Xiaoyue Zhao

Estrogen Receptor β Binds to and Regulates Three Distinct Classes of Target Genes

Estrogen receptor β (ERβ) has potent antiproliferative and anti-inflammatory properties, suggesting that ERβ-selective agonists might be a new class of therapeutic and chemopreventative agents. To understand how ERβ regulates genes, we identified genes regulated by the unliganded and liganded forms of ERα and ERβ in U2OS cells. Microarray data demonstrated that virtually no gene regulation occurred with unliganded ERα, whereas many genes were regulated by estradiol (E2). These results demonstrated that ERα requires a ligand to regulate a single class of genes. In contrast, ERβ regulated three classes of genes. Class I genes were regulated primarily by unliganded ERβ. Class II genes were regulated only with E2, whereas class III genes were regulated by both unliganded ERβ and E2. There were 453 class I genes, 258 class II genes, and 83 class III genes. To explore the mechanism whereby ERβ regulates different classes of genes, chromatin immunoprecipitation-sequencing was performed to identify ERβ binding sites and adjacent transcription factor motifs in regulated genes. AP1 binding sites were more enriched in class I genes, whereas ERE, NFκB1, and SP1 sites were more enriched in class II genes. ERβ bound to all three classes of genes, demonstrating that ERβ binding is not responsible for differential regulation of genes by unliganded and liganded ERβ. The coactivator NCOA2 was differentially recruited to several target genes. Our findings indicate that the unliganded and liganded forms of ERβ regulate three classes of genes by interacting with different transcription factors and coactivators.

Finding short DNA motifs using permuted markov models

Many short DNA motifs such as transcription factor binding sites (TFBS) and splice sites exhibit strong local as well as non-local dependence. We introduce permuted variable length Markov models (PVLMM) which could capture the potentially important dependencies among positions, and apply them to the problem of detecting splice and TFB sites. They have been satisfactory from the viewpoint of prediction performance, and also give ready biological interpretations of the sequence dependence observed. The issue of model selection is also studied.

Drug and Cell Type-Specific Regulation of Genes with Different Classes of Estrogen Receptor β-Selective Agonists

Estrogens produce biological effects by interacting with two estrogen receptors, ERα and ERβ. Drugs that selectively target ERα or ERβ might be safer for conditions that have been traditionally treated with non-selective estrogens. Several synthetic and natural ERβ-selective compounds have been identified. One class of ERβ-selective agonists is represented by ERB-041 (WAY-202041) which binds to ERβ much greater than ERα. A second class of ERβ-selective agonists derived from plants include MF101, nyasol and liquiritigenin that bind similarly to both ERs, but only activate transcription with ERβ. Diarylpropionitrile represents a third class of ERβ-selective compounds because its selectivity is due to a combination of greater binding to ERβ and transcriptional activity. However, it is unclear if these three classes of ERβ-selective compounds produce similar biological activities. The goals of these studies were to determine the relative ERβ selectivity and pattern of gene expression of these three classes of ERβ-selective compounds compared to estradiol (E2), which is a non-selective ER agonist. U2OS cells stably transfected with ERα or ERβ were treated with E2 or the ERβ-selective compounds for 6 h. Microarray data demonstrated that ERB-041, MF101 and liquiritigenin were the most ERβ-selective agonists compared to estradiol, followed by nyasol and then diarylpropionitrile. FRET analysis showed that all compounds induced a similar conformation of ERβ, which is consistent with the finding that most genes regulated by the ERβ-selective compounds were similar to each other and E2. However, there were some classes of genes differentially regulated by the ERβ agonists and E2. Two ERβ-selective compounds, MF101 and liquiritigenin had cell type-specific effects as they regulated different genes in HeLa, Caco-2 and Ishikawa cell lines expressing ERβ. Our gene profiling studies demonstrate that while most of the genes were commonly regulated by ERβ-selective agonists and E2, there were some genes regulated that were distinct from each other and E2, suggesting that different ERβ-selective agonists might produce distinct biological and clinical effects.

Finding short DNA motifs using permuted Markov models.

Many short DNA motifs, such as transcription factor binding sites (TFBS) and splice sites, exhibit strong local as well as nonlocal dependence. We introduce permuted variable length Markov models (PVLMM) which could capture the potentially important dependencies among positions and apply them to the problem of detecting splice and TFB sites. They have been satisfactory from the viewpoint of prediction performance and also give ready biological interpretations of the sequence dependence observed. The issue of model selection is also studied.

