Sequential depletion of human serum for the search of osteoarthritis biomarkers

ABSTRACT: BACKGROUND: The field of biomarker discovery, development and application has been the subject of intense interest and activity, especially with the recent emergence of new technologies, such as proteomics-based approaches. In proteomics, search for biomarkers in biological fluids such as human serum is a challenging issue, mainly due to the high dynamic range of proteins present in these types of samples. Methods for reducing the content of most highly abundant proteins have been developed, including immunodepletion or protein equalization. In this work, we report for the first time the combination of a chemical sequential depletion method based in two protein precipitations with acetonitrile and DTT, with a subsequent two-dimensional difference in-gel electrophoresis (2D-DIGE) analysis for the search of osteoarthritis (OA) biomarkers in human serum. The depletion method proposed is non-expensive, of easy implementation and allows fast sample throughput. RESULTS: Following this workflow, we have compared sample pools of human serum obtained from 20 OA patients and 20 healthy controls. The DIGE study led to the identification of 16 protein forms (corresponding to 14 different proteins) that were significantly (p < 0.05) altered in OA when compared to controls (8 increased and 7 decreased). Immunoblot analyses confirmed for the first time the increase of an isoform of Haptoglobin beta chain (HPT) in sera from OA patients. CONCLUSIONS: Altogether, these data demonstrate the utility of the proposed chemical sequential depletion for the analysis of sera in protein biomarker discovery approaches, exhibit the usefulness of quantitative 2D gel-based strategies for the characterization of disease-specific patterns of protein modifications, and also provide a list of OA biomarker candidates for validation.     

Quantitative proteomics suggests decrease in the secretogranin‐1 cerebrospinal fluid levels during the disease course of multiple sclerosis

Multiple sclerosis (MS) is a chronic inflammatory disease of the CNS with unknown cause. Proteins with different abundance in the cerebrospinal fluid (CSF) from relapsing‐remitting MS (RRMS) patients and neurological controls could give novel insight to the MS pathogenesis and be used to improve diagnosis, predict prognosis and disease course, and guide in therapy decisions. We combined iTRAQ labeling and Orbitrap mass spectrometry to discover proteins with different CSF abundance between six RRMS patients and 18 neurological disease controls. From 777 quantified proteins seven were selected as biomarker candidates, namely chitinase‐3‐like protein 1, secretogranin‐1 (Sg1), cerebellin‐1, neuroserpin, cell surface glycoprotein MUC18, testican‐2 and glutamate receptor 4. An independent sample set of 13 early‐MS patients, 13 RRMS patients and 13 neurological controls was used in a multiple reaction monitoring verification study. We found the intracellular calcium binding protein Sg1 to be increased in early‐MS patients compared to RRMS and neurological controls. Sg1 should be included in further studies to elucidate its role in the early phases of MS pathogenesis and its potential as a biomarker for this disease.     

Proteomic analysis of urinary exosomes from patients of early IgA nephropathy and thin basement membrane nephropathy

To identify biomarker candidates associated with early IgA nephropathy (IgAN) and thin basement membrane nephropathy (TBMN), the most common causes presenting isolated hematuria in childhood, a proteomic approach of urinary exosomes from early IgAN and TBMN patients was introduced. The proteomic results from the patients were compared with a normal group to understand the pathophysiological processes associated with these diseases at the protein level. The urinary exosomes, which reflect pathophysiological processes, collected from three groups of young adults (early IgAN, TBMN, and normal) were trypsin-digested using a gel-assisted protocol, and quantified by label-free LC-MS/MS, using an MS(E) mode. A total of 1877 urinary exosome proteins, including cytoplasmic, membrane, and vesicle trafficking proteins, were identified. Among the differentially expressed proteins, four proteins (aminopeptidase N, vasorin precursor, α-1-antitrypsin, and ceruloplasmin) were selected as biomarker candidates to differentiate early IgAN from TBMN. We confirmed the protein levels of the four biomarker candidates by semi-quantitative immunoblot analysis in urinary exosomes independently prepared from other patients, including older adult groups. Further clinical studies are needed to investigate the diagnostic and prognostic value of these urinary markers for early IgAN and TBMN. Taken together, this study showed the possibility of identifying biomarker candidates for human urinary diseases using urinary exosomes and might help to understand the pathophysiology of early IgAN and TBMN at the protein level.     

