Toward next generation plasma profiling via heat-induced epitope retrieval and array-based assays

A Significant Contribution of the Classical Pathway of Complement in SARS-CoV-2 Neutralization of Convalescent and Vaccinee Sera

Although high titers of neutralizing Abs in human serum are associated with protection from reinfection by SARS-CoV-2, there is considerable heterogeneity in human serum-neutralizing Abs against SARS-CoV-2 during convalescence between individuals. Standard human serum live virus neutralization assays require inactivation of serum/plasma prior to testing. In this study, we report that the SARS-CoV-2 neutralization titers of human convalescent sera were relatively consistent across all disease states except for severe COVID-19, which yielded significantly higher neutralization titers. Furthermore, we show that heat inactivation of human serum significantly lowered neutralization activity in a live virus SARS-CoV-2 neutralization assay. Heat inactivation of human convalescent serum was shown to inactivate complement proteins, and the contribution of complement in SARS-CoV-2 neutralization was often >50% of the neutralizing activity of human sera without heat inactivation and could account for neutralizing activity when standard titers were zero after heat inactivation. This effect was also observed in COVID-19 vaccinees and could be abolished in individuals who were undergoing treatment with therapeutic anti-complement Abs. Complement activity was mainly dependent on the classical pathway with little contributions from mannose-binding lectin and alternative pathways. Our study demonstrates the importance of the complement pathway in significantly increasing viral neutralization activity against SARS-CoV-2 in spike seropositive individuals.

Integrative analysis of transcriptomic and metabolomic profiles reveals enhanced arginine metabolism in androgen-independent prostate cancer cells

BACKGROUND

Prostate cancer is a common solid tumor that affects a significant number of men worldwide. Conventional androgen deprivation therapy (ADT) increases the risk of developing castration-resistant prostate cancer (CRPC). Effective clinical management of patients with CRPC is challenging due to the limited understanding.

METHODS

In this study, transcriptomic and metabolomic profiles of androgen-dependent prostate cancer cell line LNCaP and the androgen-independent cells developed from LNCaP cells (LNCaP-ADR) were investigated using RNA-sequencing and LC-MS/MS, respectively. The differentially expressed genes and metabolites were analyzed, and integrative analysis of transcriptomic and metabolomic data was further conducted to obtain a comprehensive understanding of the metabolic characteristics in LNCaP-ADR cells. Quantitative real-time PCR (QPCR) was employed to ascertain the mRNA expression levels of the selected differentially expressed genes.

RESULTS

The arginine and proline metabolism pathway was identified as a commonly altered pathway at both the transcriptional and metabolic levels. In the LNCaP-ADR cells, significant upregulation was observed for metabolites including 5-Aminopentanoic acid, L-Arginine, L-Glutamic acid, N-Acetyl-L-alanine, and Pyrrole-2-carboxylic acid at the metabolic level. At the transcriptional level, MAOA, ALDH3A2, ALDH2, ARG1, CKMT2, and CNDP1 were found to be significantly upregulated in the LNCaP-ADR cells. Gene set enrichment analysis (GSEA) identified various enriched gene sets in the LNCaP-ADR cells, encompassing inflammatory response, 9plus2 motile cilium, motile cilium, ciliary plasm, cilium or flagellum-dependent cell motility, cilium movement, cilium, response to endoplasmic reticulum stress, PTEN DN.V1 DN, SRC UP.V1 UP, IL15 UP.V1 DN, RB DN.V1 DN, AKT UP MTOR DN.V1 UP, VEGF A UP.V1 UP, and KRAS.LUNG.BREAST UP.V1 UP.

CONCLUSIONS

These findings highlight the substantial association between the arginine and proline metabolism pathway and CRPC, emphasizing the need to prioritize strategies that target dysregulated metabolites and differentially expressed genes as essential interventions in the clinical management of CRPC.

Altered plasma protein profiles in genetic FTD - a GENFI study

BACKGROUND

Plasma biomarkers reflecting the pathology of frontotemporal dementia would add significant value to clinical practice, to the design and implementation of treatment trials as well as our understanding of disease mechanisms. The aim of this study was to explore the levels of multiple plasma proteins in individuals from families with genetic frontotemporal dementia.

