Multiple Reaction Monitoring-based, Multiplexed, Absolute Quantitation of 45 Proteins in Human Plasma

Mass spectrometry-based multiple reaction monitoring (MRM) quantitation of proteins can dramatically impact the discovery and quantitation of biomarkers via rapid, targeted, multiplexed protein expression profiling of clinical samples. A mixture of 45 peptide standards, easily adaptable to common plasma proteomics work flows, was created to permit absolute quantitation of 45 endogenous proteins in human plasma trypsin digests. All experiments were performed on simple tryptic digests of human EDTA-plasma without prior affinity depletion or enrichment. Stable isotope-labeled standard peptides were added immediately following tryptic digestion because addition of stable isotope-labeled standard peptides prior to trypsin digestion was found to generate elevated and unpredictable results. Proteotypic tryptic peptides containing isotopically coded amino acids ([¹³C₆]Arg or [¹³C₆]Lys) were synthesized for all 45 proteins. Peptide purity was assessed by capillary zone electrophoresis, and the peptide quantity was determined by amino acid analysis. For maximum sensitivity and specificity, instrumental parameters were empirically determined to generate the most abundant precursor ions and y ion fragments. Concentrations of individual peptide standards in the mixture were optimized to approximate endogenous concentrations of analytes and to ensure the maximum linear dynamic range of the MRM assays. Excellent linear responses (r > 0.99) were obtained for 43 of the 45 proteins with attomole level limits of quantitation (<20% coefficient of variation) for 27 of the 45 proteins. Analytical precision for 44 of the 45 assays varied by <10%. LC-MRM/MS analyses performed on 3 different days on different batches of plasma trypsin digests resulted in coefficients of variation of <20% for 42 of the 45 assays. Concentrations for 39 of the 45 proteins are within a factor of 2 of reported literature values. This mixture of internal standards has many uses and can be applied to the characterization of trypsin digestion kinetics and plasma protein expression profiling because 31 of the 45 proteins are putative biomarkers of cardiovascular disease.MS is capable of sensitive and accurate protein quantitation based on the quantitation of proteolytic peptides as surrogates for the corresponding intact proteins. Over the past 10 years, MS-based protein quantitation based on the analysis of peptides (in other words, based on “bottom-up” proteomics) has had a profound impact on how biological problems can be addressed (1, 2). Although advances in MS instrumentation have contributed to the improvement of MS-based protein quantitation, the use of stable isotopes in quantitative work flows has arguably had the greatest impact in improving the quality and reproducibility of MS-based protein quantitation (3–5).The ongoing development of untargeted MS-based quantitation work flows has focused on increasingly exhaustive sample prefractionation methods, at both the protein and peptide levels, with the goal of detecting and quantifying entire proteomes (6). Although untargeted MS-based quantitation work flows have their utility, they are costly in terms of lengthy MS data acquisition and analysis times, and as a result, they are often limited to quantifying differences between small sample sets (n < 10). To facilitate rapid quantitation of larger, clinically relevant sample sets (n > 100) there is a need to both simplify sample preparation and reduce MS analysis time.Multiple reaction monitoring (MRM)¹ is a tandem MS (MS/MS) scan mode unique to triple quadrupole MS instrumentation that is capable of rapid, sensitive, and specific quantitation of analytes in highly complex sample matrices (7). MRM is a targeted approach that requires knowledge of the molecular weight of an analyte and its fragmentation behavior under CID. MRM is capable of highly reproducible concentration determination when stable isotope-labeled internal standards are included in work flows and has been used for decades for the quantitation of low molecular mass analytes (<1000 Da) in pharmaceutical, clinical, and environmental applications (7, 8).The combination of triple quadrupole MS instrumentation with nanoliter flow rate high performance LC and nanoelectrospray ionization provides the necessary sensitivity for detection and quantitation of biological molecules such as peptides in complex samples such as plasma by MRM. When combined with the use of isotopically labeled synthetic peptide standards, MRM analysis is capable of sensitive (attomole level) and absolute determination of peptide concentrations across a wide concentration scale spanning a dynamic range of 10³–10⁴ (1, 9–13).Several recent studies involving MRM-based analysis of plasma proteins have focused on increasing MRM detection sensitivity by fractionating plasma using either multidimensional liquid chromatography, affinity depletion of high abundance proteins (11, 14, 15), or affinity enrichment of low abundance peptides (16, 17). Anderson and Hunter (14) have shown that LC-MRM/MS analysis is capable of detecting 47 moderate to high abundance proteins in plasma without depletion even though ∼90% of the total protein by weight in trypsin-digested plasma can be attributed to 10 high abundance proteins (18).Relative abundance of a protein does not preclude its involvement in disease. In fact, 32 of the 47 plasma proteins detected by Anderson and Hunter (14) have been implicated as putative markers for cardiovascular disease. The ability to rapidly quantify proteins in a highly multiplexed manner using MRM and internal standard peptides expands the potential application of MRM quantitation beyond biomarker validation and into the field of biomarker discovery. Targeted, simultaneous quantitation of hundreds of proteins in a single analysis will enable rapid protein expression profiling of large (n > 100) clinically relevant sample sets in a manner similar to DNA microarray expression profiling. By allowing researchers to look at patterns of expression levels of a large number of proteins in a large number of samples (as opposed to looking at the expression levels of only a single protein), multiplexed MRM-based quantitation will allow the correlation of expression patterns with particular diseases. Once these characteristic patterns have been established, physicians will be able to use these protein expression patterns to diagnose diseases in the same way they currently use blood chemistry panels or comprehensive metabolic panels.When considering the clinical utility of MS-based assays, direct comparisons are often made to ELISA, which is considered the “gold standard” for protein quantitation in clinical samples. Attributes of ELISAs, such as “time to first result” (1–2 h (19)) and the ability to quantify 96 or 384 samples in parallel because of their microtiter plate-based format, are currently difficult to match with MS-based protein assays. However, MRM protein assays may surpass ELISA in the rapid development of clinically useful, multiplexed protein assays. The impact of multiplexed assays in the field of genomics has increased interest in multiplexed quantitation of many proteins in individual clinical samples (19). Development and characterization of MRM-based protein assays using isotopically labeled peptides is rapid and inexpensive compared with the time and cost associated with the generation and characterization of antibodies for ELISA development.In this study, we describe the creation of a customizable mixture of concentration-balanced stable isotope-labeled standard (SIS) peptides representing an initial panel of 45 human plasma proteins. We used this mixture of SIS peptides to develop a suite of multiplexed, rapid, and reproducible MRM-based assays for expression profiling of these 45 proteins in simple tryptic digests of whole plasma. Additionally we characterized the analytical performance of these MRM peptide assays with respect to their reproducibility, and we demonstrated their utility for absolute protein concentration determination.Multiplexed MRM quantitation of peptides for protein quantitation has the potential to replace iTRAQ or other isotope label and label-free quantitative proteomics approaches because the approach is much faster than these other methods (30–60 min per analysis compared with 4 days for LC-MALDI-based iTRAQ), has greater reproducibility (CV <5% versus iTRAQ CV >20%), and enables absolute quantitation (concentration and copy number versus only x-fold up- or down-regulated). Additionally MRM-based quantitation with SIS peptides does not “miss” peptides because the SIS peptide must be detected in every sample: this means that if an endogenous peptide is not observed then it is below the limit of detection.     

