Use of an immunoaffinity-mass spectrometry-based approach for the quantification of protein biomarkers from serum samples of lung cancer patients

A simplified lateral flow immunosensor for the assay of carcinoembryonic antigen in low-resource settings

Carcinoembryonic antigen (CEA) is a glycoprotein widely used as a tumor marker. In this work, a colorimetric lateral flow immunosensor is developed for rapid and low-cost quantification of CEA in human blood serum. The immunosensor consists of a glass fiber sample/conjugation pad, a nitrocellulose detection pad and a cellulose absorption pad. The detection is based on a sandwich immunoreaction: the sample/conjugation pad is modified with gold nanoparticles (GNPs)-labeled anti-CEA conjugate probes which bind to the CEA target molecules in the sample and the complexes are captured at capture anti-CEA immobilized at the test line. The color intensity of the test line, measured from a scanned image of the strip, is related to the CEA concentration in the sample. The different assay parameters are studied in detail. The linearity holds from 1.25 to 640 ng mL-1 of CEA, the instrumental and visual limits of detection are 0.45 and 0.63 ng mL-1, respectively, and the total assay time is 15 min. The specificity of the immunoassay versus other cancer biomarkers is satisfactory. The recovery in samples of human serum spiked with CEA is in the range of 81-118% and the coefficient of variation of the method is ≤10%. Results obtained with the lateral flow immunosensor correlated well with a reference radioimmunoassay method (R2 = 0.99). This immunosensor can be readily applied to CEA monitoring at the point-of-care (POC) or in resource-limited settings thanks to its low-cost and simplicity.

Multiplexed quantitative proteomics in prostate cancer biomarker development

Prostate cancer (PCa) is the most common non-skin cancer among men in the United States. However, the widely used protein biomarker in PCa, prostate-specific antigen (PSA), while useful for initial detection, its use alone cannot detect aggressive PCa and can lead to overtreatment. This chapter provides an overview of PCa protein biomarker development. It reviews the state-of-the-art liquid chromatography-mass spectrometry-based proteomics technologies for PCa biomarker development, such as enhancing the detection sensitivity of low-abundance proteins through antibody-based or antibody-independent protein/peptide enrichment, enriching post-translational modifications such as glycosylation as well as information-rich extracellular vesicles, and increasing accuracy and throughput using advanced data acquisition methodologies. This chapter also summarizes recent PCa biomarker validation studies that applied those techniques in diverse specimen types, including cell lines, tissues, proximal fluids, urine, and blood, developing novel protein biomarkers for various clinical applications, including early detection and diagnosis, prognosis, and therapeutic intervention of PCa.

Diagnostic Potential of Serum Glycome Analysis in Lung Cancer: A Glycopattern Study

Lung cancer is the leading cause of cancer-related death, with high morbidity and mortality rates due to the lack of reliable methods for diagnosing lung cancer at an early stage. Low-dose computed tomography can help detect abnormal areas in the lungs, but only 16% of cases are diagnosed early. Tests for lung cancer markers are often employed to determine genetic expression or mutations in lung carcinogenesis. Serum glycome analysis is a promising new method for early lung cancer diagnosis as glycopatterns exhibit significant differences in lung cancer patients. In this study, we employed a solid-phase chemoenzymatic method to systematically compare glycopatterns in benign cases, adenocarcinoma before and after surgery, and advanced stages of adenocarcinoma. Our findings indicate that serum high-mannose levels are elevated in both benign cases and adenocarcinoma, while complex N-glycans, including fucose and 2,6-linked sialic acid, are downregulated in the serum. Subsequently, we developed an algorithm that utilizes 16 altered N-glycans, 7 upregulated and 9 downregulated, to generate a score based on their intensity. This score can predict the stages of cancer progression in patients through glycan characterization. This methodology offers a potential means of diagnosing lung cancer through serum glycome analysis.

Liquid Biopsy Snapshots of Key Phosphoproteomic Pathways in Lung Cancer Patients for Diagnosis and Therapy Monitoring

Phosphorylation is a post-translational modification in proteins that changes protein conformation and activity for regulating signal transduction pathways. This mechanism is frequently impaired in lung cancer, resulting in permanently active constitutive phosphorylation to initiate tumor growth and/or reactivate pathways in response to therapy. We developed a multiplexed phosphoprotein analyzer chip (MPAC) that enables rapid (detection time: 5 min) and sensitive (LOD: 2 pg/μL) detection of protein phosphorylation and presents phosphoproteomic profiling of major phosphorylation pathways in lung cancer. We monitored phosphorylated receptors and downstream proteins involved in mitogen-activated protein kinase (MAPK) and PI3K/AKT/mTOR pathways in lung cancer cell line models and patient-derived extracellular vesicles (EV). Using kinase inhibitor drugs in cell line models, we found that the drug can inhibit the phosphorylation and/or activation of the kinase pathway. We then generated a phosphorylation heatmap by EV phosphoproteomic profiling of plasma samples isolated from 36 lung cancer patients and 8 noncancer individuals. The heatmap showed a clear difference between the noncancer and cancer samples and identify the specific proteins that are activated in the cancer samples. Our data also showed that MPAC could monitor immunotherapy responses by assessment of the phosphorylation states of the proteins, particularly for PD-L1. Finally, with a longitudinal study, we found that the phosphorylation levels of the proteins were indicative of a positive response to therapy. We believe that this study will lead to personalized treatment by providing a better understanding of the active and resistant pathways and will provide a tool for selecting combined and targeted therapies for precision medicine.