Cell type- and estrogen receptor-subtype specific regulation of selective estrogen receptor modulator regulatory elements

Selective estrogen receptor modulators (SERMs), such as tamoxifen and raloxifene can act as estrogen receptor (ER) antagonists or agonists depending on the cell type. The antagonistic action of tamoxifen has been invaluable for treating breast cancer, whereas the agonist activity of SERMs also has important clinical applications as demonstrated by the use of raloxifene for osteoporosis. Whereas the mechanism whereby SERMs function as antagonists has been studied extensively very little is known about how SERMs produce agonist effects in different tissues with the two ER types; ERalpha and ERbeta. We examined the regulation of 32 SERM-responsive regions with ERalpha and ERbeta in transiently transfected MCF-7 breast, Ishikawa endometrial, HeLa cervical and WAR-5 prostate cancer cells. The regions were regulated by tamoxifen and raloxifene in some cell types, but not in all cell lines. Tamoxifen activated similar number of regions with ERalpha and ERbeta in the cell lines, whereas raloxifene activated over twice as many regions with ERbeta compared to ERalpha. In Ishikawa endometrial cancer cells, tamoxifen activated 17 regions with ERalpha, whereas raloxifene activated only 2 regions, which might explain their different effects on the endometrium. Microarray studies also found that raloxifene regulated fewer genes than tamoxifen in U2OS bone cancer cells expressing ERalpha, whereas tamoxifen was equally effective at regulating genes with ERalpha and ERbeta. Our studies indicate that tamoxifen is a non-selective agonist, whereas raloxifene is a relative ERbeta-selective agonist, and suggest that ERbeta-selective SERMs might be safer for treating clinical conditions that are dependent on the agonist property of SERMs.

Selective concomitant inhibition of mTORC1 and mTORC2 activity in estrogen receptor negative breast cancer cells by BN107 and oleanolic acid.

Hormonal, targeted and chemotherapeutic strategies largely depend on the expression of their cognate receptors and are often accompanied by intolerable toxicities. Effective and less toxic therapies for estrogen receptor negative (ER−) breast cancers are urgently needed. Here, we present the potential molecular mechanisms mediating the selective pro‐apoptotic effect induced by BN107 and its principle terpene, oleanolic acid (OA), on ER− breast cancer cells. A panel of breast cancer cell lines was examined and the most significant cytotoxic effect was observed in ER− breast lines. Apoptosis was the major cellular pathway mediating the cytotoxicity of BN107. We demonstrated that sensitivity to BN107 was correlated to the status of ERα. Specifically, the presence of functional ERα protected cells from BN107‐induced apoptosis and absence of ERα increased the sensitivity. BN107, an extract rich in OA derivatives, caused rapid alterations in cholesterol homeostasis, presumably by depleting cholesterol in lipid rafts (LRs), which subsequently interfered with signaling mediated by LRs. We showed that BN107 or OA treatment in ER− breast cancer cells resulted in rapid and specific inhibition of LR‐mediated survival signaling, namely mTORC1 and mTORC2 activities, by decreasing the levels of the mTOR/FRAP1, RAPTOR and RICTOR. Cotreatment with cholesterol abolished the proapoptotic effect and restored the disrupted mTOR activities. This is the first report demonstrating possible concomitant inhibition of both mTORC1 and mTORC2 activities by modulating the levels of protein constituents present in these signaling complexes, and thus provides a basis for future development of OA‐based mTOR inhibitors.

Finding anchors for genomic sequence comparison

Recent sequencing of the human and other mammalian genomes has brought about the necessity to align them, to identify and characterize their commonalities and differences. Programs that align whole genomes generally use a seed-and-extend technique, starting from exact or near-exact matches and selecting a reliable subset of these, called anchors, and then filling in the remaining portions between the anchors using a combination of local and global alignment algorithms, but their choices for the parameters so far have been primarily heuristic. We present a statistical framework and practical methods for selecting a set of matches that is both sensitive and specific and can constitute a reliable set of anchors for a one-to-one mapping of two genomes from which a whole-genome alignment can be built. Starting from exact matches, we introduce a novel per-base repeat annotation, the

Unliganded estrogen receptor-β regulation of genes is inhibited by tamoxifen

Z

Estrogenic Plant Extracts Reverse Weight Gain and Fat Accumulation without Causing Mammary Gland or Uterine Proliferation

-score, from which noise and repeat filtering conditions are explored. Dynamic programming-based chaining algorithms are also evaluated as context-based filters. We apply the methods described here to the comparison of two progressive assemblies of the human genome, NCBI build 28 and build 34 http://genome.ucsc.edu), and show that a significant portion of the two genomes can be found in selected exact matches, with very limited amount of sequence duplication.

Finding anchors for genomic sequence comparison.

Tamoxifen can stimulate the growth of some breast tumors and others can become resistant to tamoxifen. We previously showed that unliganded ERbeta inhibits ERalpha-mediated proliferation of MCF-7 cells. We investigated if tamoxifen might have a potential negative effect on some breast cancer cells by blocking the effects of unliganded ERbeta on gene regulation. Gene expression profiles demonstrated that unliganded ERbeta upregulated 196 genes in MCF-7 cells. Tamoxifen significantly inhibited 73 of these genes by greater than 30%, including several growth-inhibitory genes. To explore the mechanism whereby unliganded ERbeta activates genes and how tamoxifen blocks this effect, we used doxycycline-inducible U2OS-ERbeta cells to produce unliganded ERbeta. Doxycycline produced a dose-dependent activation of the NKG2E, MSMB and TUB3A genes, which was abolished by tamoxifen. Unliganded ERbeta recruitment of SRC-2 to the NKG2E gene was blocked by tamoxifen. Our findings suggest that tamoxifen might exert a negative effect on ERbeta expressing tumors due to its antagonistic action on unliganded ERbeta.