P23-M Limit of Quantitation for Low-Abundance Proteins in Plasma by Targeted MS

Biomarker discovery results in the creation of candidate lists of potential markers that must be subsequently verified in plasma.¹ The most mature methods at present require abundant protein depletion and fractionation at the protein/peptide levels in order to detect and quantitate low ng/mL concentrations of plasma proteins by stable isotope dilution mass spectrometry. Sample-processing methods with sufficient throughput, recovery, and reproducibility to enable robust detection and quantitation of candidate bio-marker proteins were evaluated by adding five non-native proteins to immunoaffinity-depleted female plasma at varying concentrations (1000, 100, 50, 25, and 10 ng/mL). Each protein was monitored by one or more representative synthetic tryptic peptides labeled with [¹³C₆]leucine or [¹³C₅] valine. Following reduction, carbamidomethylation, and enzymatic digestion, two separate processing paths were compared. In path 1, digested plasma was diluted 1:10 and [¹³C] internal standards were added just prior to direct analysis by multiple reaction monitoring with LC-MS/MS (MRM LC-MS/MS). In path 2, peptides were separated by strong cation exchange, and [¹³C] internal standards were added to corresponding SCX fractions prior to analysis by MRM LC-MS/MS. Detection and quantitation by MRM used the response of at least two product ions from each of the signature peptides. Using processing path 1, we achieved detection and quantitation down to 50 ng/mL in depleted plasma. However, using processing path 2, we achieved detection and quantitation of all spiked proteins, including the non-native protein at 10 ng/mL. While analysis of non-fractionated plasma achieved higher recovery of those proteins detected in both processes, SCX fractionation at the peptide level clearly increases detection and LOQs for potential biomarker proteins in plasma.     

Accurate inclusion mass screening: a bridge from unbiased discovery to targeted assay development for biomarker verification

Verification of candidate biomarker proteins in blood is typically done using multiple reaction monitoring (MRM) of peptides by LC-MS/MS on triple quadrupole MS systems. MRM assay development for each protein requires significant time and cost, much of which is likely to be of little value if the candidate biomarker is below the detection limit in blood or a false positive in the original discovery data. Here we present a new technology, accurate inclusion mass screening (AIMS), designed to provide a bridge from unbiased discovery to MS-based targeted assay development. Masses on the software inclusion list are monitored in each scan on the Orbitrap MS system, and MS/MS spectra for sequence confirmation are acquired only when a peptide from the list is detected with both the correct accurate mass and charge state. The AIMS experiment confirms that a given peptide (and thus the protein from which it is derived) is present in the plasma. Throughput of the method is sufficient to qualify up to a hundred proteins/week. The sensitivity of AIMS is similar to MRM on a triple quadrupole MS system using optimized sample preparation methods (low tens of ng/ml in plasma), and MS/MS data from the AIMS experiments on the Orbitrap can be directly used to configure MRM assays. The method was shown to be at least 4-fold more efficient at detecting peptides of interest than undirected LC-MS/MS experiments using the same instrumentation, and relative quantitation information can be obtained by AIMS in case versus control experiments. Detection by AIMS ensures that a quantitative MRM-based assay can be configured for that protein. The method has the potential to qualify large number of biomarker candidates based on their detection in plasma prior to committing to the time- and resource-intensive steps of establishing a quantitative assay.     

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.     

Mass Spectrometric Identification of Proteotypic Peptides from Clinically Used Tumor Markers

Introduction

With the rapid development of mass spectrometry-based technologies such as multiple reaction monitoring and heavy-isotope-labeled-peptide standards, quantitative analysis of biomarker proteins using mass spectrometry is rapidly progressing toward detection of target proteins/peptides from clinical samples. Proteotypic peptides are a few peptides that are repeatedly and consistently identified from a protein in a mixture and are used for quantitative analysis of the protein in a complex biological sample by mass spectrometry.

Materials and Methods

Using mass spectrometry, we identified peptide sequences and provided a list of tryptic peptides and glycopeptides as proteotypic peptides from five clinically used tumor markers, including prostate-specific antigen, carcinoembryonic antigen, Her-2, human chorionic gonadotropin, and CA125.

Conclusion

These proteotypic peptides have potential for targeted detection as well as heavy-isotope-peptide standards for quantitative analysis of marker proteins in clinical specimens using a highly specific, sensitive, and high-throughout mass spectrometry-based analysis method.     

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.     

Sialic Acid-focused Quantitative Mouse Serum Glycoproteomics by Multiple Reaction Monitoring Assay

Despite increasing importance of protein glycosylation, most of the large-scale glycoproteomics have been limited to profiling the sites of N-glycosylation. However, in-depth knowledge of protein glycosylation to uncover functions and their clinical applications requires quantitative glycoproteomics eliciting both peptide and glycan sequences concurrently. Here we describe a novel strategy for the multiplexed quantitative mouse serum glycoproteomics based on a specific chemical ligation, namely, reverse glycoblotting technique, focusing sialic acids and multiple reaction monitoring (MRM). LC-MS/MS analysis of de-glycosylated peptides identified 270 mouse serum peptides (95 glycoproteins) as sialylated glycopeptides, of which 67 glycopeptides were fully characterized by MS/MS analyses in a straightforward manner. We revealed the importance of a fragment ion containing innermost N-acetylglucosamine (GlcNAc) residue as MRM transitions regardless the sequence of the peptides. Versatility of the reverse glycoblotting-assisted MRM assays was demonstrated by quantitative comparison of 25 targeted glycopeptides from 16 proteins between mice with homo and hetero types of diabetes disease model.Clinical proteomics focusing on the identification and validation of biomarkers and the discovery of proteins as therapeutic targets is an emerging and highly important area of proteomics. Biomarkers are measurable indicators of a specific biological state (particularly one relevant to the risk of contraction) and the presence or the stage of disease, and are thus expected to be useful for the prediction, detection, and diagnosis of disease as well as to follow the efficacy, toxicology, and side effects of drug treatment, and to provide new functional insights into biological processes.At present, proteomics methods based on mass spectrometry (MS) have emerged as the preferred strategy for discovery of diagnostic, prognostic, and therapeutic protein biomarkers. Most biomarker discovery studies use unbiased, “identified-based” approaches that rely on high performance mass spectrometers and extensive sample processing. Semiquantitative comparisons of protein relative abundance between disease and control patient samples are used to identify proteins that are differentially expressed and, thus, to populate lists of potential biomarkers. De novo proteomics discovery experiments often result in tens to hundreds of candidate biomarkers that must be subsequently verified in serum. However, despite the large numbers of putative biomarkers, only a small number of them are passed through the development and validation process into clinical practice, and their rate of introduction is declining. The first non-standard abbreviation (MS above is standard) must be footnoted the same as the abbreviation footnote, and MRM must be the first abbreviation in the list because it is the one footnoted. After that the order does not matter.Targeted proteomics using multiple reaction monitoring (MRM)1 is emerging as a technology that complements the discovery capabilities of shotgun strategies as well as an alternative powerful novel MS-based approach to measure a series of candidate biomarkers (1–7). Therefore, MRM is expected to provide a powerful high throughput platform for biomarker validation, although clinical validation of novel biomarkers has been traditionally relying on immunoassays (8, 9). MRM exploits the unique capabilities of triple quadrupoles (QQQ) MS for quantitative analysis. In MRM, the first and the third quadrupoles act as filters to specifically select predefined m/z values corresponding to the peptide precursor ion and specific fragment ion of the peptide, whereas the second quadrupole serves as collision cell. Several such transitions (precursor/fragment ion pairs) are monitored over time, yielding a set of chromatographic traces with retention time and signal intensity for a specific transition as coordinates. These measurements have been multiplexed to provide 30 or more specific assays in one run. Such methods are slowly gaining acceptance in the clinical laboratory for the routine measurement of endogenous metabolites (10) (e.g. in screening newborns for a panel of inborn errors of metabolism) some drugs (11) (e.g. immunosuppressants), and the component analysis of sugars (12).One of the profound challenges in clinical proteomics is the need to handle highly complex biological mixtures. This complexity presents unique analytical challenges that are further magnified with the use of clinical serum/plasma samples to search for novel biomarkers of human disease. The serum proteome is composed of tens of thousands of unique proteins, of which concentrations may exceed 10 orders of magnitude. Protein glycosylation, one of the most common post-translational modifications, generates tremendous diversity, complexity, and heterogeneity of gene products. It changes the biological and physical properties of proteins, which include functions as signals or ligands to control their distribution, antigenicity, metabolic fate, stability, and solubility. Protein glycosylation, in particular by N-linked glycans, is prevalent in proteins destined for extracellular environments. These include proteins on the extracellular side of the plasma membrane, secreted proteins, and proteins contained in body fluids (such as blood serum, cerebrospinal fluid, urine, breast milk, saliva, lung lavage fluid, or pancreatic juice). Considering that such body fluids are most easily accessible for diagnostic and therapeutic purposes, it is not surprising that many clinical biomarkers and therapeutic targets are glycoproteins. These include, for example, cancer antigen 125 (CA125) in ovarian cancer, human epidermal growth factor receptor 2 (Her2/neu) in breast cancer, and prostate-specific antigen (PSA) in prostate cancer. In addition, changes in the extent of glycosylation and the structure of N-glycans or O-glycans attached to proteins on the cell surface and in body fluids have been shown to correlate with cancer and other disease states, highlighting the clinical importance of this modification as an indicator or effector of pathologic mechanisms (13–16). Thus, clinical proteomic platforms should have capability to provide protein glycosylation information as well as sufficient analytical depth to reliably detect and quantify specific proteins with sufficient accuracy and throughput.To improve the detection limits to the required sensitivities, one needs to dramatically reduce the complexity of the sera samples. For focused glycoproteomics, several techniques using lectins or antibodies enabling the large-scale identification of glycoproteins have recently been developed (17–19). Notably, Zhang et al. reported a method for the selective isolation of peptides based on chemical oxidation of the carbohydrate moiety and subsequent conjugation to a solid support using hydrazide chemistry (20–26). However, it is not possible to provide any structural information about N-glycans because the MS analysis is performed on peptides of which N-glycans are removed preferentially by treating with peptide N-glycanase (PNGase). In 2007, we developed a method for rapid enrichment analysis of peptides bearing sialylated N-glycans on the MALDI-TOF-MS platform (27). The method involves highly selective oxidation of sialic acid residues of glycopeptides to elaborate terminal aldehyde group and subsequent enrichment by chemical ligation with a polymer reagent, namely, reverse glycoblotting technique inspired from an original concept of glycoblotting method (28). This method, in principle, is capable identifying both glycan and peptide sequences concurrently. Recently, Nilsson et al. reported that glycopeptides from human cerebrospinal fluid can be enriched on the basis of the same principle as the reverse glycoblotting protocol, and captured glycopeptides were analyzed with ESI FT-ICR MS (29). Because it is well known that sialic acids play important roles in various biological processes including cell differentiation, immune response, and oncogenesis (30–34), our attention has been directed toward feasibility of the reverse glycoblotting technique in quantitative analysis of the specific glycopeptides carrying sialic acid(s) by combining with multiplexed MRM-based MS.     

