Human nuclear receptors (NRs) genes have prognostic significance in hepatocellular carcinoma patients.

BACKGROUND: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality in the world. METHOD: We downloaded the mRNA profiles and clinical information of 371 HCC patients from The Cancer Genome Atlas (TCGA) database. The consensus clustering analysis with the mRNA levels of 48 nuclear receptors (NRs) was performed by the "ConsensusClusterPlus." The univariate Cox regression analysis was performed to predict the prognostic significance of NRs on HCC. The risk score was calculated by the prognostic model constructed based on eight optimal NRs. Then multivariate Cox regression analysis was performed to determine whether the risk score is an independent prognostic signature. Finally, the nomogram based on multiple independent prognostic factors was used to predict the long-term survival of HCC patients. RESULTS: The prognostic model constructed based on the eight optimal NRs (NR1H3, ESR1, NR1I2, NR2C1, NR6A1, PPARD, PPARG, and VDR) could effectively predict the prognosis of HCC patients as an independent prognostic signature. Moreover, the nomogram was constructed based on multiple independent prognostic factors including risk score and tumor node metastasis (TNM) stage and could better predict the long-term survival for 3- and 5-year of HCC patients. CONCLUSION: Our results provided novel evidences that NRs could act as the potential prognostic signatures for HCC patients.

The EDCMET Project: Metabolic Effects of Endocrine Disruptors.

Endocrine disruptors (EDs) are defined as chemicals that mimic, block, or interfere with hormones in the body's endocrine systems and have been associated with a diverse array of health issues. The concept of endocrine disruption has recently been extended to metabolic alterations that may result in diseases, such as obesity, diabetes, and fatty liver disease, and constitute an increasing health concern worldwide. However, while epidemiological and experimental data on the close association of EDs and adverse metabolic effects are mounting, predictive methods and models to evaluate the detailed mechanisms and pathways behind these observed effects are lacking, thus restricting the regulatory risk assessment of EDs. The EDCMET (Metabolic effects of Endocrine Disrupting Chemicals: novel testing METhods and adverse outcome pathways) project brings together systems toxicologists; experimental biologists with a thorough understanding of the molecular mechanisms of metabolic disease and comprehensive in vitro and in vivo methodological skills; and, ultimately, epidemiologists linking environmental exposure to adverse metabolic outcomes. During its 5-year journey, EDCMET aims to identify novel ED mechanisms of action, to generate (pre)validated test methods to assess the metabolic effects of Eds, and to predict emergent adverse biological phenotypes by following the adverse outcome pathway (AOP) paradigm.

In vitro study on the agonistic and antagonistic activities of bisphenol-S and other bisphenol-A congeners and derivatives via nuclear receptors.

Bisphenols are a group of chemicals structurally similar to bisphenol-A (BPA) in current use as the primary raw material in the production of polycarbonate and epoxy resins. Some bisphenols are intended to replace BPA in several industrial applications. This is the case of bisphenol-S (BPS), which has an excellent stability at high temperature and resistance to sunlight. Studies on the endocrine properties of BPS have focused on its interaction with human estrogen receptor alpha (hERα), but information on its interaction with other nuclear receptors is scarce. The aim of this study was to investigate interactions of BPS, BPF, BPA and its halogenated derivatives, tetrachlorobisphenol A (TCBPA), and tetrabromobisphenol A (TBBPA), with human estrogen receptors (hERα and hERß), androgen receptor (hAR), and pregnane X receptor (hPXR), using a panel of in vitro bioassays based on competitive binding to nuclear receptors (NRs), reporter gene expression, and cell proliferation assessment. BPS, BPF, and BPA efficiently activated both ERs, while TCBPA behaved as weak hERα agonist. Unlike BPF and BPA, BPS was more active in the hERß versus hERα assay. BPF and BPA were full hAR antagonists (BPA>BPF), whereas BPA and BPS were weak hAR agonists. Only BPA, TCBPA, and TBBPA, were hPXR agonists (TCBPA>TBBPA>BPA). These findings provide evidence that BPA congeners and derivatives disrupt multiple NRs and may therefore interfere with the endocrine system. Hence, further research is needed to evaluate the potential endocrine-disrupting activity of putative BPA substitutes.

Nuclear receptors and transcriptional regulation in non-alcoholic fatty liver disease.

BACKGROUND: As a result of a sedentary lifestyle and excess food consumption in modern society, non-alcoholic fatty liver disease (NAFLD) characterized by fat accumulation in the liver is becoming a major disease burden. Non-alcoholic steatohepatitis (NASH) is an advanced form of NAFLD characterized by inflammation and fibrosis that can lead to hepatocellular carcinoma and liver failure. Nuclear receptors (NRs) are a family of ligand-regulated transcription factors that closely control multiple aspects of metabolism. Their transcriptional activity is modulated by various ligands, including hormones and lipids. NRs serve as potential pharmacological targets for NAFLD/NASH and other metabolic diseases. SCOPE OF REVIEW: In this review, we provide a comprehensive overview of NRs that have been studied in the context of NAFLD/NASH with a focus on their transcriptional regulation, function in preclinical models, and studies of their clinical utility. MAJOR CONCLUSIONS: The transcriptional regulation of NRs is context-dependent. During the dynamic progression of NAFLD/NASH, NRs play diverse roles in multiple organs and different cell types in the liver, which highlights the necessity of targeting NRs in a stage-specific and cell-type-specific manner to enhance the efficacy and safety of treatment methods.

