Development of quantitative plasma N-glycoproteomics using label-free 2-D LC-MALDI MS and its applicability for biomarker discovery in hepatocellular carcinoma

There has been rapid progress in the development of clinical proteomic methodologies with improvements in mass spectrometric technologies and bioinformatics, leading to many new methodologies for biomarker discovery from human plasma. However, it is not easy to find new biomarkers because of the wide dynamic range of plasma proteins and the need for their quantification. Here, we report a new methodology for relative quantitative proteomic analysis combining large-scale glycoproteomics with label-free 2-D LC-MALDI MS. In this method, enrichment of glycopeptides using hydrazide resin enables focusing on plasma proteins with lower abundance corresponding to the tissue leakage region. On quantitative analysis, signal intensities by 2-D LC-MALDI MS were normalized using a peptide internal control, and the values linked to LC data were treated with DeView? software. Our proteomic method revealed that the quantitative dynamic ranged from 102 to 10? pg/mL of plasma proteins with good reproducibility, and the limit of detection was of the order of a few ng/mL of proteins in biological samples. To evaluate the applicability of our method for biomarker discovery, we performed a feasibility study using plasma samples from patients with hepatocellular carcinoma, and identified biomarker candidates, including ceruloplasmin, alpha-1 antichymotrypsin, and multimerin-1.     

A quantitative proteomic approach to prion disease biomarker research: delving into the glycoproteome

Mass spectrometry (MS) -- based proteomic approaches have evolved as powerful tools for the discovery of biomarkers. However, the identification of potential protein biomarkers from biofluid samples is challenging because of the limited dynamic range of detection. Currently there is a lack of sensitive and reliable premortem diagnostic test for prion diseases. Here, we describe the use of a combined MS-based approach for biomarker discovery in prion diseases from mouse plasma samples. To overcome the limited dynamic range of detection and sample complexity of plasma samples, we used lectin affinity chromatography and multidimensional separations to enrich and isolate glycoproteins at low abundance. Relative quantitation of a panel of proteins was obtained by a combination of isotopic labeling and validated by spectral counting. Overall 708 proteins were identified, 53 of which showed more than 2-fold increase in concentration whereas 58 exhibited more than 2-fold decrease. A few of the potential candidate markers were previously associated with prion or other neurodegenerative diseases.     

Enhanced detection of low abundance human plasma proteins using a tandem IgY12-SuperMix immunoaffinity separation strategy

The enormous dynamic range of human bodily fluid proteomes poses a significant challenge for current MS-based proteomics technologies as it makes it especially difficult to detect low abundance proteins in human biofluids such as blood plasma, which is an essential aspect for successful biomarker discovery efforts. Here we present a novel tandem IgY12-SuperMix immunoaffinity separation system for enhanced detection of low abundance proteins in human plasma. The tandem IgY12-SuperMix system separates approximately 60 abundant proteins from the low abundance proteins in plasma, allowing for significant enrichment of low abundance plasma proteins in the SuperMix flow-through fraction. High reproducibility of the tandem separations was observed in terms of both sample processing recovery and LC-MS/MS identification results based on spectral count data. The ability to quantitatively measure differential protein abundances following application of the tandem separations was demonstrated by spiking six non-human standard proteins at three different levels into plasma. A side-by-side comparison between the SuperMix flow-through and IgY12 flow-through samples analyzed by both one- and two-dimensional LC-MS/MS revealed a 60-80% increase in proteome coverage as a result of the SuperMix separations, suggesting significantly enhanced detection of low abundance proteins. A total of 695 plasma proteins were confidently identified in a single analysis (with a minimum of two peptides per protein) by coupling the tandem separation strategy with two-dimensional LC-MS/MS, including 42 proteins with reported normal concentrations of approximately 100 pg/ml to 100 ng/ml. The concentrations of two selected proteins, macrophage colony-stimulating factor 1 and matrix metalloproteinase-8, were independently validated by ELISA as 202 pg/ml and 12.4 ng/ml, respectively. Evaluation of binding efficiency revealed that 45 medium abundance proteins were efficiently captured by the SuperMix column with >90% retention. Taken together, these results illustrate the potential broad utilities of this tandem IgY12-SuperMix strategy for proteomics applications involving human biofluids where effectively addressing the dynamic range challenge of the specimen is imperative.     

