Protein networks in induced sputum from smokers and COPD patients

Wearable sampling of proteins from human exhaled aerosols for nano-liquid chromatography-tandem mass spectrometry analysis: A pilot study

RATIONALE

Human exhaled breath usually contains unique proteins that may provide clues to characterize individual physiological activities and many diseases. However, the concentration of exhaled proteins in exhaled breath is extremely low and usually does not reach the detection limits of all online breath mass spectrometry instruments. Therefore, developing a new breath sampler for collecting and characterizing exhaled proteins is important.

METHODS

In this study, a new mask-based wearable sampler was developed by fixing metal materials into the inner surface of the KN95 mask. Human exhaled proteins could be directly adsorbed onto the metal material while wearing the mask. After sampling, the collected proteins were eluted, digested, and identified using nano-liquid chromatography-tandem mass spectrometry (nano-LC-MS/MS).

RESULTS

The adsorption of exhaled proteins was evaluated, showing that modified gold foil is an effective material for collecting exhaled proteins. Various endogenous proteins were successfully identified from exhaled breath, many of which can be potential biomarkers for disease diagnosis.

CONCLUSIONS

By coupling the newly developed mask sampler with nano-LC-MS/MS, human exhaled proteins were successfully collected and identified. Our results show that the mask sampler is wearable, simple, and convenient, and the method is noninvasive for investigating disease diagnosis and human health.

Proteomic Blood Profiles Obtained by Totally Blind Biological Clustering in Stable and Exacerbated COPD Patients

Although Chronic Obstructive Pulmonary Disease (COPD) is highly prevalent, it is often underdiagnosed. One of the main characteristics of this heterogeneous disease is the presence of periods of acute clinical impairment (exacerbations). Obtaining blood biomarkers for either COPD as a chronic entity or its exacerbations (AECOPD) will be particularly useful for the clinical management of patients. However, most of the earlier studies have been characterized by potential biases derived from pre-existing hypotheses in one or more of their analysis steps: some studies have only targeted molecules already suggested by pre-existing knowledge, and others had initially carried out a blind search but later compared the detected biomarkers among well-predefined clinical groups. We hypothesized that a clinically blind cluster analysis on the results of a non-hypothesis-driven wide proteomic search would determine an unbiased grouping of patients, potentially reflecting their endotypes and/or clinical characteristics. To check this hypothesis, we included the plasma samples from 24 clinically stable COPD patients, 10 additional patients with AECOPD, and 10 healthy controls. The samples were analyzed through label-free liquid chromatography/tandem mass spectrometry. Subsequently, the Scikit-learn machine learning module and K-means were used for clustering the individuals based solely on their proteomic profiles. The obtained clusters were confronted with clinical groups only at the end of the entire procedure. Although our clusters were unable to differentiate stable COPD patients from healthy individuals, they segregated those patients with AECOPD from the patients in stable conditions (sensitivity 80%, specificity 79%, and global accuracy, 79.4%). Moreover, the proteins involved in the blind grouping process to identify AECOPD were associated with five biological processes: inflammation, humoral immune response, blood coagulation, modulation of lipid metabolism, and complement system pathways. Even though the present results merit an external validation, our results suggest that the present blinded approach may be useful to segregate AECOPD from stability in both the clinical setting and trials, favoring more personalized medicine and clinical research.

