Shotgun MS proteomic analysis of bronchoalveolar lavage fluid in normal subjects

We provide a review of proteomic techniques used to characterize the bronchoalveolar lavage fluid (BALF) proteome of normal healthy subjects. Bronchoalveolar lavage (BAL) is the most common technique for sampling the components of the alveolar space. The proteomic techniques used to study normal BALF include protein separation by 2DE, whereby proteins were identified by comparison to a reference gel as well as high pressure liquid chromatography (HPLC)-MS/MS, also known as shotgun proteomics. We summarize recent progress using shotgun MS technologies to define the normal BALF proteome. Surprisingly, we find that despite advances in shotgun proteomic technologies over the course of the last 10 years, which have resulted in greater numbers of proteins being identified, the functional landscape of normal BALF proteome was similarly described by all methods examined.     

Proteomic analysis of serum, plasma, and lymph for the identification of biomarkers

Probably no topic has generated more excitement in the world of proteomics than the search for biomarkers. This excitement has been generated by two realities: the constant need for better biomarkers that can be used for disease diagnosis and prognosis, and the recent developments in proteomic technologies that are capable of scanning the individual proteins within varying complex clinical samples. Ideally a biomarker would be assayable from a noninvasively collected sample, therefore, much of the focus in proteomics has been on the analysis of biofluids such as serum, plasma, urine, cerebrospinal fluid, lymph, etc. While the discovery of biomarkers has been elusive, there have been many advances made in the understanding of the proteome content of various biofluids, and in the technologies used for their analysis, that continues to point the research community toward new methods for achieving the ultimate goal of identifying novel disease-specific biomarkers. In this review, we will describe and discuss many of the proteomic approaches taken in an attempt to find novel biomarkers in serum, plasma, and lymph.     

Mass spectrometry-based proteomics of endoscopically collected pancreatic fluid in chronic pancreatitis research

MS-based investigation of pancreatic fluid enables the high-throughput identification of proteins present in the pancreatic secretome. Pancreatic fluid is a complex admixture of digestive, inflammatory, and other proteins secreted by the pancreas into the duodenum, and thus is amenable to MS-based proteomic analysis. Recent advances in endoscopic techniques, in particular the endoscopic pancreatic function test (ePFT), have improved the collection methodology of pancreatic fluid for proteomic analysis. Here, we provide an overview of MS-based proteomic techniques as applied to the study of pancreatic fluid. We address sample collection, protein extraction, MS sample preparation and analysis, and bioinformatic approaches, and summarize current MS-based investigations of pancreatic fluid. We then examine the limitations and the future potential of such technologies in the investigation of pancreatic disease. We conclude that pancreatic fluid represents a rich reservoir of potential biomarkers and that the study of the molecular mechanisms of chronic pancreatitis may benefit substantially from MS-based proteomics.     

Quantitative proteomics for identification of cancer biomarkers

Quantitative proteomics can be used for the identification of cancer biomarkers that could be used for early detection, serve as therapeutic targets, or monitor response to treatment. Several quantitative proteomics tools are currently available to study differential expression of proteins in samples ranging from cancer cell lines to tissues to body fluids. 2-DE, which was classically used for proteomic profiling, has been coupled to fluorescence labeling for differential proteomics. Isotope labeling methods such as stable isotope labeling with amino acids in cell culture (SILAC), isotope-coded affinity tagging (ICAT), isobaric tags for relative and absolute quantitation (iTRAQ), and (18) O labeling have all been used in quantitative approaches for identification of cancer biomarkers. In addition, heavy isotope labeled peptides can be used to obtain absolute quantitative data. Most recently, label-free methods for quantitative proteomics, which have the potential of replacing isotope-labeling strategies, are becoming popular. Other emerging technologies such as protein microarrays have the potential for providing additional opportunities for biomarker identification. This review highlights commonly used methods for quantitative proteomic analysis and their advantages and limitations for cancer biomarker analysis.     

High-resolution biomarker discovery: Moving from large-scale proteome profiling to quantitative validation of lead candidates

Diverse proteomic techniques based on protein MS have been introduced to systematically characterize protein perturbations associated with disease. Progress in clinical proteomics is essential for personalized medicine, wherein treatments will be tailored to individual needs based on patient stratification using noninvasive disease monitoring procedures to reveal the most appropriate therapeutic targets. However, breakthroughs await the successful development and application of a robust proteomic pipeline capable of identifying and rigorously assessing the relevance of multiple candidate proteins as informative diagnostic and prognostic indicators or suitable drug targets involved in a pathological process. While steady progress has been made toward more comprehensive proteome profiling, the emphasis must now shift from in depth screening of reference samples to stringent quantitative validation of selected lead candidates in a broader clinical context. Here, we present an overview of the emerging proteomic strategies for high-throughput protein detection focused primarily on targeted MS/MS as the basis for biomarker verification in large clinical cohorts. We discuss the conceptual promise and practical pitfalls of these methods in terms of achieving higher dynamic range, higher throughput, and more reliable quantification, highlighting research avenues that merit additional inquiry.     

