Activity and expression of histone acetylases and deacetylases in inflammatory phenotypes of asthma

2013 ◽  
Vol 44 (1) ◽  
pp. 47-57 ◽  
Author(s):  
L. P. Gunawardhana ◽  
P. G. Gibson ◽  
J. L. Simpson ◽  
H. Powell ◽  
K. J. Baines
Keyword(s):  
Inflammatory Phenotypes ◽  
Histone Acetylases

scholarly journals Metabolic Factors Affecting Tumor Immunogenicity: What Is Happening at the Cellular Level?

2021 ◽  
Vol 22 (4) ◽  
pp. 2142
Author(s):  
Rola El Sayed ◽  
Yolla Haibe ◽  
Ghid Amhaz ◽  
Youssef Bouferraa ◽  
Ali Shamseddine
Keyword(s):  
Fatty Acid ◽  
Tumor Microenvironment ◽  
Immune Cells ◽  
Immune Modulation ◽  
Checkpoint Inhibitors ◽  
Therapeutic Option ◽  
Effector Memory ◽  
Acid Oxidation ◽  
Checkpoint Inhibition ◽  
Inflammatory Phenotypes

Immunotherapy has changed the treatment paradigm in multiple solid and hematologic malignancies. However, response remains limited in a significant number of cases, with tumors developing innate or acquired resistance to checkpoint inhibition. Certain “hot” or “immune-sensitive” tumors become “cold” or “immune-resistant”, with resultant tumor growth and disease progression. Multiple factors are at play both at the cellular and host levels. The tumor microenvironment (TME) contributes the most to immune-resistance, with nutrient deficiency, hypoxia, acidity and different secreted inflammatory markers, all contributing to modulation of immune-metabolism and reprogramming of immune cells towards pro- or anti-inflammatory phenotypes. Both the tumor and surrounding immune cells require high amounts of glucose, amino acids and fatty acids to fulfill their energy demands. Thus, both compete over one pool of nutrients that falls short on needs, obliging cells to resort to alternative adaptive metabolic mechanisms that take part in shaping their inflammatory phenotypes. Aerobic or anaerobic glycolysis, oxidative phosphorylation, tryptophan catabolism, glutaminolysis, fatty acid synthesis or fatty acid oxidation, etc. are all mechanisms that contribute to immune modulation. Different pathways are triggered leading to genetic and epigenetic modulation with consequent reprogramming of immune cells such as T-cells (effector, memory or regulatory), tumor-associated macrophages (TAMs) (M1 or M2), natural killers (NK) cells (active or senescent), and dendritic cells (DC) (effector or tolerogenic), etc. Even host factors such as inflammatory conditions, obesity, caloric deficit, gender, infections, microbiota and smoking status, may be as well contributory to immune modulation, anti-tumor immunity and response to immune checkpoint inhibition. Given the complex and delicate metabolic networks within the tumor microenvironment controlling immune response, targeting key metabolic modulators may represent a valid therapeutic option to be combined with checkpoint inhibitors in an attempt to regain immune function.

scholarly journals Serum Metabolomics Analysis of Asthma in Different Inflammatory Phenotypes: A Cross-Sectional Study in Northeast China

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Zhiqiang Pang ◽  
Guoqiang Wang ◽  
Cuizhu Wang ◽  
Weijie Zhang ◽  
Jinping Liu ◽  
...  
Keyword(s):  
Metabolic Profile ◽  
Ultra Performance Liquid Chromatography ◽  
Cross Sectional Study ◽  
Sphingolipid Metabolism ◽  
Cross Sectional ◽  
Asthma Phenotypes ◽  
Novel Approach ◽  
Retinol Metabolism ◽  
Inflammatory Phenotypes ◽  
Serum Metabolomics

Background and Objective. Asthma as a chronic heterogeneous disease seriously affects the quality of life. Incorrect identification for its clinical phenotypes lead to a huge waste of medical resources. Metabolomic technique as a novel approach to explore the pathogenesis of diseases have not been used to study asthma based on their clear defined inflammatory phenotypes. This study is aimed to distinguish the divergent metabolic profile in different asthma phenotypes and clarify the pathogenesis of them.Methods. Participants including eosinophilic asthmatics (EA, n=13), noneosinophilic asthmatics (NEA, n=16), and healthy controls (HC, n=15) were enrolled. A global profile of untargeted serum metabolomics was identified with Ultra Performance Liquid Chromatography–Mass Spectrometry technique.Results. Multivariate analysis was performed and showed a clear distinction between EA, NEA, and HC. A total of 18 different metabolites were recognized between the three groups based on OPLS-DA model and involved in 10 perturbed metabolic pathways. Glycerophospholipid metabolism, retinol metabolism, and sphingolipid metabolism were identified as the most significant changed three pathways (impact > 0.1 and -log(P) > 4) between the phenotypes.Conclusions. We showed that the different inflammatory phenotypes of asthma involve the immune regulation, energy, and nutrients metabolism. The clarified metabolic profile contributes to understanding the pathophysiology of asthma phenotypes and optimizing the therapeutic strategy against asthma heterogeneity.

scholarly journals Cells surviving fractional killing by TRAIL exhibit transient but sustainable resistance and inflammatory phenotypes

2013 ◽  
Vol 24 (14) ◽  
pp. 2186-2200 ◽  
Author(s):  
Deborah A. Flusberg ◽  
Jérémie Roux ◽  
Sabrina L. Spencer ◽  
Peter K. Sorger
Keyword(s):  
Cell Death ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Therapeutic Agents ◽  
Inflammatory Phenotype ◽  
Drug Naïve ◽  
Apoptosis Inducing Agents ◽  
Inflammatory Phenotypes ◽  
Survival Mechanisms ◽  
Necrosis Factor

