A comprehensive nuclear receptor network for breast cancer cells

Construction and Analysis of a Mitochondrial Metabolism-Related Prognostic Model for Breast Cancer to Evaluate Survival and Immunotherapy

As one of the most prevalent malignancies among women, breast cancer (BC) is tightly linked to metabolic dysfunction. However, the correlation between mitochondrial metabolism-related genes (MMRGs) and BC remains unclear. The training and validation datasets for BC were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases, respectively. MMRG-related data were obtained from the Molecular Signatures Database. A risk score prognostic model incorporating MMRGs was established based on univariate, LASSO, and multivariate Cox regression analyses. Independent factors affecting BC prognosis were identified through regression analysis and presented in a nomogram. Single-sample gene set enrichment analysis was employed to assess the immune levels of high-risk (HR) and low-risk (LR) groups. The sensitivity of BC patients in the two groups to common anti-tumor drugs was evaluated by utilizing the Genomics of Drug Sensitivity in Cancer database. 12 MMRGs significantly associated with survival were selected from 1234 MMRGs. A 12-gene risk score prognostic model was built. In the multivariate regression analysis incorporating classical clinical factors, the MMRG-related risk score remained an independent prognostic factor. As revealed by tumor immune microenvironment analysis, the LR group with higher survival rates had elevated immune levels. The drug sensitivity results unmasked that the LR group demonstrated higher sensitivity to Irinotecan, Nilotinib, and Oxaliplatin, while the HR group demonstrated higher sensitivity to Lapatinib. The development of MMRG characteristics provides a comprehensive understanding of mitochondrial metabolism in BC, aiding in the prediction of prognosis and tumor microenvironment, and offering promising therapeutic choices for BC patients with different MMRG risk scores.

Steroid hormone signaling synchronizes cell migration machinery, adhesion and polarity to direct collective movement

Migratory cells - either individually or in cohesive groups - are critical for spatiotemporally regulated processes such as embryonic development and wound healing. Their dysregulation is the underlying cause of formidable health problems such as congenital abnormalities and metastatic cancers. Border cell behavior during Drosophila oogenesis provides an effective model to study temporally regulated, collective cell migration in vivo. Developmental timing in flies is primarily controlled by the steroid hormone ecdysone, which acts through a well-conserved, nuclear hormone receptor complex. Ecdysone signaling determines the timing of border cell migration, but the molecular mechanisms governing this remain obscure. We found that border cell clusters expressing a dominant-negative form of ecdysone receptor extended ineffective protrusions. Additionally, these clusters had aberrant spatial distributions of E-cadherin (E-cad), apical domain markers and activated myosin that did not overlap. Remediating their expression or activity individually in clusters mutant for ecdysone signaling did not restore proper migration. We propose that ecdysone signaling synchronizes the functional distribution of E-cadherin, atypical protein kinase C (aPKC), Discs large (Dlg1) and activated myosin post-transcriptionally to coordinate adhesion, polarity and contractility and temporally control collective cell migration.

The contributions of DNA accessibility and transcription factor occupancy to enhancer activity during cellular differentiation

During gene regulation, DNA accessibility is thought to limit the availability of transcription factor (TF) binding sites, while TFs can increase DNA accessibility to recruit additional factors that upregulate gene expression. Given this interplay, the causative regulatory events in the modulation of gene expression remain unknown for the vast majority of genes. We utilized deeply sequenced ATAC-Seq data and site-specific knock-in reporter genes to investigate the relationship between the binding-site resolution dynamics of DNA accessibility and the expression dynamics of the enhancers of Cebpa during macrophage-neutrophil differentiation. While the enhancers upregulate reporter expression during the earliest stages of differentiation, there is little corresponding increase in their total accessibility. Conversely, total accessibility peaks during the last stages of differentiation without any increase in enhancer activity. The accessibility of positions neighboring C/EBP-family TF binding sites, which indicates TF occupancy, does increase significantly during early differentiation, showing that the early upregulation of enhancer activity is driven by TF binding. These results imply that a generalized increase in DNA accessibility is not sufficient, and binding by enhancer-specific TFs is necessary, for the upregulation of gene expression. Additionally, high-coverage ATAC-Seq combined with time-series expression data can infer the sequence of regulatory events at binding-site resolution.

Epigenetic disruption of the RARγ complex impairs its function to bookmark AR enhancer interactions required for enzalutamide sensitivity in prostate cancer

The current study in prostate cancer (PCa) focused on the genomic mechanisms at the cross-roads of pro-differentiation signals and the emergence of lineage plasticity. We explored an understudied cistromic mechanism involving RARγ's ability to govern AR cistrome-transcriptome relationships, including those associated with more aggressive PCa features. The RARγ complex in PCa cell models was enriched for canonical cofactors, as well as proteins involved in RNA processing and bookmarking. Identifying the repertoire of miR-96 bound and regulated gene targets, including those recognition elements marked by m6A, revealed their significant enrichment in the RARγ complex. RARγ significantly enhanced the AR cistrome, particularly in active enhancers and super-enhancers, and overlapped with the binding of bookmarking factors. Furthermore, RARγ expression led to nucleosome-free chromatin enriched with H3K27ac, and significantly enhanced the AR cistrome in G2/M cells. RARγ functions also antagonized the transcriptional actions of the lineage master regulator ONECUT2. Similarly, gene programs regulated by either miR-96 or antagonized by RARγ were enriched in alternative lineages and more aggressive PCa phenotypes. Together these findings reveal an under-investigated role for RARγ, modulated by miR-96, to bookmark enhancer sites during mitosis. These sites are required by the AR to promote transcriptional competence, and emphasize luminal differentiation, while antagonizing ONECUT2.

International Union of Basic and Clinical Pharmacology CXIII: Nuclear Receptor Superfamily-Update 2023

The NR superfamily comprises 48 transcription factors in humans that control a plethora of gene network programs involved in a wide range of physiologic processes. This review will summarize and discuss recent progress in NR biology and drug development derived from integrating various approaches, including biophysical techniques, structural studies, and translational investigation. We also highlight how defective NR signaling results in various diseases and disorders and how NRs can be targeted for therapeutic intervention via modulation via binding to synthetic lipophilic ligands. Furthermore, we also review recent studies that improved our understanding of NR structure and signaling. SIGNIFICANCE STATEMENT: Nuclear receptors (NRs) are ligand-regulated transcription factors that are critical regulators of myriad physiological processes. NRs serve as receptors for an array of drugs, and in this review, we provide an update on recent research into the roles of these drug targets.

MicroRNA-Mediated Regulation of Histone-Modifying Enzymes in Cancer: Mechanisms and Therapeutic Implications

In the past decade, significant advances in molecular research have provided a deeper understanding of the intricate regulatory mechanisms involved in carcinogenesis. MicroRNAs, short non-coding RNA sequences, exert substantial influence on gene expression by repressing translation or inducing mRNA degradation. In the context of cancer, miRNA dysregulation is prevalent and closely associated with various stages of carcinogenesis, including initiation, progression, and metastasis. One crucial aspect of the cancer phenotype is the activity of histone-modifying enzymes that govern chromatin accessibility for transcription factors, thus impacting gene expression. Recent studies have revealed that miRNAs play a significant role in modulating these histone-modifying enzymes, leading to significant implications for genes related to proliferation, differentiation, and apoptosis in cancer cells. This article provides an overview of current research on the mechanisms by which miRNAs regulate the activity of histone-modifying enzymes in the context of cancer. Both direct and indirect mechanisms through which miRNAs influence enzyme expression are discussed. Additionally, potential therapeutic implications arising from miRNA manipulation to selectively impact histone-modifying enzyme activity are presented. The insights from this analysis hold significant therapeutic promise, suggesting the utility of miRNAs as tools for the precise regulation of chromatin-related processes and gene expression. A contemporary focus on molecular regulatory mechanisms opens therapeutic pathways that can effectively influence the control of tumor cell growth and dissemination.

