A model of estrogen-related gene expression reveals non-linear effects in transcriptional response to tamoxifen

Immortalization Reversibility in the Context of Cell Therapy Biosafety

Immortalization (genetically induced prevention of replicative senescence) is a promising approach to obtain cellular material for cell therapy or for bio-artificial organs aimed at overcoming the problem of donor material shortage. Immortalization is reversed before cells are used in vivo to allow cell differentiation into the mature phenotype and avoid tumorigenic effects of unlimited cell proliferation. However, there is no certainty that the process of de-immortalization is 100% effective and that it does not cause unwanted changes in the cell. In this review, we discuss various approaches to reversible immortalization, emphasizing their advantages and disadvantages in terms of biosafety. We describe the most promising approaches in improving the biosafety of reversibly immortalized cells: CRISPR/Cas9-mediated immortogene insertion, tamoxifen-mediated self-recombination, tools for selection of successfully immortalized cells, using a decellularized extracellular matrix, and ensuring post-transplant safety with the use of suicide genes. The last process may be used as an add-on for previously existing reversible immortalized cell lines.

Deep neural networks with knockoff features identify nonlinear causal relations and estimate effect sizes in complex biological systems

BACKGROUND

Learning the causal structure helps identify risk factors, disease mechanisms, and candidate therapeutics for complex diseases. However, although complex biological systems are characterized by nonlinear associations, existing bioinformatic methods of causal inference cannot identify the nonlinear relationships and estimate their effect size.

RESULTS

To overcome these limitations, we developed the first computational method that explicitly learns nonlinear causal relations and estimates the effect size using a deep neural network approach coupled with the knockoff framework, named causal directed acyclic graphs using deep learning variable selection (DAG-deepVASE). Using simulation data of diverse scenarios and identifying known and novel causal relations in molecular and clinical data of various diseases, we demonstrated that DAG-deepVASE consistently outperforms existing methods in identifying true and known causal relations. In the analyses, we also illustrate how identifying nonlinear causal relations and estimating their effect size help understand the complex disease pathobiology, which is not possible using other methods.

CONCLUSIONS

With these advantages, the application of DAG-deepVASE can help identify driver genes and therapeutic agents in biomedical studies and clinical trials.

Relating past and present diet to phenotypic and transcriptomic variation in the fruit fly

Background

Sub-optimal developmental diets often have adverse effects on long-term fitness and health. One hypothesis is that such effects are caused by mismatches between the developmental and adult environment, and may be mediated by persistent changes in gene expression. However, there are few experimental tests of this hypothesis. Here we address this using the fruit fly, Drosophila melanogaster. We vary diet during development and adulthood in a fully factorial design and assess the consequences for both adult life history traits and gene expression at middle and old age.

Results

We find no evidence that mismatches between developmental and adult diet are detrimental to either lifespan or fecundity. Rather, developmental and adult diet exert largely independent effects on both lifespan and gene expression, with adult diet having considerably more influence on both traits. Furthermore, we find effects of developmental diet on the transcriptome that persist into middle and old-age. Most of the genes affected show no correlation with the observed phenotypic effects of larval diet on lifespan. However, in each sex we identify a cluster of ribosome, transcription, and translation-related genes whose expression is altered across the lifespan and negatively correlated with lifespan.

Conclusions

As several recent studies have linked decreased expression of ribosomal and transcription related proteins to increased lifespan, these provide promising candidates for mediating the effects of larval diet on lifespan. We place our findings in the context of theories linking developmental conditions to late-life phenotypes and discuss the likelihood that gene expression differences caused by developmental exposure causally relate to adult ageing phenotypes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3968-z) contains supplementary material, which is available to authorized users.

International Union of Basic and Clinical Pharmacology. XCVII. G Protein-Coupled Estrogen Receptor and Its Pharmacologic Modulators

Estrogens are critical mediators of multiple and diverse physiologic effects throughout the body in both sexes, including the reproductive, cardiovascular, endocrine, nervous, and immune systems. As such, alterations in estrogen function play important roles in many diseases and pathophysiological conditions (including cancer), exemplified by the lower prevalence of many diseases in premenopausal women. Estrogens mediate their effects through multiple cellular receptors, including the nuclear receptor family (ERα and ERβ) and the G protein-coupled receptor (GPCR) family (GPR30/G protein-coupled estrogen receptor [GPER]). Although both receptor families can initiate rapid cell signaling and transcriptional regulation, the nuclear receptors are traditionally associated with regulating gene expression, whereas GPCRs are recognized as mediating rapid cellular signaling. Estrogen-activated pathways are not only the target of multiple therapeutic agents (e.g., tamoxifen, fulvestrant, raloxifene, and aromatase inhibitors) but are also affected by a plethora of phyto- and xeno-estrogens (e.g., genistein, coumestrol, bisphenol A, dichlorodiphenyltrichloroethane). Because of the existence of multiple estrogen receptors with overlapping ligand specificities, expression patterns, and signaling pathways, the roles of the individual receptors with respect to the diverse array of endogenous and exogenous ligands have been challenging to ascertain. The identification of GPER-selective ligands however has led to a much greater understanding of the roles of this receptor in normal physiology and disease as well as its interactions with the classic estrogen receptors ERα and ERβ and their signaling pathways. In this review, we describe the history and characterization of GPER over the past 15 years focusing on the pharmacology of steroidal and nonsteroidal compounds that have been employed to unravel the biology of this most recently recognized estrogen receptor.

