Nonalcoholic Fatty Liver Disease: Focus on Lipoprotein and Lipid Deregulation

Obesity with associated comorbidities is currently a worldwide epidemic and among the most challenging health conditions in the 21st century. A major metabolic consequence of obesity is insulin resistance which underlies the pathogenesis of the metabolic syndrome. Nonalcoholic fatty liver disease (NAFLD) is the hepatic manifestation of obesity and metabolic syndrome. It comprises a disease spectrum ranging from simple steatosis (fatty liver), through nonalcoholic steatohepatitis (NASH) to fibrosis, and ultimately liver cirrhosis. Abnormality in lipid and lipoprotein metabolism accompanied by chronic inflammation is the central pathway for the development of metabolic syndrome-related diseases, such as atherosclerosis, cardiovascular disease (CVD), and NAFLD. This paper focuses on pathogenic aspect of lipid and lipoprotein metabolism in NAFLD and the relevant mouse models of this complex multifactorial disease

Cell-specific secretory granule sorting mechanisms: the role of MAGEL2 and retromer in hypothalamic regulated secretion

Intracellular protein trafficking and sorting are extremely arduous in endocrine and neuroendocrine cells, which synthesize and secrete on-demand substantial quantities of proteins. To ensure that neuroendocrine secretion operates correctly, each step in the secretion pathways is tightly regulated and coordinated both spatially and temporally. At the trans-Golgi network (TGN), intrinsic structural features of proteins and several sorting mechanisms and distinct signals direct newly synthesized proteins into proper membrane vesicles that enter either constitutive or regulated secretion pathways. Furthermore, this anterograde transport is counterbalanced by retrograde transport, which not only maintains membrane homeostasis but also recycles various proteins that function in the sorting of secretory cargo, formation of transport intermediates, or retrieval of resident proteins of secretory organelles. The retromer complex recycles proteins from the endocytic pathway back to the plasma membrane or TGN and was recently identified as a critical player in regulated secretion in the hypothalamus. Furthermore, melanoma antigen protein L2 (MAGEL2) was discovered to act as a tissue-specific regulator of the retromer-dependent endosomal protein recycling pathway and, by doing so, ensures proper secretory granule formation and maturation. MAGEL2 is a mammalian-specific and maternally imprinted gene implicated in Prader-Willi and Schaaf-Yang neurodevelopmental syndromes. In this review, we will briefly discuss the current understanding of the regulated secretion pathway, encompassing anterograde and retrograde traffic. Although our understanding of the retrograde trafficking and sorting in regulated secretion is not yet complete, we will review recent insights into the molecular role of MAGEL2 in hypothalamic neuroendocrine secretion and how its dysregulation contributes to the symptoms of Prader-Willi and Schaaf-Yang patients. Given that the activation of many secreted proteins occurs after they enter secretory granules, modulation of the sorting efficiency in a tissue-specific manner may represent an evolutionary adaptation to environmental cues

The Sterolgene v0 cDNA microarray: a systemic approach to studies of cholesterol homeostasis and drug metabolism

<p>Abstract</p> <p>Background</p> <p>Cholesterol homeostasis and xenobiotic metabolism are complex biological processes, which are difficult to study with traditional methods. Deciphering complex regulation and response of these two processes to different factors is crucial also for understanding of disease development. Systems biology tools as are microarrays can importantly contribute to this knowledge and can also discover novel interactions between the two processes.</p> <p>Results</p> <p>We have developed a low density Sterolgene v0 cDNA microarray dedicated to studies of cholesterol homeostasis and drug metabolism in the mouse. To illustrate its performance, we have analyzed mouse liver samples from studies focused on regulation of cholesterol homeostasis and drug metabolism by diet, drugs and inflammation. We observed down-regulation of cholesterol biosynthesis during fasting and high-cholesterol diet and subsequent up-regulation by inflammation. Drug metabolism was down-regulated by fasting and inflammation, but up-regulated by phenobarbital treatment and high-cholesterol diet. Additionally, the performance of the Sterolgene v0 was compared to the two commercial high density microarray platforms: the Agilent cDNA (G4104A) and the Affymetrix MOE430A GeneChip. We hybridized identical RNA samples to the commercial microarrays and showed that the performance of Sterolgene is comparable to commercial arrays in terms of detection of changes in cholesterol homeostasis and drug metabolism.</p> <p>Conclusion</p> <p>Using the Sterolgene v0 microarray we were able to detect important changes in cholesterol homeostasis and drug metabolism caused by diet, drugs and inflammation. Together with its next generations the Sterolgene microarrays represent original and dedicated tools enabling focused and cost effective studies of cholesterol homeostasis and drug metabolism. These microarrays have the potential of being further developed into screening or diagnostic tools.</p

Heterogeneity in hormone-dependent breast cancer and therapy: Steroid hormones, HER2, melanoma antigens, and cannabinoid receptors