Evaluation of a pretreatment method for two-dimensional gel electrophoresis of synovial fluid using cartilage oligomeric matrix protein as a marker

Osteoarthritis (OA) is the most common rheumatic pathology. One of the major objectives of OA research is the development of early diagnostic strategies such as those using proteomic technology. Synovial fluid (SF) in OA patients is a potential source of biomarkers for OA. The efficient and reliable preparation of SF proteomes is a critical step towards biomarker discovery. In this study, we have optimized a pretreatment method for two-dimensional gel electrophoresis (2DE) separation of the SF proteome, by enriching low-abundance proteins and simultaneously removing hyaluronic acid, albumin, and IgG. SF samples pretreated using this optimized method were then evaluated by 1DE and 2DE separation followed by immunodetection of cartilage oligomeric matrix protein (COMP), a known OA biomarker, and by the identification of 3 proteins (apolipoprotein, haptoglobin precursor, and fibrinogen D fragment) that are related to joint diseases.     

iTRAQ-based proteomics reveals novel biomarkers of osteoarthritis

Abstract

Objective: We performed comprehensive proteomic analyses of articular cartilage by using the isobaric tags for relative and absolute quantitation (iTRAQ) method, and searched for candidate biomarkers for osteoarthritis (OA).

Methods: Articular cartilage was collected from patients with OA or femoral neck fracture for the control group. Molecular variations were detected by the iTRAQ method, and quantitative analyses were performed by western blot.

Results: Using the iTRAQ method, we identified 76 proteins with different expression levels in OA patients and the control group. Among these proteins, we selected LECT2 (leukocyte cell-derived chemotaxin-2), BAALC (brain and acute leukemia, cytoplasmic), and PRDX6 (peroxiredoxin-6), which had not been reported as biomarkers for OA.

Conclusions: Use of these proteins in combination with conventional OA biomarkers may better reflect the grade and prognosis of OA.     

Discovery of Colorectal Cancer Biomarker Candidates by Membrane Proteomic Analysis and Subsequent Verification using Selected Reaction Monitoring (SRM) and Tissue Microarray (TMA) Analysis