When clonal populations of human cells are exposed to apoptosis-inducing agents, some cells die and others survive. This fractional killing arises not from mutation but from preexisting, stochastic differences in the levels and activities of proteins regulating apoptosis. Here we examine the properties of cells that survive treatment with agonists of two distinct death receptors, tumor necrosis factor–related apoptosis-inducing ligand (TRAIL) and anti-FasR antibodies. We find that “survivor” cells are highly resistant to a second ligand dose applied 1 d later. Resistance is reversible, resetting after several days of culture in the absence of death ligand. “Reset” cells appear identical to drug-naive cells with respect to death ligand sensitivity and gene expression profiles. TRAIL survivors are cross-resistant to activators of FasR and vice versa and exhibit an NF-κB–dependent inflammatory phenotype. Remarkably, reversible resistance is induced in the absence of cell death when caspase inhibitors are present and can be sustained for 1 wk or more, also without cell death, by periodic ligand exposure. Thus stochastic differences in cell state can have sustained consequences for sen­sitivity to prodeath ligands and acquisition of proinflammatory phenotypes. The important role played by periodicity in TRAIL exposure for induction of opposing apoptosis and survival mechanisms has implications for the design of optimal therapeutic agents and protocols.

scholarly journals Advantages of osteoarthritis combined treatment with symptomatic slow-acting drugs

2021 ◽  
Vol 15 (2) ◽  
pp. 126-131
Author(s):  
E. V. Zonova
Keyword(s):  
Cardiovascular Diseases ◽  
Intestinal Microbiota ◽  
Combined Treatment ◽  
Pleiotropic Effects ◽  
Immunological Activity ◽  
Inflammatory Phenotypes ◽  
The Relationship ◽  
Combined Drugs ◽  
Development Risk ◽  
Overall Mortality

The effectiveness of combined drugs, consisting of chondroitin and glucosamine (GA) in the treatment of osteoarthritis (OA) is discussed. Due to their high safety and pleiotropic effects, these drugs can be used in patients with OA (primarily with metabolic and inflammatory phenotypes) and comorbid diseases. The effect of oral chondroitin and GA on the intestinal microbiota is described: regulation of the composition, metabolic and immunological activity of intestinal microbiota. The relationship between the regular administration of chondroitin and GA and decrease in overall mortality and mortality from cardiovascular diseases, as well as the decrease of malignancy development risk is marked.

Anti-Viral Innate Immunity Varies Across Different Asthma Inflammatory Phenotypes

2014 ◽  
Vol 133 (2) ◽  
pp. AB140
Author(s):  
John W. Upham ◽  
Melanie Carroll ◽  
Peter Gibson ◽  
Ian A. Yang ◽  
Jodie Simpson
Keyword(s):  
Innate Immunity ◽  
Inflammatory Phenotypes

Childhood asthma- pathogenesis and phenotypes

2021 ◽  
pp. 2100731
Author(s):  
Mariëlle W Pijnenburg ◽  
Urs Frey ◽  
Johan C De Jongste ◽  
Sejal Saglani
Keyword(s):  
Lung Function ◽  
Childhood Asthma ◽  
Treatment Options ◽  
Critical Factor ◽  
Tobacco Smoke Exposure ◽  
Pathophysiological Mechanism ◽  
Asthma In Children ◽  
Infant Weight Gain ◽  
Inflammatory Phenotypes ◽  
Early Life Exposures

In the pathogenesis of asthma in children there is a pivotal role for a type 2 inflammatory response to early life exposures or events. Interactions between infections, atopy, genetic susceptibility, and environmental exposures (such as farmyard environment, air pollution, tobacco smoke exposure) influence the development of wheezing illness and the risk for progression to asthma. The immune system, lung function and the microbiome in gut and airways develop in parallel and dysbiosis of the microbiome may be a critical factor in asthma development. Increased infant weight gain and preterm birth are other risk factors for development of asthma and reduced lung function. The complex interplay between these factors explains the heterogeneity of asthma in children. Subgroups of patients can be identified as phenotypes based on clinical parameters, or endotypes, based on a specific pathophysiological mechanism. Paediatric asthma phenotypes and endotypes may ultimately help to improve diagnosis of asthma, prediction of asthma development and treatment of individual children, based on clinical, temporal, developmental or inflammatory characteristics. Unbiased, data-driven clustering, using a multidimensional or systems biology approach may be needed to better define phenotypes. The present knowledge on inflammatory phenotypes of childhood asthma has now been successfully applied in the treatment with biologicals of children with severe therapy resistant asthma, and it is to be expected that more personalized treatment options may become available.

Detection of Asthma Inflammatory Phenotypes Using Artificial Neural Network

2021 ◽  
pp. 69-75
Author(s):  
Selma Delić ◽  
Tijana Cvjetković ◽  
Medina Čajo ◽  
Ismet Fatih Čančar ◽  
Adna Čolak ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Artificial Neural ◽  
Inflammatory Phenotypes

scholarly journals Chitinase-like protein YKL-40 correlates with inflammatory phenotypes, anti-asthma responsiveness and future exacerbations

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Lei Liu ◽  
Xin Zhang ◽  
Ying Liu ◽  
Li Zhang ◽  
Jing Zheng ◽  
...  
Keyword(s):  
Inflammatory Phenotypes
Sign in / Sign up

Export Citation Format

Share Document