Dataset Information

Probing Cellular and Molecular Mechanisms of Cigarette Smoke-Induced Immune Response in the Progression of Chronic Obstructive Pulmonary Disease Using Multiscale Network Modeling.

ABSTRACT: Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disorder characterized by progressive destruction of lung tissues and airway obstruction. COPD is currently the third leading cause of death worldwide and there is no curative treatment available so far. Cigarette smoke (CS) is the major risk factor for COPD. Yet, only a relatively small percentage of smokers develop the disease, showing that disease susceptibility varies significantly among smokers. As smoking cessation can prevent the disease in some smokers, quitting smoking cannot halt the progression of COPD in others. Despite extensive research efforts, cellular and molecular mechanisms of COPD remain elusive. In particular, the disease susceptibility and smoking cessation effects are poorly understood. To address these issues in this work, we develop a multiscale network model that consists of nodes, which represent molecular mediators, immune cells and lung tissues, and edges describing the interactions between the nodes. Our model study identifies several positive feedback loops and network elements playing a determinant role in the CS-induced immune response and COPD progression. The results are in agreement with clinic and laboratory measurements, offering novel insight into the cellular and molecular mechanisms of COPD. The study in this work also provides a rationale for targeted therapy and personalized medicine for the disease in future.

SUBMITTER: Pan Z

PROVIDER: S-EPMC5036797 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Probing Cellular and Molecular Mechanisms of Cigarette Smoke-Induced Immune Response in the Progression of Chronic Obstructive Pulmonary Disease Using Multiscale Network Modeling.

Pan Zhichao Z Yu Haishan H Liao Jie-Lou JL

PloS one 20160926 9

Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disorder characterized by progressive destruction of lung tissues and airway obstruction. COPD is currently the third leading cause of death worldwide and there is no curative treatment available so far. Cigarette smoke (CS) is the major risk factor for COPD. Yet, only a relatively small percentage of smokers develop the disease, showing that disease susceptibility varies significantly among smokers. As smoking cessation can ...[more]

PMID: 27669518

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Project description:Chronic obstructive pulmonary disease (COPD) is a debilitating disease caused by chronic exposure to cigarette smoke (CS). Celastrol is a pentacyclic triterpenoid compound exhibits potent antioxidant and anti-inflammatory activities. Also it is presently known to protect against liver damage induced by type II diabetes. However, its role in COPD is unclear. In this study, we investigated the effects of Celastrol on cellular inflammation in mice exposed to CS and Beas-2B cells treated with CS extract (CSE). C57BL/6 mice and Beas-2B cells were randomly divided into three groups: control group, COPD or CSE group, and Celastrol treatment group. The COPD mice models were subjected to smoke exposure and cell models were treated with CSE. Bioinformatics analysis was performed to identify differentially expressed genes following treatment with Celastrol in COPD, the molecular networks was mapped by Cytoscape. The levels of inflammatory cytokinesinterleukin-8, tumor necrosis factor ?, monocyte chemoattractant protein-1, and oxidative stress factors superoxide dismutase and catalase were measured by enzyme-linked immunosorbent assay. Hematoxylin and eosin staining to detect the injury of mouse lung tissue. mRNA and protein levels of Ednrb and Kng1 in the tissues and cells were measured by quantitative polymerase chain reaction (PCR) and western blotting, respectively. Apoptosis was measured by flow cytometry and TUNEL staining. Compared to mice in the COPD group, mice treated with Celastrol had significantly reduced levels of inflammatory cytokines interleukin-8, tumor necrosis factor ? and monocyte chemoattractant protein-1 in the serum and bronchoalveolar lavage fluid, and significantly increased levels of oxidative stress factors superoxide dismutase and catalase. The same results were obtained at the cellular level using Beas-2B cells. Compared to the model groups, Celastrol reduced lung injury in mice and significantly reduced cellular apoptosis. Bioinformatics analysis showed that Ednrb is a target gene of Celastrol and differentially expressed in COPD. Quantitative PCR analysis showed that Ednrb expression in patients with COPD was significantly increased compared to that in healthy controls. Additionally, Celastrol effectively reduced Ednrb/Kng1 expression in both cell and animal models. Celastrol has a therapeutic effect on COPD and may alleviate COPD by inhibiting inflammation development by suppressing the Ednrb/Kng1 signaling pathway.

Project description:Rationale: The decades-long progression of chronic obstructive pulmonary disease (COPD) renders identifying different trajectories of disease progression challenging.Objectives: To identify subtypes of patients with COPD with distinct longitudinal progression patterns using a novel machine-learning tool called "Subtype and Stage Inference" (SuStaIn) and to evaluate the utility of SuStaIn for patient stratification in COPD.Methods: We applied SuStaIn to cross-sectional computed tomography imaging markers in 3,698 Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1-4 patients and 3,479 controls from the COPDGene (COPD Genetic Epidemiology) study to identify subtypes of patients with COPD. We confirmed the identified subtypes and progression patterns using ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) data. We assessed the utility of SuStaIn for patient stratification by comparing SuStaIn subtypes and stages at baseline with longitudinal follow-up data.Measurements and Main Results: We identified two trajectories of disease progression in COPD: a "Tissue→Airway" subtype (n = 2,354, 70.4%), in which small airway dysfunction and emphysema precede large airway wall abnormalities, and an "Airway→Tissue" subtype (n = 988, 29.6%), in which large airway wall abnormalities precede emphysema and small airway dysfunction. Subtypes were reproducible in ECLIPSE. Baseline stage in both subtypes correlated with future FEV1/FVC decline (r = -0.16 [P < 0.001] in the Tissue→Airway group; r = -0.14 [P = 0.011] in the Airway→Tissue group). SuStaIn placed 30% of smokers with normal lung function at elevated stages, suggesting imaging changes consistent with early COPD. Individuals with early changes were 2.5 times more likely to meet COPD diagnostic criteria at follow-up.Conclusions: We demonstrate two distinct patterns of disease progression in COPD using SuStaIn, likely representing different endotypes. One third of healthy smokers have detectable imaging changes, suggesting a new biomarker of "early COPD."

Dataset Information

Probing Cellular and Molecular Mechanisms of Cigarette Smoke-Induced Immune Response in the Progression of Chronic Obstructive Pulmonary Disease Using Multiscale Network Modeling.

Publications

Probing Cellular and Molecular Mechanisms of Cigarette Smoke-Induced Immune Response in the Progression of Chronic Obstructive Pulmonary Disease Using Multiscale Network Modeling.

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