Low abundance protein enrichment for discovery of candidate plasma protein biomarkers for early detection of breast cancer

Molecular biomarkers of early stage breast cancer may improve the sensitivity and specificity of diagnosis. Plasma biomarkers have additional value in that they can be monitored with minimal invasiveness. Plasma biomarker discovery by genome-wide proteomic methods is impeded by the wide dynamic range of protein abundance and the heterogeneity of protein expression in healthy and disease populations which requires the analysis of a large number of samples. We addressed these issues through the development of a novel protocol that couples a combinatorial peptide ligand library protein enrichment strategy with isobaric label-based 2D LC-MS/MS for the identification of candidate biomarkers in high throughput. Plasma was collected from patients with stage I breast cancer or benign breast lesions. Low abundance proteins were enriched using a bead-based combinatorial library of hexapeptides. This resulted in the identification of 397 proteins, 22% of which are novel plasma proteins. Twenty-three differentially expressed plasma proteins were identified, demonstrating the effectiveness of the described protocol and defining a set of candidate biomarkers to be validated in independent samples. This work can be used as the basis for the design of properly powered investigations of plasma protein expression for biomarker discovery in larger cohorts of patients with complex disease.     

Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer

Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery. To minimize biological variation and facilitate testing of proteomic approaches, we employed a mouse model of breast cancer. Specifically, we performed LC-MS/MS of tumor and normal mammary tissue from a conditional HER2/Neu-driven mouse model of breast cancer, identifying 6758 peptides representing >700 proteins. We developed a novel statistical approach (SASPECT) for prioritizing proteins differentially represented in LC-MS/MS datasets and identified proteins over- or under-represented in tumors. Using a combination of antibody-based approaches and multiple reaction monitoring-mass spectrometry (MRM-MS), we confirmed the overproduction of multiple proteins at the tissue level, identified fibulin-2 as a plasma biomarker, and extensively characterized osteopontin as a plasma biomarker capable of early disease detection in the mouse. Our results show that a staged pipeline employing shotgun-based comparative proteomics for biomarker discovery and multiple reaction monitoring for confirmation of biomarker candidates is capable of finding novel tissue and plasma biomarkers in a mouse model of breast cancer. Furthermore, the approach can be extended to find biomarkers relevant to human disease.     

A pipeline that integrates the discovery and verification of plasma protein biomarkers reveals candidate markers for cardiovascular disease

We developed a pipeline to integrate the proteomic technologies used from the discovery to the verification stages of plasma biomarker identification and applied it to identify early biomarkers of cardiac injury from the blood of patients undergoing a therapeutic, planned myocardial infarction (PMI) for treatment of hypertrophic cardiomyopathy. Sampling of blood directly from patient hearts before, during and after controlled myocardial injury ensured enrichment for candidate biomarkers and allowed patients to serve as their own biological controls. LC-MS/MS analyses detected 121 highly differentially expressed proteins, including previously credentialed markers of cardiovascular disease and >100 novel candidate biomarkers for myocardial infarction (MI). Accurate inclusion mass screening (AIMS) qualified a subset of the candidates based on highly specific, targeted detection in peripheral plasma, including some markers unlikely to have been identified without this step. Analyses of peripheral plasma from controls and patients with PMI or spontaneous MI by quantitative multiple reaction monitoring mass spectrometry or immunoassays suggest that the candidate biomarkers may be specific to MI. This study demonstrates that modern proteomic technologies, when coherently integrated, can yield novel cardiovascular biomarkers meriting further evaluation in large, heterogeneous cohorts.     