On-line duplex molecularly imprinted solid-phase extraction for analysis of low-abundant biomarkers in human serum by liquid chromatography-tandem mass spectrometry

In the present work, a pair of molecularly imprinted polymers (MIPs) targeting distinct peptide targets were packed into trap columns and combined for automated duplex analysis of two low abundant small cell lung cancer biomarkers (neuron-specific enolase [NSE] and progastrin-releasing peptide [ProGRP]). Optimization of the on-line molecularly imprinted solid-phase extraction (MISPE) protocol ensured that the MIPs had the necessary affinity and selectivity towards their respective signature peptide targets - NLLGLIEAK (ProGRP) and ELPLYR (NSE) - in serum. Two duplex formats were evaluated: a physical mixture of the two MIPs (1:1 w/w ratio) inside a single trap column, and two separate MIP trap columns connected in series. Both duplex formats enabled the extraction of the peptides from serum. However, the trap columns in series gave superior extraction efficiency (85.8±3.8% and 49.1±6.7% for NLLGLIEAK and ELPLYR, respectively). The optimized protocol showed satisfactory intraday (RSD≤23.4 %) and interday (RSD≤14.6%) precision. Duplex analysis of NSE and ProGRP spiked into digested human serum was linear (R²≥0.98) over the disease range (0.3-30 nM). The estimated limit of detection (LOD) and limit of quantification (LOQ) were 0.11 nM and 0.37 nM, respectively, for NSE, and 0.06 nM and 0.2 nM, respectively, for ProGRP. Both biomarkers were determined at clinically relevant levels. To the best of our knowledge, the present work is the first report of an automated MIP duplex biomarker analysis. It represents a proof of concept for clinically viable duplex analysis of low abundant biomarkers present in human serum or other biofluids.

Evaluation of Aptamers as Affinity Reagents for an Enhancement of SRM-Based Detection of Low-Abundance Proteins in Blood Plasma

Selected reaction monitoring (SRM) is a mass spectrometric technique characterized by the exceptionally high selectivity and sensitivity of protein detection. However, even with this technique, the quantitative detection of low- and ultralow-abundance proteins in blood plasma, which is of great importance for the search and verification of novel protein disease markers, is a challenging task due to the immense dynamic range of protein abundance levels. One approach used to overcome this problem is the immunoaffinity enrichment of target proteins for SRM analysis, employing monoclonal antibodies. Aptamers appear as a promising alternative to antibodies for affinity enrichment. Here, using recombinant protein SMAD4 as a model target added at known concentrations to human blood plasma and SRM as a detection method, we investigated a relationship between the initial amount of the target protein and its amount in the fraction enriched with SMAD4 by an anti-SMAD4 DNA-aptamer immobilized on magnetic beads. It was found that the aptamer-based enrichment provided a 30-fold increase in the sensitivity of SRM detection of SMAD4. These results indicate that the aptamer-based affinity enrichment of target proteins can be successfully employed to improve quantitative detection of low-abundance proteins by SRM in undepleted human blood plasma.

Abundant plasma protein depletion using ammonium sulfate precipitation and Protein A affinity chromatography

Plasma is a highly valuable resource for biomarker research since it is easy obtainable and contains a high amount of information on patient health status. Although advancements in the field of proteomics enabled analysis of the plasma proteome, identification of low abundant proteins remains challenging due to high complexity and large dynamic range. In order to reduce the dynamic range of protein concentrations, a tandem depletion technique consisting of ammonium sulfate precipitation and Protein A affinity chromatography was developed. Using this method, 50% of albumin, together with other high abundant proteins such as alpha-1-antitrypsin, was depleted from the plasma sample at 20% to 40% ammonium sulfate saturation levels. In combination with immunoglobulin removal using a Protein A column, this technique delivered up to 40 new low- to medium abundance protein identifications when performing a shotgun mass spectrometry analysis. Compared to non-depleted plasma, 270 additional protein spots were observed during 2D-PAGE analysis. These results illustrate that this tandem depletion method is equivalent to commercial kits which are based on immune-affinity chromatography. Moreover, this method using Protein A immunoglobulin depletion was shown to be highly reproducible and a minimal amount of non-target proteins was depleted. The combination of ammonium sulfate precipitation and Protein A affinity chromatography offers a low cost, efficient, straightforward and reproducible alternative to commercial kits, with proteins remaining in native conformation, allowing protein activity and protein interaction studies.

Peptide and Protein Quantification Using Automated Immuno-MALDI (iMALDI)

Mass spectrometry (MS) is one of the most commonly used technologies for quantifying proteins in complex samples, with excellent assay specificity as a result of the direct detection of the mass-to-charge ratio of each target molecule. However, MS-based proteomics, like most other analytical techniques, has a bias towards measuring high-abundance analytes, so it is challenging to achieve detection limits of low ng/mL or pg/mL in complex samples, and this is the concentration range for many disease-relevant proteins in biofluids such as human plasma. To assist in the detection of low-abundance analytes, immuno-enrichment has been integrated into the assay to concentrate and purify the analyte before MS measurement, significantly improving assay sensitivity. In this work, the immuno- Matrix-Assisted Laser Desorption/Ionization (iMALDI) technology is presented for the quantification of proteins and peptides in biofluids, based on immuno-enrichment on beads, followed by MALDI-MS measurement without prior elution. The anti-peptide antibodies are functionalized on magnetic beads, and incubated with samples. After washing, the beads are directly transferred onto a MALDI target plate, and the signals are measured by a MALDI-Time of Flight (MALDI-TOF) instrument after the matrix solution has been applied to the beads. The sample preparation procedure is simplified compared to other immuno-MS assays, and the MALDI measurement is fast. The whole sample preparation is automated with a liquid handling system, with improved assay reproducibility and higher throughput. In this article, the iMALDI assay is used for determining the peptide angiotensin I (Ang I) concentration in plasma, which is used clinically as readout of plasma renin activity for the screening of primary aldosteronism (PA).

