Prolonged oral cannabinoid administration prevents neuroinflammation, lowers β-amyloid levels and improves cognitive performance in Tg APP 2576 mice

Background: Alzheimer’s disease (AD) brain shows an ongoing inflammatory condition and non-steroidal antiinflammatories diminish the risk of suffering the neurologic disease. Cannabinoids are neuroprotective and antiinflammatory agents with therapeutic potential. Methods: We have studied the effects of prolonged oral administration of transgenic amyloid precursor protein (APP) mice with two pharmacologically different cannabinoids (WIN 55,212-2 and JWH-133, 0.2 mg/kg/day in the drinking water during 4 months) on inflammatory and cognitive parameters, and on 18F-fluoro-deoxyglucose (18FDG) uptake by positron emission tomography (PET). Results: Novel object recognition was significantly reduced in 11 month old Tg APP mice and 4 month administration of JWH was able to normalize this cognitive deficit, although WIN was ineffective. Wild type mice cognitive performance was unaltered by cannabinoid administration. Tg APP mice showed decreased 18FDG uptake in hippocampus and cortical regions, which was counteracted by oral JWH treatment. Hippocampal GFAP immunoreactivity and cortical protein expression was unaffected by genotype or treatment. In contrast, the density of Iba1 positive microglia was increased in Tg APP mice, and normalized following JWH chronic treatment. Both cannabinoids were effective at reducing the enhancement of COX-2 protein levels and TNF-a mRNA expression found in the AD model. Increased cortical b-amyloid (Ab) levels were significantly reduced in the mouse model by both cannabinoids. Noteworthy both cannabinoids enhanced Ab transport across choroid plexus cells in vitro. Conclusions: In summary we have shown that chronically administered cannabinoid showed marked beneficial effects concomitant with inflammation reduction and increased Ab clearanceThis work was supported by the Spanish Ministry of Science and Technology (SAF 2005-02845 to M.L.C). A.M.M-M. was recipient a fellowship from the Ministry of Education and Scienc

Transthyretin Protects against A-Beta Peptide Toxicity by Proteolytic Cleavage of the Peptide: A Mechanism Sensitive to the Kunitz Protease Inhibitor

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the deposition of amyloid β-peptide (A-Beta) in the brain. Transthyretin (TTR) is a tetrameric protein of about 55 kDa mainly produced in the liver and choroid plexus of the brain. The known physiological functions of TTR are the transport of thyroid hormone T4 and retinol, through binding to the retinol binding protein. TTR has also been established as a cryptic protease able to cleave ApoA-I in vitro. It has been described that TTR is involved in preventing A-Beta fibrilization, both by inhibiting and disrupting A-Beta fibrils, with consequent abrogation of toxicity. We further characterized the nature of the TTR/A-Beta interaction and found that TTR, both recombinant or isolated from human sera, was able to proteolytically process A-Beta, cleaving the peptide after aminoacid residues 1, 2, 3, 10, 13, 14,16, 19 and 27, as determined by mass spectrometry, and reversed phase chromatography followed by N-terminal sequencing. A-Beta peptides (1–14) and (15–42) showed lower amyloidogenic potential than the full length counterpart, as assessed by thioflavin binding assay and ultrastructural analysis by transmission electron microscopy. A-Beta cleavage by TTR was inhibited in the presence of an αAPP peptide containing the Kunitz Protease Inhibitor (KPI) domain but not in the presence of the secreted αAPP derived from the APP isoform 695 without the KPI domain. TTR was also able to degrade aggregated forms of A-Beta peptide. Our results confirmed TTR as a protective molecule in AD, and prompted A-Beta proteolysis by TTR as a protective mechanism in this disease. TTR may prove to be a useful therapeutic agent for preventing or retarding the cerebral amyloid plaque formation implicated in AD pathology

Regulators of genetic risk of breast cancer identified by integrative network analysis.

Genetic risk for breast cancer is conferred by a combination of multiple variants of small effect. To better understand how risk loci might combine, we examined whether risk-associated genes share regulatory mechanisms. We created a breast cancer gene regulatory network comprising transcription factors and groups of putative target genes (regulons) and asked whether specific regulons are enriched for genes associated with risk loci via expression quantitative trait loci (eQTLs). We identified 36 overlapping regulons that were enriched for risk loci and formed a distinct cluster within the network, suggesting shared biology. The risk transcription factors driving these regulons are frequently mutated in cancer and lie in two opposing subgroups, which relate to estrogen receptor (ER)(+) luminal A or luminal B and ER(-) basal-like cancers and to different luminal epithelial cell populations in the adult mammary gland. Our network approach provides a foundation for determining the regulatory circuits governing breast cancer, to identify targets for intervention, and is transferable to other disease settings.This work was funded by Cancer Research UK and the Breast Cancer Research Foundation. MAAC is funded by the National Research Council (CNPq) of Brazil. TEH held a fellowship from the US DOD Breast Cancer Research Program (W81XWH-11-1-0592) and is currently supported by an RAH Career Development Fellowship (Australia). TEH and WDT are funded by the NHMRC of Australia (NHMRC) (ID: 1008349 WDT; 1084416 WDT, TEH) and Cancer Australia/National Breast Cancer Foundation (ID 627229; WDT, TEH). BAJP is a Gibb Fellow of Cancer Research UK. We would like to acknowledge the support of The University of Cambridge, Cancer Research UK and Hutchison Whampoa Limited.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/ng.345