Advancing the sensitivity of selected reaction monitoring-based targeted quantitative proteomics

Selected reaction monitoring (SRM) - also known as multiple reaction monitoring (MRM) - has emerged as a promising high-throughput targeted protein quantification technology for candidate biomarker verification and systems biology applications. A major bottleneck for current SRM technology, however, is insufficient sensitivity for, e.g. detecting low-abundance biomarkers likely present at the low ng/mL to pg/mL range in human blood plasma or serum, or extremely low-abundance signaling proteins in cells or tissues. Herein, we review recent advances in methods and technologies, including front-end immunoaffinity depletion, fractionation, selective enrichment of target proteins/peptides including posttranslational modifications, as well as advances in MS instrumentation which have significantly enhanced the overall sensitivity of SRM assays and enabled the detection of low-abundance proteins at low- to sub-ng/mL level in human blood plasma or serum. General perspectives on the potential of achieving sufficient sensitivity for detection of pg/mL level proteins in plasma are also discussed.     

High dynamic range characterization of the trauma patient plasma proteome

Although human plasma represents an attractive sample for disease biomarker discovery, the extreme complexity and large dynamic range in protein concentrations present significant challenges for characterization, candidate biomarker discovery, and validation. Herein we describe a strategy that combines immunoaffinity subtraction and subsequent chemical fractionation based on cysteinyl peptide and N-glycopeptide captures with two-dimensional LC-MS/MS to increase the dynamic range of analysis for plasma. Application of this "divide-and-conquer" strategy to trauma patient plasma significantly improved the overall dynamic range of detection and resulted in confident identification of 22,267 unique peptides from four different peptide populations (cysteinyl peptides, non-cysteinyl peptides, N-glycopeptides, and non-glycopeptides) that covered 3,654 different proteins with 1,494 proteins identified by multiple peptides. Numerous low abundance proteins were identified, exemplified by 78 "classic" cytokines and cytokine receptors and by 136 human cell differentiation molecules. Additionally a total of 2,910 different N-glycopeptides that correspond to 662 N-glycoproteins and 1,553 N-glycosylation sites were identified. A panel of the proteins identified in this study is known to be involved in inflammation and immune responses. This study established an extensive reference protein database for trauma patients that provides a foundation for future high throughput quantitative plasma proteomic studies designed to elucidate the mechanisms that underlie systemic inflammatory responses.     

Combination of abundant protein depletion and multi-lectin affinity chromatography (M-LAC) for plasma protein biomarker discovery

We report on the development of a robust and relatively high-throughput method for in-depth proteomic analysis of human plasma suitable for biomarker discovery. The method consists of depletion of albumin and IgG and multi-lectin affinity chromatography (M-LAC), followed by nanoLC-MS/MS analysis of digested proteins and label-free comparative quantitation of proteins. The performance of the method is monitored by multiple quality control points to ensure reproducibility of the analysis. The method identifies proteins that are reported to be present in normal plasma at concentrations of 10-100 ng/mL and that may be of particular interest when studying a variety of disease conditions. Numerous tissue leakage proteins of potentially even lower concentrations are also identified. When the method was used in a study to identify potential biomarkers of psoriasis, the differential abundance of proteins present at low mug/mL level was quantitated and later verified by ELISA measurements.     

Multiplexed MRM‐based quantitation of candidate cancer biomarker proteins in undepleted and non‐enriched human plasma

An emerging approach for multiplexed targeted proteomics involves bottom‐up LC‐MRM‐MS, with stable isotope‐labeled internal standard peptides, to accurately quantitate panels of putative disease biomarkers in biofluids. In this paper, we used this approach to quantitate 27 candidate cancer‐biomarker proteins in human plasma that had not been treated by immunoaffinity depletion or enrichment techniques. These proteins have been reported as biomarkers for a variety of human cancers, from laryngeal to ovarian, with breast cancer having the highest correlation. We implemented measures to minimize the analytical variability, improve the quantitative accuracy, and increase the feasibility and applicability of this MRM‐based method. We have demonstrated excellent retention time reproducibility (median interday CV: 0.08%) and signal stability (median interday CV: 4.5% for the analytical platform and 6.1% for the bottom‐up workflow) for the 27 biomarker proteins (represented by 57 interference‐free peptides). The linear dynamic range for the MRM assays spanned four orders‐of‐magnitude, with 25 assays covering a 10³–10⁴ range in protein concentration. The lowest abundance quantifiable protein in our biomarker panel was insulin‐like growth factor 1 (calculated concentration: 127 ng/mL). Overall, the analytical performance of this assay demonstrates high robustness and sensitivity, and provides the necessary throughput and multiplexing capabilities required to verify and validate cancer‐associated protein biomarker panels in human plasma, prior to clinical use.     