Sequential Validation of Blood-Based Protein Biomarker Candidates for Early-Stage Pancreatic Cancer

Background

CA19-9, which is currently in clinical use as a pancreatic ductal adenocarcinoma (PDAC) biomarker, has limited performance in detecting early-stage disease. We and others have identified protein biomarker candidates that have the potential to complement CA19-9. We have carried out sequential validations starting with 17 protein biomarker candidates to determine which markers and marker combination would improve detection of early-stage disease compared with CA19-9 alone.

Methods

Candidate biomarkers were subjected to enzyme-linked immunosorbent assay based sequential validation using independent multiple sample cohorts consisting of PDAC cases (n = 187), benign pancreatic disease (n = 93), and healthy controls (n = 169). A biomarker panel for early-stage PDAC was developed based on a logistic regression model. All statistical tests for the results presented below were one-sided.

Results

Six out of the 17 biomarker candidates and CA19-9 were validated in a sample set consisting of 75 PDAC patients, 27 healthy subjects, and 19 chronic pancreatitis patients. A second independent set of 73 early-stage PDAC patients, 60 healthy subjects, and 74 benign pancreatic disease patients (combined validation set) yielded a model that consisted of TIMP1, LRG1, and CA19-9. Additional blinded testing of the model was done using an independent set of plasma samples from 39 resectable PDAC patients and 82 matched healthy subjects (test set). The model yielded areas under the curve (AUCs) of 0.949 (95% confidence interval [CI] = 0.917 to 0.981) and 0.887 (95% CI = 0.817 to 0.957) with sensitivities of 0.849 and 0.667 at 95% specificity in discriminating early-stage PDAC vs healthy subjects in the combined validation and test sets, respectively. The performance of the biomarker panel was statistically significantly improved compared with CA19-9 alone (P < .001, combined validation set; P = .008, test set).

Conclusion

The addition of TIMP1 and LRG1 immunoassays to CA19-9 statistically significantly improves the detection of early-stage PDAC.

A Timely Shift from Shotgun to Targeted Proteomics and How It Can Be Groundbreaking for Cancer Research

The fact that cancer is a leading cause of death all around the world has naturally sparked major efforts in the pursuit of novel and more efficient biomarkers that could better serve as diagnostic tools, prognostic predictors, or therapeutical targets in the battle against this type of disease. Mass spectrometry-based proteomics has proven itself as a robust and logical alternative to the immuno-based methods that once dominated the field. Nevertheless, intrinsic limitations of classic proteomic approaches such as the natural gap between shotgun discovery-based methods and clinically applicable results have called for the implementation of more direct, hypothesis-based studies such as those made available through targeted approaches, that might be able to streamline biomarker discovery and validation as a means to increase survivability of affected patients. In fact, the paradigm shifting potential of modern targeted proteomics applied to cancer research can be demonstrated by the large number of advancements and increasing examples of new and more useful biomarkers found during the course of this review in different aspects of cancer research. Out of the many studies dedicated to cancer biomarker discovery, we were able to devise some clear trends, such as the fact that breast cancer is the most common type of tumor studied and that most of the research for any given type of cancer is focused on the discovery diagnostic biomarkers, with the exception of those that rely on samples other than plasma and serum, which are generally aimed toward prognostic markers. Interestingly, the most common type of targeted approach is based on stable isotope dilution-selected reaction monitoring protocols for quantification of the target molecules. Overall, this reinforces that notion that targeted proteomics has already started to fulfill its role as a groundbreaking strategy that may enable researchers to catapult the number of viable, effective, and validated biomarkers in cancer clinical practice.

Clinical Validation of a Serum Protein Panel (FLNA, FLNB and KRT19) for Diagnosis of Prostate Cancer

This study reports on the development of a novel serum protein panel of three prostate cancer biomarkers, Filamin A, Filamin B and Keratin-19 (FLNA, FLNB and KRT19) using multivariate models for disease screening and prognosis. ELISA and IPMRM (LC-MS/MS) based assays were developed and analytically validated by quantitative measurements of the biomarkers in serum. Retrospectively collected and clinically annotated serum samples with PSA values and Gleason scores were analyzed from subjects who underwent prostate biopsy, and showed no evidence of cancer with or without indication of prostatic hyperplasia, or had a definitive pathology diagnosis of prostatic adenocarcinoma. Probit linear regression models were used to combine the analytes into score functions to address the following clinical questions: does the biomarker test augment PSA for population screening? Can aggressive disease be differentiated from lower risk disease, and can the panel discriminate between prostate cancer and benign prostate hyperplasia? Modelling of the data showed that the new prostate biomarkers and PSA in combination were better than PSA alone in identifying prostate cancer, improved the prediction of high and low risk disease, and improved prediction of cancer versus benign prostate hyperplasia.