METHODS

Blood samples from 693 participants in the GENetic Frontotemporal Dementia Initiative study were analysed using a multiplexed antibody array targeting 158 proteins.

RESULTS

We found 13 elevated proteins in symptomatic mutation carriers, when comparing plasma levels from people diagnosed with genetic FTD to healthy non-mutation controls and 10 proteins that were elevated compared to presymptomatic mutation carriers.

CONCLUSION

We identified plasma proteins with altered levels in symptomatic mutation carriers compared to non-carrier controls as well as to presymptomatic mutation carriers. Further investigations are needed to elucidate their potential as fluid biomarkers of the disease process.

A wide scan of plasma proteins demonstrates thioredoxin reductase 1 as a potential new diagnostic biomarker for hepatocellular carcinoma

BACKGROUND

Patients with liver cirrhosis are recommended ultrasonography screening for early detection of hepatocellular carcinoma to increase the chances of curative treatment. However, ultrasonography alone lacks in sensitivity. Adding plasma biomarkers may increase the detection rate. We performed a broad exploratory analysis to find new plasma proteins with potential applicability for HCC screening in patients with cirrhosis.

METHODS

In a protein discovery cohort of 172 patients with cirrhosis or HCC, we screened for 481 proteins with suspension bead array or proximity extension assay. From these, 24 proteins were selected for further analysis in a protein verification cohort (n = 160), using ELISA, Luminex or an electrochemiluminescence platform. A cut-off model and a stepwise logistic regression model were used to find combinations of proteins with the best discriminatory performance between HCC and cirrhosis.

RESULTS

Stepwise logistic regression revealed alpha-fetoprotein (AFP), decarboxy-prothrombin (DCP), thioredoxin reductase 1 (TXNRD1), and fibroblast growth factor 21 (FGF21) as the proteins with the best discriminatory performance between HCC and cirrhosis. Adding TXNRD1 to DCP and AFP increased the AUC from 0.844 to 0.878, and combining AFP, DCP and TXNRD1 with age and sex resulted in an AUC of 0.920. FGF21, however, did not further increase the performance when including age and sex.

CONCLUSION

In the present study, TXNRD1 improves the sensitivity and specificity of AFP and DCP as HCC screening tools in patients with cirrhosis. We suggest that TXNRD1 should be validated in prospective settings as a new complementary HCC biomarker together with AFP and DCP.

Systematic evaluation of plasma signaling cascades by functional proteomics approaches: SARS-CoV-2 infection as model

PURPOSE

Acute phase reactants (APRs) play a critical role in inflammation. The difference in their physiological functions or the different dynamic ranges of these proteins in plasma makes it difficult to detect them simultaneously and to use several of these proteins as a tool in clinical practice.

EXPERIMENTAL DESIGN

A novel multiplex assay has been designed and optimized to carry out a high-throughput and simultaneous screening of APRs, allowing the detection of each of them at the same time and in their corresponding dynamic range.

RESULTS

Using Sars-CoV-2 infection as a model, it has been possible to profile different patterns of acute phase proteins that vary significantly between healthy and infected patients. In addition, severity profiles (acute respiratory distress syndrome and sepsis) have been established.

CONCLUSIONS AND CLINICAL RELEVANCE

Differential profiles in acute phase proteins can serve as a diagnostic and prognostic tool, among patient stratification. The design of this new platform for their simultaneous detection paves the way for them to be more extensive use in clinical practice.

