Enhancer RNA m6A methylation facilitates transcriptional condensate formation and gene activation.

The mechanistic understanding of nascent RNAs in transcriptional control remains limited. Here, by a high sensitivity method methylation-inscribed nascent transcripts sequencing (MINT-seq), we characterized the landscapes of N6-methyladenosine (m6A) on nascent RNAs. We uncover heavy but selective m6A deposition on nascent RNAs produced by transcription regulatory elements, including promoter upstream antisense RNAs and enhancer RNAs (eRNAs), which positively correlates with their length, inclusion of m6A motif, and RNA abundances. m6A-eRNAs mark highly active enhancers, where they recruit nuclear m6A reader YTHDC1 to phase separate into liquid-like condensates, in a manner dependent on its C terminus intrinsically disordered region and arginine residues. The m6A-eRNA/YTHDC1 condensate co-mixes with and facilitates the formation of BRD4 coactivator condensate. Consequently, YTHDC1 depletion diminished BRD4 condensate and its recruitment to enhancers, resulting in inhibited enhancer and gene activation. We propose that chemical modifications of eRNAs together with reader proteins play broad roles in enhancer activation and gene transcriptional control.

Transcriptional coactivation of NRF2 signaling in cardiac fibroblasts promotes resistance to oxidative stress.

We recently discovered that steroid receptor coactivators (SRCs) SRCs-1, 2 and 3, are abundantly expressed in cardiac fibroblasts (CFs) and their activation with the SRC small molecule stimulator MCB-613 improves cardiac function and dramatically lowers pro-fibrotic signaling in CFs post-myocardial infarction. These findings suggest that CF-derived SRC activation could be beneficial in the mitigation of chronic heart failure after ischemic insult. However, the cardioprotective mechanisms by which CFs contribute to cardiac pathological remodeling are unclear. Here we present studies designed to identify the molecular and cellular circuitry that governs the anti-fibrotic effects of an MCB-613 derivative, MCB-613-10-1, in CFs. We performed cytokine profiling and whole transcriptome and proteome analyses of CF-derived signals in response to MCB-613-10-1. We identified the NRF2 pathway as a direct MCB-613-10-1 therapeutic target for promoting resistance to oxidative stress in CFs. We show that MCB-613-10-1 promotes cell survival of anti-fibrotic CFs exposed to oxidative stress by suppressing apoptosis. We demonstrate that an increase in HMOX1 expression contributes to CF resistance to oxidative stress-mediated apoptosis via a mechanism involving SRC co-activation of NRF2, hence reducing inflammation and fibrosis. We provide evidence that MCB-613-10-1 acts as a protectant against oxidative stress-induced mitochondrial damage. Our data reveal that SRC stimulation of the NRF2 transcriptional network promotes resistance to oxidative stress and highlights a mechanistic approach toward addressing pathologic cardiac remodeling.

Nuclear receptors in cancer - uncovering new and evolving roles through genomic analysis.

Nuclear receptors (NRs) have historically been at the forefront of cancer research, where they are known to act as critical regulators of disease. They also serve as biomarkers for tumour subclassification and targets for hormone therapy. However, most tumour types express extensive repertoires of NRs, whose interactions provide multiple paths for disease progression and offer potentially untapped mechanisms for therapeutic interventions. Recently, next-generation sequencing technologies have provided genome-wide insights into the complex interplay of NR transcriptional networks and their contribution to the development and progression of cancer. These findings have altered the traditional understanding of NR activities in oncogenesis.

Coactivators enable glucocorticoid receptor recruitment to fine-tune estrogen receptor transcriptional responses.

Nuclear receptors (NRs) are central regulators of pathophysiological processes; however, how their responses intertwine is still not fully understood. The aim of this study was to determine whether and how steroid NRs can influence each other's activity under co-agonist treatment. We used a unique system consisting of a multicopy integration of an estrogen receptor responsive unit that allows direct visualization and quantification of estrogen receptor alpha (ERα) DNA binding, co-regulator recruitment and transcriptional readout. We find that ERα DNA loading is required for other type I nuclear receptors to be co-recruited after dual agonist treatment. We focused on ERα/glucocorticoid receptor interplay and demonstrated that it requires steroid receptor coactivators (SRC-2, SRC-3) and the mediator component MED14. We then validated this cooperative interplay on endogenous target genes in breast cancer cells. Taken together, this work highlights another layer of mechanistic complexity through which NRs cross-talk with each other on chromatin under multiple hormonal stimuli.