Proteomic profiling predicts drug response to novel targeted anticancer therapeutics

Most recently approved anti-cancer drugs by the US FDA are targeted therapeutic agents and this represents an important trend for future anticancer therapy. Unlike conventional chemotherapy that rarely considers individual differences, it is crucial for targeted therapies to identify the beneficial subgroup of patients for the treatment. Currently, genomics and transcriptomics are the major 'omic' analytics used in studies of drug response prediction. However, proteomic profiling excels both in its advantages of directly detecting an instantaneous dynamic of the whole proteome, which contains most current diagnostic markers and therapeutic targets. Moreover, proteomic profiling improves understanding of the mechanism for drug resistance and helps finding optimal combination therapy. This article reviews the recent success of applications of proteomic analytics in predicting the response to targeted anticancer therapeutics, and discusses the potential avenues and pitfalls of proteomic platforms and techniques used most in the field.

Automated Microchromatography Enables Multiplexing of Immunoaffinity Enrichment of Peptides to Greater than 150 for Targeted MS-Based Assays

Immunoaffinity enrichment of peptides coupled with analysis by stable isotope dilution multiple reaction mass spectrometry has been shown to have analytical performance and detection limits suitable for many biomarker verification studies and biological applications. Prior studies have shown that antipeptide antibodies can be multiplexed up to 50 in a single assay without significant loss of performance. Achieving higher multiplex levels is relevant to all studies involving precious biological material as this minimizes the amount of sample that must be consumed to measure a given set of analytes and reduces the assay cost per analyte. Here we developed automated methods employing the Agilent AssayMAP Bravo microchromatography platform and used these methods to characterize the performance of immunoaffinity enrichment of peptides up to multiplex levels of 172. Median capture efficiency for the target peptides remained high (88%) even at levels of 150-plex and declined to 70% at 172-plex compared to antibody performance observed at standard lower multiplex levels (n = 25). Subsequently, we developed and analytically characterized a multiplexed immuno-multiple reaction monitoring-mass spectrometry (immuno-MRM-MS) assay (n = 110) and applied it to measure candidate protein biomarkers of cardiovascular disease in plasma of patients undergoing planned myocardial infarction. The median lower limit of detection of all peptides was 71.5 amol/μL (nM), and the coefficient of variation (CV) was less than 15% at the lower limit of quantification. The results demonstrate that high multiplexed immuno-MRM-MS assays are readily achievable using the optimized sample processing and peptide capture methods described here.

Complexity reduction of clinical samples for routine mass spectrometric analysis

The precise measurement of protein abundance levels in highly complex biological samples such as plasma remains challenging. The wide range of protein concentrations impairs the detection of low-abundant species and the high number of peptide components to analyze results in interferences leading to erroneous quantitative results. The advances in MS instrumentation, with improved selectivity and sensitivity, partially address these issues, but sample preparation techniques remain the pivotal element to obtain robust routine mass spectrometric assays with a low LOD. A number of methodologies have been proposed and refined over the past two decades to reduce the range of protein concentrations and the number of peptide components. Whereas most of the methods have proven their utility for discovery studies, only a few are actually applicable to routine quantitative studies. In this account, common protein- and peptide-based fractionation methods are discussed, and illustrated with practical examples, with a focus on methods suited for clinical samples scheduled for biomarker validation assays and subsequent routine clinical mass spectrometric analyses.

Accuracy and Reproducibility in Quantification of Plasma Protein Concentrations by Mass Spectrometry without the Use of Isotopic Standards

Background

Quantitative proteomic analysis with mass spectrometry holds great promise for simultaneously quantifying proteins in various biosamples, such as human plasma. Thus far, studies addressing the reproducible measurement of endogenous protein concentrations in human plasma have focussed on targeted analyses employing isotopically labelled standards. Non-targeted proteomics, on the other hand, has been less employed to this end, even though it has been instrumental in discovery proteomics, generating large datasets in multiple fields of research.

Results

Using a non-targeted mass spectrometric assay (LCMS^E), we quantified abundant plasma proteins (43 mg/mL—40 ug/mL range) in human blood plasma specimens from 30 healthy volunteers and one blood serum sample (ProteomeXchange: PXD000347). Quantitative results were obtained by label-free mass spectrometry using a single internal standard to estimate protein concentrations. This approach resulted in quantitative results for 59 proteins (cut off ≥11 samples quantified) of which 41 proteins were quantified in all 31 samples and 23 of these with an inter-assay variability of ≤ 20%. Results for 7 apolipoproteins were compared with those obtained using isotope-labelled standards, while 12 proteins were compared to routine immunoassays. Comparison of quantitative data obtained by LCMS^E and immunoassays showed good to excellent correlations in relative protein abundance (r = 0.72–0.96) and comparable median concentrations for 8 out of 12 proteins tested. Plasma concentrations of 56 proteins determined by LCMS^E were of similar accuracy as those reported by targeted studies and 7 apolipoproteins quantified by isotope-labelled standards, when compared to reference concentrations from literature.

Conclusions

This study shows that LCMS^E offers good quantification of relative abundance as well as reasonable estimations of concentrations of abundant plasma proteins.

Applications of targeted proteomics in systems biology and translational medicine

Biological systems are composed of numerous components of which proteins are of particularly high functional significance. Network models are useful abstractions for studying these components in context. Network representations display molecules as nodes and their interactions as edges. Because they are difficult to directly measure, functional edges are frequently inferred from suitably structured datasets consisting of the accurate and consistent quantification of network nodes under a multitude of perturbed conditions. For the precise quantification of a finite list of proteins across a wide range of samples, targeted proteomics exemplified by selected/multiple reaction monitoring (SRM, MRM) mass spectrometry has proven useful and has been applied to a variety of questions in systems biology and clinical studies. Here, we survey the literature of studies using SRM-MS in systems biology and clinical proteomics. Systems biology studies frequently examine fundamental questions in network biology, whereas clinical studies frequently focus on biomarker discovery and validation in a variety of diseases including cardiovascular disease and cancer. Targeted proteomics promises to advance our understanding of biological networks and the phenotypic significance of specific network states and to advance biomarkers into clinical use.