Recent advances in quantitative proteomic technology have enabled the large-scale validation of biomarkers. We here performed a quantitative proteomic analysis of membrane fractions from colorectal cancer tissue to discover biomarker candidates, and then extensively validated the candidate proteins identified. A total of 5566 proteins were identified in six tissue samples, each of which was obtained from polyps and cancer with and without metastasis. GO cellular component analysis predicted that 3087 of these proteins were membrane proteins, whereas TMHMM algorithm predicted that 1567 proteins had a transmembrane domain. Differences were observed in the expression of 159 membrane proteins and 55 extracellular proteins between polyps and cancer without metastasis, while the expression of 32 membrane proteins and 17 extracellular proteins differed between cancer with and without metastasis. A total of 105 of these biomarker candidates were quantitated using selected (or multiple) reaction monitoring (SRM/MRM) with stable synthetic isotope-labeled peptides as an internal control. The results obtained revealed differences in the expression of 69 of these proteins, and this was subsequently verified in an independent set of patient samples (polyps (n = 10), cancer without metastasis (n = 10), cancer with metastasis (n = 10)). Significant differences were observed in the expression of 44 of these proteins, including ITGA5, GPRC5A, PDGFRB, and TFRC, which have already been shown to be overexpressed in colorectal cancer, as well as proteins with unknown function, such as C8orf55. The expression of C8orf55 was also shown to be high not only in colorectal cancer, but also in several cancer tissues using a multicancer tissue microarray, which included 1150 cores from 14 cancer tissues. This is the largest verification study of biomarker candidate membrane proteins to date; our methods for biomarker discovery and subsequent validation using SRM/MRM will contribute to the identification of useful biomarker candidates for various cancers. Data are available via ProteomeXchange with identifier PXD000851.Recent advances in proteomic technology have contributed to the identification of biomarkers for various diseases. Improvements in LC-MS technology have led to an increase in the number of proteins that have been identified. In addition, a stable isotopic labeling method using isobaric tag for relative and absolute quantitation (iTRAQ)¹ and stable isotope labeling by amino acids in cell culture has enabled the quantitative analysis of multiple samples (1, 2). Therefore, a large number of proteins have already been identified as biomarker candidates; however, only a few of these have been used in practical applications because most have not yet progressed to the validation stage, in which potential biomarker candidates are quantified on a large scale. The validation of biomarker candidates is generally accomplished using Western blotting and enzyme-linked immunosorbent assays (ELISA) if specific and well-characterized antibodies for these candidates are available. However, highly specific antibodies are not currently available for most novel biomarker candidate proteins, and it takes a significant amount of time and money to obtain these antibodies and optimize ELISA assay systems for many candidates; therefore, another validation assay system needs to be developed. Selected (or multiple) reaction monitoring (SRM or MRM) was previously shown to be a potentially effective method for the validation of biomarker candidates (3–5). The SRM/MRM assay can measure multiple targets at high sensitivity and throughput without antibodies; hence, it is useful for initial quantitative evaluations and the large-scale validation of biomarker candidates, which defines validation of hundreds of biomarker candidate proteins simultaneously.In addition to these technical improvements, the fractionation process also plays an important role in proteome analysis for biomarker discovery. This procedure very effectively analyzes the proteomes of specific cellular compartments or organelles in detail, which reduces sample complexity. The preparation of a membrane fraction was previously shown to be useful for identifying membrane proteins that are generally expressed at relatively low levels. Membrane proteins play critical roles in many biological functions, such as signal transduction, cell-cell interactions, and ion transport, account for ∼38% of all proteins encoded by the mammalian genome and more than one-third of biomarker candidates, and are also potential targets for drug therapy (6, 7). Therefore, membrane proteome analysis is important for biomarker discovery. However, difficulties have been associated with extracting and solubilizing membrane proteins and subsequent protease digestion. Many procedures have consequently been developed to improve the solubilization and digestion of membrane proteins (8–11), and a protocol using phase transfer surfactant (PTS) was shown to be suitable for membrane proteomics using LC-MS/MS (12, 13).The selection of a control group for comparisons is also important for identifying potential biomarkers. Tissue samples from cancer patients have been used in many studies to discover biomarker candidates by proteomic analysis. Previous studies, including our own, attempted to compare cancer tissues with matched normal tissue (14–17). However, marked differences have been reported in the histology, genetics, and proteomics of normal and cancer tissues, and many biomarker candidates have been identified, by making it difficult to narrow down more reliable candidates for further validation. Lazebnik recently emphasized that the features of malignant, but not benign tumors could be used as a hallmark of cancer (18), and also that premalignant lesions were more appropriate controls for cancer tissue than normal tissue for the identification of biomarker candidates involved in cancer progression. Moreover, comparisons of cancer with and without metastasis may also assist in the discovery of biomarker candidates involved in cancer metastasis. Therefore, the identification of biomarker candidates that can be used to diagnose and determine the prognosis of cancer should become more effective by comparing cancer tissues at different stages, including benign tumors.We performed a shotgun proteomic analysis of membrane fractions prepared from colorectal cancer tissue and benign polyps in the present study to identify biomarker candidates for the diagnosis and treatment of cancer. We identified a large number of biomarker candidate proteins associated with the progression of colon cancer by using membrane protein extraction with PTS followed by iTRAQ labeling. SRM/MRM confirmed the altered expression of these biomarker candidates, and these results were further verified using an independent set of tissue samples. A protein with uncharacterized function, C8orf55, was also validated with a tissue microarray that included various types of cancers.     

Identification of novel biomarker candidates for immunohistochemical diagnosis to distinguish low‐grade chondrosarcoma from enchondroma

Chondrosarcoma is the third most common primary bone cancer, requiring surgical resection. However, differentiation of low‐grade chondrosarcoma (grade 1) from enchondroma that is benign and only requires regular follow‐up is one of the most frequent diagnostic dilemmas facing orthopedic oncologists in clinical management. Although multiple techniques are applied to make the distinction, immunohistochemistry is an important ancillary technique, especially when a histopathological stain of specimen must be obtained in order to guarantee an accurate confirmation. Currently, no adequate immunohistochemical diagnostic protein biomarkers are available to distinguish low‐grade chondrosarcoma from enchondroma. To discover novel protein biomarker candidates, an LC‐MS/MS approach was applied to directly compare formalin‐fixed, paraffin‐embedded low‐grade chondrosarcoma with enchondroma tissue samples. The proteomics analysis revealed 17 protein biomarker candidates. A principle was developed to prioritize the candidates using category and ranking. An algorithm, prioritization index of biomarker candidates for immunohistochemistry on tissue specimens, was developed to rank the candidates inside each category. Using the proteomics data and bioinformatics results, the prioritization index of biomarker candidates for immunohistochemistry on tissue revealed periostin as a top candidate. Immunohistochemical staining of periostin in 23 low‐grade chondrosarcoma and 31 enchondroma tissue specimens disclosed 87% specificity and 70% sensitivity.     