LucFlow: A method to measure Luciferase reporter expression in single cells

Reporter assays, in which the expression of an inert protein is driven by gene regulatory elements such as promoters and enhancers, are a workhorse for investigating gene regulation. Techniques for measuring reporter gene expression vary from single-cell or single-molecule approaches having low throughput to bulk Luciferase assays that have high throughput. We developed a Luciferase Reporter Assay using Flow-Cytometry (LucFlow), which measures reporter expression in single cells immunostained for Luciferase. We optimized and tested LucFlow with a murine cell line that can be differentiated into neutrophils, into which promoter-reporter and enhancer-promoter-reporter constructs have been integrated in a site-specific manner. The single-cell measurements are comparable to bulk ones but we found that dead cells have no detectable Luciferase protein, so that bulk assays underestimate reporter expression. LucFlow is able to achieve a higher accuracy than bulk methods by excluding dead cells during flow cytometry. Prior to fixation and staining, the samples are spiked with stained cells that can be discriminated during flow cytometry and control for tube-to-tube variation in experimental conditions. Computing fold change relative to control cells allows LucFlow to achieve a high level of precision. LucFlow, therefore, enables the accurate and precise measurement of reporter expression in a high throughput manner.

The contributions of DNA accessibility and transcription factor occupancy to enhancer activity during cellular differentiation

The upregulation of gene expression by enhancers depends upon the interplay between the binding of sequence-specific transcription factors (TFs) and DNA accessibility. DNA accessibility is thought to limit the ability of TFs to bind to their sites, while TFs can increase accessibility to recruit additional factors that upregulate gene expression. Given this interplay, the causative regulatory events underlying the modulation of gene expression during cellular differentiation remain unknown for the vast majority of genes. We investigated the binding-site resolution dynamics of DNA accessibility and the expression dynamics of the enhancers of an important neutrophil gene, Cebpa, during macrophage-neutrophil differentiation. Reporter genes were integrated in a site-specific manner in PUER cells, which are progenitors that can be differentiated into neutrophils or macrophages in vitro by activating the pan-leukocyte TF PU.1. Time series data show that two enhancers upregulate reporter expression during the first 48 hours of neutrophil differentiation. Surprisingly, there is little or no increase in the total accessibility, measured by ATAC-Seq, of the enhancers during the same time period. Conversely, total accessibility peaks 96 hrs after PU.1 activation-consistent with its role as a pioneer-but the enhancers do not upregulate gene expression. Combining deeply sequenced ATAC-Seq data with a new bias-correction method allowed the profiling of accessibility at single-nucleotide resolution and revealed protected regions in the enhancers that match all previously characterized TF binding sites and ChIP-Seq data. Although the accessibility of most positions does not change during early differentiation, that of positions neighboring TF binding sites, an indicator of TF occupancy, did increase significantly. The localized accessibility changes are limited to nucleotides neighboring C/EBP-family TF binding sites, showing that the upregulation of enhancer activity during early differentiation is driven by C/EBP-family TF binding. These results show that increasing the total accessibility of enhancers is not sufficient for upregulating their activity and other events such as TF binding are necessary for upregulation. Also, TF binding can cause upregulation without a perceptible increase in total accessibility. Finally, this study demonstrates the feasibility of comprehensively mapping individual TF binding sites as footprints using high coverage ATAC-Seq and inferring the sequence of events in gene regulation by combining with time-series gene expression data.

The Role of PPARs in Breast Cancer

Breast cancer is a malignant tumor with high morbidity and lethality. Its pathogenesis is related to the abnormal expression of many genes. The peroxisome proliferator-activated receptors (PPARs) are a class of ligand-dependent transcription factors in the nuclear receptor superfamily. They can regulate the transcription of a large number of target genes, which are involved in life activities such as cell proliferation, differentiation, metabolism, and apoptosis, and regulate physiological processes such as glucose metabolism, lipid metabolism, inflammation, and wound healing. Further, the changes in its expression are associated with various diseases, including breast cancer. The experimental reports related to "PPAR" and "breast cancer" were retrieved from PubMed since the discovery of PPARs and summarized in this paper. This review (1) analyzed the roles and potential molecular mechanisms of non-coordinated and ligand-activated subtypes of PPARs in breast cancer progression; (2) discussed the correlations between PPARs and estrogen receptors (ERs) as the nuclear receptor superfamily; and (3) investigated the interaction between PPARs and key regulators in several signaling pathways. As a result, this paper identifies PPARs as targets for breast cancer prevention and treatment in order to provide more evidence for the synthesis of new drugs targeting PPARs or the search for new drug combination treatments.

Hepatic Adropin is Regulated by Estrogen and Contributes to Adverse Metabolic Phenotypes in Ovariectomized Mice

Objective

Menopause is associated with visceral adiposity, hepatic steatosis and increased risk for cardiovascular disease. As estrogen replacement therapy is not suitable for all postmenopausal women, a need for alternative therapeutics and biomarkers has emerged.

Methods

9-week-old C57BL/6 J female mice were subjected to ovariectomy (OVX) or SHAM surgery (n = 10 per group), fed a standard diet and sacrificed 6- & 12 weeks post-surgery.

Results

Increased weight gain, hepatic triglyceride content and changes in hepatic gene expression of Cyp17a1, Rgs16, Fitm1 as well as Il18, Rares2, Retn, Rbp4 in mesenteric visceral adipose tissue (VAT) were observed in OVX vs. SHAM. Liver RNA-sequencing 6-weeks post-surgery revealed changes in genes and microRNAs involved in fat metabolism in OVX vs. SHAM mice. Energy Homeostasis Associated gene (Enho) coding for the hepatokine adropin was significantly reduced in OVX mice livers and strongly inversely correlated with weight gain (r = −0.7 p < 0.001) and liver triglyceride content (r = −0.4, p = 0.04), with a similar trend for serum adropin. In vitro, Enho expression was tripled by 17β-estradiol in BNL 1 ME liver cells with increased adropin in supernatant. Analysis of open-access datasets revealed increased hepatic Enho expression in estrogen treated OVX mice and estrogen dependent ERα binding to Enho. Treatment of 5-month-old OVX mice with Adropin (i.p. 450 nmol/kg/twice daily, n = 4,5 per group) for 6-weeks reversed adverse adipokine gene expression signature in VAT, with a trended increase in lean body mass and decreased liver TG content with upregulation of Rgs16.

Conclusions

OVX is sufficient to induce deranged metabolism in adult female mice. Hepatic adropin is regulated by estrogen, negatively correlated with adverse OVX-induced metabolic phenotypes, which were partially reversed with adropin treatment. Adropin should be further explored as a potential therapeutic target and biomarker for menopause-related metabolic derangement.

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OVX increased body weight, liver fat & adverse visceral fat adipokine signature.

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OVX altered liver transcriptome & miRNA profile including fat metabolism pathways.

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Enho was downregulated by OVX & inversely correlated with weight gain & liver fat.

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Hepatic adropin expression was upregulated by estrogen in-vitro & in-vivo.

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Adropin treatment partially reversed OVX induced adverse metabolic phenotypes.

Assessing Performance of Wastewater Treatment Using in Vitro Cell-based Assays

Bioanalytical tools, namely in vitro bioassays, can be employed in tandem with chemical analyses to assess the efficacy of wastewater treatment and the potential for adverse effects from the discharges of wastewater into receiving waters. In the present study, samples of untreated wastewater (i.e., influent) and treated wastewater (i.e., effluent) were collected from two wastewater treatment plants and a wastewater treatment lagoon to investigate potential differences in treatment performance. In addition, grab samples of surface water were collected downstream of the lagoon discharge to evaluate the water quality in the receiving stream. After solid-phase extraction (SPE) using ion exchange columns for basic/neutral and acidic compounds, respectively, the extracts were analyzed for a suite of 16 indicator compounds. The two SPE extracts were combined for analysis of biological responses in four in vitro cell-based bioassays. The concentrations of several indicator compounds, including the estrogens, 17β-estradiol (E2) and 17α-ethinylestradiol (EE2), were below the limits of detection. However, androstenedione and estrone were detected in several influent samples. The concentrations of these steroid hormones and some of the other indicator compounds declined during treatment, but acesulfame K, carbamazepine, trimethoprim and DEET persisted in the effluent. The MTS-CellTiter 96® AQueous One Solution Cell Proliferation Assay (MTS) indicated that cell viability was not affected by exposure to the extracts. The Qiagen Nuclear Receptors 10-Pathway Reporter Array indicated that several cellular pathways were upregulated, with the greatest upregulation observed with the estrogen receptor (i.e., induction ratios of 12 to 47) and the liver X receptor (i.e., induction ratios of 10 to 45). The ERα CALUX assay indicated that estrogenic activity was lower in effluents compared to influents, but the expected improved removal of estrogenic activity during nitrification was not observed. The results of the Nrf2 Luciferase Luminescence Assay indicated a lower oxidative stress in the effluent samples, except for the lagoon. Overall, the present study further demonstrates that bioassays provide complementary information to chemical analyses and offer a way to assess treatment performance, even when target contaminants are not detected. There are thus advantages to using a combination of chemical analyses and in vitro bioassays to monitor the treatment efficiency of wastewater treatment plants and to predict the potential impacts of wastewater discharges into receiving waters.