Immunocapture-Selected Reaction Monitoring Screening Facilitates the Development of ELISA for the Measurement of Native TEX101 in Biological Fluids

Monoclonal antibodies that bind the native conformation of proteins are indispensable reagents for the development of immunoassays, production of therapeutic antibodies and delineating protein interaction networks by affinity purification-mass spectrometry. Antibodies generated against short peptides, protein fragments, or even full length recombinant proteins may not bind the native protein form in biological fluids, thus limiting their utility. Here, we report the application of immunocapture coupled with selected reaction monitoring measurements (immunocapture-SRM), in the rapid screening of hybridoma culture supernatants for monoclonal antibodies that bind the native protein conformation. We produced mouse monoclonal antibodies, which detect in human serum or seminal plasma the native form of the human testis-expressed sequence 101 (TEX101) protein-a recently proposed biomarker of male infertility. Pairing of two monoclonal antibodies against unique TEX101 epitopes led to the development of an ELISA for the measurement of TEX101 in seminal plasma (limit of detection: 20 pg/ml) and serum (limit of detection: 40 pg/ml). Measurements of matched seminal plasma samples, obtained from men pre- and post-vasectomy, confirmed the absolute diagnostic specificity and sensitivity of TEX101 for noninvasive identification of physical obstructions in the male reproductive tract. Measurement of male and female serum samples revealed undetectable levels of TEX101 in the systemic circulation of healthy individuals. Immunocapture-SRM screening may facilitate development of monoclonal antibodies and immunoassays against native forms of challenging protein targets.

Recent advances in targeted proteomics for clinical applications

MS-based approaches using targeted methods have been widely adopted by the proteomics community to study clinical questions such as the evaluation of biomarkers. At present, the most widely used targeted MS method is the SRM technique typically performed on a triple quadrupole instrument. However, the high analytical demands for performing clinical studies in combination with the extreme complexity of the samples involved are a serious challenge. The segmentation of the biomarker evaluation workflow has only partially alleviated these issues by differently balancing the analytical requirements and throughput at different stages of the process. The recent introduction of targeted high-resolution and accurate-mass analyses on fast sequencing mass spectrometers operated in parallel reaction monitoring (PRM) mode offers new avenues to conduct clinical studies and thus overcome some of the limitations of the triple quadrupole instrument. This article discusses the attributes and specificities of the PRM technique, in terms of experimental design, execution, and data analysis, and the implications for biomarker evaluation. The benefits of PRM on data quality and the impact on the consistency of results are highlighted and the definitive progress on the overall output of clinical studies, including high throughput, is discussed.

Parallel protein detection by solid-phase proximity ligation assay with real-time PCR or sequencing

Proximity ligation assays are a group of protein detection techniques in which reagents with affinity for target proteins, typically antibodies, are coupled to short strands of DNA. DNA-modified affinity reagents are combined in assays constructed such that the coordinated binding of individual target molecules or complexes of interacting proteins by two or more of the reagents, followed by DNA ligation and/or polymerization reactions, gives rise to amplifiable DNA reporter strands. Proximity ligation assays have been shown to exhibit excellent sensitivity in single and multiplexed protein assays for individual or interacting proteins, both in solution and in situ. This unit describes procedures for developing solid-phase proximity ligation assays for soluble proteins using either real-time PCR or DNA sequencing as the readout. In addition, critical steps for assay optimization are discussed.

Sample preparation strategies for targeted proteomics via proteotypic peptides in human blood using liquid chromatography tandem mass spectrometry

The simultaneous quantification of protein concentrations via proteotypic peptides in human blood by liquid chromatography coupled to quadrupole MS/MS is an important field of bioanalytical research with a high potential for routine diagnostic applications. This review summarizes currently available sample preparation procedures and trends for absolute protein quantification in blood using LC-MS/MS. It discusses approaches of transferring established qualitative protocols to a quantitative analysis regarding their reliability and reproducibility. Techniques used to enhance method sensitivity such as the depletion of high-abundant proteins or the immunoaffinity enrichment of proteins and peptides are described. Furthermore, workflows for (i) protein denaturation, (ii) disulfide bridge reduction and (iii) thiol alkylation as well as (iv) enzymatic digestion for absolute protein quantification are presented. The main focus is on the tryptic digestion as a bottleneck of protein quantification via proteotypic peptides. Conclusively, requirements for a high-throughput application are discussed.

Advances in Proteomic Technologies and Its Contribution to the Field of Cancer

Systematic studies of the cancer genome have generated a wealth of knowledge in recent years. These studies have uncovered a number of new cancer genes not previously known to be causal targets in cancer. Genetic markers can be used to determine predisposition to tumor development, but molecularly targeted treatment strategies are not widely available for most cancers. Precision care plans still must be developed by understanding and implementing basic science research into clinical treatment. Proteomics is continuing to make major strides in the discovery of fundamental biological processes as well as more recent transition into an assay platform capable of measuring hundreds of proteins in any biological system. As such, proteomics can translate basic science discoveries into the clinical practice of precision medicine. The proteomic field has progressed at a fast rate over the past five years in technology, breadth and depth of applications in all areas of the bioscience. Some of the previously experimental technical approaches are considered the gold standard today, and the community is now trying to come to terms with the volume and complexity of the data generated. Here I describe contribution of proteomics in general and biological mass spectrometry in particular to cancer research, as well as related major technical and conceptual developments in the field.