Optimizing a Proteomics Platform for Urine Biomarker Discovery

Biomarker discovery approaches in urine have been hindered by concerns for reproducibility and inadequate standardization of proteomics protocols. In this study, we describe an optimized quantitative proteomics strategy for urine biomarker discovery, which is applicable to fresh or long frozen samples. We used urine from healthy controls to standardize iTRAQ (isobaric tags for relative and absolute quantitation) for variation induced by protease inhibitors, starting protein and iTRAQ label quantities, protein extraction methods, and depletion of albumin and immunoglobulin G (IgG). We observed the following: (a) Absence of protease inhibitors did not affect the number or identity of the high confidence proteins. (b) Use of less than 20 μg of protein per sample led to a significant drop in the number of identified proteins. (c) Use of as little as a quarter unit of an iTRAQ label did not affect the number or identity of the identified proteins. (d) Protein extraction by methanol precipitation led to the highest protein yields and the most reproducible spectra. (e) Depletion of albumin and IgG did not increase the number of identified proteins or deepen the proteome coverage. Applying this optimized protocol to four pairs of long frozen urine samples from diabetic Pima Indians with or without nephropathy, we observed patterns suggesting segregation of cases and controls by iTRAQ spectra. We also identified several previously reported candidate biomarkers that showed trends toward differential expression, albeit not reaching statistical significance in this small sample set.With ongoing advances in mass spectrometry (MS) and proteomics technology, proteomics analysis is progressively occupying a central position in biomarker discovery platforms. Biofluids such as urine and blood are the preferred media for proteomics analysis because of their ease of collection and extensive history of use in clinical laboratory practice. Urine, in particular, is an information-rich fluid that can be collected non-invasively and in large quantities. Many urine proteins are produced or shed in the kidney and urogenital tract (1), making urine a promising proximal source of biomarkers for diseases affecting these structures.However, proteomics-based biomarker discovery in urine faces multiple challenges. Urine proteomics is complicated by low urine protein concentration, variations in pH, and high concentrations of salts and urea or other urine components that interfere with sample processing. The urine proteome can also change with individual variables such as hydration, diurnal change, diet, and physical activity as well as variation in sample collection, processing, and storage. In addition, urine proteomics shares the usual challenges of biomarker discovery in other biofluids such as throughput, cost, and the need for a reproducible and quantitative work flow.Isotopic or isobaric labeling methods to reduce variation, increase throughput, and enable quantitative analysis have been developed to address some of these challenges. One such method, isobaric tags for relative and absolute quantitation (iTRAQ)¹ (2), combines relative and absolute peptide quantification with multiplexing ability to enable an increased throughput as well as simultaneous comparison of up to eight samples within one experimental run. Variations induced by urine sample processing have been systematically evaluated for proteomics analyses using two-dimensional gel electrophoresis (3–6), differential gel electrophoresis (7), and liquid chromatography-coupled mass spectrometry (LC-MS) (5, 8, 9). However, no systematic analyses of urine sample collection and processing have been reported for iTRAQ.Before utilizing iTRAQ-based quantitative proteomics for urine biomarker discovery, we evaluated the impact of variation in several processing steps (addition of protease inhibitors, the starting protein quantities, quantity of the iTRAQ label, protein extraction methods, and depletion of abundant proteins) on iTRAQ protein identification and quantitation. Applying this optimized biomarker discovery protocol to small quantities of long frozen urine samples from the Pima longitudinal study of diabetic nephropathy, we observed patterns suggestive of segregation of cases and controls by iTRAQ spectra. We also observed trends toward differential expression in several proteins that had been identified as putative biomarkers in previous studies. However, given the small sample size, none of these proteins retained statistical significance after multiple testing correction.     

