Suppressors of Cytokine Signaling in Sickness and in Health of Pancreatic β-Cells

Systematic Bayesian posterior analysis guided by Kullback-Leibler divergence facilitates hypothesis formation

Bayesian inference produces a posterior distribution for the parameters of a mathematical model that can be used to guide the formation of hypotheses; specifically, the posterior may be searched for evidence of alternative model hypotheses, which serves as a starting point for hypothesis formation and model refinement. Previous approaches to search for this evidence are largely qualitative and unsystematic; further, demonstrations of these approaches typically stop at hypothesis formation, leaving the questions they raise unanswered. Here, we introduce a Kullback-Leibler (KL) divergence-based ranking to expedite Bayesian hypothesis formation and investigate the hypotheses it generates, ultimately generating novel, biologically significant insights. Our approach uses KL divergence to rank parameters by how much information they gain from experimental data. Subsequently, rather than searching all model parameters at random, we use this ranking to prioritize examining the posteriors of the parameters that gained the most information from the data for evidence of alternative model hypotheses. We test our approach with two examples, which showcase the ability of our approach to systematically uncover different types of alternative hypothesis evidence. First, we test our KL divergence ranking on an established example of Bayesian hypothesis formation. Our top-ranked parameter matches the one previously identified to produce alternative hypotheses. In the second example, we apply our ranking in a novel study of a computational model of prolactin-induced JAK2-STAT5 signaling, a pathway that mediates beta cell proliferation. Within the top 3 ranked parameters (out of 33), we find a bimodal posterior revealing two possible ranges for the prolactin receptor degradation rate. We go on to refine the model, incorporating new data and determining which degradation rate is most plausible. Overall, while the effectiveness of our approach depends on having a properly formulated prior and on the form of the posterior distribution, we demonstrate that our approach offers a novel and generalizable quantitative framework for Bayesian hypothesis formation and use it to produce a novel, biologically-significant insight into beta cell signaling.

Inhibition of anti-inflammatory pathway through suppressors of cytokine signalling (Socs2/Socs3) in the initiation of hepatocellular carcinoma

Hepatocellular carcinoma (HCC), a leading cause of cancer related deaths is predominantly driven by chronic inflammatory responses. Due to asymptomatic nature and lack of early patient biopsies, precise involvement of inflammation in hepatic injury initiation remains unidentified. Aim of the study was to elucidate the regulation patterns of inflammatory signalling from initiation of hepatic injury to development of HCC. HCC mice model was established using DEN followed by repeated doses of CCl₄ and sacrificed at three different stages of disease comprising 7, 14 and 21 weeks. Serum biochemical tests, hepatic lipids quantification, histopathology and qPCR analyses were conducted to characterize the initiation and progression of liver injury and inflammatory signalling. Notably, at 7 weeks, we observed hepatocyte damage and periportal necrotic bodies coupled with induction of Socs2/Socs3 and anti-inflammatory cytokine Il-10. At 14 weeks, mice liver showed advancement of liver injury with micro-vesicular steatosis and moderate collagen deposition around portal zone. With progression of injury, the expression of Socs3 was declined with further reduction of Il-10 and Tgf-β indicating the disturbance of anti-inflammatory mechanism. In contrast, pro-inflammatory cytokines Il1-β, Il6 and Tnf-α were upregulated contributing inflammation. Subsequently, at 21 weeks severe liver damage was estimated as characterized by macro-vesicular steatosis, perisinusoidal collagen bridging, immune cell recruitment and significant upregulation of Col-1α and α-Sma. In parallel, there was significant upregulation of pro/anti-inflammatory cytokines highlighting the commencement of chronic inflammation.

Findings of the study suggest that differential regulation of cytokine suppressors and inflammatory cytokines might play role in the initiation and progression of hepatic injury leading towards HCC.

Targeting the JAK-STAT pathway in autoimmune diseases and cancers: A focus on molecular mechanisms and therapeutic potential

The Janus kinase (JAK)/signal transducer and activator of transcription (STAT) signaling pathway is characterized by diverse immune regulatory systems involving cell proliferation, survival, and inflammation and immune tolerance. Aberrant JAK/STAT transduction activates proinflammatory cytokine signaling that jeopardize the immune balance and thus contributes to the development of autoimmune diseases and cancer progression. The success of several small-molecule JAK inhibitors in the treatment of rheumatologic diseases demonstrates that targeting the JAK/STAT pathway is efficient in suppressing inflammation and sheds light on their therapeutic potential in several autoimmune diseases and cancers. In this review, we discuss the signal transduction and molecular mechanism involving immune function through the JAK-STAT pathway, outline the role of this pathway in autoimmunity and oncoimmunology, and explain the preclinical and clinical trial evidence for the therapeutic potential of targeting the JAK-STAT signaling pathway. Issues regarding the safety and clinical efficacy of JAK inhibitors are reviewed. Ongoing studies are addressed with a focus on emerging indications for JAK inhibition and explanations of the novel mechanisms of JAK-STAT signaling blockade.

Dynamic Regulation of JAK-STAT Signaling Through the Prolactin Receptor Predicted by Computational Modeling

Introduction

The expansion of insulin-producing beta cells during pregnancy is critical to maintain glucose homeostasis in the face of increasing insulin resistance. Prolactin receptor (PRLR) signaling is one of the primary mediators of beta cell expansion during pregnancy, and loss of PRLR signaling results in reduced beta cell mass and gestational diabetes. Harnessing the proliferative potential of prolactin signaling to expand beta cell mass outside of the context of pregnancy requires quantitative understanding of the signaling at the molecular level.

