Insight into glucocorticoid receptor signalling through interactome model analysis

Glucocorticoid hormones (GCs) are used to treat a variety of diseases because of their potent anti-inflammatory effect and their ability to induce apoptosis in lymphoid malignancies through the glucocorticoid receptor (GR). Despite ongoing research, high glucocorticoid efficacy and widespread usage in medicine, resistance, disease relapse and toxicity remain factors that need addressing. Understanding the mechanisms of glucocorticoid signalling and how resistance may arise is highly important towards improving therapy. To gain insight into this we undertook a systems biology approach, aiming to generate a Boolean model of the glucocorticoid receptor protein interaction network that encapsulates functional relationships between the GR, its target genes or genes that target GR, and the interactions between the genes that interact with the GR. This model named GEB052 consists of 52 nodes representing genes or proteins, the model input (GC) and model outputs (cell death and inflammation), connected by 241 logical interactions of activation or inhibition. 323 changes in the relationships between model constituents following in silico knockouts were uncovered, and steady-state analysis followed by cell-based microarray genome-wide model validation led to an average of 57% correct predictions, which was taken further by assessment of model predictions against patient microarray data. Lastly, semi-quantitative model analysis via microarray data superimposed onto the model with a score flow algorithm has also been performed, which demonstrated significantly higher correct prediction ratios (average of 80%), and the model has been assessed as a predictive clinical tool using published patient microarray data. In summary we present an in silico simulation of the glucocorticoid receptor interaction network, linked to downstream biological processes that can be analysed to uncover relationships between GR and its interactants. Ultimately the model provides a platform for future development both by directing laboratory research and allowing for incorporation of further components, encapsulating more interactions/genes involved in glucocorticoid receptor signalling

Can a systems approach produce a better understanding of mood disorders?

Background: One in twenty-five people suffer from a mood disorder. Current treatments are sub-optimal with poor patient response and uncertain modes-of-action. There is thus a need to better understand underlying mechanisms that determine mood, and how these go wrong in affective disorders. Systems biology approaches have yielded important biological discoveries for other complex diseases such as cancer, and their potential in affective disorders will be reviewed. Scope of review: This review will provide a general background to affective disorders, plus an outline of experimental and computational systems biology. The current application of these approaches in understanding affective disorders will be considered, and future recommendations made. Major conclusions: Experimental systems biology has been applied to the study of affective disorders, especially at the genome and transcriptomic levels. However, data generation has been slowed by a lack of human tissue or suitable animal models. At present, computational systems biology has only be applied to understanding affective disorders on a few occasions. These studies provide sufficient novel biological insight to motivate further use of computational biology in this field. General significance: In common with many complex diseases much time and money has been spent on the generation of large-scale experimental datasets. The next step is to use the emerging computational approaches, predominantly developed in the field of oncology, to leverage the most biological insight from these datasets. This will lead to the critical breakthroughs required for more effective diagnosis, stratification and treatment of affective disorders

Analysis of drug resistance and the role of the stem cell niche in leukaemia

Glucocorticoids and etoposide are used to treat acute lymphoblastic leukaemia (ALL) as they induce death in lymphoblasts through the glucocorticoid receptor (GR) and p53. However, glucocorticoid resistance, cell death mechanisms and the contribution of the bone marrow microenvironment to drug response/resistance all require investigation. Using microenvironment-mimicking conditioned media (CM), dexamethasone (a synthetic glucocorticoid) and etoposide to treat glucocorticoid-sensitive (C7-14) and glucocorticoid-resistant (C1-15) cells, pathways by which the microenvironment exerts its chemoprotective effect have been investigated. CM reduced caspase-3/8 activation, downregulated RIPK1 (necroptotic marker), and limited chemotherapy-induced BECN1 downregulation, suggesting protective effects of CM. Glucocorticoids upregulated BIRC3 (which ubiquitinates RIPK1), whilst CM altered GR phosphorylation. GR occupancy was observed on the RIPK1, BECN1 and BIRC3 promoters and changed depending on its phosphorylation. High-molecular weight proteins reacting with the RIPK1 antibody increased with CM, and reduced following AT406 BIRC3 inhibitor treatment suggesting they represent ubiquitinated RIPK1. These results suggest mechanisms by which CM promotes survival, as well as indicating novel glucocorticoid-regulated pathways. Complementing laboratory investigation is the construction of a Boolean model of the GR interaction network (GEB052, GR “interactome”) containing 52 nodes (proteins, inputs/outputs) connected by 241 interactions. In silico mutations and analyses have generated predictions that were subsequently validated on a genome-wide scale via comparison to microarray data. GEB052 demonstrated high prediction accuracy, consistently achieving a better prediction rate than a randomised model. Quantitative algorithmic analysis via microarray superimposition has also been performed, and lastly the model has been preliminarily validated as a clinical tool via superimposition of patient microarray data and comparing model predictions to clinical data. In summary, this thesis provides novel insight into the effects of the microenvironment, and identifies new glucocorticoid-regulated pathways. The GEB052 model of GR signalling represents the novel application of this modelling approach to GR research, and generates accurate predictions