Construction of 2DE Patterns of Plasma Proteins: Aspect of Potential Tumor Markers

The use of tumor markers aids in the early detection of cancer recurrence and prognosis. There is a hope that they might also be useful in screening tests for the early detection of cancer. Here, the question of finding ideal tumor markers, which should be sensitive, specific, and reliable, is an acute issue. Human plasma is one of the most popular samples as it is commonly collected in the clinic and provides noninvasive, rapid analysis for any type of disease including cancer. Many efforts have been applied in searching for “ideal” tumor markers, digging very deep into plasma proteomes. The situation in this area can be improved in two ways—by attempting to find an ideal single tumor marker or by generating panels of different markers. In both cases, proteomics certainly plays a major role. There is a line of evidence that the most abundant, so-called “classical plasma proteins”, may be used to generate a tumor biomarker profile. To be comprehensive these profiles should have information not only about protein levels but also proteoform distribution for each protein. Initially, the profile of these proteins in norm should be generated. In our work, we collected bibliographic information about the connection of cancers with levels of “classical plasma proteins”. Additionally, we presented the proteoform profiles (2DE patterns) of these proteins in norm generated by two-dimensional electrophoresis with mass spectrometry and immunodetection. As a next step, similar profiles representing protein perturbations in plasma produced in the case of different cancers will be generated. Additionally, based on this information, different test systems can be developed.

SARS-CoV-2 Infection Triggers Auto-Immune Response in ARDS

Acute respiratory distress syndrome (ARDS) is a severe pulmonary disease, which is one of the major complications in COVID-19 patients. Dysregulation of the immune system and imbalances in cytokine release and immune cell activation are involved in SARS-CoV-2 infection. Here, the inflammatory, antigen, and auto-immune profile of patients presenting COVID-19-associated severe ARDS has been analyzed using functional proteomics approaches. Both, innate and humoral responses have been characterized through acute-phase protein network and auto-antibody signature. Severity and sepsis by SARS-CoV-2 emerged to be correlated with auto-immune profiles of patients and define their clinical progression, which could provide novel perspectives in therapeutics development and biomarkers of COVID-19 patients. Humoral response in COVID-19 patients’ profile separates with significant differences patients with or without ARDS. Furthermore, we found that this profile can be correlated with COVID-19 severity and results more common in elderly patients.

Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study

The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired β cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments.

Deciphering Biomarkers for Leptomeningeal Metastasis in Malignant Hemopathies (Lymphoma/Leukemia) Patients by Comprehensive Multipronged Proteomics Characterization of Cerebrospinal Fluid

Simple Summary

The early diagnosis of leptomeningeal disease is a challenge because it is asymptomatic in the early stages. Consequently, it is important to identify a panel of biomarkers to help in its diagnosis and/or prognosis. For this purpose, we explored a multipronged proteomics approach in cerebrospinal fluid (CSF) to determine a potential panel of biomarkers. Thus, a systematic and exhaustive characterization of more than 300 CSF samples was performed by an integrated approach by Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) and functional proteomics analysis to establish protein profiles, which were useful for developing a panel of biomarkers validated by in silico approaches.

Abstract

In the present work, leptomeningeal disease, a very destructive form of systemic cancer, was characterized from several proteomics points of view. This pathology involves the invasion of the leptomeninges by malignant tumor cells. The tumor spreads to the central nervous system through the cerebrospinal fluid (CSF) and has a very grim prognosis; the average life expectancy of patients who suffer it does not exceed 3 months. The early diagnosis of leptomeningeal disease is a challenge because, in most of the cases, it is an asymptomatic pathology. When the symptoms are clear, the disease is already in the very advanced stages and life expectancy is low. Consequently, there is a pressing need to determine useful CSF proteins to help in the diagnosis and/or prognosis of this disease. For this purpose, a systematic and exhaustive proteomics characterization of CSF by multipronged proteomics approaches was performed to determine different protein profiles as potential biomarkers. Proteins such as PTPRC, SERPINC1, sCD44, sCD14, ANPEP, SPP1, FCGR1A, C9, sCD19, and sCD34, among others, and their functional analysis, reveals that most of them are linked to the pathology and are not detected on normal CSF. Finally, a panel of biomarkers was verified by a prediction model for leptomeningeal disease, showing new insights into the research for potential biomarkers that are easy to translate into the clinic for the diagnosis of this devastating disease.