A Targeted Quantitative Proteomics Strategy for Global Kinome Profiling of Cancer Cells and Tissues

Kinases are among the most intensively pursued enzyme superfamilies as targets for anti-cancer drugs. Large data sets on inhibitor potency and selectivity for more than 400 human kinases became available recently, offering the opportunity to design rationally novel kinase-based anti-cancer therapies. However, the expression levels and activities of kinases are highly heterogeneous among different types of cancer and even among different stages of the same cancer. The lack of effective strategy for profiling the global kinome hampers the development of kinase-targeted cancer chemotherapy. Here, we introduced a novel global kinome profiling method, based on our recently developed isotope-coded ATP-affinity probe and a targeted proteomic method using multiple-reaction monitoring (MRM), for assessing simultaneously the expression of more than 300 kinases in human cells and tissues. This MRM-based assay displayed much better sensitivity, reproducibility, and accuracy than the discovery-based shotgun proteomic method. Approximately 250 kinases could be routinely detected in the lysate of a single cell line. Additionally, the incorporation of iRT into MRM kinome library rendered our MRM kinome assay easily transferrable across different instrument platforms and laboratories. We further employed this approach for profiling kinase expression in two melanoma cell lines, which revealed substantial kinome reprogramming during cancer progression and demonstrated an excellent correlation between the anti-proliferative effects of kinase inhibitors and the expression levels of their target kinases. Therefore, this facile and accurate kinome profiling assay, together with the kinome-inhibitor interaction map, could provide invaluable knowledge to predict the effectiveness of kinase inhibitor drugs and offer the opportunity for individualized cancer chemotherapy.Protein phosphorylation, one of the most important types of post-translational modifications (PTMs)¹, is catalyzed by protein kinases (collectively referred to as the kinome), which are encoded by over 500 genes in higher eukaryotes (1). Aberrant expression and/or activation/deactivation of kinases have been implicated as among the major mechanisms through which cancer cells escape normal physiological constraints of cell growth and survival (2). Additionally, dynamic kinome reprogramming has been found to be closely associated with resistance toward cancer chemotherapy (3). Owing to their crucial roles in cancer development, kinases have become one of the most intensively pursued enzyme superfamilies as drug targets for cancer chemotherapy and more than 130 distinct kinase inhibitors have been developed for phase 1–3 clinical trials (4). Recently, inhibitor potency and selectivity for more than 400 kinases have been reported, which provided a comprehensive target-inhibition profile for the majority of the human kinome (5–7). Therefore, the kinome-inhibitor interaction networks coupled with comprehensive profiling of global kinome expression and activity associated with certain types of cancer could be invaluable for understanding the mechanisms of carcinogenesis and for designing rationally novel kinase-directed anti-cancer chemotherapies.Unfortunately, currently there is no optimal strategy for profiling the expression levels of the entire kinome at the protein level. Traditional methods for measuring kinase expression rely primarily on antibody-based immunoassays because of their high specificity and sensitivity (8). The immunoassays, however, are limited by the availability of high-quality antibodies; therefore, these methods are only useful for assessing a small number of kinases in low-throughput. Recent advances in MS instrumentation and bioinformatic tools enable the identification and quantification of a significant portion of the human proteome from complex samples (9). However, proteomic studies of global kinome by MS are still very challenging, which is largely attributed to the fact that, similar as other regulatory enzymes, protein kinases are generally expressed at low levels in cells (10). This analytical challenge is further aggravated in shotgun proteomics approach where even more complex mixtures of peptides instead of proteins from whole cell or tissue extracts are analyzed (11). Therefore, selective enrichment of protein kinases from cellular extracts is essential for the comprehensive identification and quantification of the global kinome.Affinity columns immobilized with kinase inhibitors have been employed as capture ligands for the enrichment of kinases, and ∼200 protein kinases could be identified and quantified by subsequent LC-MS/MS analyses (3, 10, 12). Recently, we and others reported the application of biotin-conjugated acyl nucleotide probes for the enrichment and identification of kinases from complex protein mixtures (13–17). This enrichment technique, in combination with multi-dimensional LC-MS platform, facilitates the identification of ∼200 protein kinases (15). Despite these advances, such large-scale kinome studies are often performed in the data-dependent acquisition (DDA) mode, where typically 10–20 most abundant ions found in MS are subsequently selected for fragmentation in MS/MS to enable peptide identification (18). Although this discovery-mode (or shotgun) proteomic approach provides the potential to uncover novel protein targets, sample complexity, together with inherent variation in automated peak selection, results in compromised sensitivity and reproducibility for protein quantification. As a result, only partially overlapping sets of proteins can be identified even from substantially similar samples (11). The inadequate sensitivity and reproducibility of these kinome detection strategies hamper their utility in biomarker discovery and clinical studies.Targeted proteomics technique, which relies on multiple-reaction monitoring (MRM) on triple quadrupole mass spectrometers, has become increasingly used in quantitative proteomics studies (19). In the MRM mode, mass filtering of both the precursor and product ions is employed to provide high specificity for the quantification of target proteins. Additionally, this MRM-based targeted MS analysis permits rapid and continuous monitoring of specific ions of interest, which enhances the sensitivity for peptide detection by up to 100-fold relative to MS analysis in DDA-based discovery mode (20). Therefore, the MRM-based targeted proteomic approach may enable global kinome profiling with high specificity, sensitivity, throughput, and reproducibility.Here, we developed the first MRM-based platform to support the multiplexed, reproducible, and sensitive quantification of ∼300 protein kinases in the human kinome. Aside from conventional MRM-based assay design, we selectively label and enrich kinases from complex human proteome prior to MRM analysis with the use of desthiobiotin-based isotope-coded ATP-affinity probe (ICAP) (21) to attain high specificity and sensitivity. We demonstrated that this MRM-based kinome detection strategy coupled with ICAP reagent is applicable for clinical samples that are not amenable to metabolic labeling. Additionally, this MRM-based kinome assay is easily transferable between instruments and laboratories, rendering it a facile and universal strategy for global kinome detection.     

