Proteomics methods and applications for the practicing clinician

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.

Proteomic-based biomarker discovery for development of next generation diagnostics

In the post-genome age, proteomics is receiving significant attention because they provide an invaluable source of biological structures and functions at the protein level. The search for disease-specific biomarkers for diagnostic and/or therapeutic applications is one of the areas that proteomics is having a significant impact. Thus, the identification of a "good" biomarker enables a more accurate early diagnosis and prognosis of disease. Rapid advancements in mass spectrometry (MS) instrumentation, liquid chromatography MS (LCMS), protein microarray technology, and other protein profiling methodologies have a substantial expansion of our toolbox to identify disease-specific protein and peptide biomarkers. This review covers a selection of widely used proteomic technologies for biomarker discovery. In addition, we describe the most commonly used approaches for diagnosis based on proteomic biomarkers and further discuss trends and critical challenges during development of cost-effective rapid diagnostic tests and microfluidic diagnostic systems based on proteomic biomarkers.

Biomarker discovery in asthma and COPD by proteomic approaches

Asthma and chronic obstructive pulmonary disease (COPD) are multifactorial respiratory diseases, characterized by reversible and irreversible airway obstruction, respectively. Even if the primary causes of these diseases remain unknown, inflammation is a central feature that leads to progressive and permanent pulmonary tissue damage (airway remodeling) up to the total loss of lung function. Therefore, the elucidation of the inflammation mechanisms and the characterization of the biological pathways, involved in asthma and COPD pathogenesis, are relevant in finding new possible diagnostic/prognostic biomarkers and for the validation of new drug targets. In this context, current advances in proteomic approaches, especially those based on MS, provide new tools to facilitate the discovery-driven studies of new biomarkers in respiratory diseases and improve the clinical reliability of the next generation of biomarkers for these diseases consisting of multiple phenotypes. This review will report an overview of the current proteomic methods applied to the discovery of candidate biomarkers for asthma and COPD, giving a special emphasis to emerging MS-based techniques.

Significance of bioinformatics in research of chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is an inflammatory disease characterized by the progressive deterioration of pulmonary function and increasing airway obstruction, with high morality all over the world. The advent of high-throughput omics techniques provided an opportunity to gain insights into disease pathogenesis and process which contribute to the heterogeneity, and find target-specific and disease-specific therapies. As an interdispline, bioinformatics supplied vital information on integrative understanding of COPD. This review focused on application of bioinformatics in COPD study, including biomarkers searching and systems biology. We also presented the requirements and challenges in implementing bioinformatics to COPD research and interpreted these results as clinical physicians.

AllerML: markup language for allergens

Many concerns have been raised about the potential allergenicity of novel, recombinant proteins into food crops. Guidelines, proposed by WHO/FAO and EFSA, include the use of bioinformatics screening to assess the risk of potential allergenicity or cross-reactivities of all proteins introduced, for example, to improve nutritional value or promote crop resistance. However, there are no universally accepted standards that can be used to encode data on the biology of allergens to facilitate using data from multiple databases in this screening. Therefore, we developed AllerML a markup language for allergens to assist in the automated exchange of information between databases and in the integration of the bioinformatics tools that are used to investigate allergenicity and cross-reactivity. As proof of concept, AllerML was implemented using the Structural Database of Allergenic Proteins (SDAP; http://fermi.utmb.edu/SDAP/) database. General implementation of AllerML will promote automatic flow of validated data that will aid in allergy research and regulatory analysis.