A novel ERß high throughput microscopy platform for testing endocrine disrupting chemicals.

In this study we present an inducible biosensor model for the Estrogen Receptor Beta (ERß), GFP-ERß:PRL-HeLa, a single-cell-based high throughput (HT) in vitro assay that allows direct visualization and measurement of GFP-tagged ERß binding to ER-specific DNA response elements (EREs), ERß-induced chromatin remodeling, and monitor transcriptional alterations via mRNA fluorescence in situ hybridization for a prolactin (PRL)-dsRED2 reporter gene. The model was used to accurately (Z' = 0.58-0.8) differentiate ERß-selective ligands from ERα ligands when treated with a panel of selective agonists and antagonists. Next, we tested an Environmental Protection Agency (EPA)-provided set of 45 estrogenic reference chemicals with known ERα in vivo activity and identified several that activated ERß as well, with varying sensitivity, including a subset that is completely novel. We then used an orthogonal ERE-containing transgenic zebrafish (ZF) model to cross validate ERß and ERα selective activities at the organism level. Using this environmentally relevant ZF assay, some compounds were confirmed to have ERß activity, validating the GFP-ERß:PRL-HeLa assay as a screening tool for potential ERß active endocrine disruptors (EDCs). These data demonstrate the value of sensitive multiplex mechanistic data gathered by the GFP-ERß:PRL-HeLa assay coupled with an orthogonal zebrafish model to rapidly identify environmentally relevant ERß EDCs and improve upon currently available screening tools for this understudied nuclear receptor.

Characterization of flavonoids with potent and subtype-selective actions on estrogen receptors alpha and beta.

The initial step in estrogen-regulated transcription is the binding of a ligand to its cognate receptors, named estrogen receptors (ERα and ERß). Phytochemicals present in foods and environment can compete with endogenous hormones to alter physiological responses. We screened 224 flavonoids in our engineered biosensor ERα and ERß PRL-array cell lines to characterize their activity on several steps of the estrogen signaling pathway. We identified 83 and 96 flavonoids that can activate ERα or ERß, respectively. While most act on both receptors, many appear to be subtype-selective, including potent flavonoids that activate ER at sub-micromolar concentrations. We employed an orthogonal assay using a transgenic zebrafish in vivo model that validated the estrogenic potential of these compounds. To our knowledge, this is the largest study thus far on flavonoids and the ER pathway, facilitating the identification of a new set of potential endocrine disruptors acting on both ERα and ERß.

SPACe (Swift Phenotypic Analysis of Cells): an open-source, single cell analysis of Cell Painting data.

Phenotypic profiling by high throughput microscopy has become one of the leading tools for screening large sets of perturbations in cellular models. Of the numerous methods used over the years, the flexible and economical Cell Painting (CP) assay has been central in the field, allowing for large screening campaigns leading to a vast number of data-rich images. Currently, to analyze data of this scale, available open-source software ( i.e. , CellProfiler) requires computational resources that are not available to most laboratories worldwide. In addition, the image-embedded cell-to-cell variation of responses within a population, while collected and analyzed, is usually averaged and unused. Here we introduce SPACe ( S wift P henotypic A nalysis of Ce lls), an open source, Python-based platform for the analysis of single cell image-based morphological profiles produced by CP experiments. SPACe can process a typical dataset approximately ten times faster than CellProfiler on common desktop computers without loss in mechanism of action (MOA) recognition accuracy. It also computes directional distribution-based distances (Earth Mover's Distance - EMD) of morphological features for quality control and hit calling. We highlight several advantages of SPACe analysis on CP assays, including reproducibility across multiple biological replicates, easy applicability to multiple (∼20) cell lines, sensitivity to variable cell-to-cell responses, and biological interpretability to explain image-based features. We ultimately illustrate the advantages of SPACe in a screening campaign of cell metabolism small molecule inhibitors which we performed in seven cell lines to highlight the importance of testing perturbations across models.

Endocrine disrupting chemicals differentially alter intranuclear dynamics and transcriptional activation of estrogen receptor-α.