Fusion Peptides from Oncogenic Chimeric Proteins as Putative Specific Biomarkers of Cancer

Chromosomal translocations encoding chimeric fusion proteins constitute one of the most common mechanisms underlying oncogenic transformation in human cancer. Fusion peptides resulting from such oncogenic chimeric fusions, though unique to specific cancer subtypes, are unexplored as cancer biomarkers. Here we show, using an approach termed fusion peptide multiple reaction monitoring mass spectrometry, the direct identification of different cancer-specific fusion peptides arising from protein chimeras that are generated from the juxtaposition of heterologous genes fused by recurrent chromosomal translocations. Using fusion peptide multiple reaction monitoring mass spectrometry in a clinically relevant scenario, we demonstrate the specific, sensitive, and unambiguous detection of a specific diagnostic fusion peptide in clinical samples of anaplastic large cell lymphoma, but not in a diverse array of benign lymph nodes or other forms of primary malignant lymphomas and cancer-derived cell lines. Our studies highlight the utility of fusion peptides as cancer biomarkers and carry broad implications for the use of protein biomarkers in cancer detection and monitoring.A cancer biomarker is generally an analyte that indicates the presence or extent of a specific form of cancer. A useful cancer biomarker should reliably distinguish between benign and malignant states and, ideally, distinguish one form of cancer from other, related differential diagnoses. Many human cancers contain recurrent chromosomal translocations and chimeric gene fusions that could be exploited as cancer-specific biomarkers (1, 2). Indeed, several structural aberrations are specific and pathognomonic for distinct types of cancer (3). Moreover, as new molecular therapies increasingly target oncogenic fusion proteins, the detection and quantitation of these proteins may also provide important, direct therapeutic guidance (4–6). Although genomic techniques targeting fusion partner genes are routinely used for diagnosing cancers, fusion peptides resulting from oncogenic chimeric fusions are unexplored as biomarker candidates for cancer detection. The specificity and qualitative/binary nature (i.e. present or absent) of fusion proteins in specific tumor types make these analytes attractive candidates for cancer detection.Advances in mass spectrometry permit the direct and unbiased interrogation of proteins and peptides in complex mixtures with unambiguous identification of specific proteins (7, 8). Multiple reaction monitoring (MRM)¹ via mass spectrometry is a powerful approach for the targeted detection of biomarker candidates in a complex background (9). MRM involves the focused interrogation of specific m/z windows for the precursor analyte, as well as selected fragment ions, following MS/MS analysis. By focusing only on specific m/z windows, one increases the sensitivity of detection dramatically, and within the context of a complex mixture there is the potential for a reproducible dynamic range spanning ≥4 orders of magnitude (10, 11).Despite their enormous potential as biomarkers, fusion peptides resulting from oncogenic chimeric fusions have not been exploited for the specific and sensitive detection of cancer. Here we demonstrate the detection of unique fusion peptides that are specific for various forms of cancer. To demonstrate applicability in a clinically relevant scenario, we show the utility of our MRM-based MS approach combined with an innovative double stable isotope strategy for the identification of nucleophosmin-anaplastic lymphoma kinase (NPM-ALK) fusion peptide arising from the corresponding chimeric fusion protein for the identification of NPM-ALK-positive anaplastic large cell lymphoma (ALCL). We show the exquisite specificity and sensitivity of this fusion peptide (FP) MRM approach and the extraordinary accuracy of its application with clinical biopsy material.     

Accurate quantification of cardiovascular biomarkers in serum using Protein Standard Absolute Quantification (PSAQ™) and selected reaction monitoring

Development of new biomarkers needs to be significantly accelerated to improve diagnostic, prognostic, and toxicity monitoring as well as therapeutic follow-up. Biomarker evaluation is the main bottleneck in this development process. Selected Reaction Monitoring (SRM) combined with stable isotope dilution has emerged as a promising option to speed this step, particularly because of its multiplexing capacities. However, analytical variabilities because of upstream sample handling or incomplete trypsin digestion still need to be resolved. In 2007, we developed the PSAQ™ method (Protein Standard Absolute Quantification), which uses full-length isotope-labeled protein standards to quantify target proteins. In the present study we used clinically validated cardiovascular biomarkers (LDH-B, CKMB, myoglobin, and troponin I) to demonstrate that the combination of PSAQ and SRM (PSAQ-SRM) allows highly accurate biomarker quantification in serum samples. A multiplex PSAQ-SRM assay was used to quantify these biomarkers in clinical samples from myocardial infarction patients. Good correlation between PSAQ-SRM and ELISA assay results was found and demonstrated the consistency between these analytical approaches. Thus, PSAQ-SRM has the capacity to improve both accuracy and reproducibility in protein analysis. This will be a major contribution to efficient biomarker development strategies.Introduction of new diagnostic assays in the clinical setting requires an operating pipeline to efficiently translate putative biomarkers into validated biomarkers. Despite the discovery platforms'' capacity to generate well populated lists of candidate biomarkers, very few proteins reach the patient bedside as fully fledged “FDA-approved” biomarkers. This is largely because of divergences between analytical needs and performances of the techniques available for candidate biomarker evaluation (1, 2).Candidate biomarker evaluation is a major process of the biomarker pipeline, positioned downstream of the biomarker discovery phase and necessary before clinical validation. Candidate evaluation aims to select, among hundreds of putative biomarkers, those of clinical relevance. Evaluation phase combines two steps which respectively consist in: (1) confirming a difference between physiological and pathological concentrations in biofluids (the so-called “qualification phase”) and (2) assessing the specificity of candidate biomarkers (the so-called “verification phase”) (1). Currently, because of its high throughput and high sensitivity, quantitative ELISA is the preferred assay format for studies evaluating biomarkers. However, as most candidates are likely to fail as relevant biomarkers, developing ELISA tests (with high quality antibodies) for all candidates is a financial burden for the diagnostics industry (3).Thus, there exists an urgent need to develop analytical methods capable of reliable candidate evaluation, at high throughput and reasonable cost. Selected Reaction Monitoring (SRM)¹ mass spectrometry combined with stable isotope dilution (SID-SRM) has shown promise as a solution to this technological hurdle (4, 5). MS analysis in SRM mode offers the unique possibility to specifically and simultaneously monitor the signatures of hundreds of target peptides generated by trypsin digestion of proteins. Combined with isotope-labeled quantification standards (6), SRM can provide quantitative data for each protein targeted (5).Recently, in an effort to demonstrate the potential of SID-SRM for candidate biomarker evaluation, a multilaboratory study was set up to assess its analytical performances and potential transferability (7). Exogenous proteins, seven in all, were added to unfractionated plasma samples. The spiked samples were analyzed by eight independent laboratories using SRM and isotope-labeled peptides as standards. The results obtained clearly demonstrated the capacity of SID-SRM to specifically and precisely quantify protein biomarkers in plasma. However, the results also revealed that the protein digestion rate was highly variable between laboratories. This variability had a significant effect on peptide recovery and on the accuracy of protein quantification. As suggested by the authors, this type of bias could be avoided if properly folded isotope-labeled protein standards were used as quantification standards (7, 8).In 2007, we developed the PSAQ™ (Protein Standard Absolute Quantification) method, which uses full-length isotope-labeled proteins as internal standards for absolute quantitative MS analysis. We demonstrated that, in contrast with peptide standards, adding isotope-labeled proteins before sample digestion enables accurate protein quantification, even for proteins resistant to trypsin digestion (9, 10). In addition, we, and others, have shown that this type of protein standard (“PSAQ standard”) also corrects for protein losses that may occur during sample handling prior to trypsin digestion and liquid chromatography (LC)-MS analysis (11–17). This latter feature is a particular advantage for MS analysis of blood biomarkers. Indeed, as plasma/serum are highly complex matrices and display a huge dynamic range, sample prefractionation must be performed to detect low-abundance protein biomarkers (4).In this study, we have tested a combination of the PSAQ strategy with SRM (PSAQ-SRM) for quantification of cardiovascular biomarkers in serum samples. Selected biomarkers include LDH-B, CKMB, myoglobin, and troponin I. For some of these validated biomarkers, a comparison of PSAQ-SRM data and ELISA results was performed on samples from patients having suffered myocardial infarction.     