Quantitation of human peptides and proteins via MS: review of analytically validated assays

Since the development of monoclonal antibodies in the 1970s, antibody-based assays have been used for the quantitation of proteins and peptides and, today, they are the most widely used technology in routine laboratory medicine and bioanalysis. However, in the last couple of decades, liquid chromatography-mass spectrometry/mass spectrometry (LC–MS/MS) techniques have been adopted in the quantitation of small molecules, and more recently have made significant contributions in the quantitation of proteins and peptides. In this article, we will review clinical MS-based assays for endogenous peptides, proteins, and therapeutic antibodies, for which validated methods exist. We will also cover the measurement of protein turnover and the unique solutions that MS can offer in this field.

Mass spectrometry-based plasma proteomics: state of the art and future outlook

Mass spectrometry-based plasma proteomics is a field where intense research has been performed during the last decade. Being closely linked to biomarker discovery, the field has received a fair amount of criticism, mostly due to the low number of novel biomarkers reaching the clinic. However, plasma proteomics is under gradual development with improvements on fractionation methods, mass spectrometry instrumentation and analytical approaches. These recent developments have contributed to the revival of plasma proteomics. The goal of this review is to summarize these advances, focusing in particular on fractionation methods, both for targeted and global mass spectrometry-based plasma analysis.

Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays

In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers.

An ultrasensitive method for the quantitation of active and inactive GLP-1 in human plasma via immunoaffinity LC–MS/MS

Background: Measuring endogenous levels of incretin hormones, like GLP-1, is critical in the development of antidiabetic compounds. However, the assays used to measure these molecules often have analytical issues. Results: We have developed an ultrasensitive, highly-selective immunoaffinity LC–MS/MS (IA LC–MS/MS) assay capable of quantitating endogenous levels of active (7–36 amide) and inactive (9–36 amide) GLP-1 in human plasma. We performed fit-for-purpose validation of the assay by assessing the following assay performance characteristics: inter-assay precision, sensitivity, spike recovery, dilution linearity, absolute recovery, matrix effect, immunoprecipitation efficiency, and food effect. Conclusion: We have developed a robust analytical method for the quantitation of endogenous active and inactive GLP-1 in human plasma. In addition, we employed this method to measure the typical changes in GLP-1 levels after food intake. The sensitivity of this assay is better than another LC–MS/MS GLP-1 assay previously reported and many commercially available immunoassays. This important analytical tool could be used to qualify and/or harmonize the different immunoassays used for the quantitation of GLP-1.

Comparison of protein immunoprecipitation-multiple reaction monitoring with ELISA for assay of biomarker candidates in plasma

Quantitative analysis of protein biomarkers in plasma is typically done by ELISA, but this method is limited by the availability of high-quality antibodies. An alternative approach is protein immunoprecipitation combined with multiple reaction monitoring mass spectrometry (IP-MRM). We compared IP-MRM to ELISA for the analysis of six colon cancer biomarker candidates (metalloproteinase inhibitor 1 (TIMP1), cartilage oligomeric matrix protein (COMP), thrombospondin-2 (THBS2), endoglin (ENG), mesothelin (MSLN) and matrix metalloproteinase-9 (MMP9)) in plasma from colon cancer patients and noncancer controls. Proteins were analyzed by multiplex immunoprecipitation from plasma with the ELISA capture antibodies, further purified by SDS-PAGE, digested and analyzed by stable isotope dilution MRM. IP-MRM provided linear responses (r = 0.978–0.995) between 10 and 640 ng/mL for the target proteins spiked into a “mock plasma” matrix consisting of 60 mg/mL bovine serum albumin. Measurement variation (coefficient of variation at the limit of detection) for IP-MRM assays ranged from 2.3 to 19%, which was similar to variation for ELISAs of the same samples. IP-MRM and ELISA measurements for all target proteins except ENG were highly correlated (r = 0.67–0.97). IP-MRM with high-quality capture antibodies thus provides an effective alternative method to ELISA for protein quantitation in biological fluids.

MALDI-target integrated platform for affinity-captured protein digestion

To address immunocapture of proteins in large cohorts of clinical samples high throughput sample processing is required. Here a method using the proteomic sample platform, ISET (integrated selective enrichment target) that integrates highly specific immunoaffinity capture of protein biomarker, digestion and sample cleanup with a direct interface to mass spectrometry is presented. The robustness of the on-ISET protein digestion protocol was validated by MALDI MS analysis of model proteins, ranging from 40 fmol to 1 pmol per nanovial. On-ISET digestion and MALDI MS/MS analysis of immunoaffinity captured disease-associated biomarker PSA (prostate specific antigen) from human seminal plasma are presented.