Application of Machine Learning Methods in Predicting Nuclear Receptors and their Families.

Nuclear receptors (NRs) are a superfamily of ligand-dependent transcription factors that are closely related to cell development, differentiation, reproduction, homeostasis, and metabolism. According to the alignments of the conserved domains, NRs are classified and assigned the following seven subfamilies or eight subfamilies: (1) NR1: thyroid hormone like (thyroid hormone, retinoic acid, RAR-related orphan receptor, peroxisome proliferator activated, vitamin D3- like), (2) NR2: HNF4-like (hepatocyte nuclear factor 4, retinoic acid X, tailless-like, COUP-TFlike, USP), (3) NR3: estrogen-like (estrogen, estrogen-related, glucocorticoid-like), (4) NR4: nerve growth factor IB-like (NGFI-B-like), (5) NR5: fushi tarazu-F1 like (fushi tarazu-F1 like), (6) NR6: germ cell nuclear factor like (germ cell nuclear factor), and (7) NR0: knirps like (knirps, knirpsrelated, embryonic gonad protein, ODR7, trithorax) and DAX like (DAX, SHP), or dividing NR0 into (7) NR7: knirps like and (8) NR8: DAX like. Different NRs families have different structural features and functions. Since the function of a NR is closely correlated with which subfamily it belongs to, it is highly desirable to identify NRs and their subfamilies rapidly and effectively. The knowledge acquired is essential for a proper understanding of normal and abnormal cellular mechanisms. With the advent of the post-genomics era, huge amounts of sequence-known proteins have increased explosively. Conventional methods for accurately classifying the family of NRs are experimental means with high cost and low efficiency. Therefore, it has created a greater need for bioinformatics tools to effectively recognize NRs and their subfamilies for the purpose of understanding their biological function. In this review, we summarized the application of machine learning methods in the prediction of NRs from different aspects. We hope that this review will provide a reference for further research on the classification of NRs and their families.

IDPs and their complexes in GPCR and nuclear receptor signaling.

G protein-coupled receptors (GPCRs) and Nuclear Receptors (NRs) are two signaling machineries that are involved in major physiological processes and, as a consequence, in a substantial number of diseases. Therefore, they actually represent two major targets for drugs with potential applications in almost all public health issues. Full exploitation of these targets for therapeutic purposes nevertheless requires opening original avenues in drug design, and this in turn implies a better understanding of the molecular mechanisms underlying their functioning. However, full comprehension of how these complex systems function and how they are deregulated in a physiopathological context is obscured by the fact that these proteins include a substantial number of disordered regions that are central to their mechanism of action but whose structural and functional properties are still largely unexplored. In this chapter, we describe how these intrinsically disordered regions (IDR) or proteins (IDP) intervene, control and finely modulate the thermodynamics of complexes involved in GPCR and NR regulation, which in turn triggers a multitude of cascade of events that are exquisitely orchestrated to ultimately control the biological output.

A comprehensive data mining study shows that most nuclear receptors act as newly proposed homeostasis-associated molecular pattern receptors.

BACKGROUND: Nuclear receptors (NRs) can regulate gene expression; therefore, they are classified as transcription factors. Despite the extensive research carried out on NRs, still several issues including (1) the expression profile of NRs in human tissues, (2) how the NR expression is modulated during atherosclerosis and metabolic diseases, and (3) the overview of the role of NRs in inflammatory conditions are not fully understood. METHODS: To determine whether and how the expression of NRs are regulated in physiological/pathological conditions, we took an experimental database analysis to determine expression of all 48 known NRs in 21 human and 17 murine tissues as well as in pathological conditions. RESULTS: We made the following significant findings: (1) NRs are differentially expressed in tissues, which may be under regulation by oxygen sensors, angiogenesis pathway, stem cell master regulators, inflammasomes, and tissue hypo-/hypermethylation indexes; (2) NR sequence mutations are associated with increased risks for development of cancers and metabolic, cardiovascular, and autoimmune diseases; (3) NRs have less tendency to be upregulated than downregulated in cancers, and autoimmune and metabolic diseases, which may be regulated by inflammation pathways and mitochondrial energy enzymes; and (4) the innate immune sensor inflammasome/caspase-1 pathway regulates the expression of most NRs. CONCLUSIONS: Based on our findings, we propose a new paradigm that most nuclear receptors are anti-inflammatory homeostasis-associated molecular pattern receptors (HAMPRs). Our results have provided a novel insight on NRs as therapeutic targets in metabolic diseases, inflammations, and malignancies.