Identification of lipocalin and apolipoprotein A1 as biomarkers of chronic obstructive pulmonary disease

A systematic analysis of eluted fraction of plasma post immunoaffinity depletion: implications in biomarker discovery

Plasma is the most easily accessible source for biomarker discovery in clinical proteomics. However, identifying potential biomarkers from plasma is a challenge given the large dynamic range of proteins. The potential biomarkers in plasma are generally present at very low abundance levels and hence identification of these low abundance proteins necessitates the depletion of highly abundant proteins. Sample pre-fractionation using immuno-depletion of high abundance proteins using multi-affinity removal system (MARS) has been a popular method to deplete multiple high abundance proteins. However, depletion of these abundant proteins can result in concomitant removal of low abundant proteins. Although there are some reports suggesting the removal of non-targeted proteins, the predominant view is that number of such proteins is small. In this study, we identified proteins that are removed along with the targeted high abundant proteins. Three plasma samples were depleted using each of the three MARS (Hu-6, Hu-14 and Proteoprep 20) cartridges. The affinity bound fractions were subjected to gelC-MS using an LTQ-Orbitrap instrument. Using four database search algorithms including MassWiz (developed in house), we selected the peptides identified at <1% FDR. Peptides identified by at least two algorithms were selected for protein identification. After this rigorous bioinformatics analysis, we identified 101 proteins with high confidence. Thus, we believe that for biomarker discovery and proper quantitation of proteins, it might be better to study both bound and depleted fractions from any MARS depleted plasma sample.

Potential therapeutic target discovery by 2D-DIGE proteomic analysis in mouse models of asthma

As asthma physiopathology is complex and not fully understood to date; it is expected that new key mediators are still to be unveiled in this disease. The main objective of this study was to discover potential new target proteins with a molecular weight >20 kDa by using two-dimensional differential in-gel electrophoresis (2D-DIGE) on lung parenchyma extracts from control or allergen-exposed mice (ovalbumin). Two different mouse models leading to the development of acute airway inflammation (5 days allergen exposure) and airway remodeling (10 weeks allergen exposure) were used. This experimental setting allowed the discrimination of 33 protein spots in the acute inflammation model and 31 spots in the remodeling model displaying a differential expression. Several proteins were then identified by MALDI-TOF/TOF MS. Among those differentially expressed proteins, PDIA6, GRP78, Annexin A6, hnRPA3, and Enolase display an increased expression in lung parenchyma from mice exposed to allergen for 5 days. Conversely, Apolipoprotein A1 was shown to be decreased after allergen exposure in the same model. Analysis on lung parenchyma of mice exposed to allergens for 10 weeks showed decreased calreticulin levels. Changes in the levels of those different mediators were confirmed by Western blot and immunohistochemical analysis. Interestingly, alveolar macrophages isolated from lungs in the acute inflammation model displayed enhanced levels of GRP78. Moreover, intratracheal instillation of anti-GRP78 siRNA in allergen-exposed animals led to a decrease in eosinophilic inflammation and bronchial hyperresponsiveness. This study unveils new mediators of potential importance that are up- and down-regulated in asthma. Among up-regulated mediators, GRP-78 appears as a potential new therapeutic target worthy of further investigations.

Mass spectrometry-coupled techniques for viral-related disease biomarker identification

The advent of high-resolution mass spectrometers coupled with proteomic techniques has facilitated the discovery and characterization of novel viral proteins and the detection of virus-induced changes in the cellular proteome. These advances have enabled a more comprehensive characterization of viral interactions involved in infection and pathogenesis, and allowed the discovery of viral biomarkers. This article focuses on the role of mass spectrometry proteomic techniques to identify and characterize both prospective and verified viral biomarkers, and their implications on the diagnosis of disease.

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.

Biomarkers in COPD

Although there is increasing interest in using pulmonary biomarkers for a more complete and clinically relevant assessment of COPD and a plethora of biomarkers are becoming available, there is little information regarding their reproducibility and correlation with other outcome measurements in COPD. The lack of well-validated biomarkers that can be used for monitoring disease activity, predicting future clinical outcomes and the effect of therapeutic interventions highlights the factual need to identify new biomarkers in COPD. It is likely that, using what is called 'integrative functional informatics', which is a novel direction in the interfacing and integration of different technologies (genomics, proteomics, metabolomics and metabonomics, pharmacogenetics, and integrative approaches) for collection and analysis of data on biomarkers, we will be able to identify robust, reliable, and reproducible biomarkers in COPD.