From Proteomics to Prescription—The Search for COPD Biomarkers

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.

Proteomics of pulmonary hypertension: could personalized profiles lead to personalized medicine?

Pulmonary hypertension (PH) is a fatal syndrome that arises from a multifactorial and complex background, is characterized by increased pulmonary vascular resistance and right heart afterload, and often leads to cor pulmonale. Over the past decades, remarkable progress has been made in reducing patient symptoms and delaying the progression of the disease. Unfortunately, PH remains a disease with no cure. The substantial heterogeneity of PH continues to be a major limitation to the development of newer and more efficacious therapies. New advances in our understanding of the biological pathways leading to such a complex pathogenesis will require the identification of the important proteins and protein networks that differ between a healthy lung (or right ventricle) and a remodeled lung in an individual with PH. In this article, we present the case for the increased use of proteomics--the study of proteins and protein networks--as a discovery tool for key proteins and protein networks operational in the PH lung. We review recent applications of proteomics in PH, and summarize the biological pathways identified. Finally, we attempt to presage what the future will bring with regard to proteomics in PH and offer our perspectives on the prospects of developing personalized proteomics and custom-tailored therapies.

Asthma and COPD proteomics: current approaches and future directions

Although asthma and chronic obstructive pulmonary disease COPD represent the two most common chronic respiratory diseases worldwide, the mechanisms underlying their pathobiology need to be further elucidated. Presently, differentiation of asthma and COPD are largely based on clinical and lung function parameters. However, the complexity of these multifactorial diseases may lead to misclassification and to inappropriate management strategies. Recently, tremendous progress in MS has extended the sensitivity, accuracy, and speed of analysis, enabling the identification of thousands of proteins per experiment. Beyond identification, MS has also greatly implemented quantitation issues allowing to assess qualitative-quantitative differences in protein profiles of different samples, in particular diseased versus normal. Herein, we provide a summary of recent proteomics-based investigations in the field of asthma/COPD, highlighting major issues related to sampling and processing procedures for proteomic analyses of specific airway and parenchymal specimens (induced sputum, exhaled breath condensate, epithelial lining fluid, bronchoalveolar and nasal lavage fluid), as well as blood-derived specimen (plasma and serum). Within such a context, together with current difficulties and limitations mainly due to lack of general standardization in preanalytical sampling procedure, our discussion will focus on the challenges and possible benefits of proteomic studies in phenotypic stratification of asthma and COPD.

Susceptibility to COPD: differential proteomic profiling after acute smoking

Cigarette smoking is the main risk factor for COPD (Chronic Obstructive Pulmonary Disease), yet only a subset of smokers develops COPD. Family members of patients with severe early-onset COPD have an increased risk to develop COPD and are therefore defined as “susceptible individuals”. Here we perform unbiased analyses of proteomic profiles to assess how “susceptible individuals” differ from age-matched “non-susceptible individuals” in response to cigarette smoking. Epithelial lining fluid (ELF) was collected at baseline and 24 hours after smoking 3 cigarettes in young individuals susceptible or non-susceptible to develop COPD and older subjects with established COPD. Controls at baseline were older healthy smoking and non-smoking individuals. Five samples per group were pooled and analysed by stable isotope labelling (iTRAQ) in duplicate. Six proteins were selected and validated by ELISA or immunohistochemistry. After smoking, 23 proteins increased or decreased in young susceptible individuals, 7 in young non-susceptible individuals, and 13 in COPD in the first experiment; 23 proteins increased or decreased in young susceptible individuals, 32 in young non-susceptible individuals, and 11 in COPD in the second experiment. SerpinB3 and Uteroglobin decreased after acute smoke exposure in young non-susceptible individuals exclusively, whereas Peroxiredoxin I, S100A9, S100A8, ALDH3A1 (Aldehyde dehydrogenase 3A1) decreased both in young susceptible and non-susceptible individuals, changes being significantly different between groups for Uteroglobin with iTRAQ and for Serpin B3 with iTRAQ and ELISA measures. Peroxiredoxin I, SerpinB3 and ALDH3A1 increased in COPD patients after smoking. We conclude that smoking induces a differential protein response in ELF of susceptible and non-susceptible young individuals, which differs from patients with established COPD. This is the first study applying unbiased proteomic profiling to unravel the underlying mechanisms that induce COPD. Our data suggest that SerpinB3 and Uteroglobin could be interesting proteins in understanding the processes leading to COPD.