Proteomics of Microparticles with SILAC Quantification (PROMIS-Quan): A Novel Proteomic Method for Plasma Biomarker Quantification

Unbiased proteomic analysis of plasma samples holds the promise to reveal clinically invaluable disease biomarkers. However, the tremendous dynamic range of the plasma proteome has so far hampered the identification of such low abundant markers. To overcome this challenge we analyzed the plasma microparticle proteome, and reached an unprecedented depth of over 3000 plasma proteins in single runs. To add a quantitative dimension, we developed PROMIS-Quan—PROteomics of MIcroparticles with Super-Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC) Quantification, a novel mass spectrometry-based technology for plasma microparticle proteome quantification. PROMIS-Quan enables a two-step relative and absolute SILAC quantification. First, plasma microparticle proteomes are quantified relative to a super-SILAC mix composed of cell lines from distinct origins. Next, the absolute amounts of selected proteins of interest are quantified relative to the super-SILAC mix. We applied PROMIS-Quan to prostate cancer and compared plasma microparticle samples of healthy individuals and prostate cancer patients. We identified in total 5374 plasma-microparticle proteins, and revealed a predictive signature of three proteins that were elevated in the patient-derived plasma microparticles. Finally, PROMIS-Quan enabled determination of the absolute quantitative changes in prostate specific antigen (PSA) upon treatment. We propose PROMIS-Quan as an innovative platform for biomarker discovery, validation, and quantification in both the biomedical research and in the clinical worlds.Biomarker discovery in plasma is one of the holy grails of the proteomic field toward the development of noninvasive diagnostic/prognostic tests (1). To achieve this goal, proteomics necessitates a comprehensive view of the plasma proteome, accurate proteome quantification, combined with relatively short analytical times to enable multiple sample comparisons. However, MS-based biomarker discovery is limited by the vast dynamic range of the plasma, over 11 orders of magnitude (2, 3), which leads to the masking of “tissue leakage” proteins that comprise of potential biomarkers by the core plasma proteins. Two main complementary strategies have been employed to reach identification of low abundance proteins: (i) Targeted proteomics, in which the MS identifies and quantifies only predetermined peptides, thereby circumventing the system''s inherent tendency to preferentially detect abundant proteins. This approach is utilized for validation of preselected candidate markers (4–6). (ii) Plasma fractionation, which biochemically reduces the complexity of the proteomes, and enables discovery of novel biomarkers (7, 8).Targeted MS analysis is dominated by the selected reaction monitoring approach, often in combination with antibody-based enrichment of proteins or peptides and stable isotope labeled standards for quantification (9). This approach benefits from the sensitivity and quantitative capabilities of the triple-quadrupole instruments. Its major limitation is that it relies on prior discovery of candidates within the plasma samples using extensive tissue/cell-line-based analysis and prediction of potential biomarkers. The fractionation strategy reduces both the complexity and the dynamic range of the plasma through depletion of the most abundant plasma proteins, and/or through extensive biochemical separation of proteins and peptides. Although these fractionation approaches enabled identification of thousands of plasma proteins (7), they dramatically reduce the throughput of the method, and thus, the applicability to clinical studies.A distinct fractionation approach involves the isolation of plasma microparticles and exosomes. Microparticles are large vesicles (100 nm–1 μm), which protrude directly from the plasma membrane, whereas exosomes are smaller (40–100 nm) and originate from endocytic compartments known as the multivesicular endosomes. These microvesicles are constitutively shed from all cell types into the blood, carrying a proteomic signature of their cells of origin (10). Microparticles mediate local and systemic communication in various conditions, in particularly in cancer, where they can promote metastasis, immune evasion of cancer cells and angiogenesis (10–13), but also in other conditions including autoimmune diseases (14) and cardiovascular disorders (15). Therefore, circulating plasma microparticle proteomics can reveal biomarkers of various diseases as the basis for further diagnostic test development.The profiling of plasma microparticle proteomes initiated by Jin et al. in 2005, with the analysis of 16 samples using two-dimensional (2D)-gels followed by matrix assisted laser desorption ionization- time of flight (MALDI-TOF) MS analysis, which resulted in the identification of 83 proteins (16). In the following years, low resolution MS analysis of plasma microparticles reached up to 229 plasma microparticle proteins and high resolution MS analysis reached 458 proteins (all without false discovery rate (FDR)¹ correction)(17, 18). The latest and most comprehensive study of plasma microparticles proteome profiling was published in 2012 by Ostergaard et al., who analyzed 12 samples on the LTQ Orbitrap XL mass spectrometer and identified 536 proteins in total, after 1% FDR correction (19). Other studies have profiled the proteomes of microparticles and exosomes derived from various body fluids other than plasma, including urine (20), saliva (21), cerebral spinal fluid (22), breast milk (23), amniotic fluid (24), seminal fluid (25), and more. However, despite the dramatic reduction of the dynamic range of the analytes, so far it has not yet provided sufficient depth for biomarker discovery. Nevertheless, it has a good prospective for discovering biomarkers. For example, biochemical analysis of breast cancer patient leukocytes-derived microparticles correlated between increased tumor size and increased levels of carcinoembryonic antigen (CEA) and cancer antigen 15-3 (CA15-3), two well-known prognostic markers for colon and breast cancer, respectively (26).Combining all of the plasma proteomics approaches mentioned above, several prominent surveys of the human plasma proteome have been reported. The first large-scale collaborative study was conducted by the Human Proteome Organization (HuPO) group, which collectively identified 3020 proteins (7). These were later condensed to a list of 889 nonredundant proteins, after taking into account multiple hypotheses control with at least 95% confidence in protein identification (27). The Peptide Atlas team initially combined 91 studies, including the one conducted by HuPO, and altogether produced a list of 1929 proteins (28). Recently this team has elaborated their survey by assembling 127 studies (29) and reached the largest high-confidence list published so far of overall 3677 plasma proteins.In the current work we applied state of the art proteomics to study the microparticle proteome and developed the PROteomics of MIcroparticles with Super-SILAC Quantification (PROMIS-Quan) method, which combines deep plasma microparticle coverage of more than 3200 proteins in a single run, with dual-mode relative and absolute Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC) quantification. We demonstrated its utilization on samples of prostate cancer patients, and calculated the absolute amount of PSA, a well-known prostate cancer biomarker.     