Quantitative proteomics analysis reveals that proteins differentially expressed in chronic pancreatitis are also frequently involved in pancreatic cancer

The effective treatment of pancreatic cancer relies on the diagnosis of the disease at an early stage, a difficult challenge. One major obstacle in the development of diagnostic biomarkers of early pancreatic cancer has been the dual expression of potential biomarkers in both chronic pancreatitis and cancer. To better understand the limitations of potential protein biomarkers, we used ICAT technology and tandem mass spectrometry-based proteomics to systematically study protein expression in chronic pancreatitis. Among the 116 differentially expressed proteins identified in chronic pancreatitis, most biological processes were responses to wounding and inflammation, a finding consistent with the underlining inflammation and tissue repair associated with chronic pancreatitis. Furthermore 40% of the differentially expressed proteins identified in chronic pancreatitis have been implicated previously in pancreatic cancer, suggesting some commonality in protein expression between these two diseases. Biological network analysis further identified c-MYC as a common prominent regulatory protein in pancreatic cancer and chronic pancreatitis. Lastly five proteins were selected for validation by Western blot and immunohistochemistry. Annexin A2 and insulin-like growth factor-binding protein 2 were overexpressed in cancer but not in chronic pancreatitis, making them promising biomarker candidates for pancreatic cancer. In addition, our study validated that cathepsin D, integrin beta1, and plasminogen were overexpressed in both pancreatic cancer and chronic pancreatitis. The positive involvement of these proteins in chronic pancreatitis and pancreatic cancer will potentially lower the specificity of these proteins as biomarker candidates for pancreatic cancer. Altogether our study provides some insights into the molecular events in chronic pancreatitis that may lead to diverse strategies for diagnosis and treatment of these diseases.     

Proteomic comparison of colorectal tumours and non-neoplastic mucosa from paired patient samples using iTRAQ mass spectrometry

Quantitative mass spectrometry using iTRAQ was used to identify differentially expressed proteins from 16 colorectal cancer (CRC) tumours compared to patient-paired adjacent normal mucosa. Over 1400 proteins were identified and quantitated, with 118 determined as differentially expressed by >1.3-fold, with false discovery rate < 0.05. Gene Ontology analysis indicated that proteins with increased expression levels in CRC tumours include those associated with glycolysis, calcium binding, and protease inhibition. Proteins with reduced levels in CRC tumours were associated with loss of ATP production through: (i) reduced β-oxidation of fatty acids, (ii) reduced NADH production by the tricarboxylic acid cycle and (iii) decreased oxidative phosphorylation activity. Additionally, biosyntheses of glycosaminoglycans and proteoglycans were significantly reduced in tumour samples. Validation experiments using immunoblotting and immunohistochemistry (IHC) showed strong concordance with iTRAQ data suggesting that this workflow is suitable for identifying biomarker candidates. We discuss the uses and challenges of this approach to generate biomarker leads for patient prognostication.     

Urinary proteome alterations in HER2 enriched breast cancer revealed by multipronged quantitative proteomics

Globally, breast cancer is the second most common cancer among women. Although biomarker discoveries through various proteomic approaches of tissue and serum samples have been studied in breast cancer, urinary proteome alterations in breast cancer are least studied. Urine being a noninvasive biofluid and a significant source of proteins, it has the potential in early diagnosis of breast cancer. This study used complementary quantitative gel‐based and gel‐free proteomic approaches to find a panel of urinary protein markers that could discriminate HER2 enriched (HE) subtype breast cancer from the healthy controls. A total of 183 differentially expressed proteins were identified using three complementary approaches, namely 2D‐DIGE, iTRAQ, and sequential window acquisition of all theoretical mass spectra. The differentially expressed proteins were subjected to various bioinformatics analyses for deciphering the biological context of these proteins using protein analysis through evolutionary relationships, database for annotation, visualization and integrated discovery, and STRING. Multivariate statistical analysis was undertaken to identify the set of most significant proteins, which could discriminate HE breast cancer from healthy controls. Immunoblotting and MRM‐based validation in a separate cohort testified a panel of 21 proteins such as zinc‐alpha2‐glycoprotein, A2GL, retinol‐binding protein 4, annexin A1, SAP3, SRC8, gelsolin, kininogen 1, CO9, clusterin, ceruloplasmin, and α1‐antitrypsin could be a panel of candidate markers that could discriminate HE breast cancer from healthy controls.     

