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

Phenotyping of Severe Asthma in the Era of Broad-Acting Anti-Asthma Biologics

Severe asthma is associated with significant morbidity and mortality despite the maximal use of inhaled corticosteroids and additional controller medications, and has a high economic burden. Biologic therapies are recommended for the management of severe, uncontrolled asthma to help to prevent exacerbations and to improve symptoms and health-related quality of life. The effective management of severe asthma requires consideration of clinical heterogeneity that is driven by varying clinical and inflammatory phenotypes, which are reflective of distinct underlying disease mechanisms. Phenotyping patients using a combination of clinical characteristics such as the age of onset or comorbidities and biomarker profiles, including blood eosinophil counts and levels of fractional exhaled nitric oxide and serum total immunoglobulin E, is important for the differential diagnosis of asthma. In addition, phenotyping is beneficial for risk assessment, selection of treatment, and monitoring of the treatment response in patients with asthma. This review describes the clinical and inflammatory phenotypes of asthma, provides an overview of biomarkers routinely used in clinical practice and those that have recently been explored for phenotyping, and aims to assess the value of phenotyping in severe asthma management in the current era of biologics.

An integrated metabo-lipidomics profile of induced sputum for the identification of novel biomarkers in the differential diagnosis of asthma and COPD

BACKGROUND

Due to their complexity and to the presence of common clinical features, differentiation between asthma and chronic obstructive pulmonary disease (COPD) can be a challenging task, complicated in such cases also by asthma-COPD overlap syndrome. The distinct immune/inflammatory and structural substrates of COPD and asthma are responsible for significant differences in the responses to standard pharmacologic treatments. Therefore, an accurate diagnosis is of central relevance to assure the appropriate therapeutic intervention in order to achieve safe and effective patient care. Induced sputum (IS) accurately mirrors inflammation in the airways, providing a more direct picture of lung cell metabolism in comparison to those specimen that reflect analytes in the systemic circulation.

METHODS

An integrated untargeted metabolomics and lipidomics analysis was performed in IS of asthmatic (n = 15) and COPD (n = 22) patients based on Ultra-High-Pressure Liquid Chromatography-Mass Spectrometry (UHPLC-MS) and UHPLC-tandem MS (UHPLC-MS/MS). Partial Least Squares-Discriminant Analysis (PLS-DA) was applied to resulting dataset. The analysis of main enriched metabolic pathways and the association of the preliminary metabolites/lipids pattern identified to clinical parameters of asthma/COPD differentiation were explored. Multivariate ROC analysis was performed in order to determine the discriminatory power and the reliability of the putative biomarkers for diagnosis between COPD and asthma.

RESULTS

PLS-DA indicated a clear separation between COPD and asthmatic patients. Among the 15 selected candidate biomarkers based on Variable Importance in Projection scores, putrescine showed the highest score. A differential IS bio-signature of 22 metabolites and lipids was found, which showed statistically significant variations between asthma and COPD. Of these 22 compounds, 18 were decreased and 4 increased in COPD compared to asthmatic patients. The IS levels of Phosphatidylethanolamine (PE) (34:1), Phosphatidylglycerol (PG) (18:1;18:2) and spermine were significantly higher in asthmatic subjects compared to COPD.

CONCLUSIONS

This is the first pilot study to analyse the IS metabolomics/lipidomics signatures relevant in discriminating asthma vs COPD. The role of polyamines, of 6-Hydroxykynurenic acid and of D-rhamnose as well as of other important players related to the alteration of glycerophospholipid, aminoacid/biotin and energy metabolism provided the construction of a diagnostic model that, if validated on a larger prospective cohort, might be used to rapidly and accurately discriminate asthma from COPD.

Developing technologies and areas of interest in lung cancer screening adjuncts

Lung cancer remains the leading cause of cancer mortality. Screening guidelines have been implemented in the past decade to aid in earlier detection of at-risk groups. Nevertheless, computed tomography (CT) scans, the principal screening modality in use today, are still low yield, with 3.6% of lung cancer confirmed amongst 39.1% of lesions detected over a 3-year period. They also carry relatively high false positive rates, between 9% and 27%, which can bear unnecessary financial and emotional costs to patients. As such, research efforts have been dedicated to the development of lung cancer screening adjuncts to improve detection reliability. We herein review several emerging technologies in this specific arena and their efficacy. These include plasma markers (microDNA, DNA methylation, and tumor-associated antibodies), breath/sputum biomarkers [volatile organic compounds (VOCs) and exhaled breath condensate (EBC)], proteomics, metabolomics, and machine learning, such as radiomics technology. We find that, across the board, they offer promising results in terms of non-invasive diagnostics, genetic sequencing for higher-risk individuals, and accessibility for a diverse cohort of patients. While these screening adjuncts are unlikely to completely replace the current standard of care at the moment, continued research into these technologies is crucial to improve and personalize the identification, treatment, and outcome of lung cancer patients in the near future.