Enhanced Sensitivity for Selected Reaction Monitoring Mass Spectrometry-based Targeted Proteomics Using a Dual Stage Electrodynamic Ion Funnel Interface

Selected reaction monitoring mass spectrometry (SRM-MS) is playing an increasing role in quantitative proteomics and biomarker discovery studies as a method for high throughput candidate quantification and verification. Although SRM-MS offers advantages in sensitivity and quantification compared with other MS-based techniques, current SRM technologies are still challenged by detection and quantification of low abundance proteins (e.g. present at ∼10 ng/ml or lower levels in blood plasma). Here we report enhanced detection sensitivity and reproducibility for SRM-based targeted proteomics by coupling a nanospray ionization multicapillary inlet/dual electrodynamic ion funnel interface to a commercial triple quadrupole mass spectrometer. Because of the increased efficiency in ion transmission, significant enhancements in overall signal intensities and improved limits of detection were observed with the new interface compared with the original interface for SRM measurements of tryptic peptides from proteins spiked into non-depleted mouse plasma over a range of concentrations. Overall, average SRM peak intensities were increased by ∼70-fold. The average level of detection for peptides also improved by ∼10-fold with notably improved reproducibility of peptide measurements as indicated by the reduced coefficients of variance. The ability to detect proteins ranging from 40 to 80 ng/ml within mouse plasma was demonstrated for all spiked proteins without the application of front-end immunoaffinity depletion and fractionation. This significant improvement in detection sensitivity for low abundance proteins in complex matrices is expected to enhance a broad range of SRM-MS applications including targeted protein and metabolite validation.Although mass spectrometry (MS)-based proteomics is a promising high throughput technology for biomarker discovery and validation (1–5), only a handful of cancer biomarkers have been approved by the United States Food and Drug Administration for clinical use in the last decade (6, 7). Assuming that low abundance biomarkers do exist in the biofluids to be studied, the success of biomarker discovery efforts primarily depends on the sensitivity, accuracy, and robustness of the measurement technologies; the quality and size of patient cohorts and clinical samples and execution within the context of an overall difficult and expensive path to clinical application that encompasses discovery, verification, and validation stages (1, 5, 8–10). A multiplexed assay platform increasingly considered for biomarker verification is selected reaction monitoring (SRM)¹ by tandem mass spectrometry using e.g. a triple quadrupole (QqQ) mass spectrometer to attain high throughput quantitative measurements of targeted proteins in complex matrices (1, 11, 12).SRM utilizes two stages of mass filtering by selecting a specific analyte ion of interest (precursor ion) in the first stage followed by a specific fragment ion derived from the precursor (fragment ion) filter in the second stage after collision-activated dissociation. Typically, several transitions (precursor/fragment ion pairs) are monitored for greater selectivity and confidence in a targeted peptide assay, and large numbers of peptides can be monitored during a single LC-MS/MS analysis. The two-stage mass selection by individual quadrupoles enables more rapid and continuous monitoring of specific ions derived from analytes of interest such as peptides and leads to significantly enhanced detection sensitivity and quantitative accuracy compared with broad (i.e. non-targeted) LC-MS or LC-MS/MS measurements (11, 12). Both the sensitivity and selectivity of SRM-MS make this technique well suited for the targeted detection and quantification of low abundance proteins in highly complex biofluids (13–16). The precision and reproducibility of SRM-based measurements of proteins in plasma across different laboratories have recently been assessed (17).Despite its promise, present SRM measurements still do not provide sufficient sensitivity for reliable detection and quantification of low abundance proteins in biofluids (e.g. present in plasma at ∼10 ng/ml or lower levels) primarily because of factors related to high sample complexity and the large dynamic range of relative protein abundances (7, 18, 19). Given sufficient selectivity, the sensitivity achievable is generally related to the peptide MS and MS/MS signal intensities obtained. One of the key factors limiting peptide MS intensities is the significant ion losses encountered between the electrospray ionization (ESI) source and the interface to the mass spectrometer. In typical LC-ESI-MS interfaces, the mass spectrometer inlet (e.g. heated capillary followed by a skimmer) presently provides total ion utilization and ion transmission efficiencies on the order of ∼1% (20) due to a combination of limited ion sampling from the atmospheric pressure ion source into the inlet and inefficient transmission of ions entering the first reduced pressure stage of the mass spectrometer.The electrodynamic ion funnel (21), which has been developed to efficiently capture, focus, and transmit ions to the high vacuum region of the mass spectrometer, is expected to provide a large benefit to SRM analyses. The original ion funnel interfaces, which operated at a maximum of ∼5 torr, were able to enhance signal intensities for a variety of MS analyzers (22–24) by replacing the inefficient skimmer interface. Although achieving near lossless ion transmission to high vacuum, losses at the atmospheric pressure interface went unmitigated. More recently, a high pressure ion funnel interface capable of operating at a pressure of ∼30 torr was introduced (25). The higher operating pressures accommodated greater gas loads and enabled more efficient ion sampling from atmospheric pressure through a multicapillary inlet. With a dual ion funnel interface comprising a high pressure ion funnel with a heated multicapillary inlet followed by a standard ion funnel operated at 1–2 torrs, highly efficient ion sampling from atmospheric pressure to high vacuum is readily achieved.In this study, we report the enhanced sensitivity and reproducibility of SRM-based targeted proteomics measurements achieved by implementing a dual stage electrodynamic ion funnel interface that incorporates a multicapillary inlet with a triple quadrupole mass spectrometer. A series of LC-SRM-MS measurements were made using mouse plasma samples spiked with various concentrations of tryptic peptides from five standard proteins to evaluate the improvements in detection sensitivity and reproducibility attained by this modified interface relative to a standard Thermo (single capillary inlet/skimmer) interface. A ∼10-fold improvement in the limit of detection (LOD) as well as improved measurement reproducibility was achieved.     

Quantification of Cardiovascular Biomarkers in Patient Plasma by Targeted Mass Spectrometry and Stable Isotope Dilution