Epigenetic Reprogramming Drives Epithelial Disruption in Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) remains a major public health challenge that contributes greatly to mortality and morbidity worldwide. Although it has long been recognized that the epithelium is altered in COPD, there has been little focus on targeting it to modify the disease course. Therefore, mechanisms that disrupt epithelial cell function in patients with COPD are poorly understood. In this study, we sought to determine whether epigenetic reprogramming of the cell-cell adhesion molecule E-cadherin, encoded by the CDH1 gene, disrupts epithelial integrity. By reducing these epigenetic marks, we can restore epithelial integrity and rescue alveolar airspace destruction. We used differentiated normal and COPD-derived primary human airway epithelial cells, genetically manipulated mouse tracheal epithelial cells, and mouse and human precision-cut lung slices to assess the effects of epigenetic reprogramming. We show that the loss of CDH1 in COPD is due to increased DNA methylation site at the CDH1 enhancer D through the downregulation of the ten-eleven translocase methylcytosine dioxygenase (TET) enzyme TET1. Increased DNA methylation at the enhancer D region decreases the enrichment of RNA polymerase II binding. Remarkably, treatment of human precision-cut slices derived from patients with COPD with the DNA demethylation agent 5-aza-2'-deoxycytidine decreased cell damage and reduced air space enlargement in the diseased tissue. Here, we present a novel mechanism that targets epigenetic modifications to reverse the tissue remodeling in human COPD lungs and serves as a proof of concept for developing a disease-modifying target.

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.

Role of untargeted omics biomarkers of exposure and effect for tobacco research

Tobacco research remains a clear priority to improve individual and population health, and has recently become more complex with emerging combustible and noncombustible tobacco products. The use of omics methods in prevention and cessation studies are intended to identify new biomarkers for risk, compared risks related to other products and never use, and compliance for cessation and reinitation. to assess the relative effects of tobacco products to each other. They are important for the prediction of reinitiation of tobacco use and relapse prevention. In the research setting, both technical and clinical validation is required, which presents a number of complexities in the omics methodologies from biospecimen collection and sample preparation to data collection and analysis. When the results identify differences in omics features, networks or pathways, it is unclear if the results are toxic effects, a healthy response to a toxic exposure or neither. The use of surrogate biospecimens (e.g., urine, blood, sputum or nasal) may or may not reflect target organs such as the lung or bladder. This review describes the approaches for the use of omics in tobacco research and provides examples of prior studies, along with the strengths and limitations of the various methods. To date, there is little consistency in results, likely due to small number of studies, limitations in study size, the variability in the analytic platforms and bioinformatic pipelines, differences in biospecimen collection and/or human subject study design. Given the demonstrated value for the use of omics in clinical medicine, it is anticipated that the use in tobacco research will be similarly productive.

Applying Next-Generation Sequencing and Multi-Omics in Chronic Obstructive Pulmonary Disease

Microbiomics have significantly advanced over the last decade, driven by the widespread availability of next-generation sequencing (NGS) and multi-omic technologies. Integration of NGS and multi-omic datasets allow for a holistic assessment of endophenotypes across a range of chronic respiratory disease states, including chronic obstructive pulmonary disease (COPD). Valuable insight has been attained into the nature, function, and significance of microbial communities in disease onset, progression, prognosis, and response to treatment in COPD. Moving beyond single-biome assessment, there now exists a growing literature on functional assessment and host-microbe interaction and, in particular, their contribution to disease progression, severity, and outcome. Identifying specific microbes and/or metabolic signatures associated with COPD can open novel avenues for therapeutic intervention and prognosis-related biomarkers. Despite the promise and potential of these approaches, the large amount of data generated by such technologies can be challenging to analyze and interpret, and currently, there remains a lack of standardized methods to address this. This review outlines the current use and proposes future avenues for the application of NGS and multi-omic technologies in the endophenotyping, prognostication, and treatment of COPD.

diaPASEF Proteomics and Feature Selection for the Description of Sputum Proteome Profiles in a Cohort of Different Subtypes of Lung Cancer Patients and Controls

The high mortality, the presence of an initial asymptomatic stage and the fact that diagnosis in early stages reduces mortality justify the implementation of screening programs in the populations at risk of lung cancer. It is imperative to develop less aggressive methods that can complement existing diagnosis technologies. In this study, we aimed to identify lung cancer protein biomarkers and pathways affected in sputum samples, using the recently developed diaPASEF mass spectrometry (MS) acquisition mode. The sputum proteome of lung cancer cases and controls was analyzed through nano-HPLC–MS using the diaPASEF mode. For functional analysis, the results from differential expression analysis were further analyzed in the STRING platform, and feature selection was performed using sparse partial least squares discriminant analysis (sPLS-DA). Our results showed an activation of inflammation, with an alteration of pathways and processes related to acute-phase, complement, and immune responses. The resulting sPLS-DA model separated between case and control groups with high levels of sensitivity and specificity. In conclusion, we showed how new-generation proteomics can be used to detect potential biomarkers in sputum samples, and ultimately to discriminate patients from controls and even to help to differentiate between different cancer subtypes.