Metabolic and Epigenetic Regulation by Estrogen in Adipocytes

Sex hormones contribute to differences between males and females in body fat distribution and associated disease risk. Higher concentrations of estrogens are associated with a more gynoid body shape and with more fat storage on hips and thighs rather than in visceral depots. Estrogen-mediated protection against visceral adiposity is shown in post-menopausal women with lower levels of estrogens and the reduction in central body fat observed after treatment with hormone-replacement therapy. Estrogen exerts its physiological effects via the estrogen receptors (ERα, ERβ and GPR30) in target cells, including adipocytes. Studies in mice indicate that estrogen protects against adipose inflammation and fibrosis also before the onset of obesity. The mechanisms involved in estrogen-dependent body fat distribution are incompletely understood, but involve, e.g., increased mTOR signaling and suppression of autophagy and adipogenesis/lipid storage. Estrogen plays a key role in epigenetic regulation of adipogenic genes by interacting with enzymes that remodel DNA methylation and histone tail post-translational modifications. However, more studies are needed to map the differential epigenetic effects of ER in different adipocyte subtypes, including those in subcutaneous and visceral adipose tissues. We here review recent discoveries of ER-mediated transcriptional and epigenetic regulation in adipocytes, which may explain sexual dimorphisms in body fat distribution and obesity-related disease risk.

FOXA1: A Pioneer of Nuclear Receptor Action in Breast Cancer

The pioneering function of FOXA1 establishes estrogen-responsive transcriptomes in luminal breast cancer. Dysregulated FOXA1 chromatin occupancy through focal amplification, mutation, or cofactor recruitment modulates estrogen receptor (ER) transcriptional programs and drives endocrine-resistant disease. However, ER is not the sole nuclear receptor (NR) expressed in breast cancers, nor is it the only NR for which FOXA1 serves as a licensing factor. Receptors for androgens, glucocorticoids, and progesterone are also found in the majority of breast cancers, and their functions are also impacted by FOXA1. These NRs interface with ER transcriptional programs and, depending on their activation level, can reprogram FOXA1-ER cistromes. Thus, NR interplay contributes to endocrine therapy response and resistance and may provide a vulnerability for future therapeutic benefit in patients. Herein, we review what is known regarding FOXA1 regulation of NR function in breast cancer in the context of cell identity, endocrine resistance, and NR crosstalk in breast cancer progression and treatment.

Genome-wide crosstalk between steroid receptors in breast and prostate cancers

Steroid receptors (SRs) constitute an important class of signal-dependent transcription factors (TFs). They regulate a variety of key biological processes and are crucial drug targets in many disease states. In particular, estrogen (ER) and androgen receptors (AR) drive the development and progression of breast and prostate cancer, respectively. Thus, they represent the main specific drug targets in these diseases. Recent evidence has suggested that the crosstalk between signal-dependent TFs is an important step in the reprogramming of chromatin sites; a signal-activated TF can expand or restrict the chromatin binding of another TF. This crosstalk can rewire gene programs and thus alter biological processes and influence the progression of disease. Lately, it has been postulated that there may be an important crosstalk between the AR and the ER with other SRs. Especially, progesterone (PR) and glucocorticoid receptor (GR) can reprogram chromatin binding of ER and gene programs in breast cancer cells. Furthermore, GR can take the place of AR in antiandrogen-resistant prostate cancer cells. Here, we review the current knowledge of the crosstalk between SRs in breast and prostate cancers. We emphasize how the activity of ER and AR on chromatin can be modulated by other SRs on a genome-wide scale. We also highlight the knowledge gaps in the interplay of SRs and their complex interactions with other signaling pathways and suggest how to experimentally fill in these gaps.

A seven-nuclear receptor-based prognostic signature in breast cancer

BACKGROUND

Breast cancer (BRCA) is a malignant cancer that threatened the life of female with unsatisfactory prognosis. The aim of this study was to identify prognostic nuclear receptors (NRs) signature of BRCA.

METHODS

BRCA patient samples were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Consensus clustering analysis, univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis were performed to evaluate, select NRs as prognostic factors and build Risk Score model. GSEA analysis was explored to check signaling differences between High- and Low-Risk group. Nomogram model basing on age and Risk Score was established to predict the 1-, 3- and 5-year survival. Model performance was assessed by a time-dependent receiver operating characteristic (ROC) curve and calibration plot. CIBERSORT, ESTIMATE and TIMER algorithm were introduced to evaluate the immune landscape.

RESULTS

NR3C1, NR4A3, THRA, RXRG, NR2F6, NR1D2 and RORB were optimized as a prognostic signature for BRCA. This seven-NR-based Risk Score could effectively predict overall survival status. The area under the curve (AUC) of 1-, 3- and 5-year overall survival are 0.702, 0.734 and 0.722 in TCGA training cohort, and 0.630, 0.721 and 0.823 in GEO validation cohort, respectively. Calibration plot demonstrated satisfactory agreement between predictive and observed outcomes. Nomogram model worked well on predicting survival probabilities. Multiple cancer-related pathways were highly enriched in High-Risk group. High- and Low-Risk groups showed significant differed immune cell infiltration. There exists an obvious connection between Risk Score and immune checkpoints LAG3, PD1 and TIM3.

CONCLUSION

The seven-NR-based Risk Score represents a promising signature for estimating overall survival in patients with BRCA, and is correlated with the immune microenvironment.

CrebA increases secretory capacity through direct transcriptional regulation of the secretory machinery, a subset of secretory cargo, and other key regulators

Specialization of many cells, including the acinar cells of the salivary glands and pancreas, milk-producing cells of mammary glands, mucus-secreting goblet cells, antibody-producing plasma cells, and cells that generate the dense extracellular matrices of bone and cartilage, requires scaling up both secretory machinery and cell-type specific secretory cargo. Using tissue-specific genome-scale analyses, we determine how increases in secretory capacity are coordinated with increases in secretory load in the Drosophila salivary gland (SG), an ideal model for gaining mechanistic insight into the functional specialization of secretory organs. Our findings show that CrebA, a bZIP transcription factor, directly binds genes encoding the core secretory machinery, including protein components of the signal recognition particle and receptor, ER cargo translocators, Cop I and Cop II vesicles, as well as the structural proteins and enzymes of these organelles. CrebA directly binds a subset of SG cargo genes and CrebA binds and boosts expression of Sage, a SG-specific transcription factor essential for cargo expression. To further enhance secretory output, CrebA binds and activates Xbp1 and Tudor-SN. Thus, CrebA directly upregulates the machinery of secretion and additional factors to increase overall secretory capacity in professional secretory cells; concomitant increases in cargo are achieved both directly and indirectly.

