Proteomic Network Analysis of Bronchoalveolar Lavage Fluid in Ex-Smokers to Discover Implicated Protein Targets and Novel Drug Treatments for Chronic Obstructive Pulmonary Disease

A quantitative proteomic approach to evaluate the efficacy of carnosine in a murine model of chronic obstructive pulmonary disease (COPD)

The aim of the work was to study a dose-dependent effect of inhaled carnosine (10, 50 or 100 mg/kg/day) in mice exposed to cigarette smoke as a model of chronic obstructive pulmonary disease (COPD). A dose-dependent loading of the dipeptide in lung tissue and bronchoalveolar lavage (BAL) was firstly demonstrated by LC-ESI-MS analysis. Cigarette smoke exposure induced a significant lung inflammation and oxidative stress in mice which was dose-dependently reduced by carnosine. Inflammation was firstly evaluated by measuring the cytokines content in the BAL. All the measured cytokines were found significantly higher in the smoke group in respect to control, although the data are affected by a significant variability. Carnosine was found effective only at the highest dose tested and significantly only for keratinocyte-derived cytokine (KC). Due to the high variability of cytokines, a quantitative proteomic approach to better understand the functional effect of carnosine and its molecular mechanisms was used. Proteomic data clearly indicate that smoke exposure had a great impact on lung tissue with 692 proteins differentially expressed above a threshold of 1.5-fold. Protein network analysis identified the activation of some pathways characteristic of COPD, including inflammatory response, fibrosis, induction of immune system by infiltration and migration of leukocyte pathways, altered pathway of calcium metabolism and oxidative stress. Carnosine at the tested dose of 100 mg/kg was found effective in reverting all the pathways evoked by smoke. Only a partial reverse of the dysregulated proteins was evident at low- and mid-tested doses, although, for some specific proteins, indicating an overall dose-dependent effect. Regarding the molecular mechanisms involved, we found that carnosine upregulated some key enzymes related to Nrf2 activation and in particular glutathione peroxidase, reductase, transferase, SOD, thioredoxins, and carbonyl reductase. Such mechanism would explain the antioxidant and anti-inflammatory effects of the dipeptide.

Evaluation of common protein biomarkers involved in the pathogenesis of respiratory diseases with proteomic methods: A systematic review

AIM

Respiratory disease (RD) is one of the most common diseases characterized by lung dysfunction. Many diagnostic mechanisms have been used to identify the pathogenic agents of responsible for RD. Among these, proteomics emerges as a valuable diagnostic method for pinpointing the specific proteins involved in RD pathogenesis. Therefore, in this study, for the first time, we examined the protein markers involved in the pathogenesis of chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), asthma, bronchiolitis obliterans (BO), and chemical warfare victims exposed to mustard gas, using the proteomics method as a systematic study.

MATERIALS AND METHODS

A systematic search was performed up to September 2023 on several databases, including PubMed, Scopus, ISI Web of Science, and Cochrane. In total, selected 4246 articles were for evaluation according to the criteria. Finally, 119 studies were selected for this systematic review.

RESULTS

A total of 13,806 proteins were identified, 6471 in COPD, 1603 in Asthma, 5638 in IPF, three in BO, and 91 in mustard gas exposed victims. Alterations in the expression of these proteins were observed in the respective diseases. After evaluation, the results showed that 31 proteins were found to be shared among all five diseases.

CONCLUSION

Although these 31 proteins regulate different factors and molecular pathways in all five diseases, they ultimately lead to the regulation of inflammatory pathways. In other words, the expression of some proteins in COPD and mustard-exposed patients increases inflammatory reactions, while in IPF, they cause lung fibrosis. Asthma, causes allergic reactions due to T-cell differentiation toward Th2.

Effective holistic characterization of small molecule effects using heterogeneous biological networks

The two most common reasons for attrition in therapeutic clinical trials are efficacy and safety. We integrated heterogeneous data to create a human interactome network to comprehensively describe drug behavior in biological systems, with the goal of accurate therapeutic candidate generation. The Computational Analysis of Novel Drug Opportunities (CANDO) platform for shotgun multiscale therapeutic discovery, repurposing, and design was enhanced by integrating drug side effects, protein pathways, protein-protein interactions, protein-disease associations, and the Gene Ontology, and complemented with its existing drug/compound, protein, and indication libraries. These integrated networks were reduced to a "multiscale interactomic signature" for each compound that describe its functional behavior as vectors of real values. These signatures are then used for relating compounds to each other with the hypothesis that similar signatures yield similar behavior. Our results indicated that there is significant biological information captured within our networks (particularly via side effects) which enhance the performance of our platform, as evaluated by performing all-against-all leave-one-out drug-indication association benchmarking as well as generating novel drug candidates for colon cancer and migraine disorders corroborated via literature search. Further, drug impacts on pathways derived from computed compound-protein interaction scores served as the features for a random forest machine learning model trained to predict drug-indication associations, with applications to mental disorders and cancer metastasis highlighted. This interactomic pipeline highlights the ability of Computational Analysis of Novel Drug Opportunities to accurately relate drugs in a multitarget and multiscale context, particularly for generating putative drug candidates using the information gleaned from indirect data such as side effect profiles and protein pathway information.

Advances in phosphoproteomics and its application to COPD

INTRODUCTION

Chronic obstructive pulmonary disease (COPD) was the third leading cause of global death in 2019, causing a huge economic burden to society. Therefore, it is urgent to identify specific phenotypes of COPD patients through early detection, and to promptly treat exacerbations. The field of phosphoproteomics has been a massive advancement, compelled by the developments in mass spectrometry, enrichment strategies, algorithms, and tools. Modern mass spectrometry-based phosphoproteomics allows understanding of disease pathobiology, biomarker discovery, and predicting new therapeutic modalities.

AREAS COVERED

In this article, we present an overview of phosphoproteomic research and strategies for enrichment and fractionation of phosphopeptides, identification of phosphorylation sites, chromatographic separation and mass spectrometry detection strategies, and the potential application of phosphorylated proteomic analysis in the diagnosis, treatment, and prognosis of COPD disease.

EXPERT OPINION

The role of phosphoproteomics in COPD is critical for understanding disease pathobiology, identifying potential biomarkers, and predicting new therapeutic approaches. However, the complexity of COPD requires the more comprehensive understanding that can be achieved through integrated multi-omics studies. Phosphoproteomics, as a part of these multi-omics approaches, can provide valuable insights into the underlying mechanisms of COPD.