Proteomic Analysis of Human Sputum for the Diagnosis of Lung Disorders: Where Are We Today?

The identification of markers of inflammatory activity at the early stages of pulmonary diseases which share common characteristics that prevent their clear differentiation is of great significance to avoid misdiagnosis, and to understand the intrinsic molecular mechanism of the disorder. The combination of electrophoretic/chromatographic methods with mass spectrometry is currently a promising approach for the identification of candidate biomarkers of a disease. Since the fluid phase of sputum is a rich source of proteins which could provide an early diagnosis of specific lung disorders, it is frequently used in these studies. This report focuses on the state-of-the-art of the application, over the last ten years (2011-2021), of sputum proteomics in the investigation of severe lung disorders such as COPD; asthma; cystic fibrosis; lung cancer and those caused by COVID-19 infection. Analysis of the complete set of proteins found in sputum of patients affected by these disorders has allowed the identification of proteins whose levels change in response to the organism's condition. Understanding proteome dynamism may help in associating these proteins with alterations in the physiology or progression of diseases investigated.

Sputum Proteomics in Nontuberculous Mycobacterial Lung Disease

BACKGROUND

Nontuberculous mycobacterial (NTM) infections are difficult to diagnose and treat. Biomarkers to identify patients with active infection or at risk of disease progression would have clinical utility. Sputum is the most frequently used matrix for the diagnosis of NTM lung disease.

RESEARCH QUESTION

Can sputum proteomics be used to identify NTM-associated inflammatory profiles in sputum?

STUDY DESIGN AND METHODS

Patients with NTM lung disease and a matched cohort of patients with COPD, bronchiectasis (BE), and cystic fibrosis (CF) without NTM lung disease were enrolled from two hospitals in the United Kingdom. Liquid chromatography-tandem mass spectrometry was used to identify proteomic biomarkers associated with underlying diagnosis (COPD, BE, and CF), the presence of NTM lung disease defined according to American Thoracic Society/Infectious Diseases Society of America criteria, and severity of NTM. A subset of patients receiving guideline-concordant NTM treatment were studied to identify protein changes associated with treatment response.

RESULTS

This study analyzed 95 sputum samples from 55 subjects (BE, n = 21; COPD, n = 19; CF, n = 15). Underlying disease and infection with Pseudomonas aeruginosa were the strongest drivers of sputum protein profiles. Comparing protein abundance in COPD, BE, and CF found that 12 proteins were upregulated in CF compared with COPD, including MPO, AZU1, CTSG, CAT, and RNASE3, with 21 proteins downregulated, including SCGB1A1, IGFBP2, SFTPB, GC, and CFD. Across CF, BE, and COPD, NTM infection (n = 15) was not associated with statistically significant differences in sputum protein profiles compared with those without NTM. Two proteins associated with iron chelation were significantly downregulated in severe NTM disease. NTM treatment was associated with heterogeneous changes in the sputum protein profile. Patients with NTM and a decrease in immune response proteins had a subjective symptomatic improvement.

INTERPRETATION

Sputum proteomics identified candidate biomarkers of NTM severity and treatment response. However, underlying lung disease and typical bacterial pathogens such as P aeruginosa are also key determinants of the sputum proteomic profile.