Tamoxifen induces a pluripotency signature in breast cancer cells and human tumors

Tamoxifen is the treatment of choice in estrogen receptor alpha breast cancer patients that are eligible for adjuvant endocrine therapy. However, ∼50% of ERα-positive tumors exhibit intrinsic or rapidly acquire resistance to endocrine treatment. Unfortunately, prediction of de novo resistance to endocrine therapy and/or assessment of relapse likelihood remain difficult. While several mechanisms regulating the acquisition and the maintenance of endocrine resistance have been reported, there are several aspects of this phenomenon that need to be further elucidated. Altered metabolic fate of tamoxifen within patients and emergence of tamoxifen-resistant clones, driven by evolution of the disease phenotype during treatment, appear as the most compelling hypotheses so far. In addition, tamoxifen was reported to induce pluripotency in breast cancer cell lines, in vitro. In this context, we have performed a whole transcriptome analysis of an ERα-positive (T47D) and a triple-negative breast cancer cell line (MDA-MB-231), exposed to tamoxifen for a short time frame (hours), in order to identify how early pluripotency-related effects of tamoxifen may occur. Our ultimate goal was to identify whether the transcriptional actions of tamoxifen related to induction of pluripotency are mediated through specific ER-dependent or independent mechanisms. We report that even as early as 3 hours after the exposure of breast cancer cells to tamoxifen, a subset of ERα-dependent genes associated with developmental processes and pluripotency are induced and this is accompanied by specific phenotypic changes (expression of pluripotency-related proteins). Furthermore we report an association between the increased expression of pluripotency-related genes in ERα-positive breast cancer tissues samples and disease relapse after tamoxifen therapy. Finally we describe that in a small group of ERα-positive breast cancer patients, with disease relapse after surgery and tamoxifen treatment, ALDH1A1 (a marker of pluripotency in epithelial cancers which is absent in normal breast tissue) is increased in relapsing tumors, with a concurrent modification of its intra-cellular localization. Our data could be of value in the discrimination of patients susceptible to develop tamoxifen resistance and in the selection of optimized patient-tailored therapies.

A model for aryl hydrocarbon receptor-activated gene expression shows potency and efficacy changes and predicts squelching due to competition for transcription co-activators

A stochastic model of nuclear receptor-mediated transcription was developed based on activation of the aryl hydrocarbon receptor (AHR) by 2,3,7,8-tetrachlorodibenzodioxin (TCDD) and subsequent binding the activated AHR to xenobiotic response elements (XREs) on DNA. The model was based on effects observed in cells lines commonly used as in vitro experimental systems. Following ligand binding, the AHR moves into the cell nucleus and forms a heterodimer with the aryl hydrocarbon nuclear translocator (ARNT). In the model, a requirement for binding to DNA is that a generic coregulatory protein is subsequently bound to the AHR-ARNT dimer. Varying the amount of coregulator available within the nucleus altered both the potency and efficacy of TCDD for inducing for transcription of CYP1A1 mRNA, a commonly used marker for activation of the AHR. Lowering the amount of available cofactor slightly increased the EC50 for the transcriptional response without changing the efficacy or maximal response. Further reduction in the amount of cofactor reduced the efficacy and produced non-monotonic dose-response curves (NMDRCs) at higher ligand concentrations. The shapes of these NMDRCs were reminiscent of the phenomenon of squelching. Resource limitations for transcriptional machinery are becoming apparent in eukaryotic cells. Within single cells, nuclear receptor-mediated gene expression appears to be a stochastic process; however, intercellular communication and other aspects of tissue coordination may represent a compensatory process to maintain an organism’s ability to respond on a phenotypic level to various stimuli within an inconstant environment.