Mucus Structure, Viscoelastic Properties, and Composition in Chronic Respiratory Diseases

The respiratory mucus, a viscoelastic gel, effectuates a primary line of the airway defense when operated by the mucociliary clearance. In chronic respiratory diseases (CRDs), such as asthma, chronic obstructive pulmonary disease (COPD), and cystic fibrosis (CF), the mucus is overproduced and its solid content augments, changing its structure and viscoelastic properties and determining a derangement of essential defense mechanisms against opportunistic microbial (virus and bacteria) pathogens. This ensues in damaging of the airways, leading to a vicious cycle of obstruction and infection responsible for the harsh clinical evolution of these CRDs. Here, we review the essential features of normal and pathological mucus (i.e., sputum in CF, COPD, and asthma), i.e., mucin content, structure (mesh size), micro/macro-rheology, pH, and osmotic pressure, ending with the awareness that sputum biomarkers (mucins, inflammatory proteins and peptides, and metabolites) might serve to indicate acute exacerbation and response to therapies. There are some indications that old and novel treatments may change the structure, viscoelastic properties, and biomarker content of sputum; however, a wealth of work is still needed to embrace these measures as correlates of disease severity in association with (or even as substitutes of) pulmonary functional tests.

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.

Engineering a Point-of-Care Paper-Microfluidic Electrochemical Device Applied to the Multiplexed Quantitative Detection of Biomarkers in Sputum

Health initiatives worldwide demand affordable point-of-care devices to aid in the reduction of morbidity and mortality rates of high-incidence infectious and noncommunicable diseases. However, the production of robust and reliable easy-to-use diagnostic platforms showing the ability to quantitatively measure several biomarkers in physiological fluids and that could in turn be decentralized to reach any relevant environment remains a challenge. Here, we show the particular combination of paper-microfluidic technology, electrochemical transduction, and magnetic nanoparticle-based immunoassay approaches to produce a unique, compact, and easily deployable multiplex device to simultaneously measure interleukin-8, tumor necrosis factor-α, and myeloperoxidase biomarkers in sputum, developed with the aim of facilitating the timely detection of acute exacerbations of chronic obstructive pulmonary disease. The device incorporates an on-chip electrochemical cell array and a multichannel paper component, engineered to be easily aligned into a polymeric cartridge and exchanged if necessary. Calibration curves at clinically relevant biomarker concentration ranges are produced in buffer and artificial sputum. The analysis of sputum samples of healthy individuals and acutely exacerbated patients produces statistically significant biomarker concentration differences between the two studied groups. The device can be mass-produced at a low cost, being an easily adaptable platform for measuring other disease-related target biomarkers.

Extracellular circulating miRNAs as potential non-invasive biomarkers in non-small cell lung cancer patients

Non-small cell lung cancer (NSCLC) comprises 85% of all lung cancers and is a malignant condition resistant to advanced-stage treatment. Despite the advancement in detection and treatment techniques, the disease is taking a deadly toll worldwide, being the leading cause of cancer death every year. Current diagnostic methods do not ensure the detection of the disease at an early stage, nor can they predict the risk of its development. There is an urgent need to identify biomarkers that can help predict an individual's risk of developing NSCLC, distinguish NSCLC subtype, allow monitor disease and treatment progression which can improve patient survival. Micro RNAs (miRNAs) represent the class of small and non-coding RNAs involved in gene expression regulation, influencing many biological processes such as proliferation, differentiation, and carcinogenesis. Research reports significant differences in miRNA profiles between healthy and neoplastic tissues in NSCLC. Its abundant presence in biofluids, such as serum, blood, urine, and saliva, makes them easily detectable and does not require invasive collection techniques. Many studies support miRNAs' importance in detecting, predicting, and prognosis of NSCLC, indicating their utility as a promising biomarker. In this work, we reviewed up-to-date research focusing on biofluid miRNAs' role as a diagnostic tool in NSCLC cases. We also discussed the limitations of applying miRNAs as biomarkers and highlighted future areas of interest.

Prognostic Biomarkers Based on Proteomic Technology in COPD: A Recent Review

Chronic obstructive pulmonary disease (COPD) is a common heterogeneous respiratory disease which is characterized by persistent and incompletely reversible airflow limitation. Due to the heterogeneity and phenotypic complexity of COPD, traditional diagnostic methods provide limited information and pose a great challenge to clinical management. In recent years, with the development of omics technologies, proteomics, metabolomics, transcriptomics, etc., have been widely used in the study of COPD, providing great help to discover new biomarkers and elucidate the complex mechanisms of COPD. In this review, we summarize the prognostic biomarkers of COPD based on proteomic studies in recent years and evaluate their association with COPD prognosis. Finally, we present the prospects and challenges of COPD prognostic-related studies. This review is expected to provide cutting-edge evidence in prognostic evaluation of clinical patients with COPD and to inform future proteomic studies on prognostic biomarkers of COPD.

Progress of the "Molecular Informatics" Section in 2022

This is the first Editorial of the "Molecular Informatics" Section (MIS) of the International Journal of Molecular Sciences (IJMS), which was created towards the end of 2018 (the first article was submitted on 27 September 2018) and has experienced significant growth from 2018 to now [...].

Towards Precision Prognostication and Personalized Therapeutics through Proteomics

Next-generation proteomics has allowed the implementation of biomedical proteome research to uncover disease-affected protein expression profiles [...]

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.

Mass Spectrometric Proteomics 2022

Until recently, a major challenge of biochemists working in the protein field was the identification, purification, and sequencing of an individual protein [...].