Maternal serum-derived exosomal lactoferrin as a marker in detecting and predicting ventricular septal defect in fetuses

Among different types of congenital heart diseases, ventricular septal defect is the most frequently diagnosed type and is frequently missed in early prenatal screening programs. Herein, we explored the role of maternal serum-derived exosomes in detecting and predicting ventricular septal defect in fetuses in the early stage of pregnancy. A total of 104 pregnant women consisting of 52 ventricular septal defect cases and 52 healthy controls were recruited. TMT/iTRAQ proteomic analysis uncovered 15 maternal serum exosomal proteins, which showed differential expression between ventricular septal defect and control groups. Among these, four down-regulated proteins, lactoferrin, SBSN, DCD, and MBD3, were validated by Western blot. The protein lactoferrin was additionally verified by ELISA which was able to distinguish ventricular septal defects from controls with area under the ROC curve (AUC) 0.804 (p < 0.001). Our findings reveal that lactoferrin in maternal serum-derived exosomes may be a potential biomarker for non-invasive prenatal diagnosis of fetal ventricular septal defects.     

Salivary and serum procalcitonin and C-reactive protein as biomarkers of periodontitis in United States veterans with osteoarthritis or rheumatoid arthritis

Serum procalcitonin (ProCT) is elevated in response to bacterial infections, whereas high sensitivity C-reactive protein (hsCRP) is a nonspecific inflammatory marker that is increased by excess adipose tissue. We examined the efficacy of ProCT and hsCRP as biomarkers of periodontitis in the saliva and serum of patients with arthritis, which is characterized by variable levels of systemic inflammation that potentially can confound the interpretation of inflammatory biomarkers. Blood and unstimulated whole saliva were collected from 33 patients with rheumatoid arthritis (RA) and 50 with osteoarthritis (OA). Periodontal status was assessed by full mouth examination and patients were categorized as having no/mild, moderate or severe periodontitis by standard parameters. Salivary and serum ProCT and hsCRP concentrations were compared. BMI, diabetes, anti-inflammatory medications and smoking status were ascertained from the patient records. Differences between OA and RA in proportionate numbers of patients were compared for race, gender, diabetes, adiposity and smoking status. Serum ProCT was significantly higher in arthritis patients with moderate to severe and severe periodontitis compared with no/mild periodontitis patients. There were no significant differences in salivary ProCT or salivary or serum hsCRP in RA patients related to periodontitis category. Most of the OA and RA patients were middle aged or older, 28.9% were diabetic, 78.3% were overweight or obese, and slightly more than half were either current or past smokers. The OA and RA groups differed by race, but not gender; blacks and males were predominant in both groups. The OA and RA groups did not differ in terms of controlled or uncontrolled diabetes, smoking status or BMI. The RA patients had been prescribed more anti-inflammatory medication than the OA patients. Our results demonstrate that circulating ProCT is a more discriminative biomarker for periodontitis than serum hsCRP in patients with underlying arthritis. Any elevation in salivary and serum hsCRP due to periodontitis apparently was overshadowed by differences among these patients in factors that influence CRP, such as the extent of inflammation between RA and OA, the extent of adipose tissue, the use of anti- inflammatory medications and smoking status. Although our study showed no differences in salivary ProCT related to severity of periodontitis, this biomarker also may be useful with further refinement.     

Amine-reactive isobaric tagging reagents: requirements for absolute quantification of proteins and peptides

Amine-reactive isobaric tagging reagents such as iTRAQ (isobaric tags for relative and absolute quantitation) have recently become increasing popular for relative protein quantification, cell expression profiling, and biomarker discovery. This is due mainly to the possibility of simultaneously identifying and quantifying multiple samples. The principles of iTRAQ may also be applied to absolute protein quantification with the use of synthetic peptides as standards. The prerequisites that must be fulfilled to perform absolute quantification of proteins by iTRAQ have been investigated and are described here. Three samples of somatropin were quantified using iTRAQ and synthetic peptides as standards, corresponding to a portion of the protein sequence. The results were compared with those obtained by quantification of the same protein solutions using double exact matching isotope dilution mass spectrometry (IDMS). To obtain reliable results, the appropriate standard peptides needed to be selected carefully and enzymatic digestion needed to be optimized to ensure complete release of the peptides from the protein. The kinetics and efficiency of the iTRAQ derivatization reaction of the standard peptides and digested proteins with isobaric tagging reagents were studied using a mixture of seven synthetic peptides and their corresponding labeled peptides. The implications of incomplete derivatization are also presented.     