Targeted quantification of low ng/mL level proteins in human serum without immunoaffinity depletion

We recently reported an antibody-free targeted protein quantification strategy, termed high-pressure, high-resolution separations with intelligent selection and multiplexing (PRISM), for achieving significantly enhanced sensitivity using selected reaction monitoring (SRM) mass spectrometry. Integrating PRISM with front-end IgY14 immunoaffinity depletion, sensitive detection of targeted proteins at 50-100 pg/mL levels in human blood plasma/serum was demonstrated. However, immunoaffinity depletion is often associated with undesired losses of target proteins of interest. Herein we report further evaluation of PRISM-SRM quantification of low-abundance serum proteins without immunoaffinity depletion. Limits of quantification (LOQ) at low ng/mL levels with a median coefficient of variation (CV) of ∼12% were achieved for proteins spiked into human female serum. PRISM-SRM provided >100-fold improvement in the LOQ when compared to conventional LC-SRM measurements. PRISM-SRM was then applied to measure several low-abundance endogenous serum proteins, including prostate-specific antigen (PSA), in clinical prostate cancer patient sera. PRISM-SRM enabled confident detection of all target endogenous serum proteins except the low pg/mL-level cardiac troponin T. A correlation coefficient >0.99 was observed for PSA between the results from PRISM-SRM and immunoassays. Our results demonstrate that PRISM-SRM can successfully quantify low ng/mL proteins in human plasma or serum without depletion. We anticipate broad applications for PRISM-SRM quantification of low-abundance proteins in candidate biomarker verification and systems biology studies.

Solid-phase proximity ligation assays for individual or parallel protein analyses with readout via real-time PCR or sequencing

Solid-phase proximity ligation assays share properties with the classical sandwich immunoassays for protein detection. The proteins captured via antibodies on solid supports are, however, detected not by single antibodies with detectable functions, but by pairs of antibodies with attached DNA strands. Upon recognition by these sets of three antibodies, pairs of DNA strands brought in proximity are joined by ligation. The ligated reporter DNA strands are then detected via methods such as real-time PCR or next-generation sequencing (NGS). We describe how to construct assays that can offer improved detection specificity by virtue of recognition by three antibodies, as well as enhanced sensitivity owing to reduced background and amplified detection. Finally, we also illustrate how the assays can be applied for parallel detection of proteins, taking advantage of the oligonucleotide ligation step to avoid background problems that might arise with multiplexing. The protocol for the singleplex solid-phase proximity ligation assay takes ~5 h. The multiplex version of the assay takes 7-8 h depending on whether quantitative PCR (qPCR) or sequencing is used as the readout. The time for the sequencing-based protocol includes the library preparation but not the actual sequencing, as times may vary based on the choice of sequencing platform.

Glycoproteomics-based cancer marker discovery adopting dual enrichment with Wisteria floribunda agglutinin for high specific glyco-diagnosis of cholangiocarcinoma

Cholangiocarcinoma (CC) is a lethal malignancy because it exhibits asymptomatic growth infiltrating the surrounding structures and therefore is usually detected at an advanced stage. The mainstay of treatment for CC is complete resection with negative surgical margins. Therefore, its diagnosis at a relatively early stage is demanded for performing relevant surgical resection. Since the definitive CC diagnosis depends on invasive methods such as biliary cytology and biopsy, a noninvasive assay with high diagnostic accuracy is keenly required. We therefore developed a CC marker with high specificity by the Wisteria floribunda agglutinin (WFA)-assisted glycoproteomics approach. WFA-positive glycoproteins were enriched by the direct dissection of the WFA-stained CC tissue region and following WFA-agarose column chromatography. Subsequent analysis by mass spectrometry identified 71 proteins as candidate markers. Screening of these candidates by gene expression profiling and immunohistochemistry resulted in the selection of L1 cell adhesion molecule (L1CAM) as the most specific CC marker. We confirmed the importance of WFA-positivity for L1CAM using both bile and serum of CC and benign bile duct disease patients. Specifically, WFA-positive L1CAM was enriched from serum by the WFA-assisted affinity capturing, with which CC was efficiently distinguished from benign. In the primary verification study using bile from CC patients (n=29) and that of benign bile duct disease (n=29), WFA-positive L1CAM distinguished CC with high specificity (sensitivity=0.66, specificity=0.93, overall accuracy=0.79, area under the receiver operating curve [AUC]=0.82). The combined use of the WFA-positive L1CAM assay with the high sensitive assay detecting WFA-positive sialylated mucin 1 sufficiently improved the diagnostic accuracy of CC (overall accuracy=0.84, AUC=0.93). This combination will possibly be a precise procedure for CC diagnosis compared with conventional diagnostic techniques.

BIOLOGICAL SIGNIFICANCE

In this study, we constructed the system for verification of the candidate molecules that exhibit disease specific glyco-alterations and discovered a useful CC marker by the glycoproteomics-assisted strategy for biomarker discovery. Based on the strategy, we previously found that WFA is the best probe to detect CC-specific glycosylation and WFA-positive sialyl MUC1 as a possible biomarker candidate. While the diagnostic specificity of WFA-positive sialyl MUC1 was not superb, we proposed a new biomarker candidate WFA-positive L1CAM with high specificity in bile and serum to complement the previous one. We proved that the novel combination assay of WFA-L1CAM and WFA-sialyl MUC1 selected based on our strategy has the possibility to become a reliable serological test. This study represents application of our strategy, which can be extrapolated to discovery of marker candidates for other diseases.