Verification of candidate biomarkers requires specific assays to selectively detect and quantify target proteins in accessible biofluids. The primary objective of verification is to screen potential biomarkers to ensure that only the highest quality candidates from the discovery phase are taken forward into preclinical validation. Because antibody reagents for a clinical grade immunoassay often exist for a small number of candidates, alternative methodologies are required to credential new and unproven candidates in a statistically viable number of serum or plasma samples. Using multiple reaction monitoring coupled with stable isotope dilution MS, we developed quantitative, multiplexed assays in plasma for six proteins of clinical relevance to cardiac injury. The process described does not require antibodies for immunoaffinity enrichment of either proteins or peptides. Limits of detection and quantitation for each signature peptide used as surrogates for the target proteins were determined by the method of standard addition using synthetic peptides and plasma from a healthy donor. Limits of quantitation ranged from 2 to 15 ng/ml for most of the target proteins. Quantitative measurements were obtained for one to two signature peptides derived from each target protein, including low abundance protein markers of cardiac injury in the nanogram/milliliter range such as the cardiac troponins. Intra- and interassay coefficients of variation were predominantly <10 and 25%, respectively. The configured multiplex assay was then used to measure levels of these proteins across three time points in six patients undergoing alcohol septal ablation for hypertrophic obstructive cardiomyopathy. These results are the first demonstration of a multiplexed, MS-based assay for detection and quantification of changes in concentration of proteins associated with cardiac injury in the low nanogram/milliliter range. Our results also demonstrate that these assays retain the necessary precision, reproducibility, and sensitivity to be applied to novel and uncharacterized candidate biomarkers for verification of proteins in blood.Discovery of disease-specific biomarkers with diagnostic and prognostic utility has become an important challenge in clinical proteomics. In general, unbiased discovery experiments often result in the confident identification of thousands of proteins, hundreds of which may vary significantly between case and control samples in small discovery studies. However, because of the stochastic sampling of proteomes in discovery “omics” experiments, a large fraction of the protein biomarkers “discovered” in these experiments are false positives arising from biological or technical variability. Clearly discovery omics experiments do not lead to biomarkers of immediate clinical utility but rather produce candidates that must be qualified and verified in larger sample sets than were used for discovery (1).Traditional, clinical validation of biomarkers has relied primarily on immunoassays because of their specificity and sensitivity for the target analyte and high throughput capability. However, antibody reagents for a clinical grade immunoassay often only exist for a short list of candidates. The development of a reliable sandwich immunoassay for one target protein is expensive, has a long development time, and is dependent upon the generation of high quality protein antibodies. For the large majority of new, unproven candidate biomarkers, an intermediate verification technology is required that has shorter assay development time lines, lower assay cost, and effective multiplexing of dozens of candidates in low sample volumes. Ideally the approach should be capable of analyzing hundreds of samples of serum or plasma with good precision. The desired outcome of verification is a small number of highly credentialed candidates suitable for traditional preclinical and clinical validation studies.Multiple reaction monitoring (MRM)¹ coupled with stable isotope dilution (SID) MS has recently been shown to be well suited for direct quantification of proteins in plasma (2–4) and has emerged as the core technology for candidate biomarker verification. MRM assays can be highly multiplexed such that a moderate number of candidate proteins (in the range of 10–50) can be simultaneously targeted and measured in the statistically viable number of patient samples required for verification (hundreds of serum samples). However, sensitivity for unambiguous detection and quantification of proteins by MS-based assays is often constrained by sample complexity, particularly when the measurements are being made in complex fluids such as plasma.Many biomarkers of current clinical importance, such as prostate-specific antigen and the cardiac troponins, reside in the low nanogram/milliliter range in plasma and, until recently, have been inaccessible by non-antibody approaches. Our laboratory has recently shown for the first time that a combination of abundant protein depletion with limited fractionation at the peptide level prior to SID-MRM-MS provides robust limits of quantitation (LOQs) in the 1–20 ng/ml range with coefficient of variation (CV) of 10–20% at the LOQ for proteins in plasma (3).Here we demonstrate that this work flow can be extended to configure assays for a number of known markers of cardiovascular disease and, more importantly, can be deployed to measure their concentrations in clinical samples. We modeled a verification study comprising six patients undergoing alcohol septal ablation treatment for hypertrophic obstructive cardiomyopathy, a human model of “planned” myocardial infarction (PMI), and obtained targeted, quantitative measurements for moderate to low concentrations of cardiac biomarkers in plasma. This work provides additional evidence that MS-based assays can be configured and applied to verification of new protein targets for which high quality antibody reagents are not available.     

Characterization of the Human Cervical Mucous Proteome

Introduction

Cervical cancer is among the most common cancers in women worldwide. Discovery of biomarkers for the early detection of cervical cancer would improve current screening practices and reduce the burden of disease.

Objective

In this study, we report characterization of the human cervical mucous proteome as the first step towards protein biomarker discovery.

Methods

The protein composition was characterized using one- and two-dimensional gel electrophoresis, and liquid chromatography coupled with mass spectrometry. We chose to use this combination of traditional biochemical techniques and proteomics to allow a more comprehensive analysis.

Results and Conclusion

A total of 107 unique proteins were identified, with plasma proteins being most abundant. These proteins represented the major functional categories of metabolism, immune response, and cellular transport. Removal of high molecular weight abundant proteins by immunoaffinity purification did not significantly increase the number of protein spots resolved. We also analyzed phosphorylated and glycosylated proteins by fluorescent post-staining procedures. The profiling of cervical mucous proteins and their post-translational modifications can be used to further our understanding of the cervical mucous proteome.     

Multiplexed Quantitation of Endogenous Proteins in Dried Blood Spots by Multiple Reaction Monitoring - Mass Spectrometry

Dried blood spot (DBS) sampling, coupled with multiple reaction monitoring mass spectrometry (MRM-MS), is a well-established approach for quantifying a wide range of small molecule biomarkers and drugs. This sampling procedure is simpler and less-invasive than those required for traditional plasma or serum samples enabling collection by minimally trained personnel. Many analytes are stable in the DBS format without refrigeration, which reduces the cost and logistical challenges of sample collection in remote locations. These advantages make DBS sample collection desirable for advancing personalized medicine through population-wide biomarker screening. Here we expand this technology by demonstrating the first multiplexed method for the quantitation of endogenous proteins in DBS samples. A panel of 60 abundant proteins in human blood was targeted by monitoring proteotypic tryptic peptides and their stable isotope-labeled analogs by MRM. Linear calibration curves were obtained for 40 of the 65 peptide targets demonstrating multiple proteins can be quantitatively extracted from DBS collection cards. The method was also highly reproducible with a coefficient of variation of <15% for all 40 peptides. Overall, this assay quantified 37 proteins spanning a range of more than four orders of magnitude in concentration within a single 25 min LC/MRM-MS analysis. The protein abundances of the 33 proteins quantified in matching DBS and whole blood samples showed an excellent correlation, with a slope of 0.96 and an R² value of 0.97. Furthermore, the measured concentrations for 80% of the proteins were stable for at least 10 days when stored at −20 °C, 4 °C and 37 °C. This work represents an important first step in evaluating the integration of DBS sampling with highly-multiplexed MRM for quantitation of endogenous proteins.Dried Blood Spot (DBS)¹ samples have many advantages over blood serum or plasma and are the preferred clinical sample for newborn screening for metabolic diseases (1, 2). These samples are collected by pricking a newborn''s heel and spotting a drop of blood onto specially designed filter paper collection cards. Samples are then dried under ambient conditions and are usually stored with desiccant at room temperature until analysis. This sampling procedure is simpler and less invasive then intravenous blood draws, which require a trained phlebotomist. Not surprisingly, the majority of adult patients prefer the small lancet used in finger-prick blood sampling methods to the larger needles used in intravenous blood draws (3, 4). Unlike plasma or serum samples, which consume ≥250 μl of blood and must be centrifuged within an hour of collection, DBS samples can be prepared using a volume of only 10 μl, and do not require any specialized equipment at the collection site (5). The simplicity and reduced safety risks associated with DBS sampling enables collection by minimally trained staff or by the patients themselves. In addition, many analytes are stable in the DBS format at room temperature, reducing sample transportation and storage costs, as well as the impact on the environment. Finally, DBS samples are safer to transport and are considered exempt from dangerous goods regulations (6, 7). These advantages make DBS sampling very attractive for advancing personalized medicine and population-based biomarker research (8).Numerous biomolecular targets covering genomics, metabolomics, and proteomics applications have been quantified in DBS samples using a wide array of analytical techniques (9). The most common clinical application of DBS sampling is screening newborns for metabolomics disorders by targeting small molecule biomarkers. Early screening programs relied on bacterial inhibition assays and later immunoassays, both of which required a different assay for each target of interest (2). However, the time and cost required to perform each assay independently has limited the number of diseases that could be screened nationwide to only a handful. In addition, a single biomarker often lacked the specificity to produce a definitive diagnosis, requiring extensive secondary testing. Hemoglobin is the only protein that is commonly targeted in DBS samples, and primary screening is accomplished by high-performance liquid chromatography (HPLC) or isoelectric focusing (IEF) methods (2). Similar to small-molecule screening methods, these approaches are low-throughput and are not amendable to multiplexing with additional protein targets. In newborn screening programs, these challenges associated with small molecule analysis were overcome with the introduction of multiple reaction monitoring mass spectrometry (MRM-MS) into the clinical laboratories (1, 10). The specificity of MRM enables hundreds of analytes to be monitored during a single experiment to facilitate the development of highly multiplexed assays. The addition of stable isotope-labeled internal standards (SIS) enables the acquisition of highly reproducible results across a variety of instrumentation at different institutions. It is now common for 20–30 small molecule targets including amino acids, fatty acid acylcarnitines, and organic acid acylcarnitines to be analyzed by flow injection MRM-MS, at a cost of $10–20 USD per patient sample (11). Expansion of the screening panel to include additional small-molecule biomarkers on an existing platform may cost less than $1 each. In addition to newborn screening, DBS sampling combined with MS is also gaining acceptance in small-molecule drug development (12, 13). Here the collection of smaller blood volumes allows serial sampling from mice reducing the total number of animals required to generate preclinical toxicology and pharmacokinetic data (5).Despite the successful use of DBS samples in MS-based experiments for small molecule analysis, there have been few reports of using this technology for protein targets (13). Daniel and coworkers reported a screening method for identifying β-thalassemia using the well-known biomarker HbA₂, a hemoglobin variant composed of two alpha- and two delta-globin subunits (14). Proteins were extracted in an aqueous solution, digested with trypsin in 30 min and infused for MRM-MS analysis. Multiple hemoglobin peptides were targeted to measure the abundance of the delta-globin chain, using peptides from the beta-globin chain as an internal standard. This ratio correlated well with the abundance of intact HbA₂ as determined by a well-established HPLC method. The shorter acquisition time and the increased specificity of the MS-based method showed promise for improving population-wide screening. Boemer et al. used a similar flow injection MRM-MS strategy to screen newborns for hemoglobin variants associated with sickle cell disease (15). They analyzed more than 2000 DBS samples by targeting tryptic peptides that were unique to four different beta-globin mutations and compared their results with a standard IEF method that measured the intact proteins obtained from corresponding whole blood samples. Their flow injection MRM approach was able to identify the correct phenotype for all targeted variants. Recently, deWilde et al. reported a method for screening newborn DBS samples for ceruloplasmin, a protein linked to Wilson''s disease (16). Their method combined SIS peptides with LC/MRM-MS and produced results similar to those from an immunoassay for the analysis of seven patient samples. The monitoring of a therapeutic protein in rat blood was demonstrated with Kehler et al. to evaluate the suitability of this approach for supporting preclinical trials (17). Finally, a multiplexed approach was presented by Sleczka et al. for the simultaneous quantitation of two therapeutic proteins in spiked DBS samples collected from several animal models (18).In all previous methods, only one to two proteins were targeted in DBS samples and therefore the true multiplexing capabilities of MRM were not realized. MRM-based methods using SIS peptides have already proven proficient at highly multiplexed quantitation of proteins in plasma and serum samples (19–21). Our current work demonstrates the potential for integrating DBS sampling with LC/MRM-MS for highly multiplexed quantitation of endogenous proteins. Many of the 60 proteins that we have targeted have been cleared or approved by FDA, and are already being analyzed one at a time in clinical laboratories. The assay developed in this study includes a highly reproducible method for extracting multiple proteins from DBS samples followed by trypsin digestion and surrogate peptides, along with their SIS analogs, were analyzed by a standard-flow LC/MRM-MS platform that has previously been shown to give accurate, sensitive, and robust analysis of proteotypic peptides in human plasma (21, 22). The quantitative results from whole blood and the corresponding DBS samples were compared, and the integrity of DBS samples stored under various temperatures has been evaluated.     