Methods

A mechanistic computational model was constructed to describe prolactin-mediated JAK-STAT signaling in pancreatic beta cells. The effect of different regulatory modules was explored through ensemble modeling. A Bayesian approach for likelihood estimation was used to fit the model to experimental data from the literature.

Results

Including receptor upregulation, with either inhibition by SOCS proteins, receptor internalization, or both, allowed the model to match experimental results for INS-1 cells treated with prolactin. The model predicts that faster dimerization and nuclear import rates of STAT5B compared to STAT5A can explain the higher STAT5B nuclear translocation. The model was used to predict the dose response of STAT5B translocation in rat primary beta cells treated with prolactin and reveal possible strategies to modulate STAT5 signaling.

Conclusions

JAK-STAT signaling must be tightly controlled to obtain the biphasic response in STAT5 activation seen experimentally. Receptor up-regulation, combined with SOCS inhibition, receptor internalization, or both is required to match experimental data. Modulating reactions upstream in the signaling can enhance STAT5 activation to increase beta cell survival.

Electronic supplementary material

The online version of this article (10.1007/s12195-020-00647-8) contains supplementary material, which is available to authorized users.

Prolactin Receptor Signaling Regulates a Pregnancy-Specific Transcriptional Program in Mouse Islets

Pancreatic β-cells undergo profound hyperplasia during pregnancy to maintain maternal euglycemia. Failure to reprogram β-cells into a more replicative state has been found to underlie susceptibility to gestational diabetes mellitus (GDM). We recently identified a requirement for prolactin receptor (PRLR) signaling in the metabolic adaptations to pregnancy, where β-cell-specific PRLR knockout (βPRLRKO) mice exhibit a metabolic phenotype consistent with GDM. However, the underlying transcriptional program that is responsible for the PRLR-dependent metabolic adaptations during gestation remains incompletely understood. To identify PRLR signaling gene regulatory networks and target genes within β-cells during pregnancy, we performed a transcriptomic analysis of pancreatic islets isolated from either βPRLRKO mice or littermate controls in late gestation. Gene set enrichment analysis identified forkhead box protein M1 and polycomb repressor complex 2 subunits, Suz12 and enhancer of zeste homolog 2 (Ezh2), as novel candidate regulators of PRLR-dependent β-cell adaptation. Gene ontology term pathway enrichment revealed both established and novel PRLR signaling target genes that together promote a state of increased cellular metabolism and/or proliferation. In contrast to the requirement for β-cell PRLR signaling in maintaining euglycemia during pregnancy, PRLR target genes were not induced following high-fat diet feeding. Collectively, the current study expands our understanding of which transcriptional regulators and networks mediate gene expression required for islet adaptation during pregnancy. The current work also supports the presence of pregnancy-specific adaptive mechanisms distinct from those activated by nutritional stress.

The role of growth hormone receptor in β cell function

Growth hormone (GH) exerts numerous effects on tissues through binding to its receptor, GHR, which resides on cell membranes in many different organs and tissues. Endocrine pancreatic β cells are the only source of insulin secretion in response to metabolic demand, thereby regulating blood glucose and maintaining metabolic homeostasis. β cell dysfunction is the main composition of diabetes mellitus. Numerous studies have provided strong evidence that GHR signaling plays an independent role in β cell function. In this review, we focus on the role of GHR signaling in β cell actions and the underlying molecular mechanisms.

An Overview of Herbal Products and Secondary Metabolites Used for Management of Type Two Diabetes

Diabetes mellitus is a common effect of uncontrolled high blood sugar and it is associated with long-term damage, dysfunction, and failure of various organs. In the adult population, the global prevalence of diabetes has nearly doubled since 1980. Without effective prevention and management programs, the continuing significant rise in diabetes will have grave consequences on the health and lifespan of the world population, and also on the world economy. Supplements can be used to correct nutritional deficiencies or to maintain an adequate intake of certain nutrients. These are often used as treatments for diabetes, sometimes because they have lower costs, or are more accessible or "natural" compared to prescribed medications. Several vitamins, minerals, botanicals, and secondary metabolites have been reported to elicit beneficial effects in hypoglycemic actions in vivo and in vitro; however, the data remain conflicting. Many pharmaceuticals commonly used today are structurally derived from natural compounds from traditional medicinal plants. Botanicals that are most frequently used to help manage blood glucose include: bitter melon (Momordica charantia), fenugreek (Trigonella foenum graecum), gurmar (Gymnema sylvestre), ivy gourd (Coccinia indica), nopal (Opuntia spp.), ginseng, Russian tarragon (Artemisia dracunculus), cinnamon (Cinnamomum cassia), psyllium (Plantago ovata), and garlic (Allium sativum). In majority of the herbal products and secondary metabolites used in treating diabetes, the mechanisms of action involve regulation of insulin signaling pathways, translocation of GLUT-4 receptor and/or activation the PPARγ. Several flavonoids inhibit glucose absorption by inhibiting intestinal α-amylase and α-glucosidase. In-depth studies to validate the efficacies and safeties of extracts of these traditional medicinal plants are needed, and large, well designed, clinical studies need to be carried out before the use of such preparations can be recommended for treatment and/or prevention of diabetes. The main focus of this review is to describe what we know to date of the active compounds in these, along with their glucose-lowering mechanisms, which are either through insulin-mimicking activity or enhanced glucose uptake.