Transcription is a highly regulated sequence of stochastic processes utilizing many regulators, including nuclear receptors (NR) that respond to stimuli. Endocrine disrupting chemicals (EDCs) in the environment can compete with natural ligands for nuclear receptors to alter transcription. As nuclear dynamics can be tightly linked to transcription, it is important to determine how EDCs affect NR mobility. We use an EPA-assembled set of 45 estrogen receptor-α (ERα) ligands and EDCs in our engineered PRL-Array model to characterize their effect upon transcription using fluorescence in situ hybridization and fluorescence recovery after photobleaching (FRAP). We identified 36 compounds that target ERα-GFP to a transcriptionally active, visible locus. Using a novel method for multi-region FRAP analysis we find a strong negative correlation between ERα mobility and inverse agonists. Our findings indicate that ERα mobility is not solely tied to transcription but affected highly by the chemical class binding the receptor.

Systematic identification of A-to-I editing associated regulators from multiple human cancers.

A-to-I editing is the most common editing type in humans that is catalyzed by ADAR family members (ADARs), ADAR1 and ADAR2. Although millions of A-to-I editing sites have recently been discovered, the regulation mechanisms of the RNA editing process are still not clear. Herein, we developed a two-step logistic regression model to identify genes that are potentially involved in the RNA editing process in four human cancers. In the first step, we tested the association of each editing site with known enzymes. To validate the logistic regression model, we collected 10 genes with 168 editing sites from multiple published studies and obtained a nearly 100% validation rate. ADAR1 was identified as the enzyme associated with the majority of the A-to-I editing sites. Thus, ADAR1 was taken as a control gene in the second step to identify genes that have a stronger regulation effect on editing sites than ADAR1. Using our advanced method, we successfully found a set of genes that were significantly positively or negatively associated (PA or NA) with specific sets of RNA editing sites. 51 of these genes had been reported in at least one previous study. We highlighted two genes: 1), SRSF5, supported by three previous studies, and 2) MIR22HG, supported by one previous study and two of our cancer datasets. The PA and NA genes were cancer-specific but shared common pathways. Interestingly, the PA genes from kidney cancer were enriched for survival-associated genes while the NA genes were not, indicating that the PA genes may play more important roles in kidney cancer progression.

A Mechanistic High-Content Analysis Assay Using a Chimeric Androgen Receptor That Rapidly Characterizes Androgenic Chemicals.

Human health is at risk from environmental exposures to a wide range of chemical toxicants and endocrine-disrupting chemicals (EDCs). As part of understanding this risk, the U.S. Environmental Protection Agency (EPA) has been pursuing new high-throughput in vitro assays and computational models to characterize EDCs. EPA models have incorporated our high-content analysis-based green fluorescent protein estrogen receptor (GFP-ER): PRL-HeLa assay, which allows direct visualization of ER binding to DNA regulatory elements. Here, we characterize a modified functional assay based on the stable expression of a chimeric androgen receptor (ARER), wherein a region containing the native AR DNA-binding domain (DBD) was replaced with the ERα DBD (amino acids 183-254). We demonstrate that the AR agonist dihydrotestosterone induces GFP-ARER nuclear translocation, PRL promoter binding, and transcriptional activity at physiologically relevant concentrations (<1 nM). In contrast, the AR antagonist bicalutamide induces only nuclear translocation of the GFP-ARER receptor (at µM concentrations). Estradiol also fails to induce visible chromatin binding, indicating androgen specificity. In a screen of reference chemicals from the EPA and the Agency for Toxic Substances and Disease Registry, the GFP-ARER cell model identified and mechanistically grouped activity by known (anti-)androgens based on the ability to induce nuclear translocation and/or chromatin binding. Finally, the cell model was used to identify potential (anti-)androgens in environmental samples in collaboration with the Houston Ship Channel/Galveston Bay Texas A&M University EPA Superfund Research Program. Based on these data, the chromatin-binding, in vitro assay-based GFP-ARER model represents a selective tool for rapidly identifying androgenic activity associated with drugs, chemicals, and environmental samples.

Clinical Relevance of Noncoding Adenosine-to-Inosine RNA Editing in Multiple Human Cancers.