Steroid hormones regulate genome-wide epigenetic programming and gene transcription in human endometrial cells with marked aberrancies in endometriosis

Programmed cellular responses to cycling ovarian-derived steroid hormones are central to normal endometrial function. Abnormalities therein, as in the estrogen-dependent, progesterone-"resistant" disorder, endometriosis, predispose to infertility and poor pregnancy outcomes. The endometrial stromal fibroblast (eSF) is a master regulator of pregnancy success. However, the complex hormone-epigenome-transcriptome interplay in eSF by each individual steroid hormone, estradiol (E2) and/or progesterone (P4), under physiologic and pathophysiologic conditions, is poorly understood and was investigated herein. Genome-wide analysis in normal, early and late stage eutopic eSF revealed: i) In contrast to P4, E2 extensively affected the eSF DNA methylome and transcriptome. Importantly, E2 resulted in a more open versus closed chromatin, confirmed by histone modification analysis. Combined E2 with P4 affected a totally different landscape than E2 or P4 alone. ii) P4 responses were aberrant in early and late stage endometriosis, and mapping differentially methylated CpG sites with progesterone receptor targets from the literature revealed different but not decreased P4-targets, leading to question the P4-"resistant" phenotype in endometriosis. Interestingly, an aberrant E2-response was noted in eSF from endometriosis women; iii) Steroid hormones affected specific genomic contexts and locations, significantly enriching enhancers and intergenic regions and minimally involving proximal promoters and CpG islands, regardless of hormone type and eSF disease state. iv) In eSF from women with endometriosis, aberrant hormone-induced methylation signatures were mainly due to existing DNA methylation marks prior to hormone treatments and involved known endometriosis genes and pathways. v) Distinct DNA methylation and transcriptomic signatures revealed early and late stage endometriosis comprise unique disease subtypes. Taken together, the data herein, for the first time, provide significant insight into the hormone-epigenome-transcriptome interplay of each steroid hormone in normal eSF, and aberrant E2 response, distinct disease subtypes, and pre-existing epigenetic aberrancies in the setting of endometriosis, provide mechanistic insights into how endometriosis affects endometrial function/dysfunction.

Subtype-specific transcriptional regulators in breast tumors subjected to genetic and epigenetic alterations

MOTIVATION

Breast cancer consists of multiple distinct tumor subtypes, and results from epigenetic and genetic aberrations that give rise to distinct transcriptional profiles. Despite previous efforts to understand transcriptional deregulation through transcription factor networks, the transcriptional mechanisms leading to subtypes of the disease remain poorly understood.

RESULTS

We used a sophisticated computational search of thousands of expression datasets to define extended signatures of distinct breast cancer subtypes. Using ENCODE ChIP-seq data of surrogate cell lines and motif analysis we observed that these subtypes are determined by a distinct repertoire of lineage-specific transcription factors. Furthermore, specific pattern and abundance of copy number and DNA methylation changes at these TFs and targets, compared to other genes and to normal cells were observed. Overall, distinct transcriptional profiles are linked to genetic and epigenetic alterations at lineage-specific transcriptional regulators in breast cancer subtypes.

AVAILABILITY AND IMPLEMENTATION

The analysis code and data are deposited at https://bitbucket.org/qzhu/breast.cancer.tf/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Pan-cancer analyses of human nuclear receptors reveal transcriptome diversity and prognostic value across cancer types

The human nuclear receptor (NR) superfamily comprises 48 ligand-dependent transcription factors that play regulatory roles in physiology and pathophysiology. In cancer, NRs have long served as predictors of disease stratification, treatment response, and clinical outcome. The Cancer Genome Atlas (TCGA) Pan-Cancer project provides a wealth of genetic data for a large number of human cancer types. Here, we examined NR transcriptional activity in 8,526 patient samples from 33 TCGA ‘Pan-Cancer’ diseases and 11 ‘Pan-Cancer’ organ systems using RNA sequencing data. The web-based Kaplan-Meier (KM) plotter tool was then used to evaluate the prognostic potential of NR gene expression in 21/33 cancer types. Although, most NRs were significantly underexpressed in cancer, NR expression (moderate to high expression levels) was predominantly restricted (46%) to specific tissues, particularly cancers representing gynecologic, urologic, and gastrointestinal ‘Pan-Cancer’ organ systems. Intriguingly, a relationship emerged between recurrent positive pairwise correlation of Class IV NRs in most cancers. NR expression was also revealed to play a profound effect on patient overall survival rates, with ≥5 prognostic NRs identified per cancer type. Taken together, these findings highlighted the complexity of NR transcriptional networks in cancer and identified novel therapeutic targets for specific cancer types.

BedSect: An Integrated Web Server Application to Perform Intersection, Visualization, and Functional Annotation of Genomic Regions From Multiple Datasets

A large number of genomic regions, such as transcription factor binding sites (TFBSs) captured from next generation sequencing (NGS) data analyses or those available from the public resource database ENCODE, are generally overlapped to answer a variety of biological questions. Though several command-line tools are available to perform such an analysis, there is a notable lack of an integrated webserver application with which to identify genomic region intersections, generate publication-ready plots depicting subsets of the overlapped regions, and perform functional annotation. Thus, there is an ardent need for a comprehensive and user-friendly webserver application that allows the users to either upload multiple datasets or select from the integrated Gene Transcription Regulation Database (GTRD). We thus introduce BedSect (http://imgsb.org/bedsect/.), which not only fulfils the above criteria but also performs intersection analysis along with visualization of the intersection regions as an UpSet and correlation plot using the integrated Shiny application. Moreover, analyses, including functional annotation, gene ontology, and biological pathways enrichment for the identified unique and intersected genomic regions, can also be performed using the integrated GREAT tool. To view the genomic regions in the genome browser, the inbuilt hyperlink for UCSC can redirect the user to visualize the results as custom tracks.

Retinoid X receptor gamma (RXRG) is an independent prognostic biomarker in ER-positive invasive breast cancer

BACKGROUND

Retinoid X Receptor Gamma (RXRG) is a member of the nuclear receptor superfamily and plays a role in tumour suppression. This study aims to explore the prognostic significance of RXRG in breast cancer.

METHODS

Primary breast cancer tissue microarrays (n = 923) were immuno-stained for RXRG protein and correlated with clinicopathological features, and patient outcome.

RESULTS

Nuclear RXRG expression was significantly associated with smaller tumour size (p = 0.036), lower grade (p < 0.001), lobular histology (p = 0.016), lower Nottingham Prognostic Index (p = 0.04) and longer breast cancer-specific survival (p < 0.001), and longer time to distant metastasis (p = 0.002). RXRG expression showed positive association with oestrogen receptor (ER)-related biomarkers: GATA3, FOXA1, STAT3 and MED7 (all p < 0.001) and a negative correlation with the Ki67 proliferation marker. Multivariate analysis demonstrated RXRG protein as an independent predictor of longer breast cancer-specific survival and distant metastasis-free survival. In the external validation cohorts, RXRG expression was associated with improved patients' outcome (p = 0.025). In ER-positive tumours, high expression of RXRG was associated with better patient outcome regardless of adjuvant systemic therapy. ER signalling pathway was the top predicted master regulator of RXRG protein expression (p = 0.005).

CONCLUSION

This study provides evidence for the prognostic value of RXRG in breast cancer particularly the ER-positive tumours.

Augmenting subnetwork inference with information extracted from the scientific literature

Many biological studies involve either (i) manipulating some aspect of a cell or its environment and then simultaneously measuring the effect on thousands of genes, or (ii) systematically manipulating each gene and then measuring the effect on some response of interest. A common challenge that arises in these studies is to explain how genes identified as relevant in the given experiment are organized into a subnetwork that accounts for the response of interest. The task of inferring a subnetwork is typically dependent on the information available in publicly available, structured databases, which suffer from incompleteness. However, a wealth of potentially relevant information resides in the scientific literature, such as information about genes associated with certain concepts of interest, as well as interactions that occur among various biological entities. We contend that by exploiting this information, we can improve the explanatory power and accuracy of subnetwork inference in multiple applications. Here we propose and investigate several ways in which information extracted from the scientific literature can be used to augment subnetwork inference. We show that we can use literature-extracted information to (i) augment the set of entities identified as being relevant in a subnetwork inference task, (ii) augment the set of interactions used in the process, and (iii) support targeted browsing of a large inferred subnetwork by identifying entities and interactions that are closely related to concepts of interest. We use this approach to uncover the pathways involved in interactions between a virus and a host cell, and the pathways that are regulated by a transcription factor associated with breast cancer. Our experimental results demonstrate that these approaches can provide more accurate and more interpretable subnetworks. Integer program code, background network data, and pathfinding code are available at https://github.com/Craven-Biostat-Lab/subnetwork_inference

There is a multitude of publicly available databases that contain information about biological entities (i.e., genes, proteins, and other small molecules) as well as information about how these entities interact together. However, these databases are often incomplete. There is a wealth of information present in the text of the scientific literature that is not yet available in these databases. Using tools that mine the scientific literature we are able to extract some of this potentially relevant information. In this work we show how we can use publicly available databases in conjunction with the information extracted from the scientific literature to infer the networks that are involved in specific biological processes, such as viral replication and cancer tumor growth.

