of lung, esophageal and prostate cancers. We have recently identified transcriptional activation of p27 by FOXA1. In this study, we analyzed the activities and expression pattern of FOXA1 in breast cancer. Forced expression of FOXA1 inhibited clonal growth of breast cancer cell lines, and FOXA1 levels inversely correlated with growth stimuli. In the estrogen receptor (ER)-positive MCF-7 cells, FOXA1 increased p27 promoter activity and inhibited the ER pathway activity. Analysis of FOXA1 expression in breast tissue arrays revealed significantly higher expression in pure ductal carcinomas in situ compared to invasive ductal carcinomas (IDC); and in IDC, high expression of FOXA1 was associated with favorable prognostic factors. Yet, FOXA1 expression was noted in a subset of the ER-negative tumors. Taken together, our findings suggest a growth inhibitory role for FOXA1, and identify it as a novel, potential prognostic factor in breast cancer.

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A cell-type-specific transcriptional network required for estrogen regulation of cyclin D1 and cell cycle progression in breast cancer

Estrogen stimulates the proliferation of the most common type of human breast cancer that expresses estrogen receptor alpha (ERalpha) through the activation of the cyclin D1 (CCND1) oncogene. However, our knowledge of ERalpha transcriptional mechanisms remains limited. Hence, it is still elusive why ERalpha ectopically expressed in ER-negative breast cancer cells (BCC) is functional on ectopic reporter constructs but lacks activity on many endogenous target genes, including CCND1. Here, we show that estradiol (E2) stimulation of CCND1 expression in BCC depends on a novel cell-type-specific enhancer downstream from the CCND1 coding region, which is the primary ERalpha recruitment site in estrogen-responsive cells. The pioneer factor FoxA1 is specifically required for the active chromatin state of this enhancer and as such is crucial for both CCND1 expression and subsequent cell cycle progression. Interestingly, even in BCC, CCND1 levels and proliferation are tightly controlled by E2 through the establishment of a negative feedforward loop involving the induction of NFIC, a putative tumor suppressor capable of directly repressing CCND1 transcription. Taken together, our results reveal an estrogen-regulated combinatorial network including cell-specific cis- and trans-regulators of CCND1 expression where ERalpha collaborates with other transcription factors associated with the ER-positive breast cancer phenotype, including FoxA1 and NFIC.

Discovery and validation of breast cancer subtypes

BACKGROUND

Previous studies demonstrated breast cancer tumor tissue samples could be classified into different subtypes based upon DNA microarray profiles. The most recent study presented evidence for the existence of five different subtypes: normal breast-like, basal, luminal A, luminal B, and ERBB2+.

RESULTS

Based upon the analysis of 599 microarrays (five separate cDNA microarray datasets) using a novel approach, we present evidence in support of the most consistently identifiable subtypes of breast cancer tumor tissue microarrays being: ESR1+/ERBB2-, ESR1-/ERBB2-, and ERBB2+ (collectively called the ESR1/ERBB2 subtypes). We validate all three subtypes statistically and show the subtype to which a sample belongs is a significant predictor of overall survival and distant-metastasis free probability.

CONCLUSION

As a consequence of the statistical validation procedure we have a set of centroids which can be applied to any microarray (indexed by UniGene Cluster ID) to classify it to one of the ESR1/ERBB2 subtypes. Moreover, the method used to define the ESR1/ERBB2 subtypes is not specific to the disease. The method can be used to identify subtypes in any disease for which there are at least two independent microarray datasets of disease samples.

A mixture model-based discriminate analysis for identifying ordered transcription factor binding site pairs in gene promoters directly regulated by estrogen receptor-alpha

MOTIVATION

To detect and select patterns of transcription factor binding sites (TFBSs) which distinguish genes directly regulated by estrogen receptor-alpha (ERalpha), we developed an innovative mixture model-based discriminate analysis for identifying ordered TFBS pairs.