Diacetyl Vapor Inhalation Induces Mixed, Granulocytic Lung Inflammation with Increased CD4+CD25+ T Cells in the Rat

Diacetyl (DA) is a highly reactive alpha diketone associated with flavoring-related lung disease. In rodents, acute DA vapor exposure can initiate an airway-centric, inflammatory response. However, this immune response has yet to be fully characterized in the context of flavoring-related lung disease progression. The following studies were designed to characterize the different T cell populations within the lung following repetitive DA vapor exposures. Sprague-Dawley rats were exposed to 200 parts-per-million DA vapor for 5 consecutive days × 6 h/day. Lung tissue and bronchoalveolar lavage fluid (BALF) were analyzed for changes in histology by H&E and Trichrome stain, T cell markers by flow cytometry, total BALF cell counts and differentials, BALF IL17a and total protein immediately, 1 and 2 weeks post-exposure. Lung histology and BALF cell composition demonstrated mixed, granulocytic lung inflammation with bronchial lymphoid aggregates at all time points in DA-exposed lungs compared to air controls. While no significant change was seen in percent lung CD3+, CD4+, or CD8+ T cells, a significant increase in lung CD4+CD25+ T cells developed at 1 week that persisted at 2 weeks post-exposure. Further characterization of this CD4+CD25+ T cell population identified Foxp3+ T cells at 1 week that failed to persist at 2 weeks. Conversely, BALF IL-17a increased significantly at 2 weeks in DA-exposed rats compared to air controls. Lung CD4+CD25+ T cells and BALF IL17a correlated directly with BALF total protein and inversely with rat oxygen saturations. Repetitive DA vapor exposure at occupationally relevant concentrations induced mixed, granulocytic lung inflammation with increased CD4+CD25+ T cells in the rat lung.

Changes in salivary proteome before and after cigarette smoking in smokers compared to sham smoking in nonsmokers: A pilot study

INTRODUCTION

Smoking is the leading cause of preventable disease. Although smoking results in an acute effect of relaxation and positive mood through dopamine release, smoking is thought to increase stress symptoms such as heart rate and blood pressure from nicotine-induced effects on the HPA axis and increased cortisol. Despite the importance in understanding the mechanisms in smoking maintenance, little is known about the overall protein and physiological response to smoking. There may be multiple functions involved that if identified might help in improving methods for behavioral and pharmacological interventions. Therefore, our goal for this pilot study was to identify proteins in the saliva that change in response to an acute smoking event versus acute sham smoking event in smokers and non-smokers, respectively.

METHODS

We employed the iTRAQ technique followed by Mass Spectrometry to identify differentially expressed proteins in saliva of smokers and non-smokers after smoking cigarettes and sham smoking, respectively. We also validated some of the salivary proteins by ELISA or western blotting. In addition, salivary cortisol and salivary amylase (sAA) activity were measured.

RESULTS

In all, 484 salivary proteins were identified. Several proteins were elevated as well as decreased in smokers compared to non-smokers. Among these were proteins associated with stress response including fibrinogen alpha, cystatin A and sAA. Our investigation also highlights methodological considerations in study design, sampling and iTRAQ analysis.

CONCLUSIONS

We suggest further investigation of other differentially expressed proteins in this study including ACBP, A2ML1, APOA4, BPIB1, BPIA2, CAH1, CAH6, CYTA, DSG1, EST1, GRP78, GSTO1, sAA, SAP, STAT, TCO1, and TGM3 that might assist in improving methods for behavioral and pharmacological interventions for smokers.

Protein Biomarkers for COPD Outcomes

COPD is a clinically heterogeneous syndrome characterized by injury to airways, airspaces, and lung vasculature and usually caused by tobacco smoke and/or air pollution exposure. COPD is also independently associated with nonpulmonary comorbidities (eg, cardiovascular disease) and malignancies (eg, GI, bladder), suggesting a role for systemic injury. Since not all those with exposure develop COPD, there has been a search for plasma and lung biomarkers that confer increased cross-sectional and longitudinal risk. This search typically focuses on clinically relevant COPD outcomes such as FEV1, FEV1 decline, CT measurements of emphysema, or exacerbation frequency. The rapid advances in omics technology and the molecular phenotyping of COPD cohorts now permit large-scale evaluation of genetic, transcriptomic, proteomic, and metabolic biomarkers. This review focuses on protein biomarkers associated with clinically relevant COPD outcomes. The prototypic COPD protein biomarker is alpha-1 antitrypsin; however, this biomarker only accounts for 1% to 5% of COPD. This article reviews and summarizes the evidence for other validated biomarkers for each COPD outcome, and discusses their advantages, weaknesses, and required regulatory steps to move the biomarker from the bench into clinic. Although we highlight the emergence of many novel biomarkers (eg, fibrinogen, soluble receptor for advanced glycation, surfactant protein D, club cell secretory protein), there is increasing evidence that individual biomarkers only explain a fraction of the increased COPD risk and that multiple biomarker panels are needed to completely explain clinical variation and risk in individuals and populations.