Prevalidation of potential protein biomarkers in toxicology using iTRAQ reagent technology

Today, toxicoproteomics still relies mainly on 2-DE followed by MS for detection and identification of proteins, which might characterize a certain state of disease, indicate toxicity or even predict carcinogenicity. We utilized the classical 2-DE/MS approach for the evaluation of early protein biomarkers which are predictive for chemically induced hepatocarcinogenesis in rats. We were able to identify statistically significantly deregulated proteins in N-nitrosomorpholine exposed rat liver tissue. Based on literature data, biological relevance in the early molecular process of hepatocarcinogenicity could be suggested for most of these potential biomarkers. However, in order to ensure reliable results and to create the prerequisites necessary for integration in routine toxicology studies in the future, these protein expression patterns need to be prevalidated using independent technology platforms. In the current study, we evaluated the usefulness of iTRAQ reagent technology (Applied Biosystems, Framingham, USA), a recently introduced MS-based protein quantitation method, for verification of the 2-DE/MS biomarkers. In summary, the regulation of 26 2-DE/MS derived protein biomarkers could be verified. Proteins like HSP 90-beta, annexin A5, ketohexokinase, N-hydroxyarylamine sulfotransferase, ornithine aminotransferase, and adenosine kinase showed highly comparable fold changes using both proteomic quantitation strategies. In addition, iTRAQ analysis delivered further potential biomarkers with biological relevance to the processes of hepatocarcinogenicity: e.g. placental form of glutathione S-transferase (GST-P), carbonic anhydrase, and aflatoxin B1 aldehyde reductase. Our results show both the usefulness of iTRAQ reagent technology for biomarker prevalidation as well as for identification of further potential marker proteins, which are indicative for liver hepatocarcinogenicity.     

Strategy for SRM-based Verification of Biomarker Candidates Discovered by iTRAQ Method in Limited Breast Cancer Tissue Samples

Since LC-MS-based quantitative proteomics has become increasingly applied to a wide range of biological applications over the past decade, numerous studies have performed relative and/or absolute abundance determinations across large sets of proteins. In this study, we discovered prognostic biomarker candidates from limited breast cancer tissue samples using discovery-through-verification strategy combining iTRAQ method followed by selected reaction monitoring/multiple reaction monitoring analysis (SRM/MRM). We identified and quantified 5122 proteins with high confidence in 18 patient tissue samples (pooled high-risk (n = 9) or low-risk (n = 9)). A total of 2480 proteins (48.4%) of them were annotated as membrane proteins, 16.1% were plasma membrane and 6.6% were extracellular space proteins by Gene Ontology analysis. Forty-nine proteins with >2-fold differences in two groups were chosen for further analysis and verified in 16 individual tissue samples (high-risk (n = 9) or low-risk (n = 7)) using SRM/MRM. Twenty-three proteins were differentially expressed among two groups of which MFAP4 and GP2 were further confirmed by Western blotting in 17 tissue samples (high-risk (n = 9) or low-risk (n = 8)) and Immunohistochemistry (IHC) in 24 tissue samples (high-risk (n = 12) or low-risk (n = 12)). These results indicate that the combination of iTRAQ and SRM/MRM proteomics will be a powerful tool for identification and verification of candidate protein biomarkers.     

Proteomics Profiling of Human Synovial Fluid Suggests Increased Protein Interplay in Early-Osteoarthritis (OA) That Is Lost in Late-Stage OA

The underlying molecular mechanisms in osteoarthritis (OA) development are largely unknown. This study explores the proteome and the pairwise interplay of proteins in synovial fluid from patients with late-stage knee OA (arthroplasty), early knee OA (arthroscopy due to degenerative meniscal tear), and from deceased controls without knee OA. Synovial fluid samples were analyzed using state-of-the-art mass spectrometry with data-independent acquisition. The differential expression of the proteins detected was clustered and evaluated with data mining strategies and a multilevel model. Group-specific slopes of associations were estimated between expressions of each pair of identified proteins to assess the co-expression (i.e., interplay) between the proteins in each group. More proteins were increased in early-OA versus controls than late-stage OA versus controls. For most of these proteins, the fold changes between late-stage OA versus controls and early-stage OA versus controls were remarkably similar suggesting potential involvement in the OA process. Further, for the first time, this study illustrated distinct patterns in protein co-expression suggesting that the interplay between the protein machinery is increased in early-OA and lost in late-stage OA. Further efforts should focus on earlier stages of the disease than previously considered.