Lysosomal proteomics and disease

A recent trend in proteomic studies has been to analyze macromolecular complexes such as subcellular organelles instead of complete cells or tissues. This "divide and conquer" approach circumvents some of the formidable problems associated with whole proteome analyses and allows focus on a subset of proteins that may be involved in a particular process or disease of interest. One organelle that has been the focus of considerable attention in proteomic studies is the lysosome, an acidic, membrane-delimited compartment that plays an essential role in the degradation and recycling of biological macromolecules. Lysosomal proteomics have been driven in part by the well-established involvement of this organelle in numerous human diseases, but also by the availability of approaches to selectively visualize and/or isolate subsets of lysosomal proteins. In terms of clinical application, proteomic studies of the lysosome have led to the identification of gene defects in three human hereditary diseases. This review summarizes past progress, current limitations and future directions in the field of lysosomal proteomics.     

Colorectal cancer proteomics, molecular characterization and biomarker discovery

Colorectal cancer (CRC) is a widespread disease, whose major genetic changes and mutations have been well characterized in the sporadic form. Much less is known at the protein and proteome level. Still, CRC has been the subject of multiple proteomic studies due to the urgent necessity of finding clinically relevant markers and to elucidate the molecular mechanisms underlying the progression of the disease. These proteomic approaches have been limited by different technical issues, mainly related with sensitivity and reproducibility. However, recent advances in proteomic techniques and MS systems have rekindled the quest for new biomarkers in CRC and an improved molecular characterization. In this review, we will discuss the application of different proteomic approaches to the identification of differentially expressed proteins in CRC. In particular, we will make a critical assessment about the use of 2-D DIGE, MS and protein microarray technologies, in their different formats, to identify up- or downregulated proteins and/or autoantibodies profiles that could be useful for CRC characterization and diagnosis. Despite a wide list of potential biomarkers, it is clear that more scientific efforts and technical advances are still needed to cover the range of low-abundant proteins, which may play a key role in CRC diagnostics and progression.     

Review of methods for determination of total protein and peptide concentration in biological samples

Clinical proteomics can be defined as the use of proteomic technologies to identify and measure biomarkers in fluids and tissues. The current work is intended to review various methods used for the determination of the total concentration of protein or peptide in fluids and tissues and the application of such methods to clinical proteomics. Specifically, this article considers the approaches to the measurement of total protein concentration, not the measurement of the concentration of a specific protein or group of proteins in a larger mixture of proteins. The necessity of understanding various concepts such as fit-for-use, quality-by-design, and other regulatory elements is discussed, as is the significance of using suitable standards for the protein quality of various samples.     

Application of proteomic technologies to discover and identify biomarkers for periodontal diseases in gingival crevicular fluid: A review

Periodontal disease is a bacterial infection that destroys the gingiva and surrounding tissues of the oral cavity. In recent years, studies have shown a definite association between periodontal disease and other inflammatory conditions of the body. High-throughput analysis of proteins has become possible with the development of MS technology. This breakthrough in proteome technology enables comparative studies of comprehensive protein expression and identification of protein. In case of periodontal disease, proteome analysis using 2DE, as well as gel-free methods, has been reported. As a fluid lying in close proximity to periodontal tissue, the gingival crevicular fluid (GCF) is the principal target in the search for biomarkers of periodontal disease, because its protein composition may reflect the disease pathophysiology. Biochemical marker analysis of GCF is effective for objective diagnosis in the early and advanced stages of periodontal disease. Increasing numbers of recent reports have provided evidence that the proteomic approach is a promising tool for the discovery and identification of biochemical markers of periodontal disease. This search is of continuing interest in the field of experimental and clinical periodontal disease research. In this article, we summarize recent comprehensive proteomic studies aimed at discovering and identifying biomarkers of periodontal disease in GCF.     

Proteomics and the lung: Analysis of bronchoalveolar lavage fluid

Our knowledge of the complex bronchoalveolar lavage fluid (BALF) proteome has increased significantly over the last decade; but still, there remain many aspects of the BALF proteome that need characterization. Current proteomic methodologies resolve proteins within limited dynamic ranges: thereby, being limited in their ability to examine important areas of the BALF proteome, such as low molecular weight, low abundance proteins. To ensure proper coverage of these proteins in the BALF proteome, a refined 2-DE standard operation protocol is presented, highlighting important issues in sample collection, sample preparation, and 2-D DIGE analysis. It is hoped that this will help advance the field of BALF proteomics, BALFomics, which has lagged behind similar biofluids such as plasma and serum.     