Sputum Proteome Signatures of Mechanically Ventilated Intensive Care Unit Patients Distinguish Samples with or without Anti-pneumococcal Activity

Mechanically ventilated patients are at risk of contracting pneumonia. Therefore, these patients often receive prophylactic systemic antimicrobial therapy. Intriguingly however, a previous study showed that antimicrobial activity in bronchoalveolar aspirates (here referred to as “sputa”) from ventilated patients was only partially explained by antibiotic therapy. Here we report that sputa from these patients presented distinct proteome signatures depending on the presence or absence of antimicrobial activity. Moreover, we show that the same distinction applied to antibodies against Streptococcus pneumoniae, which is a major causative agent of pneumonia. Specifically, the investigated sputa that inhibited growth of S. pneumoniae, while containing subinhibitory levels of the antibiotic cefotaxime, presented elevated levels of proteins implicated in innate immune defenses, including complement and apolipoprotein-associated proteins. In contrast, S. pneumoniae-inhibiting sputa with relatively high cefotaxime concentrations or noninhibiting sputa contained higher levels of proteins involved in inflammatory responses, such as neutrophil elastase-associated proteins. In an immunoproteomics analysis, 18 out of 55 S. pneumoniae antigens tested showed significantly increased levels of IgGs in inhibiting sputa. Hence, proteomics and immunoproteomics revealed elevated levels of antimicrobial host proteins or S. pneumoniae antigen-specific IgGs in pneumococcal growth-inhibiting sputa, thus explaining their anti-pneumococcal activity.

IMPORTANCE Respiratory pathogens like Streptococcus pneumoniae can cause severe pneumonia. Nonetheless, mechanically ventilated intensive care patients, who have a high risk of contracting pneumonia, rarely develop pneumococcal pneumonia. This suggests the presence of potentially protective antimicrobial agents in their lung environment. Our present study shows for the first time that bronchoalveolar aspirates, “sputa,” of ventilated patients in a Dutch intensive care unit were characterized by three distinct groups of proteome abundance signatures that can explain their anti-pneumococcal activity. Importantly, this anti-pneumococcal sputum activity was related either to elevated levels of antimicrobial host proteins or to antibiotics and S. pneumoniae-specific antibodies. Further, the sputum composition of some patients changed over time. Therefore, we conclude that our study may provide a novel tool to measure changes that are indicative of infection-related conditions in the lungs of mechanically ventilated patients.

Neutral Desorption Extractive Electrospray Ionization Mass Spectrometry Analysis Sputum for Non-Invasive Lung Adenocarcinoma Detection

Purpose

Increased use of low-dose spiral computed tomography (LDCT: low-dose computed tomography) screening has contributed to more frequent incidental detection of peripheral lung nodules, part of them were adenocarcinoma, which need to be further evaluated to establish a definitive diagnosis. Here, our primary objective was to evaluate the ambient mass spectrometry (AMS) sputum analysis as a non-invasive lung adenocarcinoma (LAC) diagnosis solution.

Patients and Methods

Neutral desorption extractive electrospray ionization mass spectrometry (ND-EESI-MS) and collision induced dissociation (CID) were used to detect sputum metabolites from 143 spontaneous sputum samples. Partial least squares-discriminant analysis (PLS-DA) was used to refine the biomarker panel, whereas orthogonal PLS-DA (OPLS-DA) was used to operationalize the enhanced biomarker panel for diagnosis.