Quantitative analysis of the human AKR family members in cancer cell lines using the mTRAQ/MRM approach

Members of human aldo-keto reductase (AKR) superfamily have been reported to be involved in cancer progression, whereas the final conclusion is not generally accepted. Herein, we propose a quantitative method to measure human AKR proteins in cells using mTRAQ-based multiple reaction monitoring (MRM). AKR peptides with multiple transitions were carefully selected upon tryptic digestion of the recombinant AKR proteins, while AKR proteins were identified by SDS-PAGE fractionation coupled with LC-MS/MS. Utilizing mTRAQ triplex labeling to produce the derivative peptides, calibration curves were generated using the mixed lysate as background, and no significantly different quantification of AKRs was elicited from the two sets of calibration curves under the mixed and single lysate as background. We employed this approach to quantitatively determine the 6 AKR proteins, AKR1A1, AKR1B1, AKR1B10, AKR1C1/C2, AKR1C3, and AKR1C4, in 7 different cancer cell lines and for the first time to obtain the absolute quantities of all the AKR proteins in each cell. The cluster plot revealed that AKR1A and AKR1B were widely distributed in most cancer cells with relatively stable abundances, whereas AKR1Cs were unevenly detected among these cells with diverse dynamic abundances. The AKR quantitative distribution in different cancer cells, therefore, may assist further exploration toward how the AKR proteins are involved in tumorigenesis.

Using pure protein to build a multiple reaction monitoring mass spectrometry assay for targeted detection and quantitation

Multiple reaction monitoring (MRM) is an increasingly popular mass spectrometry-based method to simultaneously detect and quantify multiple proteins. MRM is particularly useful for validating biomarkers discovered with a mass spectrometer and any analite discovered by MS can be monitored by MR because an MRM assay can be developed without the need to generate specific antibodies. In this chapter, we present a robust and systematic procedure to rapidly build a high-sensitivity MRM assay using purified protein as the starting material. Theoretical digestion of the protein with trypsin is used to identify mass spectrometry--compatible peptides and to generate preliminary MRM transitions to detect these peptides. Peptides generated by trypsin cleavage of the actual protein are then run on a liquid chromatography column coupled to a triple quadrupole mass spectrometer, which is programmed with the preliminary transitions. Whenever a transition is detected, it triggers dissociation of the corresponding peptide and collection of a full mass range scan of the resulting fragment ions. From this scan, fragment ions yielding the strongest and most reproducible signals are utilized to design empirical MRM transitions. The assay is further refined by optimizing the collision energy and creating a standard curve to measure sensitivity. Once MRM transitions have been established for a particular protein, they can be combined with transitions for other target proteins to create multiplex assays and used to quantify proteins in samples arising from serum, urine, subcellular fractions, or any other specemen of interest.

The application of quantification techniques in proteomics for biomedical research

The systematic analysis of biological processes requires an understanding of the quantitative expression patterns of proteins, their interacting partners and their subcellular localization. This information was formerly difficult to accrue as the relative quantification of proteins relied on antibody-based methods and other approaches with low throughput. The advent of soft ionization techniques in mass spectrometry plus advances in separation technologies has aligned protein systems biology with messenger RNA, DNA, and microarray technologies to provide data on systems as opposed to singular protein entities. Another aspect of quantitative proteomics that increases its importance for the coming few years is the significant technical developments underway both for high pressure liquid chromatography and mass spectrum devices. Hence, robustness, reproducibility and mass accuracy are still improving with every new generation of instruments. Nonetheless, the methods employed require validation and comparison to design fit for purpose experiments in advanced protein analyses. This review considers the newly developed systematic protein investigation methods and their value from the standpoint that relative or absolute protein quantification is required de rigueur in biomedical research.

Lung cancer signature biomarkers: tissue specific semantic similarity based clustering of digital differential display (DDD) data

BACKGROUND

The tissue-specific Unigene Sets derived from more than one million expressed sequence tags (ESTs) in the NCBI, GenBank database offers a platform for identifying significantly and differentially expressed tissue-specific genes by in-silico methods. Digital differential display (DDD) rapidly creates transcription profiles based on EST comparisons and numerically calculates, as a fraction of the pool of ESTs, the relative sequence abundance of known and novel genes. However, the process of identifying the most likely tissue for a specific disease in which to search for candidate genes from the pool of differentially expressed genes remains difficult. Therefore, we have used 'Gene Ontology semantic similarity score' to measure the GO similarity between gene products of lung tissue-specific candidate genes from control (normal) and disease (cancer) sets. This semantic similarity score matrix based on hierarchical clustering represents in the form of a dendrogram. The dendrogram cluster stability was assessed by multiple bootstrapping. Multiple bootstrapping also computes a p-value for each cluster and corrects the bias of the bootstrap probability.

RESULTS

Subsequent hierarchical clustering by the multiple bootstrapping method (α = 0.95) identified seven clusters. The comparative, as well as subtractive, approach revealed a set of 38 biomarkers comprising four distinct lung cancer signature biomarker clusters (panel 1-4). Further gene enrichment analysis of the four panels revealed that each panel represents a set of lung cancer linked metastasis diagnostic biomarkers (panel 1), chemotherapy/drug resistance biomarkers (panel 2), hypoxia regulated biomarkers (panel 3) and lung extra cellular matrix biomarkers (panel 4).

CONCLUSIONS

Expression analysis reveals that hypoxia induced lung cancer related biomarkers (panel 3), HIF and its modulating proteins (TGM2, CSNK1A1, CTNNA1, NAMPT/Visfatin, TNFRSF1A, ETS1, SRC-1, FN1, APLP2, DMBT1/SAG, AIB1 and AZIN1) are significantly down regulated. All down regulated genes in this panel were highly up regulated in most other types of cancers. These panels of proteins may represent signature biomarkers for lung cancer and will aid in lung cancer diagnosis and disease monitoring as well as in the prediction of responses to therapeutics.