The miR-96 and RARγ signaling axis governs androgen signaling and prostate cancer progression

Expression levels of retinoic acid receptor gamma (NR1B3/RARG, encodes RARγ) are commonly reduced in prostate cancer (PCa). Therefore, we sought to establish the cellular and gene regulatory consequences of reduced RARγ expression, and determine RARγ regulatory mechanisms. RARG shRNA approaches in non-malignant (RWPE-1 and HPr1-AR) and malignant (LNCaP) prostate models revealed that reducing RARγ levels, rather than adding exogenous retinoid ligand, had the greatest impact on prostate cell viability and gene expression. ChIP-Seq defined the RARγ cistrome, which was significantly enriched at active enhancers associated with AR binding sites. Reflecting a significant genomic role for RARγ to regulate androgen signaling, RARγ knockdown in HPr1-AR cells significantly regulated the magnitude of the AR transcriptome. RARγ downregulation was explained by increased miR-96 in PCa cell and mouse models, and TCGA PCa cohorts. Biochemical approaches confirmed that miR-96 directly regulated RARγ expression and function. Capture of the miR-96 targetome by biotin-miR-96 identified that RARγ and a number of RARγ interacting co-factors including TACC1 were all targeted by miR-96, and expression of these genes were prominently altered, positively and negatively, in the TCGA-PRAD cohort. Differential gene expression analyses between tumors in the TCGA-PRAD cohort with lower quartile expression levels of RARG and TACC1 and upper quartile miR-96, compared to the reverse, identified a gene network including several RARγ target genes (e.g., SOX15) that significantly associated with worse disease-free survival (hazard ratio 2.23, 95% CI 1.58 to 2.88, p = 0.015). In summary, miR-96 targets a RARγ network to govern AR signaling, PCa progression and disease outcome.

Specificity landscapes unmask submaximal binding site preferences of transcription factors

We have developed Differential Specificity and Energy Landscape (DiSEL) analysis to comprehensively compare DNA-protein interactomes (DPIs) obtained by high-throughput experimental platforms and cutting edge computational methods. While high-affinity DNA binding sites are identified by most methods, DiSEL uncovered nuanced sequence preferences displayed by homologous transcription factors. Pairwise analysis of 726 DPIs uncovered homolog-specific differences at moderate- to low-affinity binding sites (submaximal sites). DiSEL analysis of variants of 41 transcription factors revealed that many disease-causing mutations result in allele-specific changes in binding site preferences. We focused on a set of highly homologous factors that have different biological roles but "read" DNA using identical amino acid side chains. Rather than direct readout, our results indicate that DNA noncontacting side chains allosterically contribute to sculpt distinct sequence preferences among closely related members of transcription factor families.

Chromatin reprogramming in breast cancer

Reprogramming of the chromatin landscape is a critical component to the transcriptional response in breast cancer. Effects of sex hormones such as estrogens and progesterone have been well described to have a critical impact on breast cancer proliferation. However, the complex network of the chromatin landscape, enhancer regions and mode of function of steroid receptors (SRs) and other transcription factors (TFs), is an intricate web of signaling and functional processes that is still largely misunderstood at the mechanistic level. In this review, we describe what is currently known about the dynamic interplay between TFs with chromatin and the reprogramming of enhancer elements. Emphasis has been placed on characterizing the different modes of action of TFs in regulating enhancer activity, specifically, how different SRs target enhancer regions to reprogram chromatin in breast cancer cells. In addition, we discuss current techniques employed to study enhancer function at a genome-wide level. Further, we have noted recent advances in live cell imaging technology. These single-cell approaches enable the coupling of population-based assays with real-time studies to address many unsolved questions about SRs and chromatin dynamics in breast cancer.

Estrogen and progesterone signalling in the normal breast and its implications for cancer development

The ovarian hormones estrogen and progesterone are master regulators of the development and function of a broad spectrum of human tissues, including the breast, reproductive and cardiovascular systems, brain and bone. Acting through the nuclear estrogen (ER) and progesterone receptors (PR), both play complex and essential coordinated roles in the extensive development of the lobular alveolar epithelial structures of the normal breast during puberty, the normal menstrual cycle and pregnancy. The past decade has seen major advances in understanding the mechanisms of action of estrogen and progesterone in the normal breast and in the delineation of the complex hierarchy of cell types regulated by ovarian hormones in this tissue. There is evidence for a role for both ER and PR in driving breast cancer, and both are favourable prognostic markers with respect to outcome. In this review, we summarize current knowledge of the mechanisms of action of ER and PR in the normal breast, and implications for the development and management of breast cancer.

Epigenome-wide SRC-1-Mediated Gene Silencing Represses Cellular Differentiation in Advanced Breast Cancer

Purpose: Despite the clinical utility of endocrine therapies for estrogen receptor-positive (ER) breast cancer, up to 40% of patients eventually develop resistance, leading to disease progression. The molecular determinants that drive this adaptation to treatment remain poorly understood. Methylome aberrations drive cancer growth yet the functional role and mechanism of these epimutations in drug resistance are poorly elucidated.Experimental Design: Genome-wide multi-omics sequencing approach identified a differentially methylated hub of prodifferentiation genes in endocrine resistant breast cancer patients and cell models. Clinical relevance of the functionally validated methyl-targets was assessed in a cohort of endocrine-treated human breast cancers and patient-derived ex vivo metastatic tumors.Results: Enhanced global hypermethylation was observed in endocrine treatment resistant cells and patient metastasis relative to sensitive parent cells and matched primary breast tumor, respectively. Using paired methylation and transcriptional profiles, we found that SRC-1-dependent alterations in endocrine resistance lead to aberrant hypermethylation that resulted in reduced expression of a set of differentiation genes. Analysis of ER-positive endocrine-treated human breast tumors (n = 669) demonstrated that low expression of this prodifferentiation gene set significantly associated with poor clinical outcome (P = 0.00009). We demonstrate that the reactivation of these genes in vitro and ex vivo reverses the aggressive phenotype.Conclusions: Our work demonstrates that SRC-1-dependent epigenetic remodeling is a 'high level' regulator of the poorly differentiated state in ER-positive breast cancer. Collectively these data revealed an epigenetic reprograming pathway, whereby concerted differential DNA methylation is potentiated by SRC-1 in the endocrine resistant setting. Clin Cancer Res; 24(15); 3692-703. ©2018 AACR.

EPRS is a critical regulator of cell proliferation and estrogen signaling in ER+ breast cancer

Aminoacyl tRNA synthetases (ARSs) are a class of enzymes with well-conserved housekeeping functions in cellular translation. Recent evidence suggests that ARS genes may participate in a wide array of cellular processes, and may contribute to the pathology of autoimmune disease, cancer, and other diseases. Several studies have suggested a role for the glutamyl prolyl tRNA synthetase (EPRS) in breast cancers, although none has identified any underlying mechanism about how EPRS contributes to carcinogenesis. In this study, we identified EPRS as upregulated in estrogen receptor positive (ER+) human breast tumors in the TCGA and METABRIC cohorts, with copy number gains in nearly 50% of samples in both datasets. EPRS expression is associated with reduced overall survival in patients with ER+ tumors in TCGA and METABRIC datasets. EPRS expression was also associated with reduced distant relapse-free survival in patients treated with adjuvant tamoxifen monotherapy for five years, and EPRS-correlated genes were highly enriched for genes predictive of a poor response to tamoxifen. We demonstrated the necessity of EPRS for proliferation of tamoxifen-resistant ER+ breast cancer, but not ER- breast cancer cells. Transcriptomic profiling showed that EPRS regulated cell cycle and estrogen response genes. Finally, we constructed a causal gene network based on over 2500 ER+ breast tumor samples to build up an EPRS-estrogen signaling pathway. EPRS and its regulated estrogenic gene network may offer a promising alternative approach to target ER+ breast cancers that are refractory to current anti-estrogens.