Mesenchymal Transition and PDGFRA Amplification/Mutation Are Key Distinct Oncogenic Events in Pediatric Diffuse Intrinsic Pontine Gliomas

Diffuse intrinsic pontine glioma (DIPG) is one of the most frequent malignant pediatric brain tumor and its prognosis is universaly fatal. No significant improvement has been made in last thirty years over the standard treatment with radiotherapy. To address the paucity of understanding of DIPGs, we have carried out integrated molecular profiling of a large series of samples obtained with stereotactic biopsy at diagnosis. While chromosomal imbalances did not distinguish DIPG and supratentorial tumors on CGHarrays, gene expression profiling revealed clear differences between them, with brainstem gliomas resembling midline/thalamic tumours, indicating a closely-related origin. Two distinct subgroups of DIPG were identified. The first subgroup displayed mesenchymal and pro-angiogenic characteristics, with stem cell markers enrichment consistent with the possibility to grow tumor stem cells from these biopsies. The other subgroup displayed oligodendroglial features, and appeared largely driven by PDGFRA, in particular through amplification and/or novel missense mutations in the extracellular domain. Patients in this later group had a significantly worse outcome with an hazard ratio for early deaths, ie before 10 months, 8 fold greater that the ones in the other subgroup (p = 0.041, Cox regression model). The worse outcome of patients with the oligodendroglial type of tumors was confirmed on a series of 55 paraffin-embedded biopsy samples at diagnosis (median OS of 7.73 versus 12.37 months, p = 0.045, log-rank test). Two distinct transcriptional subclasses of DIPG with specific genomic alterations can be defined at diagnosis by oligodendroglial differentiation or mesenchymal transition, respectively. Classifying these tumors by signal transduction pathway activation and by mutation in pathway member genes may be particularily valuable for the development of targeted therapies

Linking Proteomic and Transcriptional Data through the Interactome and Epigenome Reveals a Map of Oncogene-induced Signaling

Cellular signal transduction generally involves cascades of post-translational protein modifications that rapidly catalyze changes in protein-DNA interactions and gene expression. High-throughput measurements are improving our ability to study each of these stages individually, but do not capture the connections between them. Here we present an approach for building a network of physical links among these data that can be used to prioritize targets for pharmacological intervention. Our method recovers the critical missing links between proteomic and transcriptional data by relating changes in chromatin accessibility to changes in expression and then uses these links to connect proteomic and transcriptome data. We applied our approach to integrate epigenomic, phosphoproteomic and transcriptome changes induced by the variant III mutation of the epidermal growth factor receptor (EGFRvIII) in a cell line model of glioblastoma multiforme (GBM). To test the relevance of the network, we used small molecules to target highly connected nodes implicated by the network model that were not detected by the experimental data in isolation and we found that a large fraction of these agents alter cell viability. Among these are two compounds, ICG-001, targeting CREB binding protein (CREBBP), and PKF118–310, targeting β-catenin (CTNNB1), which have not been tested previously for effectiveness against GBM. At the level of transcriptional regulation, we used chromatin immunoprecipitation sequencing (ChIP-Seq) to experimentally determine the genome-wide binding locations of p300, a transcriptional co-regulator highly connected in the network. Analysis of p300 target genes suggested its role in tumorigenesis. We propose that this general method, in which experimental measurements are used as constraints for building regulatory networks from the interactome while taking into account noise and missing data, should be applicable to a wide range of high-throughput datasets.National Science Foundation (U.S.) (DB1-0821391)National Institutes of Health (U.S.) (Grant U54-CA112967)National Institutes of Health (U.S.) (Grant R01-GM089903)National Institutes of Health (U.S.) (P30-ES002109

The modular systems biology approach to investigate the control of apoptosis in Alzheimer's disease neurodegeneration

Apoptosis is a programmed cell death that plays a critical role during the development of the nervous system and in many chronic neurodegenerative diseases, including Alzheimer's disease (AD). This pathology, characterized by a progressive degeneration of cholinergic function resulting in a remarkable cognitive decline, is the most common form of dementia with high social and economic impact. Current therapies of AD are only symptomatic, therefore the need to elucidate the mechanisms underlying the onset and progression of the disease is surely needed in order to develop effective pharmacological therapies. Because of its pivotal role in neuronal cell death, apoptosis has been considered one of the most appealing therapeutic targets, however, due to the complexity of the molecular mechanisms involving the various triggering events and the many signaling cascades leading to cell death, a comprehensive understanding of this process is still lacking. Modular systems biology is a very effective strategy in organizing information about complex biological processes and deriving modular and mathematical models that greatly simplify the identification of key steps of a given process. This review aims at describing the main steps underlying the strategy of modular systems biology and briefly summarizes how this approach has been successfully applied for cell cycle studies. Moreover, after giving an overview of the many molecular mechanisms underlying apoptosis in AD, we present both a modular and a molecular model of neuronal apoptosis that suggest new insights on neuroprotection for this disease