Proteomic expression analysis of surgical human colorectal cancer tissues: up-regulation of PSB7, PRDX1, and SRP9 and hypoxic adaptation in cancer

Colorectal adenocarcinoma is one of the worldwide leading causes of cancer deaths. Discovery of specific biomarkers for early detection of cancer progression and the identification of underlying pathogenetic mechanisms are important tasks. Global proteomic approaches have thus far been limited by the large dynamic range of molecule concentrations in tissues and the lack of selective enrichment of the low-abundance proteome. We studied paired cancerous and normal clinical tissue specimens from patients with colorectal adenocarcinomas by heparin affinity fractionation enrichment (HAFE) followed by 2-D PAGE and tandem mass spectrometric (MS/MS) identification. Fifty-six proteins were found to be differentially expressed, of which 32 low-abundance proteins were only detectable after heparin affinity enrichment. MS/MS was used to identify 5 selected differentially expressed proteins as proteasome subunit beta type 7 (PSB7), hemoglobin alpha subunit (HBA), peroxiredoxin-1 (PRDX1), argininosuccinate synthase (ASSY), and signal recognition particle 9 kDa protein (SRP9). This is the first proteomic study detecting the differential expression of these proteins in human colorectal cancer tissue. Several of the proteins are functionally related to tissue hypoxia and hypoxic adaptation. The relative specificities of PSB7, PRDX1, and SRP9 overexpression in colon cancer were investigated by Western blot analysis of patients with colon adenocarcinomas and comparison with a control cohort of patients with lung adenocarcinomas. Furthermore, immunohistochemistry on tissue sections was used to define the specific locations of PSB7, PRDX1, and SRP9 up-regulation within heterogeneous primary human tumor tissue. Overexpression of the three proteins was restricted to the neoplastic cancer cell population within the tumors, demonstrating both cytoplasmic and nuclear localization of PSB7 and predominantly cytoplasmic localization of PRDX1 and SRP9. In summary, we describe heparin affinity fractionation enrichment (HAFE) as a prefractionation tool for the study of the human primary tissue proteome and the discovery of PSB7, PRDX1, and SRP9 up-regulation as candidate biomarkers of colon cancer.     

Affinity enrichment for mass spectrometry: improving the yield of low abundance biomarkers

Introduction: Mass spectrometry (MS) is the premier tool for discovering novel disease-associated protein biomarkers. Unfortunately, when applied to complex body fluid samples, MS has poor sensitivity for the detection of low abundance biomarkers (?10 ng/mL), derived directly from the diseased tissue cells or pathogens.

Areas covered: Herein we discuss the strengths and drawbacks of technologies used to concentrate low abundance analytes in body fluids, with the aim to improve the effective sensitivity for MS discovery. Solvent removal by dry-down or dialysis, and immune-depletion of high abundance serum or plasma proteins, is shown to have disadvantages compared to positive selection of the candidate biomarkers by affinity enrichment. A theoretical analysis of affinity enrichment reveals that the yield for low abundance biomarkers is a direct function of the binding affinity (Association/Dissociation rates) used for biomarker capture. In addition, a high affinity capture pre processing step can effectively dissociate the candidate biomarker from partitioning with high abundance proteins such as albumin.

Expert commentary: Properly designed high affinity capture materials can enrich the yield of low abundance (0.1–10 picograms/mL) candidate biomarkers for MS detection. Affinity capture and concentration, as an upfront step in sample preparation for MS, combined with MS advances in software and hardware that improve the resolution of the chromatographic separation can yield a transformative new class of low abundance biomarkers predicting disease risk or disease latency.     