Results

In this approach, 19 altered metabolites were detected by ND-EESI-MS from 76 cases of LAC and 67 cases of control. Significance testing and receiver operating characteristic (ROC) analysis identified 5 metabolites [hydroxyphenyllactic acid, phytosphingosine, N-nonanoylglycine, sphinganine, S-carboxymethyl-L-cysteine] with p <0.05 and AUC >0.75, respectively. Evaluation of model performance for prediction of LAC resulted in a cross-validation classification accuracy of 87.9%. Metabolic pathway analysis showed that sphingolipid metabolism, fatty acid metabolism, carnitine synthesis and Warburg effect were most impacted in response to disease.

Conclusion

This study indicates that the application of ND-EESI-MS to sputum analysis can be used as a non-invasive detection of peripheral lung nodules. The use of sputum metabolite biomarkers may aid in the development of a further evaluation program for lung adenocarcinoma.

Increased MUC1 plus a larger quantity and complex size for MUC5AC in the peripheral airway lumen of long-term tobacco smokers

There is little information on mucins versus potential regulatory factors in the peripheral airway lumen of long-term smokers with (LTS+) and without (LTS-) chronic obstructive pulmonary disease (COPD). We explored these matters in bronchoalveolar lavage (BAL) samples from two study materials, both including LTS+ and LTS- with a very similar historic exposure to tobacco smoke, and healthy non-smokers (HNSs; n=4-20/group). Utilizing slot blot and immunodetection of processed (filtered and centrifuged), as well as unprocessed BAL samples from one of the materials, we compared the quantity and fraction of large complexes of mucins. All LTS displayed an enhanced (median) level of MUC5AC compared with HNS. LTS- displayed a higher level of large MUC5AC complexes than HNS while LTS+ displayed a similar trend. In all LTS, total MUC5AC correlated with blood leukocytes, BAL neutrophil elastase and net gelatinase activity. Large mucin complexes accounted for most MUC5B, without clear group differences. In all LTS, total MUC5B correlated with total MUC5AC and local bacteria. In the same groups, large MUC5B complexes correlated with serum cotinine. MUC1 was increased and correlated with BAL leukocytes in all LTS whereas MUC2 was very low and without clear group differences. Thus, the main part of MUC5AC and MUC5B is present as large complexes in the peripheral airway lumen and historic as well as current exposure to tobacco smoke emerge as potential regulatory factors, regardless of COPD per se. Bacteria, leukocytes and proteinases also constitute potential regulatory factors, of interest for future therapeutic strategies.

Proteomics: Clinical and research applications in respiratory diseases

The proteome is the study of the protein content of a definable component of an organism in biology. However, the tissue-specific expression of proteins and the varied post-translational modifications, splice variants and protein-protein complexes that may form, make the study of protein a challenging yet vital tool in answering many of the unanswered questions in medicine and biology to date. Indeed, the spatial, temporal and functional composition of proteins in the human body has proven difficult to elucidate for many years. Given the effect of microRNA and epigenetic regulation on silencing and enhancing gene transcription, the study of protein arguably provides more accurate information on homeostasis and perturbation in health and disease. There have been significant advances in the field of proteomics in recent years, with new technologies and platforms available to the research community. In this review, we briefly discuss some of these new technologies and developments in the context of respiratory disease. We also discuss the types of data science approaches to analyses and interpretation of the large volumes of data generated in proteomic studies. We discuss the application of these technologies with regard to respiratory disease and highlight the potential for proteomics in generating major advances in the understanding of respiratory pathophysiology into the future.

Searching for biomarkers of chronic obstructive pulmonary disease using proteomics: The current state

Detection of proteins which may be potential biomarkers of disorders represents a big step forward in understanding the molecular mechanisms that underlie pathological processes. In this context proteomics plays the important role of opening a path for the identification of molecular signatures that can potentially assist in early diagnosis of several clinical disturbances. Aim of this report is to provide an overview of the wide variety of proteomic strategies that have been applied to the investigation of chronic obstructive pulmonary disease (COPD), a severe disorder that causes an irreversible damage to the lungs and for which there is no cure yet. The results in this area published over the past decade show that proteomics indeed has the ability of monitoring alterations in expression profiles of proteins from fluids/tissues of patients affected by COPD and healthy controls. However, these data also suggest that proteomics, while being an attractive tool for the identification of novel pathological mediators of COPD, remains a technique mainly generated and developed in research laboratories. Great efforts dedicated to the validation of these biological signatures will result in the proof of their clinical utility.