A kinetic model identifies phosphorylated estrogen receptor-α (ERα) as a critical regulator of ERα dynamics in breast cancer

Receptor levels are a key mechanism by which cells regulate their response to stimuli. The levels of estrogen receptor-α (ERα) impact breast cancer cell proliferation and are used to predict prognosis and sensitivity to endocrine therapy. Despite the clinical application of this information, it remains unclear how different cellular processes interact as a system to control ERα levels. To address this question, experimental results from the ERα-positive human breast cancer cell line (MCF-7) treated with 17-β-estradiol or vehicle control were used to develop a mass-action kinetic model of ERα regulation. Model analysis determined that RNA dynamics could be captured through phosphorylated ERα (pERα)-dependent feedback on transcription. Experimental analysis confirmed that pERα-S118 binds to the estrogen receptor-1 (ESR1) promoter, suggesting that pERα can feedback on ESR1 transcription. Protein dynamics required a separate mechanism in which the degradation rate for pERα was 8.3-fold higher than nonphosphorylated ERα. Using a model with both mechanisms, the root mean square error was 0.078. Sensitivity analysis of this combined model determined that while multiple mechanisms regulate ERα levels, pERα-dependent feedback elicited the strongest effect. Combined, our computational and experimental results identify phosphorylation of ERα as a critical decision point that coordinates the cellular circuitry to regulate ERα levels.

Promoting E2F1-mediated apoptosis in oestrogen receptor-α-negative breast cancer cells

Background

Because oestrogen receptor α (ERα) regulates E2F1 expression to mediate tamoxifen resistance in ERα-positive breast cancer cells, we aimed to define the possible roles of ERα and E2F1 in promoting the resistance of ERα-negative breast cancer cells to 4-hydroxy-tamoxifen (4OHT).

Methods

This study utilised conventional techniques to demonstrate the effects of 4OHT on the expression of ERα and E2F1 and also examined the individual and combined effects of 4OHT with dipyridamole (DIPY) and 3-O-(3,4,5-trimethoxybenzoyl)-(-)-catechin (TMCG) on the oestrogen-negative MDA-MB-231 breast cancer cell line using viability assays, Hoechst staining, MALDI-TOF mass spectroscopy, and confocal microscopy.

Results

Despite the ERα-negative status of the MDA-MB-231 cells, we observed that 4OHT efficiently up-regulated ERα in these cells and that this upregulation promoted E2F1-mediated cell growth. Because E2F1 plays a dual role in cell growth/apoptosis, we designed a therapy incorporating TMCG/DIPY to take advantage of the elevated E2F1 expression in these 4OHT-treated cells. 4OHT enhances the toxicity of TMCG/DIPY in these ERα-negative breast cancer cells.

Conclusions

Because TMCG/DIPY treatment modulates the methylation status/stability of E2F1, the results demonstrate that therapies targeting the epigenetic machinery of cancer cells in the presence of overexpressed E2F1 may result in efficient E2F1-mediated cell death.

Progesterone receptor assembly of a transcriptional complex along with activator protein 1, signal transducer and activator of transcription 3 and ErbB-2 governs breast cancer growth and predicts response to endocrine therapy

INTRODUCTION

The role of the progesterone receptor (PR) in breast cancer remains a major clinical challenge. Although PR induces mammary tumor growth, its presence in breast tumors is a marker of good prognosis. We investigated coordinated PR rapid and nonclassical transcriptional effects governing breast cancer growth and endocrine therapy resistance.

METHODS

We used breast cancer cell lines expressing wild-type and mutant PRs, cells sensitive and resistant to endocrine therapy, a variety of molecular and cellular biology approaches, in vitro proliferation studies and preclinical models to explore PR regulation of cyclin D1 expression, tumor growth, and response to endocrine therapy. We investigated the clinical significance of activator protein 1 (AP-1) and PR interaction in a cohort of 99 PR-positive breast tumors by an immunofluorescence protocol we developed. The prognostic value of AP-1/PR nuclear colocalization in overall survival (OS) was evaluated using Kaplan-Meier method, and Cox model was used to explore said colocalization as an independent prognostic factor for OS.

RESULTS

We demonstrated that at the cyclin D1 promoter and through coordinated rapid and transcriptional effects, progestin induces the assembly of a transcriptional complex among AP-1, Stat3, PR, and ErbB-2 which functions as an enhanceosome to drive breast cancer growth. Our studies in a cohort of human breast tumors identified PR and AP-1 nuclear interaction as a marker of good prognosis and better OS in patients treated with tamoxifen (Tam), an anti-estrogen receptor therapy. Rationale for this finding was provided by our demonstration that Tam inhibits rapid and genomic PR effects, rendering breast cancer cells sensitive to its antiproliferative effects.

CONCLUSIONS

We here provided novel insight into the paradox of PR action as well as new tools to identify the subgroup of ER+/PR + patients unlikely to respond to ER-targeted therapies.