Different immunoaffinity fractionation strategies to characterize the human plasma proteome

Plasma proteins may often serve as indicators of disease and are a rich source for biomarker discovery. However, the intrinsic large dynamic range of plasma proteins makes the analysis very challenging because a large number of low abundance proteins are often masked by a few high abundance proteins. The use of prefractionation methods, such as depletion of higher abundance proteins before protein profiling, can assist in the discovery and detection of less abundant proteins that may ultimately prove to be informative biomarkers. But there are few studies on comprehensive investigation of the proteins both in the fractions depleted and remainder. In the present study, two different immunoaffinity fractionation columns for the top-6 or the top-12 proteins in plasma were investigated and both the proteins in column-bound and flow-through fractions were subsequently analyzed. A two-dimensional peptide separation strategy, utilizing chromatographic separation techniques, combined with tandem mass spectrometry (MS/MS) was employed for proteomic analysis of the four fractions. Using the established HUPO PPP criteria, a total of 2401 unique plasma proteins were identified. The Multiple Affinity Removal System yielded 921 and 725 unique proteins from the flow-through and bound fractions, respectively, whereas the Seppro MIXED 12 column yielded identification of 897 and 730 unique proteins from the flow-through and bound fractions, respectively. When more stringent criteria, based on searching against the reversed database, were implemented, 529 unique proteins were identified from the four fractions with the confidence in peptide identification increased from 73.6% to 99%. To determine whether the presence of nontarget proteins in the immunoaffinity-bound fraction could be attributed to their interaction with high abundance proteins, co-immunoprecipitation analysis with an antibody to human plasma albumin was performed, which resulted in an identification of 40 unique proteins from the coimmunoprecipitate with the more stringent criteria. This study illustrated that combining the column-bound and flow-through fractions from immunoaffinity separation affords more extensive profiling of the protein content of human plasma. The presence of nontarget proteins in the column-bound fractions may be induced by their binding to the higher abundance proteins targeted by the immunoaffinity column.     

Rat plasma proteomics: effects of abundant protein depletion on proteomic analysis

The proteomic analysis of plasma and serum samples represents a formidable challenge due to the presence of a few highly abundant proteins such as albumin and immunoglobulins. Detection of low abundance protein biomarkers requires therefore either the specific depletion of high abundance proteins with immunoaffinity columns and/or optimized protein fractionation methods based on charge, size or hydrophobicity. Here we describe the depletion of seven abundant rat plasma proteins with an immunoaffinity column with coupled antibodies directed against albumin, IgG, transferrin, IgM, haptoglobin, fibrinogen and alpha1-anti-trypsin. The IgY-R7-LC2 (Beckman Coulter) column showed high specificity for the targeted proteins and was able to efficiently remove most of the albumin, IgG and transferrin from rat plasma samples as judged by Western blot analysis. Depleted rat plasma protein samples were analyzed by SELDI-TOF MS, 2D SDS-PAGE and 2D-LC and compared to non-depleted plasma samples as well as to the abundant protein fraction that was eluted from the immunoaffinity column. Analysis of the depleted plasma protein fraction revealed improved signal to noise ratios, regardless of which proteomic method was applied. However, only a small number of new proteins were observed in the depleted protein fraction. Immunoaffinity depletion of abundant plasma proteins results in the significant dilution of the original sample which complicates subsequent analysis. Most proteomic approaches require specialized sample preparation procedures during which significant losses of less abundant proteins and potential biomarkers can occur. Even though abundant protein depletion reduces the dynamic range of the plasma proteome by about 2-3 orders of magnitude, the difference between medium-abundant and low abundant plasma proteins is still in the range of 7-8 orders of magnitude and beyond the dynamic range of current proteomic technologies. Thus, exploring the plasma proteome in greater detail remains a daunting task.     

A novel approach and protocol for discovering extremely low-abundance proteins in serum

The proteomic analysis of serum (plasma) has been a major approach to determining biomarkers essential for early disease diagnoses and drug discoveries. The determination of these biomarkers, however, is analytically challenging since the dynamic concentration range of serum proteins/peptides is extremely wide (more than 10 orders of magnitude). Thus, the reduction in sample complexity prior to proteomic analyses is essential, particularly in analyzing low-abundance protein biomarkers. Here, we demonstrate a novel approach to the proteomic analyses of human serum that uses an originally developed serum protein separation device and a sequentially linked 3-D-LC-MS/MS system. Our hollow-fiber-membrane-based serum pretreatment device can efficiently deplete high-molecular weight proteins and concentrate low-molecular weight proteins/peptides automatically within 1 h. Four independent analyses of healthy human sera pretreated using this unique device, followed by the 3-D-LC-MS/MS successfully produced 12 000-13 000 MS/MS spectra and hit around 1800 proteins (>95% reliability) and 2300 proteins (>80% reliability). We believe that the unique serum pretreatment device and proteomic analysis protocol reported here could be a powerful tool for searching physiological biomarkers by its high throughput (3.7 days per one sample analysis) and high performance of finding low abundant proteins from serum or plasma samples.     