Breast cancer is the most frequently diagnosed cancer and the leading cause of death by cancer among women worldwide. The prognosis of the disease and patients’ response to different types of therapies varies in different subgroups of this heterogeneous disease. The subgroups are based on histological and molecular characteristics of the tumor, especially the expression of estrogen (ER) and progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Hormone-dependent breast cancer, determined predominantly by the presence of ER, is the most common type of breast cancer. Patients with hormone-dependent breast cancer have an available targeted therapy, however, tumor cells can develop resistance to the therapy, which is a major obstacle limiting the success of treatment and enabling relapse to metastatic disease. The complicated crosstalk of both tumor-intrinsic and exogenous factors may contribute to endocrine resistance, although the underlying molecular details are still enigmatic. For example, the expression of the melanoma antigen genes (MAGE) correlates with a worse clinical prognosis and therapy resistance in many types of cancers, including breast cancer. Recent studies suggested that cancers co-opt MAGEs’ physiological functions to promote therapy resistance and potentially metastasis development. The response to the therapy can be also affected by the concurrent use of alternative therapy, e.g., cannabinoid use is popular among breast cancer patients. Cannabinoids interact with endogenous estrogen function, however, how they interfere with breast cancer therapy is still poorly understood. In this review, we summarize the role of ER, PR, and HER2 in hormone-dependent breast cancer; provide current knowledge of MAGEs and cannabinoid receptors in breast cancer; ultimately discuss the potential interlacement of their signaling paths which may underlay diverse responses to therapies in breast cancer patients simultaneously using cannabinoids. These interactions are poorly understood but critical for the advancement of conventional and complementary treatment options for patients, particularly the ones with metastatic disease

Cumulus Cells Gene Expression Profiling in Terms of Oocyte Maturity in Controlled Ovarian Hyperstimulation Using GnRH Agonist or GnRH Antagonist

<div><p>In <em>in vitro</em> fertilization (IVF) cycles controlled ovarian hyperstimulation (COH) is established by gonadotropins in combination with gonadotropin-releasing hormone (GnRH) agonists or antagonists, to prevent premature luteinizing hormone (LH) surge. The aim of our study was to improve the understanding of gene expression profile of cumulus cells (CC) in terms of ovarian stimulation protocol and oocyte maturity. We applied Affymetrix gene expression profiling in CC of oocytes at different maturation stages using either GnRH agonists or GnRH antagonists. Two analyses were performed: the first involved CC of immature metaphase I (MI) and mature metaphase II (MII) oocytes where 359 genes were differentially expressed, and the second involved the two GnRH analogues where no differentially expressed genes were observed at the entire transcriptome level. A further analysis of 359 differentially genes was performed, focusing on anti-Müllerian hormone receptor 2 (<em>AMHR2</em>), follicle stimulating hormone receptor (<em>FSHR</em>), vascular endothelial growth factor C (<em>VEGFC</em>) and serine protease inhibitor E2 (<em>SERPINE2</em>). Among other differentially expressed genes we observed a marked number of new genes connected to cell adhesion and neurotransmitters such as dopamine, glycine and γ-Aminobutyric acid (GABA). No differential expression in CC between the two GnRH analogues supports the findings of clinical studies where no significant difference in live birth rates between both GnRH analogues has been proven.</p> </div

Schematic representation of microarray data analysis according to oocyte maturity.

<p>Boxes represent CC samples at different oocyte stages and their numbers; large box represents CC samples merged from MII-NF and MII-BL oocytes. Contrasts and corresponding numbers of differentially expressed genes are shown in circles. CC MI: cumulus cells of metaphase I oocytes; CC MII-NF: cumulus cells of unfertilized metaphase II oocytes; CC MII-BL: cumulus cells of metaphase II oocytes developed to the blastocyst stage; CC MII-NF vs. CC MI: contrast between CC MII-NF and CC MI; CC MII-BL vs. CC MI: contrast between CC MII-BL and CC MI; CC MII-BL vs. CC MII-NF: contrast between CC MII-BL and CC MII-NF; CC MII vs. CC MI: contrast between CC MII and CC MI.</p

Subgroup of genes connected to follicle stimulating hormone (FSH) and luteinizing hormone (LH) from a top ranked gene network.

<p>It is associated with Post-Translational Modification, Cellular Development, Cellular Growth and Proliferation as identified by Ingenuity Pathways Analysis. Top ranked gene network was obtained from comparisons of differential expression between CC MII and CC MI. Genes are represented as nodes, and the biological relationship between two nodes is represented as edge (line): a plain line indicates direct interaction, a dashed line indicates indirect interaction; a line without arrowhead indicates binding only, a line finishing with a vertical line indicates inhibition; a line with an arrowhead indicates ‘acts on’. The green colour intensity of the nodes indicates the degree of down-regulation in the CC MII group. CC MI: cumulus cells of metaphase I oocytes. CC MII: cumulus cells of metaphase II oocytes.</p