The logic of transcriptional regulator recruitment architecture at cis-regulatory modules controlling liver functions

Control of gene transcription relies on concomitant regulation by multiple transcriptional regulators (TRs). However, how recruitment of a myriad of TRs is orchestrated at cis-regulatory modules (CRMs) to account for coregulation of specific biological pathways is only partially understood. Here, we have used mouse liver CRMs involved in regulatory activities of the hepatic TR, NR1H4 (FXR; farnesoid X receptor), as our model system to tackle this question. Using integrative cistromic, epigenomic, transcriptomic, and interactomic analyses, we reveal a logical organization where trans-regulatory modules (TRMs), which consist of subsets of preferentially and coordinately corecruited TRs, assemble into hierarchical combinations at hepatic CRMs. Different combinations of TRMs add to a core TRM, broadly found across the whole landscape of CRMs, to discriminate promoters from enhancers. These combinations also specify distinct sets of CRM differentially organized along the genome and involved in regulation of either housekeeping/cellular maintenance genes or liver-specific functions. In addition to these TRMs which we define as obligatory, we show that facultative TRMs, such as one comprising core circadian TRs, are further recruited to selective subsets of CRMs to modulate their activities. TRMs transcend TR classification into ubiquitous versus liver-identity factors, as well as TR grouping into functional families. Hence, hierarchical superimpositions of obligatory and facultative TRMs bring about independent transcriptional regulatory inputs defining different sets of CRMs with logical connection to regulation of specific gene sets and biological pathways. Altogether, our study reveals novel principles of concerted transcriptional regulation by multiple TRs at CRMs.

Emerging functional roles of nuclear receptors in breast cancer

Nuclear receptors (NRs) have been targets of intensive drug development for decades due to their roles as key regulators of multiple developmental, physiological and disease processes. In breast cancer, expression of the estrogen and progesterone receptor remains clinically important in predicting prognosis and determining therapeutic strategies. More recently, there is growing evidence supporting the involvement of multiple nuclear receptors other than the estrogen and progesterone receptors, in the regulation of various processes important to the initiation and progression of breast cancer. We review new insights into the mechanisms of action of NRs made possible by recent advances in genomic technologies and focus on the emerging functional roles of NRs in breast cancer biology, including their involvement in circadian regulation, metabolic reprogramming and breast cancer migration and metastasis.

Combinatorial bZIP dimers display complex DNA-binding specificity landscapes

How transcription factor dimerization impacts DNA-binding specificity is poorly understood. Guided by protein dimerization properties, we examined DNA binding specificities of 270 human bZIP pairs. DNA interactomes of 80 heterodimers and 22 homodimers revealed that 72% of heterodimer motifs correspond to conjoined half-sites preferred by partnering monomers. Remarkably, the remaining motifs are composed of variably-spaced half-sites (12%) or 'emergent' sites (16%) that cannot be readily inferred from half-site preferences of partnering monomers. These binding sites were biochemically validated by EMSA-FRET analysis and validated in vivo by ChIP-seq data from human cell lines. Focusing on ATF3, we observed distinct cognate site preferences conferred by different bZIP partners, and demonstrated that genome-wide binding of ATF3 is best explained by considering many dimers in which it participates. Importantly, our compendium of bZIP-DNA interactomes predicted bZIP binding to 156 disease associated SNPs, of which only 20 were previously annotated with known bZIP motifs.

PPARδ as a Metabolic Initiator of Mammary Neoplasia and Immune Tolerance

PPARδ is a ligand-activated nuclear receptor that regulates the transcription of genes associated with proliferation, metabolism, inflammation, and immunity. Within this transcription factor family, PPARδ is unique in that it initiates oncogenesis in a metabolic and tissue-specific context, especially in mammary epithelium, and can regulate autoimmunity in some tissues. This review discusses its role in these processes and how it ultimately impacts breast cancer.

HP1BP3, a Chromatin Retention Factor for Co-transcriptional MicroRNA Processing

Recent studies suggest that the microprocessor (Drosha-DGCR8) complex can be recruited to chromatin to catalyze co-transcriptional processing of primary microRNAs (pri-miRNAs) in mammalian cells. However, the molecular mechanism of co-transcriptional miRNA processing is poorly understood. Here we find that HP1BP3, a histone H1-like chromatin protein, specifically associates with the microprocessor and promotes global miRNA biogenesis in human cells. Chromatin immunoprecipitation (ChIP) studies reveal genome-wide co-localization of HP1BP3 and Drosha and HP1BP3-dependent Drosha binding to actively transcribed miRNA loci. Moreover, HP1BP3 specifically binds endogenous pri-miRNAs and facilitates the Drosha/pri-miRNA association in vivo. Knockdown of HP1BP3 compromises pri-miRNA processing by causing premature release of pri-miRNAs from the chromatin. Taken together, these studies suggest that HP1BP3 promotes co-transcriptional miRNA processing via chromatin retention of nascent pri-miRNA transcripts. This work significantly expands the functional repertoire of the H1 family of proteins and suggests the existence of chromatin retention factors for widespread co-transcriptional miRNA processing.

Expression profiling of nuclear receptors in breast cancer identifies TLX as a mediator of growth and invasion in triple-negative breast cancer

The Nuclear Receptor (NR) superfamily of transcription factors comprises 48 members, several of which have been implicated in breast cancer. Most important is estrogen receptor-α (ERα), which is a key therapeutic target. ERα action is facilitated by co-operativity with other NR and there is evidence that ERα function may be recapitulated by other NRs in ERα-negative breast cancer. In order to examine the inter-relationships between nuclear receptors, and to obtain evidence for previously unsuspected roles for any NRs, we undertook quantitative RT-PCR and bioinformatics analysis to examine their expression in breast cancer. While most NRs were expressed, bioinformatic analyses differentiated tumours into distinct prognostic groups that were validated by analyzing public microarray data sets. Although ERα and progesterone receptor were dominant in distinguishing prognostic groups, other NR strengthened these groups. Clustering analysis identified several family members with potential importance in breast cancer. Specifically, RORγ is identified as being co-expressed with ERα, whilst several NRs are preferentially expressed in ERα-negative disease, with TLX expression being prognostic in this subtype. Functional studies demonstrated the importance of TLX in regulating growth and invasion in ERα-negative breast cancer cells.

PPAR-delta promotes survival of breast cancer cells in harsh metabolic conditions

Expression of the nuclear receptor peroxisome proliferator activated receptor delta (PPARδ) in breast cancer cells is negatively associated with patient survival, but the underlying mechanisms are not clear. High PPARδ protein levels in rat breast adenocarcinomas were found to be associated with increased growth in soft agar and mice. Transgenic expression of PPARδ increased the ability of human breast cancer cell lines to migrate in vitro and form lung metastases in mice. PPARδ also conferred the ability to grow in exhausted tissue culture media and survive in low-glucose and other endoplasmic reticulum stress conditions such as hypoxia. Upregulation of PPARδ by glucocorticoids or synthetic agonists also protected human breast cancer cells from low glucose. Survival in low glucose was related to increased antioxidant defenses mediated in part by catalase and also to late AKT phosphorylation, which is associated with the prolonged glucose-deprivation response. Synthetic antagonists reversed the survival benefits conferred by PPARδ in vitro. These findings suggest that PPARδ conditions breast cancer cells to survive in harsh microenvironmental conditions by reducing oxidative stress and enhancing survival signaling responses. Drugs that target PPARδ may have a role in the treatment of breast cancer.

A Computational Drug Repositioning Approach for Targeting Oncogenic Transcription Factors

Mutations in transcription factor (TF) genes are frequently observed in tumors, often leading to aberrant transcriptional activity. Unfortunately, TFs are often considered undruggable due to the absence of targetable enzymatic activity. To address this problem, we developed CRAFTT, a computational drug-repositioning approach for targeting TF activity. CRAFTT combines ChIP-seq with drug-induced expression profiling to identify small molecules that can specifically perturb TF activity. Application to ENCODE ChIP-seq datasets revealed known drug-TF interactions, and a global drug-protein network analysis supported these predictions. Application of CRAFTT to ERG, a pro-invasive, frequently overexpressed oncogenic TF, predicted that dexamethasone would inhibit ERG activity. Dexamethasone significantly decreased cell invasion and migration in an ERG-dependent manner. Furthermore, analysis of electronic medical record data indicates a protective role for dexamethasone against prostate cancer. Altogether, our method provides a broadly applicable strategy for identifying drugs that specifically modulate TF activity.