Evaluation of the combination of bead technology with SELDI-TOF-MS and 2-D DIGE for detection of plasma proteins

Today biomarker discovery is one of the most active aspects of proteomic investigations. However, the wide dynamic range of plasma proteins makes the analysis very challenging because high abundance proteins tend to mask those of lower abundance. Using a large bead-based library of combinatorial peptide ligands (Equalizer beads or ProteoMiner), the dynamic range of the protein concentration is compressed, the high abundance proteins present in the sample are reduced and the low abundance proteins are enriched, while retaining representatives of all proteins within the sample. In the present study, the combination of beads with surface enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and two-dimensional differential gel electrophoresis (2-D DIGE) technology were evaluated considering efficiency, reproducibility, sensitivity, and compatibility. The bead technology is easily compatible with both SELDI-TOF-MS and 2-D DIGE and the samples can be analyzed directly without any processing of the sample. The use of the beads prior SELDI-TOF-MS and 2-D DIGE enabled detection of many new protein spots/peaks and increased resolution and improved intensity of low abundance proteins in a reproducible fashion compared with the depletion technique. Several proteins have been identified by the combination of beads, 2-D DIGE and MS for example different kinds of complement factors and cytoskeletal proteins. Our data suggest that integration of the bead technology with our current proteomic technologies will enhance the possibility to deliver new peptide/protein biomarker candidates in our projects.     

Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins

Quantitative LC-MS/MS assays were designed for tryptic peptides representing 53 high and medium abundance proteins in human plasma using a multiplexed multiple reaction monitoring (MRM) approach. Of these, 47 produced acceptable quantitative data, demonstrating within-run coefficients of variation (CVs) (n = 10) of 2-22% (78% of assays had CV <10%). A number of peptides gave CVs in the range 2-7% in five experiments (10 replicate runs each) continuously measuring 137 MRMs, demonstrating the precision achievable in complex digests. Depletion of six high abundance proteins by immunosubtraction significantly improved CVs compared with whole plasma, but analytes could be detected in both sample types. Replicate digest and depletion/digest runs yielded correlation coefficients (R(2)) of 0.995 and 0.989, respectively. Absolute analyte specificity for each peptide was demonstrated using MRM-triggered MS/MS scans. Reliable detection of L-selectin (measured at 0.67 microg/ml) indicates that proteins down to the microg/ml level can be quantitated in plasma with minimal sample preparation, yielding a dynamic range of 4.5 orders of magnitude in a single experiment. Peptide MRM measurements in plasma digests thus provide a rapid and specific assay platform for biomarker validation, one that can be extended to lower abundance proteins by enrichment of specific target peptides (stable isotope standards and capture by anti-peptide antibodies (SISCAPA)).     

Optimization of Plasma Sample Pretreatment for Quantitative Analysis Using iTRAQ Labeling and LC-MALDI-TOF/TOF

Shotgun proteomic methods involving iTRAQ (isobaric tags for relative and absolute quantitation) peptide labeling facilitate quantitative analyses of proteomes and searches for useful biomarkers. However, the plasma proteome''s complexity and the highly dynamic plasma protein concentration range limit the ability of conventional approaches to analyze and identify a large number of proteins, including useful biomarkers. The goal of this paper is to elucidate the best approach for plasma sample pretreatment for MS- and iTRAQ-based analyses. Here, we systematically compared four approaches, which include centrifugal ultrafiltration, SCX chromatography with fractionation, affinity depletion, and plasma without fractionation, to reduce plasma sample complexity. We generated an optimized protocol for quantitative protein analysis using iTRAQ reagents and an UltrafleXtreme (Bruker Daltonics) MALDI TOF/TOF mass spectrometer. Moreover, we used a simple, rapid, efficient, but inexpensive sample pretreatment technique that generated an optimal opportunity for biomarker discovery. We discuss the results from the four sample pretreatment approaches and conclude that SCX chromatography without affinity depletion is the best plasma sample preparation pretreatment method for proteome analysis. Using this technique, we identified 1,780 unique proteins, including 1,427 that were quantified by iTRAQ with high reproducibility and accuracy.     

