Prediction Models for DNA Transcription Termination Based on SOM Networks

This paper presents two efficient models for predicting transcription termination (TT) in human DNA. A neural network, self-organizing map, was used for finding features from a human polyadenylation (polyA) sites dataset. We derived prediction models related to different polyA signals. A program, "Dragon PolyAtt", for predicting TT regions was designed for the two most frequent polyA sites "AAUAAA" and "AUUAAA". In our tests, Dragon PolyAtt predicts TT regions with a sensitivity of 48.4% (13.6%) and specificity of 74% (79.1%) when searching for polyA signal "AAUAAA" ("AUUAAA"). Both tests were done on human chromosome 21. Results of Dragon PolyAtt system are substantially better than those obtained by the well-known "polyadq" program.

The estrogen-regulated transcription factor PITX1 coordinates gene-specific regulation by estrogen receptor-alpha in breast cancer cells

The estrogen receptor α (ERα) is a master regulator of gene expression and works along with cooperating transcription factors in mediating the actions of the hormone estradiol (E2) in ER-positive tissues and breast tumors. Here, we report that expression of paired-like homeodomain transcription factor (PITX1), a tumor suppressor and member of the homeobox family of transcription factors, is robustly up-regulated by E2 in several ERα-positive breast cancer cell lines via ERα-dependent interaction between the proximal promoter and an enhancer region 5' upstream of the PITX1 gene. Overexpression of PITX1 selectively inhibited the transcriptional activity of ERα and ERβ, while enhancing the activities of the glucocorticoid receptor and progesterone receptor. Reduction of PITX1 by small interfering RNA enhanced ERα-dependent transcriptional regulation of a subset of ERα target genes. The consensus PITX1 binding motif was found to be present in 28% of genome-wide ERα binding sites and was in close proximity to estrogen response elements in a subset of ERα binding sites, and E2 treatment enhanced PITX1 as well as ERα recruitment to these binding sites. These studies identify PITX1 as a new ERα transcriptional target that acts as a repressor to coordinate and fine tune target-specific, ERα-mediated transcriptional activity in human breast cancer cells.

Genetic variation of ESR1 and its co-activator PPARGC1B is synergistic in augmenting the risk of estrogen receptor-positive breast cancer

Introduction

Given the role of estrogen in breast carcinogenesis and the modification of estrogen receptor (ER) activity by its biochemical cofactors, we hypothesize that genetic variation within ER cofactor genes alters cellular response to estrogen exposure and consequently modifies the risk for ER-positive breast cancer.

Methods

We genotyped 790 tagging SNPs within 60 ER cofactor genes in 1,257 cases and 1,464 controls from Sweden and in 2,215 cases and 1,265 controls from Finland, and tested their associations with either ER-positive or ER-negative breast cancer.

Results

Seven SNPs showed consistent association with ER-positive breast cancer in the two independent samples, and six of them were located within PPARGC1B, encoding an ER co-activator, with the strongest association at rs741581 (odds ratio = 1.41, P = 4.84 × 10^-5) that survived Bonferroni correction for multiple testing in the combined ER-positive breast cancer sample (P_corrected = 0.03). Moreover, we also observed significant synergistic interaction (P_interaction = 0.008) between the genetic polymorphisms within PPARGC1B and ESR1 in ER-positive breast cancer. By contrast, no consistent association was observed in ER-negative breast cancer. Furthermore, we found that administration of estrogen in the MCF-7 cell line induced PPARGC1B expression and enhanced occupancies of ER and RNA polymerase II within the region of SNP association, suggesting the upregulation of PPARGC1B expression by ESR1 activation.

Conclusions

Our study revealed that DNA polymorphisms of PPARGC1B, coding a bona fide ER co-activator, are associated with ER-positive breast cancer risk. The feed-forward transcriptional regulatory loop between PPARGC1B and ESR1 further augments their protein interaction, which provides a plausible mechanistic explanation for the synergistic genetic interaction between PPARGC1B and ESR1 in ER-positive breast cancer. Our study also highlights that biochemically and genomically informed candidate gene studies can enhance the discovery of interactive disease susceptibility genes.

Genome-wide dynamics of chromatin binding of estrogen receptors alpha and beta: mutual restriction and competitive site selection

Estrogen receptors ERalpha and ERbeta, members of the nuclear receptor superfamily, exert profound effects on the gene expression and biological response programs of their target cells. Herein, we explore the dynamic interplay between these two receptors in their selection of chromatin binding sites when present separately or together in MCF-7 breast cancer cells. Treatment of cells (containing ERalpha only, ERbeta only, or ERalpha and ERbeta) with estradiol or ER subtype-selective ligands was followed by chromatin immunoprecipitation analysis with a custom-designed tiling array for ER binding sites across the genome to examine the effects of ligand-occupied and unoccupied ERalpha and ERbeta on chromatin binding. There was substantial overlap in binding sites for these estradiol-liganded nuclear receptors when present alone, but many fewer sites were shared when both ERs were present. Each ER restricted the binding site occupancy of the other, with ERalpha generally being dominant. Binding sites of both receptors were highly enriched in estrogen response element motifs, but when both ERs were present, ERalpha displaced ERbeta, shifting it into new sites less enriched in estrogen response elements. Binding regions of the two ERs also showed differences in their enrichments for other transcription factor binding motifs. Studies with ER subtype-specific ligands revealed that it was the liganded subtype that principally determined the spectrum of chromatin binding. These findings highlight the dynamic interplay between the two ERs in their selection of chromatin binding sites, with competition, restriction, and site shifting having important implications for the regulation of gene expression by these two nuclear receptors.