Genomic agonism and phenotypic antagonism between estrogen and progesterone receptors in breast cancer

The functional role of progesterone receptor (PR) and its impact on estrogen signaling in breast cancer remain controversial. In primary ER(+) (estrogen receptor-positive)/PR(+) human tumors, we report that PR reprograms estrogen signaling as a genomic agonist and a phenotypic antagonist. In isolation, estrogen and progestin act as genomic agonists by regulating the expression of common target genes in similar directions, but at different levels. Similarly, in isolation, progestin is also a weak phenotypic agonist of estrogen action. However, in the presence of both hormones, progestin behaves as a phenotypic estrogen antagonist. PR remodels nucleosomes to noncompetitively redirect ER genomic binding to distal enhancers enriched for BRCA1 binding motifs and sites that link PR and ER/PR complexes. When both hormones are present, progestin modulates estrogen action, such that responsive transcriptomes, cellular processes, and ER/PR recruitment to genomic sites correlate with those observed with PR alone, but not ER alone. Despite this overall correlation, the transcriptome patterns modulated by dual treatment are sufficiently different from individual treatments, such that antagonism of oncogenic processes is both predicted and observed. Combination therapies using the selective PR modulator/antagonist (SPRM) CDB4124 in combination with tamoxifen elicited 70% cytotoxic tumor regression of T47D tumor xenografts, whereas individual therapies inhibited tumor growth without net regression. Our findings demonstrate that PR redirects ER chromatin binding to antagonize estrogen signaling and that SPRMs can potentiate responses to antiestrogens, suggesting that cotargeting of ER and PR in ER(+)/PR(+) breast cancers should be explored.

GR and ER Coactivation Alters the Expression of Differentiation Genes and Associates with Improved ER+ Breast Cancer Outcome

In estrogen receptor (ER)-negative breast cancer, high tumor glucocorticoid receptor (GR) expression has been associated with a relatively poor outcome. In contrast, using a meta-analysis of several genomic datasets, here we find that tumor GR mRNA expression is associated with improved ER(+) relapse-free survival (RFS; independently of progesterone receptor expression). To understand the mechanism by which GR expression is associated with a better ER(+) breast cancer outcome, the global effect of GR-mediated transcriptional activation in ER(+) breast cancer cells was studied. Analysis of GR chromatin immunoprecipitation followed by high-throughput sequencing in ER(+)/GR(+) MCF-7 cells revealed that upon coactivation of GR and ER, GR chromatin association became enriched at proximal promoter regions. Furthermore, following ER activation, increased GR chromatin association was observed at ER, FOXO, and AP1 response elements. In addition, ER associated with GR response elements, suggesting that ER and GR interact in a complex. Coactivation of GR and ER resulted in increased expression (relative to ER activation alone) of transcripts that encode proteins promoting cellular differentiation (e.g., KDM4B, VDR) and inhibiting the Wnt signaling pathway (IGFBP4). Finally, expression of these individual prodifferentiation genes was associated with significantly improved RFS in ER(+) breast cancer patients. Together, these data suggest that the coexpression and subsequent activity of tumor cell GR and ER contribute to the less aggressive natural history of early-stage breast cancer by coordinating the altered expression of genes favoring differentiation.

IMPLICATIONS

The interaction between ER and GR activity highlights the importance of context-dependent nuclear receptor function in cancer. Mol Cancer Res; 14(8); 707-19. ©2016 AACR.

Computational Identification of Key Regulators in Two Different Colorectal Cancer Cell Lines

Transcription factors (TFs) are gene regulatory proteins that are essential for an effective regulation of the transcriptional machinery. Today, it is known that their expression plays an important role in several types of cancer. Computational identification of key players in specific cancer cell lines is still an open challenge in cancer research. In this study, we present a systematic approach which combines colorectal cancer (CRC) cell lines, namely 1638N-T1 and CMT-93, and well-established computational methods in order to compare these cell lines on the level of transcriptional regulation as well as on a pathway level, i.e., the cancer cell-intrinsic pathway repertoire. For this purpose, we firstly applied the Trinity platform to detect signature genes, and then applied analyses of the geneXplain platform to these for detection of upstream transcriptional regulators and their regulatory networks. We created a CRC-specific position weight matrix (PWM) library based on the TRANSFAC database (release 2014.1) to minimize the rate of false predictions in the promoter analyses. Using our proposed workflow, we specifically focused on revealing the similarities and differences in transcriptional regulation between the two CRC cell lines, and report a number of well-known, cancer-associated TFs with significantly enriched binding sites in the promoter regions of the signature genes. We show that, although the signature genes of both cell lines show no overlap, they may still be regulated by common TFs in CRC. Based on our findings, we suggest that canonical Wnt signaling is activated in 1638N-T1, but inhibited in CMT-93 through cross-talks of Wnt signaling with the VDR signaling pathway and/or LXR-related pathways. Furthermore, our findings provide indication of several master regulators being present such as MLK3 and Mapk1 (ERK2) which might be important in cell proliferation, migration, and invasion of 1638N-T1 and CMT-93, respectively. Taken together, we provide new insights into the invasive potential of these cell lines, which can be used for development of effective cancer therapy.

Nuclear tristetraprolin acts as a corepressor of multiple steroid nuclear receptors in breast cancer cells

Tristetraprolin (TTP) is a 34-kDa, zinc finger-containing factor that in mammalian cells acts as a tumor suppressor protein through two different mechanisms. In the cytoplasm TTP promotes the decay of hundreds of mRNAs encoding cell factors involved in inflammation, tissue invasion, and metastasis. In the cell nucleus TTP has been identified as a transcriptional corepressor of the estrogen receptor alpha (ERα), which has been associated to the development and progression of the majority of breast cancer tumors. In this work we report that nuclear TTP modulates the transactivation activity of progesterone receptor (PR), glucocorticoid receptor (GR) and androgen receptor (AR). In recent years these steroid nuclear receptors have been shown to be of clinical and therapeutical relevance in breast cancer. The functional association between TTP and steroid nuclear receptors is supported by the finding that TTP physically interacts with ERα, PR, GR and AR in vivo. We also show that TTP overexpression attenuates the transactivation of all the steroid nuclear receptors tested. In contrast, siRNA-mediated reduction of endogenous TTP expression in MCF-7 cells produced an increase in the transcriptional activities of ERα, PR, GR and AR. Taken together, these results suggest that the function of nuclear TTP in breast cancer cells is to act as a corepressor of ERα, PR, GR and AR. We propose that the reduction of TTP expression observed in different types of breast cancer tumors may contribute to the development of this disease by producing a dysregulation of the transactivation activity of multiple steroid nuclear receptors.

The Nuclear Receptor, RORγ, Regulates Pathways Necessary for Breast Cancer Metastasis

We have previously reported that RORγ expression was decreased in ER-ve breast cancer, and increased expression improves clinical outcomes. However, the underlying RORγ dependent mechanisms that repress breast carcinogenesis have not been elucidated. Here we report that RORγ negatively regulates the oncogenic TGF-β/EMT and mammary stem cell (MaSC) pathways, whereas RORγ positively regulates DNA-repair. We demonstrate that RORγ expression is: (i) decreased in basal-like subtype cancers, and (ii) inversely correlated with histological grade and drivers of carcinogenesis in breast cancer cohorts. Furthermore, integration of RNA-seq and ChIP-chip data reveals that RORγ regulates the expression of many genes involved in TGF-β/EMT-signaling, DNA-repair and MaSC pathways (including the non-coding RNA, LINC00511). In accordance, pharmacological studies demonstrate that an RORγ agonist suppresses breast cancer cell viability, migration, the EMT transition (microsphere outgrowth) and mammosphere-growth. In contrast, RNA-seq demonstrates an RORγ inverse agonist induces TGF-β/EMT-signaling. These findings suggest pharmacological modulation of RORγ activity may have utility in breast cancer.