Multidimensional protein identification technology analysis highlights mitoxantrone‐induced expression modulations in the primary prostate cancer cell proteome

Chemotherapeutic agents as they are used today have limited effectiveness against prostate cancer, but may potentially be used in new combinations with more efficacious results. Mitoxantrone, used for palliation of prostate cancer, has recently been found by our group to improve the susceptibility of primary prostate cancer cells to killing through the Fas‐mediated death pathway. Here we used a shotgun proteomics approach to first profile the entire prostate cancer proteome and then identify specific factors involved in this mitoxantrone response. Peptides derived from primary prostate cancer cells treated with or without 100 nM mitoxantrone were analyzed by multidimensional protein identification technology (MudPIT). Strict limits and data filtering hierarchies were applied to identify proteins with high confidence. We identified 1498 proteins belonging to the prostate cancer proteome, 83 of which were significantly upregulated and 27 of which were markedly downregulated following mitoxantrone treatment. These proteins perform diverse functions, including ceramide production, tumour suppression, and oxidative reduction. Detailed proteomic analyses of prostate cancer cells and their response to mitoxantrone will further our understanding of its mechanisms of action. Identification of proteins influenced by treatment with mitoxantrone or other compounds may lead to the development of more effective drug combinations against prostate cancer.     

Exploration of the normal human bronchoalveolar lavage fluid proteome

We obtained insight into normal lung function by proteome analysis of bronchoalveolar lavage fluid (BALF) from six normal human subjects using a "Lyse-N-Go' shotgun proteomic protocol. Intra-sample variation was calculated using three different label-free methods, (i) protein sequence coverage; (ii) peptide spectral counts and (iii) peptide single-ion current areas (PICA), which generates protein expression data by summation of the area under the curve for a given peptide single-ion current trace and then adding values for all peptides from that same parent protein. PICA gave the least intra-subject variability and was used to calculate differences in protein expression between the six subjects. We observed an average threefold inter-sample variability, which affects analysis of changes in protein expression that occur in different diseases. We detected 167 unique proteins with >100 proteins detected in each of the six individual BAL samples, 42 of which were common to all six subjects. Gene ontology analysis demonstrated enrichment of several biological processes in the lung, reflecting its expected role in gas exchange and host defense as an immune organ. The same biological processes were enriched compared to either plasma or total genome proteome, suggesting an active enrichment of plasma proteins in the lung rather than passive capillary leak.     

The human synovial fluid proteome: A key factor in the pathology of joint disease

This review aims to summarise our knowledge to date on the protein complement of the synovial fluid (SF). The tissues, structure and pathophysiology of the synovial joint are briefly described. The salient features of the SF proteome, how it is composed and the influence of arthritic disease are highlighted and discussed. The concentrations of proteins that have been detected and quantified in SF are drawn together from the literature on osteoarthritis, rheumatoid arthritis and juvenile idiopathic arthritis. The measurements are plotted to give a perspective on the dynamic range of protein levels within the SF. Approaches to proteomic analysis of SF to date are discussed along with their findings. From the recent literature reviewed within, it is becoming increasingly clear that analysis of the SF proteome as a whole, could deliver the most valuable differential diagnostic fingerprints of a number of arthritic disorders. Further development of proteomic platforms could characterise prognostic profiles to improve the clinician's ability to resolve unremitting disease by existing and novel therapeutics.     

Reconstructing the pipeline by introducing multiplexed multiple reaction monitoring mass spectrometry for cancer biomarker verification: an NCI-CPTC initiative perspective

Proteomics holds great promise in personalized medicine for cancer in the post-genomic era. In the past decade, clinical proteomics has significantly evolved in terms of technology development, optimization and standardization, as well as in advanced bioinformatics data integration and analysis. Great strides have been made for characterizing a large number of proteins qualitatively and quantitatively in a proteome, including the use of sample fractionation, protein microarrays and MS. It is believed that differential proteomic analysis of high-quality clinical biospecimen (tissue and biofluids) can potentially reveal protein/peptide biomarkers responsible for cancer by means of their altered levels of expression and/or PTMs. Multiple reaction monitoring, a multiplexed platform using stable isotope dilution-MS with sensitivity and reproducibility approaching that of traditional ELISAs commonly used in the clinical setting, has emerged as a potentially promising technique for next-generation high-throughput protein biomarker measurements for diagnostics and therapeutics.     

Analysis of biofluids for biomarker research

While many of the developments made in high-throughput proteomics were originally applied to procaryotic and simple eucaryotic organisms, the analysis of biofluids became increasingly important as the prospect of using proteomics to discover novel biomarkers became realized. Biofluids have represented a unique challenge to proteomics as they are often present only in small amounts and, particularly in the cases of serum and plasma, can have protein concentration ranges that differ by ten orders of magnitude. While the discovery of authentic, clinically useful biomarkers in the proteomics era has been lacking, there have been a number of significant developments in the ability to more comprehensively characterize biofluid proteomes. The rapid pace of these developments suggest that the eventual discovery of clinically validate biomarkers using proteomic technologies still has a bright future.