Targeting the phosphatidylinositol 3-kinase/Akt/mechanistic target of rapamycin signaling pathway in B-lineage acute lymphoblastic leukemia: An update

Despite considerable progress in treatment protocols, B-lineage acute lymphoblastic leukemia (B-ALL) displays a poor prognosis in about 15–20% of pediatric cases and about 60% of adult patients. In addition, life-long irreversible late effects from chemo- and radiation therapy, including secondary malignancies, are a growing problem for leukemia survivors. Targeted therapy holds promising perspectives for cancer treatment as it may be more effective and have fewer side effects than conventional therapies. The phosphatidylinositol 3-phosphate kinase (PI3K)/Akt/mechanistic target of rapamycin (mTOR) signaling pathway is a key regulatory cascade which controls proliferation, survival and drug-resistance of cancer cells, and it is frequently upregulated in the different subtypes of B-ALL, where it plays important roles in the pathophysiology, maintenance and progression of the disease. Moreover, activation of this signaling cascade portends a poorer prognosis in both pediatric and adult B-ALL patients. Promising preclinical data on PI3K/Akt/mTOR inhibitors have documented their anticancer activity in B-ALL and some of these novel drugs have entered clinical trials as they could lead to a longer event-free survival and reduce therapy-associated toxicity for patients with B-ALL. This review highlights the current status of PI3K/Akt/mTOR inhibitors in B-ALL, with an emphasis on emerging evidence of the superior efficacy of synergistic combinations involving the use of traditional chemotherapeutics or other novel, targeted agents

Effect of stress on protein homeostasis mediated by FKBP51 as a possible mechanism underlying stress-related disorders

Homeostasis is a dynamic equilibrium fundamental for a healthy system. A major challenge to homeostasis is environmental stress to which the organism reacts with the stress response. The hypothalamic-pituitary-adrenal (HPA) axis is the main regulator of the stress response that, upon activation, leads to the release of glucocorticoids (GCs). GCs are steroid hormones that exert their function via glucocorticoid receptors (GR). They trigger on one hand the appropriate stress response in the periphery, and, on the other, inhibit the HPA axis itself via negative feedback to restore homeostasis. FK506-binding protein 51 (FKBP51) is a co-chaperone able to modulate the GR, and therefore the HPA axis. Furthermore the expression of FKBP5, the gene coding for FKBP51, is induced by GR activation. In the last decade, increasing evidence has unveiled additional roles of FKBP51 in the regulation of several cellular pathways and functions that are independent from its inhibitory role on GR. Among these, FKBP51 has been shown to link stress signaling to macroautophagy, a lytic type of autophagy pathway. Autophagy represents one of the main mechanisms regulating cellular homeostasis and response to stress. For this reason, in the first part of this doctoral thesis, the role of GR-mediated stress was investigated on two further autophagic pathways: 1) the chaperone-mediated autophagy (CMA), a selective type of lytic autophagy, and 2) the secretory autophagy, an unconventional secretory mechanism regulated by autophagy-related proteins and found to be involved in extracellular signaling of immune response. For this aim, an in vitro approach was adopted using human and murine cell lines that were treated with dexamethasone (Dex), a synthetic GR agonist. For the first pathway, biochemical assays indicated that Dex-induced GR activation enhances CMA-mediated degradation of known CMA target proteins and that this process is dependent on FKBP51. Furthermore, the underlying molecular mechanism could be revealed by co-immunoprecipitation that displayed the co-localization of FKBP51, AKT and PHLPP on lysosomes. With a SILAC-based proteomics analysis, the proteome-wide effect of Dex-induced CMA could be observed and novel CMA targets were identified. For the second pathway, interactome and co-immunoprecipitation analyses revealed the involvement of FKBP51 in the SNARE complex assembly essential for secretory autophagy. Furthermore, treatment with Dex lead to a strengthened interaction between the SNARE proteins and FKBP51, and to an increased secretion of IL1B, a well characterized cargo of secretory autophagy, as observed with in vitro ELISA experiments and in vivo hippocampal microdialyses. A global effect of Dex-induced secretory autophagy was finally observed with a secretome analysis. The second part of my doctoral thesis focused on FKBP5/51 transcription variants and protein isoforms. In fact, despite its involvement in many cellular functions and disorders, very little is known about its four transcription variants and two isoforms. Thus, expression and degradation dynamics of FKBP51 isoforms and their differential functions in known molecular pathways were analyzed. Overall this study highlighted FKBP51 as crucial mediator of the stress response on two autophagic pathways, which might contribute to the regulation of cell and protein homeostasis. Furthermore, this regulatory mechanism might underlie the link of stress to immune and psychiatric disorders