Regulators of genetic risk of breast cancer identified by integrative network analysis

Genetic risk for breast cancer is conferred by a combination of multiple variants of small effect. To better understand how risk loci might combine, we examined whether risk-associated genes share regulatory mechanisms. We created a breast cancer gene regulatory network comprising transcription factors and groups of putative target genes (regulons) and asked whether specific regulons are enriched for genes associated with risk loci via expression quantitative trait loci (eQTLs). We identified 36 overlapping regulons that were enriched for risk loci and formed a distinct cluster within the network, suggesting shared biology. The risk transcription factors driving these regulons are frequently mutated in cancer and lie in two opposing subgroups, which relate to estrogen receptor (ER)(+) luminal A or luminal B and ER(-) basal-like cancers and to different luminal epithelial cell populations in the adult mammary gland. Our network approach provides a foundation for determining the regulatory circuits governing breast cancer, to identify targets for intervention, and is transferable to other disease settings.

3CPET: finding co-factor complexes from ChIA-PET data using a hierarchical Dirichlet process

Various efforts have been made to elucidate the cooperating proteins involved in maintaining chromatin interactions; however, many are still unknown. Here, we present 3CPET, a tool based on a non-parametric Bayesian approach, to infer the set of the most probable protein complexes involved in maintaining chromatin interactions and the regions that they may control, making it a valuable downstream analysis tool in chromatin conformation studies. 3CPET does so by combining data from ChIA-PET, transcription factor binding sites, and protein interactions. 3CPET results show biologically significant and accurate predictions when validated against experimental and simulation data.

Pan-cancer analyses of the nuclear receptor superfamily

Nuclear receptors (NR) act as an integrated conduit for environmental and hormonal signals to govern genomic responses, which relate to cell fate decisions. We review how their integrated actions with each other, shared co-factors and other transcription factors are disrupted in cancer. Steroid hormone nuclear receptors are oncogenic drivers in breast and prostate cancer and blockade of signaling is a major therapeutic goal. By contrast to blockade of receptors, in other cancers enhanced receptor function is attractive, as illustrated initially with targeting of retinoic acid receptors in leukemia. In the post-genomic era large consortia, such as The Cancer Genome Atlas, have developed a remarkable volume of genomic data with which to examine multiple aspects of nuclear receptor status in a pan-cancer manner. Therefore to extend the review of NR function we have also undertaken bioinformatics analyses of NR expression in over 3000 tumors, spread across six different tumor types (bladder, breast, colon, head and neck, liver and prostate). Specifically, to ask how the NR expression was distorted (altered expression, mutation and CNV) we have applied bootstrapping approaches to simulate data for comparison, and also compared these NR findings to 12 other transcription factor families. Nuclear receptors were uniquely and uniformly downregulated across all six tumor types, more than predicted by chance. These approaches also revealed that each tumor type had a specific NR expression profile but these were most similar between breast and prostate cancer. Some NRs were down-regulated in at least five tumor types (e.g. NR3C2/MR and NR5A2/LRH-1)) whereas others were uniquely down-regulated in one tumor (e.g. NR1B3/RARG). The downregulation was not driven by copy number variation or mutation and epigenetic mechanisms maybe responsible for the altered nuclear receptor expression.

Automated Identification of Core Regulatory Genes in Human Gene Regulatory Networks

Human gene regulatory networks (GRN) can be difficult to interpret due to a tangle of edges interconnecting thousands of genes. We constructed a general human GRN from extensive transcription factor and microRNA target data obtained from public databases. In a subnetwork of this GRN that is active during estrogen stimulation of MCF-7 breast cancer cells, we benchmarked automated algorithms for identifying core regulatory genes (transcription factors and microRNAs). Among these algorithms, we identified K-core decomposition, pagerank and betweenness centrality algorithms as the most effective for discovering core regulatory genes in the network evaluated based on previously known roles of these genes in MCF-7 biology as well as in their ability to explain the up or down expression status of up to 70% of the remaining genes. Finally, we validated the use of K-core algorithm for organizing the GRN in an easier to interpret layered hierarchy where more influential regulatory genes percolate towards the inner layers. The integrated human gene and miRNA network and software used in this study are provided as supplementary materials (S1 Data) accompanying this manuscript.

A gene regulatory network (GRN) represents how some genes encoding regulatory molecules such as transcription factors or microRNAs regulate the expression of other genes. Researchers commonly study GRNs involved in a specific biological process with the aim of identifying a few important regulatory genes. In higher organisms such as humans, a regulatory gene regulates multiple target genes and correspondingly any gene is regulated by multiple regulatory genes. Due to such multiplicity of interactions, a GRN usually resembles a tangled hairball wherein it is difficult to identify few most influential regulatory genes. In this study, we show that network analysis algorithms such as K-core, pagerank and betweenness centrality are useful for identifying a few important or core regulatory genes in a GRN, and the K-core algorithm is also useful for organizing regulatory genes in a hierarchical layered structure where the most influential genes in a GRN are found within the innermost layer or core. These few core regulatory genes determine to a large extent the expression status of the remaining genes in the network. We illustrate a pragmatic application of this technique to GRNs reconstructed from genome-wide gene expression measurements in the MCF-7 human breast cancer cell line.

CETCh-seq: CRISPR epitope tagging ChIP-seq of DNA-binding proteins

Chromatin immunoprecipitation followed by next-generation DNA sequencing (ChIP-seq) is a widely used technique for identifying transcription factor (TF) binding events throughout an entire genome. However, ChIP-seq is limited by the availability of suitable ChIP-seq grade antibodies, and the vast majority of commercially available antibodies fail to generate usable data sets. To ameliorate these technical obstacles, we present a robust methodological approach for performing ChIP-seq through epitope tagging of endogenous TFs. We used clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9-based genome editing technology to develop CRISPR epitope tagging ChIP-seq (CETCh-seq) of DNA-binding proteins. We assessed the feasibility of CETCh-seq by tagging several DNA-binding proteins spanning a wide range of endogenous expression levels in the hepatocellular carcinoma cell line HepG2. Our data exhibit strong correlations between both replicate types as well as with standard ChIP-seq approaches that use TF antibodies. Notably, we also observed minimal changes to the cellular transcriptome and to the expression of the tagged TF. To examine the robustness of our technique, we further performed CETCh-seq in the breast adenocarcinoma cell line MCF7 as well as mouse embryonic stem cells and observed similarly high correlations. Collectively, these data highlight the applicability of CETCh-seq to accurately define the genome-wide binding profiles of DNA-binding proteins, allowing for a straightforward methodology to potentially assay the complete repertoire of TFs, including the large fraction for which ChIP-quality antibodies are not available.

Molecular subtypes of urothelial carcinoma are defined by specific gene regulatory systems

Background

Molecular stratification of bladder cancer has revealed gene signatures differentially expressed across tumor subtypes. While these signatures provide important insights into subtype biology, the transcriptional regulation that governs these signatures is not well characterized.

Methods

In this study, we use publically available ChIP-Seq data on regulatory factor binding in order to link transcription factors to gene signatures defining molecular subtypes of urothelial carcinoma.

Results

We identify PPARG and STAT3, as well as ADIRF, a novel regulator of fatty acid metabolism, as putative mediators of the SCC-like phenotype. We link the PLK1-FOXM1 axis to the rapidly proliferating Genomically Unstable and SCC-like subtypes and show that differentiation programs involving PPARG/RXRA, FOXA1/GATA3 and HOXA/HOXB are differentially expressed in UC molecular subtypes. We show that gene signatures and regulatory systems defined in urothelial carcinoma operate in breast cancer in a subtype specific manner, suggesting similarities at the gene regulatory level of these two tumor types.

Conclusions

At the gene regulatory level Urobasal, Genomically Unstable and SCC-like tumors represents three fundamentally different tumor types. Urobasal tumors maintain an apparent urothelial differentiation axis composed of PPARG/RXRA, FOXA1/GATA3 and anterior HOXA and HOXB genes. Genomically Unstable and SCC-like tumors differ from Urobasal tumors by a strong increase of proliferative activity through the PLK1-FOXM1 axis operating in both subtypes. However, whereas SCC-like tumors evade urothelial differentiation by a block in differentiation through strong downregulation of PPARG/RXRA, FOXA1/GATA3, our data indicates that Genomically Unstable tumors evade differentiation in a more dynamic manner.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-015-0101-5) contains supplementary material, which is available to authorized users.