RESULTS

Biologically, our proposed new algorithm clearly suggests that TFBSs are not randomly distributed within ERalpha target promoters (P-value < 0.001). The up-regulated targets significantly (P-value < 0.01) possess TFBS pairs, (DBP, MYC), (DBP, MYC/MAX heterodimer), (DBP, USF2) and (DBP, MYOGENIN); and down-regulated ERalpha target genes significantly (P-value < 0.01) possess TFBS pairs, such as (DBP, c-ETS1-68), (DBP, USF2) and (DBP, MYOGENIN). Statistically, our proposed mixture model-based discriminate analysis can simultaneously perform TFBS pattern recognition, TFBS pattern selection, and target class prediction; such integrative power cannot be achieved by current methods.

AVAILABILITY

The software is available on request from the authors.

CONTACT

lali@iupui.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Identification of prognostic signatures in breast cancer microarray data using Bayesian techniques

We apply a new Bayesian data analysis technique (latent process decomposition) to four recent microarray datasets for breast cancer. Compared to hierarchical cluster analysis, for example, this technique has advantages such as objective assessment of the optimal number of sample or gene clusters in the data, penalization of overcomplex models fitting to noise in the data and a common latent space of explanatory variables for samples and genes. Our analysis provides a clearer insight into these datasets, enabling assignment of patients to one of four principal processes, each with a distinct clinical outcome. One process is indolent and associated with under-expression across a number of genes associated with tumour growth. One process is associated with over expression of GRB7 and ERBB2. The most aggressive process is associated with abnormal expression of transcription factor genes, including members of the FOX family of transcription factor genes.

Combinatorial analysis of transcription factor partners reveals recruitment of c-MYC to estrogen receptor-alpha responsive promoters

In breast cancer and normal estrogen target tissues, estrogen receptor-alpha (ERalpha) signaling results in the establishment of spatiotemporal patterns of gene expression. Whereas primary target gene regulation by ERalpha involves recruitment of coregulatory proteins, coactivators, or corepressors, activation of these downstream promoters by receptor signaling may also involve partnership of ERalpha with other transcription factors. By using an integrated, genome-wide approach that involves ChIP-chip and computational modeling, we uncovered 13 ERalpha-responsive promoters containing both ERalpha and c-MYC binding elements located within close proximity (13-214 bp) to each other. Estrogen stimulation enhanced the c-MYC-ERalpha interaction and facilitated the association of ERalpha, c-MYC, and the coactivator TRRAP with these estrogen-responsive promoters, resulting in chromatin remodeling and increased transcription. These results suggest that ERalpha and c-MYC physically interact to stabilize the ERalpha-coactivator complex, thereby permitting other signal transduction pathways to fine-tune estrogen-mediated signaling networks.

Estrogen receptor target gene: an evolving concept

Estrogen receptor (ER) functions as a transcription factor to induce gene expression events sufficient for cell division and breast cancer progression. A significant body of work exists on the identification of ER gene targets and the cofactors that contribute to these transcription events, yet surprisingly little is known of the cis-regulatory elements involved. In this review, we investigate the advances in technology that contribute to a comprehensive understanding of ER target genes and explore recent work identifying cis-regulatory domains that augment transcription of these targets. Specifically, we find that ER association with gene targets results from an association with the pioneer factor FoxA1, responsible for recruitment of ER to the genome. Recruitment of ER to the genome does not occur at promoter proximal regions, but instead involves distal enhancer elements that function to tether the ER complex to the target gene promoters. These advances in technology permit a more detailed investigation of ER activity and may aid in the development of superior drug interventions.

Chromosome-wide mapping of estrogen receptor binding reveals long-range regulation requiring the forkhead protein FoxA1

Estrogen plays an essential physiologic role in reproduction and a pathologic one in breast cancer. The completion of the human genome has allowed the identification of the expressed regions of protein-coding genes; however, little is known concerning the organization of their cis-regulatory elements. We have mapped the association of the estrogen receptor (ER) with the complete nonrepetitive sequence of human chromosomes 21 and 22 by combining chromatin immunoprecipitation (ChIP) with tiled microarrays. ER binds selectively to a limited number of sites, the majority of which are distant from the transcription start sites of regulated genes. The unbiased sequence interrogation of the genuine chromatin binding sites suggests that direct ER binding requires the presence of Forkhead factor binding in close proximity. Furthermore, knockdown of FoxA1 expression blocks the association of ER with chromatin and estrogen-induced gene expression demonstrating the necessity of FoxA1 in mediating an estrogen response in breast cancer cells.