PURPOSE: RNA editing is a post-transcriptional process that alters the nucleotide sequences of certain transcripts, in vertebrate most often converting adenosines to inosines. Multiple studies have recently implicated RNA editing in cancer development; however, most studies have focused on recoding RNA editing events. The function and clinical relevance of noncoding RNA (ncRNA) editing events in cancers have not been systematically examined. PATIENTS AND METHODS: We improved our previously published pipeline to identify ncRNA editing sites from four human cancers: liver hepatocellular carcinoma, lung adenocarcinoma, kidney renal clear-cell carcinoma, and thyroid carcinoma. We then developed multiple advanced statistical models to identify significantly differential edited (DE) sites between tumor and normal samples and clinical relevance ncRNA editing sites, as well as to investigate the association between gene expression, ncRNA editing, and microRNAs. Finally, we validated computational results with experiments. RESULTS: We identified 3,788 ncRNA editing sites of high confidence from the four cancers. We found thousands of DE sites which had distinct profiles across the four cancers. In kidney cancer, which had the largest uncensored survival data among the four cancers, 80 DE sites were significantly associated with patient survival. We identified 3' untranslated region (UTR) RNA editing sites that can affect gene expression, either independent of or by working with microRNAs. We validated that the 3'UTR RNA editing sites in CWF19L1 and F11R genes resulted in increased protein levels and that alterations of the expression of the two genes affected the proliferation of human embryonic kidney cells. CONCLUSION: On the basis of our computational and experimental results, we hypothesize that 3'UTR editing sites may affect their host gene expression, thereby affecting cell proliferation.

DNA Methylation Controls Metastasis-Suppressive 14q32-Encoded miRNAs.

Expression of 14q32-encoded miRNAs is a favorable prognostic factor in patients with metastatic cancer. In this study, we used genomic inhibition of DNA methylation through disruption of DNA methyltransferases DNMT1 and DNMT3B and pharmacologic inhibition with 5-Aza-2'-deoxycytidine (5-Aza-dC, decitabine) to demonstrate that DNA methylation predominantly regulates expression of metastasis-suppressive miRNAs in the 14q32 cluster. DNA demethylation facilitated CCCTC-binding factor (CTCF) recruitment to the maternally expressed gene 3 differentially methylated region (MEG3-DMR), which acts as a cis-regulatory element for 14q32 miRNA expression. 5-Aza-dC activated demethylation of the MEG3-DMR and expression of 14q32 miRNAs, which suppressed adhesion, invasion, and migration (AIM) properties of metastatic tumor cells. Cancer cells with MEG3-DMR hypomethylation exhibited constitutive expression of 14q32 miRNAs and resistance to 5-Aza-dC-induced suppression of AIM. Expression of methylation-dependent 14q32 miRNAs suppressed metastatic colonization in preclinical models of lung and liver metastasis and correlated with improved clinical outcomes in patients with metastatic cancer. These findings implicate epigenetic modification via DNA methylation in the regulation of metastatic propensity through miRNA networks and identify a previously unrecognized action of decitabine on the activation of metastasis-suppressive miRNAs. SIGNIFICANCE: This study investigates epigenetic regulation of metastasis-suppressive miRNAs and the effect on metastasis.

STING Promotes Homeostasis via Regulation of Cell Proliferation and Chromosomal Stability.

Given the integral role of stimulator of interferon genes (STING, TMEM173) in the innate immune response, its loss or impairment in cancer is thought to primarily affect antitumor immunity. Here we demonstrate a role for STING in the maintenance of cellular homeostasis through regulation of the cell cycle. Depletion of STING in human and murine cancer cells and tumors resulted in increased proliferation compared with wild-type controls. Microarray analysis revealed genes involved in cell-cycle regulation are differentially expressed in STINGko compared with WT MEFs. STING-mediated regulation of the cell cycle converged on NFκB- and p53-driven activation of p21. The absence of STING led to premature activation of cyclin-dependent kinase 1 (CDK1), early onset to S-phase and mitosis, and increased chromosome instability, which was enhanced by ionizing radiation. These results suggest a pivotal role for STING in maintaining cellular homeostasis and response to genotoxic stress. SIGNIFICANCE: These findings provide clear mechanistic understanding of the role of STING in cell-cycle regulation, which may be exploited in cancer therapy because most normal cells express STING, while many tumor cells do not.See related commentary by Gius and Zhu, p. 1295.

Differential Regulation of Progesterone Receptor-Mediated Transcription by CDK2 and DNA-PK.