Computational Biomarker Pipeline from Discovery to Clinical Implementation: Plasma Proteomic Biomarkers for Cardiac Transplantation

Recent technical advances in the field of quantitative proteomics have stimulated a large number of biomarker discovery studies of various diseases, providing avenues for new treatments and diagnostics. However, inherent challenges have limited the successful translation of candidate biomarkers into clinical use, thus highlighting the need for a robust analytical methodology to transition from biomarker discovery to clinical implementation. We have developed an end-to-end computational proteomic pipeline for biomarkers studies. At the discovery stage, the pipeline emphasizes different aspects of experimental design, appropriate statistical methodologies, and quality assessment of results. At the validation stage, the pipeline focuses on the migration of the results to a platform appropriate for external validation, and the development of a classifier score based on corroborated protein biomarkers. At the last stage towards clinical implementation, the main aims are to develop and validate an assay suitable for clinical deployment, and to calibrate the biomarker classifier using the developed assay. The proposed pipeline was applied to a biomarker study in cardiac transplantation aimed at developing a minimally invasive clinical test to monitor acute rejection. Starting with an untargeted screening of the human plasma proteome, five candidate biomarker proteins were identified. Rejection-regulated proteins reflect cellular and humoral immune responses, acute phase inflammatory pathways, and lipid metabolism biological processes. A multiplex multiple reaction monitoring mass-spectrometry (MRM-MS) assay was developed for the five candidate biomarkers and validated by enzyme-linked immune-sorbent (ELISA) and immunonephelometric assays (INA). A classifier score based on corroborated proteins demonstrated that the developed MRM-MS assay provides an appropriate methodology for an external validation, which is still in progress. Plasma proteomic biomarkers of acute cardiac rejection may offer a relevant post-transplant monitoring tool to effectively guide clinical care. The proposed computational pipeline is highly applicable to a wide range of biomarker proteomic studies.     

Quantitative, multiplexed assays for low abundance proteins in plasma by targeted mass spectrometry and stable isotope dilution

Biomarker discovery produces lists of candidate markers whose presence and level must be subsequently verified in serum or plasma. Verification represents a paradigm shift from unbiased discovery approaches to targeted, hypothesis-driven methods and relies upon specific, quantitative assays optimized for the selective detection of target proteins. Many protein biomarkers of clinical currency are present at or below the nanogram/milliliter range in plasma and have been inaccessible to date by MS-based methods. Using multiple reaction monitoring coupled with stable isotope dilution mass spectrometry, we describe here the development of quantitative, multiplexed assays for six proteins in plasma that achieve limits of quantitation in the 1-10 ng/ml range with percent coefficients of variation from 3 to 15% without immunoaffinity enrichment of either proteins or peptides. Sample processing methods with sufficient throughput, recovery, and reproducibility to enable robust detection and quantitation of candidate biomarker proteins were developed and optimized by addition of exogenous proteins to immunoaffinity depleted plasma from a healthy donor. Quantitative multiple reaction monitoring assays were designed and optimized for signature peptides derived from the test proteins. Based upon calibration curves using known concentrations of spiked protein in plasma, we determined that each target protein had at least one signature peptide with a limit of quantitation in the 1-10 ng/ml range and linearity typically over 2 orders of magnitude in the measurement range of interest. Limits of detection were frequently in the high picogram/milliliter range. These levels of assay performance represent up to a 1000-fold improvement compared with direct analysis of proteins in plasma by MS and were achieved by simple, robust sample processing involving abundant protein depletion and minimal fractionation by strong cation exchange chromatography at the peptide level prior to LC-multiple reaction monitoring/MS. The methods presented here provide a solid basis for developing quantitative MS-based assays of low level proteins in blood.