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)).     

An integrated quantification method to increase the precision,robustness, and resolution of protein measurement in human plasma samples

Background

Current quantification methods for mass spectrometry (MS)-based proteomics either do not provide sufficient control of variability or are difficult to implement for routine clinical testing.

Results

We present here an integrated quantification (InteQuan) method that better controls pre-analytical and analytical variability than the popular quantification method using stable isotope-labeled standard peptides (SISQuan). We quantified 16 lung cancer biomarker candidates in human plasma samples in three assessment studies, using immunoaffinity depletion coupled with multiple reaction monitoring (MRM) MS. InteQuan outperformed SISQuan in precision in all three studies and tolerated a two-fold difference in sample loading. The three studies lasted over six months and encountered major changes in experimental settings. Nevertheless, plasma proteins in low ng/ml to low μg/ml concentrations were measured with a median technical coefficient of variation (CV) of 11.9% using InteQuan. The corresponding median CV using SISQuan was 15.3% after linear fitting. Furthermore, InteQuan surpassed SISQuan in measuring biological difference among clinical samples and in distinguishing benign versus cancer plasma samples.

Conclusions

We demonstrated that InteQuan is a simple yet robust quantification method for MS-based quantitative proteomics, especially for applications in biomarker research and in routine clinical testing.

Electronic supplementary material

The online version of this article (doi:10.1186/1559-0275-12-3) contains supplementary material, which is available to authorized users.     

Current progress in protein profiling of complex samples

Accurate cancer biomarkers are needed for early detection, disease classification, prediction of therapeutic response and monitoring treatment. While there appears to be no shortage of candidate biomarker proteins, a major bottleneck in the biomarker pipeline continues to be their verification by enzyme linked immunosorbent assays. Multiple reaction monitoring (MRM), also known as selected reaction monitoring, is a targeted mass spectrometry approach to protein quantitation and is emerging to bridge the gap between biomarker discovery and clinical validation. Highly multiplexed MRM assays are readily configured and enable simultaneous verification of large numbers of candidates facilitating the development of biomarker panels which can increase specificity. This review focuses on recent applications of MRM to the analysis of plasma and serum from cancer patients for biomarker verification. The current status of this approach is discussed along with future directions for targeted mass spectrometry in clinical biomarker validation.     

An Automated and Multiplexed Method for High Throughput Peptide Immunoaffinity Enrichment and Multiple Reaction Monitoring Mass Spectrometry-based Quantification of Protein Biomarkers

There is an urgent need for quantitative assays in verifying and validating the large numbers of protein biomarker candidates produced in modern “-omics” experiments. Stable isotope standards with capture by anti-peptide antibodies (SISCAPA) has shown tremendous potential to meet this need by combining peptide immunoaffinity enrichment with quantitative mass spectrometry. In this study, we describe three significant advances to the SISCAPA technique. First, we develop a method for an automated magnetic bead-based platform capable of high throughput processing. Second, we implement the automated method in a multiplexed SISCAPA assay (nine targets in one assay) and assess the performance characteristics of the multiplexed assay. Using the automated, multiplexed platform, we demonstrate detection limits in the physiologically relevant ng/ml range (from 10 μl of plasma) with sufficient precision (median coefficient of variation, 12.6%) for quantifying biomarkers. Third, we demonstrate that enrichment of peptides from larger volumes of plasma (1 ml) can extend the limits of detection to the low pg/ml range of protein concentration. The method is generally applicable to any protein or biological specimen of interest and holds great promise for analyzing large numbers of biomarker candidates.The current gold standard for quantifying protein biomarkers is the ELISA. A well functioning ELISA can be run at high throughput and has excellent sensitivity; however, the cost associated with development is very high, the lead time is very long, and the failure rate can be high. In addition, sandwich immunoassays are subject to potential interference from endogenous antibodies (1). Unfortunately, there are no quantitative assays available for the majority of biomarker candidates, and a considerable investment is required to generate assays de novo, creating a bottleneck in the biomarker pipeline (2, 3).A technique that has shown potential for bridging the gap between discovery and validation of biomarkers is stable isotope standards with capture by anti-peptide antibodies (SISCAPA)¹ (4) coupled to multiple reaction monitoring (MRM) MS. SISCAPA has several advantages over other immunoassays in that the mass spectrometer provides excellent specificity for the analyte of interest; the sample (including endogenous immunoglobulins) is digested to peptides, avoiding potential interference from endogenous antibodies; and precise, relative quantification is possible via the use of an internal standard. Additionally, although it is very difficult to combine multiple analytes into one assay (i.e. multiplex) using ELISAs, SISCAPA assays can in theory be highly multiplexed as many analytes can be measured from a single enrichment step. To date, individual SISCAPA assays have been successfully configured to a number of analytes (4–9), and up to three peptides have been enriched simultaneously (7, 8). In this study, we sought to advance the utility of SISCAPA for testing large numbers of biomarker candidates in large numbers of patient samples by automating the method to improve throughput and performance, testing the performance of multiplexing analytes, and improving sensitivity.