A panel of CSF proteins separates genetic frontotemporal dementia from presymptomatic mutation carriers: a GENFI study

BACKGROUND

A detailed understanding of the pathological processes involved in genetic frontotemporal dementia is critical in order to provide the patients with an optimal future treatment. Protein levels in CSF have the potential to reflect different pathophysiological processes in the brain. We aimed to identify and evaluate panels of CSF proteins with potential to separate symptomatic individuals from individuals without clinical symptoms (unaffected), as well as presymptomatic individuals from mutation non-carriers.

METHODS

A multiplexed antibody-based suspension bead array was used to analyse levels of 111 proteins in CSF samples from 221 individuals from families with genetic frontotemporal dementia. The data was explored using LASSO and Random forest.

RESULTS

When comparing affected individuals with unaffected individuals, 14 proteins were identified as potentially important for the separation. Among these, four were identified as most important, namely neurofilament medium polypeptide (NEFM), neuronal pentraxin 2 (NPTX2), neurosecretory protein VGF (VGF) and aquaporin 4 (AQP4). The combined profile of these four proteins successfully separated the two groups, with higher levels of NEFM and AQP4 and lower levels of NPTX2 in affected compared to unaffected individuals. VGF contributed to the models, but the levels were not significantly lower in affected individuals. Next, when comparing presymptomatic GRN and C9orf72 mutation carriers in proximity to symptom onset with mutation non-carriers, six proteins were identified with a potential to contribute to a separation, including progranulin (GRN).

CONCLUSION

In conclusion, we have identified several proteins with the combined potential to separate affected individuals from unaffected individuals, as well as proteins with potential to contribute to the separation between presymptomatic individuals and mutation non-carriers. Further studies are needed to continue the investigation of these proteins and their potential association to the pathophysiological mechanisms in genetic FTD.

Multi-cohort profiling reveals elevated CSF levels of brain-enriched proteins in Alzheimer's disease

OBJECTIVE

Decreased amyloid beta (Aβ) 42 together with increased tau and phospho-tau in cerebrospinal fluid (CSF) is indicative of Alzheimer's disease (AD). However, the molecular pathophysiology underlying the slowly progressive cognitive decline observed in AD is not fully understood and it is not known what other CSF biomarkers may be altered in early disease stages.

METHODS

We utilized an antibody-based suspension bead array to analyze levels of 216 proteins in CSF from AD patients, patients with mild cognitive impairment (MCI), and controls from two independent cohorts collected within the AETIONOMY consortium. Two additional cohorts from Sweden were used for biological verification.

RESULTS

Six proteins, amphiphysin (AMPH), aquaporin 4 (AQP4), cAMP-regulated phosphoprotein 21 (ARPP21), growth-associated protein 43 (GAP43), neurofilament medium polypeptide (NEFM), and synuclein beta (SNCB) were found at increased levels in CSF from AD patients compared with controls. Next, we used CSF levels of Aβ42 and tau for the stratification of the MCI patients and observed increased levels of AMPH, AQP4, ARPP21, GAP43, and SNCB in the MCI subgroups with abnormal tau levels compared with controls. Further characterization revealed strong to moderate correlations between these five proteins and tau concentrations.

INTERPRETATION

In conclusion, we report six extensively replicated candidate biomarkers with the potential to reflect disease development. Continued evaluation of these proteins will determine to what extent they can aid in the discrimination of MCI patients with and without an underlying AD etiology, and if they have the potential to contribute to a better understanding of the AD continuum.

Nonspecific Binding-Fundamental Concepts and Consequences for Biosensing Applications

Nature achieves differentiation of specific and nonspecific binding in molecular interactions through precise control of biomolecules in space and time. Artificial systems such as biosensors that rely on distinguishing specific molecular binding events in a sea of nonspecific interactions have struggled to overcome this issue. Despite the numerous technological advancements in biosensor technologies, nonspecific binding has remained a critical bottleneck due to the lack of a fundamental understanding of the phenomenon. To date, the identity, cause, and influence of nonspecific binding remain topics of debate within the scientific community. In this review, we discuss the evolution of the concept of nonspecific binding over the past five decades based upon the thermodynamic, intermolecular, and structural perspectives to provide classification frameworks for biomolecular interactions. Further, we introduce various theoretical models that predict the expected behavior of biosensors in physiologically relevant environments to calculate the theoretical detection limit and to optimize sensor performance. We conclude by discussing existing practical approaches to tackle the nonspecific binding challenge in vitro for biosensing platforms and how we can both address and harness nonspecific interactions for in vivo systems.