Estrogen Receptors alpha and beta as determinants of gene expression: influence of ligand, dose, and chromatin binding

Estrogen receptors alpha and beta (ERalpha and ERbeta) mediate the actions of estrogens in a variety of normal and cancer target cells. Estrogens differ in their preference for these ERs, and many phytoestrogens bind preferentially to ERbeta. To investigate how phytoestrogens such as genistein impact ER-regulated gene expression, we used adenoviral gene delivery of ERbeta coupled with ERalpha depletion with small interfering RNA to generate human breast cancer (MCF-7) cells expressing four complements of ERalpha and ERbeta. We examined the dose-dependent effects of genistein on genome-wide gene expression by DNA microarrays and monitored the recruitment of ERs and coregulators to responsive regions of estrogen-regulated genes. At a low (6 nm) concentration, genistein regulated gene expression much more effectively in cells coexpressing ERalpha and ERbeta than in cells expressing ERalpha alone, whereas at high concentration (300 nm), genistein induced transcriptome changes very similar to that of 17beta-estradiol. We demonstrate that ERbeta is preferentially activated by genistein and is recruited to estrogen-responsive genomic sites and that differential occupancy of ERalpha and ERbeta by genistein and 17beta-estradiol in turn influences the recruitment patterns of coregulators such as steroid receptor coactivator 3 (SRC3) and receptor-interacting protein 140 (RIP140). Our observations indicate that genistein is a potency-selective ligand for gene expression regulation by ERalpha and ERbeta and that the ability of ERalpha and ERbeta to serve as determinants of gene expression is greatly influenced by the nature of the ligand, by ligand dose, and by the differential abilities of ligand-ER complexes to recruit different coregulators at ER binding sites of hormone-regulated genes.

Whole-genome cartography of estrogen receptor alpha binding sites

Using a chromatin immunoprecipitation-paired end diTag cloning and sequencing strategy, we mapped estrogen receptor α (ERα) binding sites in MCF-7 breast cancer cells. We identified 1,234 high confidence binding clusters of which 94% are projected to be bona fide ERα binding regions. Only 5% of the mapped estrogen receptor binding sites are located within 5 kb upstream of the transcriptional start sites of adjacent genes, regions containing the proximal promoters, whereas vast majority of the sites are mapped to intronic or distal locations (>5 kb from 5′ and 3′ ends of adjacent transcript), suggesting transcriptional regulatory mechanisms over significant physical distances. Of all the identified sites, 71% harbored putative full estrogen response elements (EREs), 25% bore ERE half sites, and only 4% had no recognizable ERE sequences. Genes in the vicinity of ERα binding sites were enriched for regulation by estradiol in MCF-7 cells, and their expression profiles in patient samples segregate ERα-positive from ERα-negative breast tumors. The expression dynamics of the genes adjacent to ERα binding sites suggest a direct induction of gene expression through binding to ERE-like sequences, whereas transcriptional repression by ERα appears to be through indirect mechanisms. Our analysis also indicates a number of candidate transcription factor binding sites adjacent to occupied EREs at frequencies much greater than by chance, including the previously reported FOXA1 sites, and demonstrate the potential involvement of one such putative adjacent factor, Sp1, in the global regulation of ERα target genes. Unexpectedly, we found that only 22%–24% of the bona fide human ERα binding sites were overlapping conserved regions in whole genome vertebrate alignments, which suggest limited conservation of functional binding sites. Taken together, this genome-scale analysis suggests complex but definable rules governing ERα binding and gene regulation.

Estrogen receptors (ERs) play key roles in facilitating the transcriptional effects of hormone functions in target tissues. To obtain a genome-wide view of ERα binding sites, we applied chromatin immunoprecipitation coupled with a cloning and sequencing strategy using chromatin immunoprecipitation pair end-tagging technology to map ERα binding sites in MCF-7 human breast cancer cells. We identified 1,234 high quality ERα binding sites in the human genome and demonstrated that the binding sites are frequently adjacent to genes significantly associated with breast cancer disease status and outcome. The mapping results also revealed that ERα can influence gene expression across distances of up to 100 kilobases or more, that genes that are induced or repressed utilize sites in different regions relative to the transcript (suggesting different mechanisms of action), and that ERα binding sites are only modestly conserved in evolution. Using computational approaches, we identified potential interactions with other transcription factor binding sites adjacent to the ERα binding elements. Taken together, these findings suggest complex but definable rules governing ERα binding and gene regulation and provide a valuable dataset for mapping the precise control nodes for one of the most important nuclear hormone receptors in breast cancer biology.