Large-Scale Label-Free Quantitative Mapping of the Sputum Proteome

Analysis of induced sputum supernatant is a minimally invasive approach to study the epithelial lining fluid and, thereby, provide insight into normal lung biology and the pathobiology of lung diseases. We present here a novel proteomics approach to sputum analysis developed within the U-BIOPRED (unbiased biomarkers predictive of respiratory disease outcomes) international project. We present practical and analytical techniques to optimize the detection of robust biomarkers in proteomic studies. The normal sputum proteome was derived using data-independent HDMS^E applied to 40 healthy nonsmoking participants, which provides an essential baseline from which to compare modulation of protein expression in respiratory diseases. The "core" sputum proteome (proteins detected in ≥40% of participants) was composed of 284 proteins, and the extended proteome (proteins detected in ≥3 participants) contained 1666 proteins. Quality control procedures were developed to optimize the accuracy and consistency of measurement of sputum proteins and analyze the distribution of sputum proteins in the healthy population. The analysis showed that quantitation of proteins by HDMS^E is influenced by several factors, with some proteins being measured in all participants' samples and with low measurement variance between samples from the same patient. The measurement of some proteins is highly variable between repeat analyses, susceptible to sample processing effects, or difficult to accurately quantify by mass spectrometry. Other proteins show high interindividual variance. We also highlight that the sputum proteome of healthy individuals is related to sputum neutrophil levels, but not gender or allergic sensitization. We illustrate the importance of design and interpretation of disease biomarker studies considering such protein population and technical measurement variance.

New Strategies and Challenges in Lung Proteomics and Metabolomics. An Official American Thoracic Society Workshop Report

This document presents the proceedings from the workshop entitled, "New Strategies and Challenges in Lung Proteomics and Metabolomics" held February 4th-5th, 2016, in Denver, Colorado. It was sponsored by the National Heart Lung Blood Institute, the American Thoracic Society, the Colorado Biological Mass Spectrometry Society, and National Jewish Health. The goal of this workshop was to convene, for the first time, relevant experts in lung proteomics and metabolomics to discuss and overcome specific challenges in these fields that are unique to the lung. The main objectives of this workshop were to identify, review, and/or understand: (1) emerging technologies in metabolomics and proteomics as applied to the study of the lung; (2) the unique composition and challenges of lung-specific biological specimens for metabolomic and proteomic analysis; (3) the diverse informatics approaches and databases unique to metabolomics and proteomics, with special emphasis on the lung; (4) integrative platforms across genetic and genomic databases that can be applied to lung-related metabolomic and proteomic studies; and (5) the clinical applications of proteomics and metabolomics. The major findings and conclusions of this workshop are summarized at the end of the report, and outline the progress and challenges that face these rapidly advancing fields.

Transcriptomics, proteomics and metabolomics driven biomarker discovery in COPD: an update

INTRODUCTION

Diagnosis of chronic obstructive pulmonary disease (COPD), characterized by progressive irreversible airflow limitation, remains a challenge. Lack of sensitive diagnostic markers and alternative treatments have limited patients' survival rate. Herein, we provide for clinicians and scientists a comprehensive review on the various omics platforms used to investigate COPD.

AREAS COVERED

This review consists of articles from PubMed (2009-2016) as well as views of the contributing authors. The review highlights the need for COPD biomarker identification and also provides an update on promising candidate markers identified in various biological fluids using omics technologies. Expert commentary: The multi-omics approach holds promise for the development of robust early stage COPD diagnostic markers, screening of high-risk population, and also improved prognosis which could lead to personalized medicine in future. Various factors regulating an omics study including sample size, control selection, disease phenotyping, usage of complementary techniques and result replication in omics-based research are outlined.