Biomarkers in chronic obstructive pulmonary disease: confusing or useful?

The field of biomarker research has almost reached unmanageable proportions in chronic obstructive pulmonary disease (COPD). The developments of new technology platforms have generated a huge information data base, both cross sectionally and increasingly, longitudinally. The knowledge emerging provides an enormous potential for understanding the disease pathophysiology, for developing markers specific for long-term outcomes, and for developing new therapeutic strategies. However, the excitement must be tempered with an understanding of the limitations of the data collection techniques, and of the variations in disease state, activity, impact, and progression. Nevertheless, the most crucial aspect in interpreting the current literature is the recognition of the relatively superficial characterization of what is a complex group of pathological processes with a common end point of airflow limitation. The current review explores some of these issues together with those areas where real progress appears to have been made, and provides caution on interpretation.

An engineering view on megatrends in radiology: digitization to quantitative tools of medicine

Within six months of the discovery of X-ray in 1895, the technology was used to scan the interior of the human body, paving the way for many innovations in the field of medicine, including an ultrasound device in 1950, a CT scanner in 1972, and MRI in 1980. More recent decades have witnessed developments such as digital imaging using a picture archiving and communication system, computer-aided detection/diagnosis, organ-specific workstations, and molecular, functional, and quantitative imaging. One of the latest technical breakthrough in the field of radiology has been imaging genomics and robotic interventions for biopsy and theragnosis. This review provides an engineering perspective on these developments and several other megatrends in radiology.

Advances in proteomic techniques for biomarker discovery in COPD

Chronic obstructive pulmonary disease (COPD) is a disorder characterized by chronic inflammation of the lung with airflow obstruction and progressive deterioration of pulmonary function. The need to discover and validate biomarkers as prognostic tools of development and progression of the disease has received further support with the advent of proteomic techniques. Liquid chromatography-mass spectrometry (LC/MS) and gel electrophoresis-mass spectrometry (2-DE/MS) have been applied to investigate the proteome of a number of lung-origin samples, including sputum, bronchoalveolar lavage fluid, exhaled-breath condensate, cells and biopsies from COPD patients. In particular, 2-DE and MS are the main proteomic approaches with 2-DE presenting the major approach for quantitative proteomics. The molecules identified as potential biomarkers of COPD may represent a preliminary step for better comprehension of the mechanisms involved in the onset/progression of the disease.

Application of mass spectrometry to study proteomics and interactomics in cystic fibrosis

The cystic fibrosis transmembrane conductance regulator (CFTR) does not function in isolation, but rather in a complex network of protein-protein interactions that dictate the physiology of a healthy cell and tissue and, when defective, the pathophysiology characteristic of cystic fibrosis (CF) disease. To begin to address the organization and operation of the extensive cystic fibrosis protein network dictated by simultaneous and sequential interactions, it will be necessary to understand the global protein environment (the proteome) in which CFTR functions in the cell and the local network that dictates CFTR folding, trafficking, and function at the cell surface. Emerging mass spectrometry (MS) technologies and methodologies offer an unprecedented opportunity to fully characterize both the proteome and the protein interactions directing normal CFTR function and to define what goes wrong in disease. Below we provide the CF investigator with a general introduction to the capabilities of modern mass spectrometry technologies and methodologies with the goal of inspiring further application of these technologies for development of a basic understanding of the disease and for the identification of novel pathways that may be amenable to therapeutic intervention in the clinic.