Progesterone receptor (PR) function is altered by cell signaling, but the mechanisms of kinase-specific regulation are not well defined. To examine the role of cell signaling in the regulation of PR transcriptional activity, we have utilized a previously developed mammalian-based estrogen-response element promoter array cell model and automated cell imaging and analysis platform to visualize and quantify effects of specific kinases on different mechanistic steps of PR-mediated target gene activation. For these studies, we generated stable estrogen-response element array cell lines expressing inducible chimeric PR that contains a swap of the estrogen receptor-α DNA-binding domain for the DNA-binding domain of PR. We have focused on 2 kinases important for steroid receptor activity: cyclin-dependent kinase 2 and DNA-dependent protein kinase. Treatment with either a Cdk1/2 inhibitor (NU6102) or a DNA-dependent protein kinase inhibitor (NU7441) decreased hormone-mediated chromatin decondensation and transcriptional activity. Further, we observed a quantitative reduction in the hormone-mediated recruitment of select coregulator proteins with NU6102 that is not observed with NU7441. In parallel, we determined the effect of kinase inhibition on hormone-mediated induction of primary and mature transcripts of endogenous genes in T47D breast cancer cells. Treatment with NU6102 was much more effective than NU7441, in inhibiting induction of PR target genes that exhibit a rapid increase in primary transcript expression in response to hormone. Taken together, these results indicate that the 2 kinases regulate PR transcriptional activity by distinct mechanisms.

High throughput microscopy identifies bisphenol AP, a bisphenol A analog, as a novel AR down-regulator.

Prostate cancer remains a deadly disease especially when patients become resistant to drugs that target the Androgen Receptor (AR) ligand binding domain. At this stage, patients develop recurring castrate-resistant prostate cancers (CRPCs). Interestingly, CRPC tumors maintain dependency on AR for growth; moreover, in CRPCs, constitutively active AR splice variants (e.g., AR-V7) begin to be expressed at higher levels. These splice variants lack the ligand binding domain and are rendered insensitive to current endocrine therapies. Thus, it is of paramount importance to understand what regulates the expression of AR and its splice variants to identify new therapeutic strategies in CRPCs. Here, we used high throughput microscopy and quantitative image analysis to evaluate effects of selected endocrine disruptors on AR levels in multiple breast and prostate cancer cell lines. Bisphenol AP (BPAP), which is used in chemical and medical industries, was identified as a down-regulator of both full length AR and the AR-V7 splice variant. We validated its activity by performing time-course, dose-response, Western blot and qPCR analyses. BPAP also reduced the percent of cells in S phase, which was accompanied by a ~60% loss in cell numbers and colony formation in anchorage-independent growth assays. Moreover, it affected mitochondria size and cell metabolism. In conclusion, our high content analysis-based screening platform was used to classify the effect of compounds on endogenous ARs, and identified BPAP as being capable of causing AR (both full-length and variants) down-regulation, cell cycle arrest and metabolic alterations in CRPC cell lines.

Defining estrogenic mechanisms of bisphenol A analogs through high throughput microscopy-based contextual assays.

Environmental exposures to chemically heterogeneous endocrine-disrupting chemicals (EDCs) mimic or interfere with hormone actions and negatively affect human health. Despite public interest and the prevalence of EDCs in the environment, methods to mechanistically classify these diverse chemicals in a high throughput (HT) manner have not been actively explored. Here, we describe the use of multiparametric, HT microscopy-based platforms to examine how a prototypical EDC, bisphenol A (BPA), and 18 poorly studied BPA analogs (BPXs), affect estrogen receptor (ER). We show that short exposure to BPA and most BPXs induces ERα and/or ERß loading to DNA changing target gene transcription. Many BPXs exhibit higher affinity for ERß and act as ERß antagonists, while they act largely as agonists or mixed agonists and antagonists on ERα. Finally, despite binding to ERs, some BPXs exhibit lower levels of activity. Our comprehensive view of BPXs activities allows their classification and the evaluation of potential harmful effects. The strategy described here used on a large-scale basis likely offers a faster, more cost-effective way to identify safer BPA alternatives.

Automated microscopy and image analysis for androgen receptor function.

Systems-level approaches have emerged that rely on analytical, microscopy-based technology for the discovery of novel drug targets and the mechanisms driving AR signaling, transcriptional activity, and ligand independence. Single cell behavior can be quantified by high-throughput microscopy methods through analysis of endogenous protein levels and localization or creation of biosensor cell lines that can simultaneously detect both acute and latent responses to known and unknown androgenic stimuli. The cell imaging and analytical protocols can be automated to discover agonist/antagonist response windows for nuclear translocation, reporter gene activity, nuclear export, and subnuclear transcription events, facilitating access to a multiplex model system that is inherently unavailable through classic biochemical approaches. In this chapter, we highlight the key steps needed for developing, conducting, and analyzing high-throughput screens to identify effectors of AR signaling.