Proteomic Analysis of Serum Differentially Expressed Proteins Between Allergic Bronchopulmonary Aspergillosis and Asthma

BACKGROUND

Allergic bronchopulmonary aspergillosis (ABPA) constantly develops in asthmatics, which has not been fully investigated.

OBJECTIVES

This study aimed to investigate serum differentially expressed proteins (DEPs) between ABPA and asthma using the new approach isobaric tags by relative and absolute quantitation (iTRAQ).

METHODS

Each 16 serum samples from ABPA or asthmatic subjects were pooled and screened using iTRAQ. After bioinformatic analysis, five candidate DEPs were validated in the enlarged serum samples from additional 21 ABPA, 31 asthmatic and 20 healthy subjects using ELISA. A receiver operating characteristic (ROC) curve was used to estimate the diagnostic power of carnosine dipeptidase 1 (CNDP1).

RESULTS

A total of 29 DEPs were screened out between ABPA and asthmatic groups. Over half of them were enriched in proteolysis and regulation of protein metabolic process. Further verification showed serum levels of immunoglobulin heavy constant gamma 1, α-1-acid glycoprotein 1, corticosteroid-binding globulin and vitronectin were neither differentially altered between ABPA and asthma nor consistent with the proteomic analysis. Only serum CNDP1 was significantly decreased in ABPA patients, compared with asthmatics and healthy controls (P < 0.01 and P < 0.05). The ROC analysis determined 10.73 ng/mL as the cutoff value of CNDP1, which could distinguish ABPA among asthmatics (AUC 0.770, 95%CI 0.632-0.875, P < 0.001).

CONCLUSIONS

This study firstly identified serological DEPs between ABPA and asthma using the new technique iTRAQ. Serum CNDP1 might assist the differential diagnosis of ABPA from asthma and serve as a new pathogenetic factor in fungal colonization and sensitization.

Systematic assessment of antibody selectivity in plasma based on a resource of enrichment profiles

There is a strong need for procedures that enable context and application dependent validation of antibodies. Here, we applied a magnetic bead assisted workflow and immunoprecipitation mass spectrometry (IP-MS/MS) to assess antibody selectivity for the detection of proteins in human plasma. A resource was built on 414 IP experiments using 157 antibodies (targeting 120 unique proteins) in assays with heat-treated or untreated EDTA plasma. For each protein we determined their antibody related degrees of enrichment using z-scores and their frequencies of identification across all IP assays. Out of 1,313 unique endogenous proteins, 426 proteins (33%) were detected in >20% of IPs, and these background components were mainly comprised of proteins from the complement system. For 45% (70/157) of the tested antibodies, the expected target proteins were enriched (z-score ≥ 3). Among these 70 antibodies, 59 (84%) co-enriched other proteins beside the intended target and mainly due to sequence homology or protein abundance. We also detected protein interactions in plasma, and for IGFBP2 confirmed these using several antibodies and sandwich immunoassays. The protein enrichment data with plasma provide a very useful and yet lacking resource for the assessment of antibody selectivity. Our insights will contribute to a more informed use of affinity reagents for plasma proteomics assays.

Levels of human proteins in plasma associated with acute paediatric malaria

Background

The intimate interaction between the pathophysiology of the human host and the biology of the Plasmodium falciparum parasite results in a wide spectrum of disease outcomes in malaria. Development of severe disease is associated with a progressively augmented imbalance in pro- and anti-inflammatory responses to high parasite loads and sequestration of parasitized erythrocytes. Although these phenomena collectively constitute common denominators for the wide variety of discrete severe malaria manifestations, the mechanistic rationales behind discrepancies in outcome are poorly understood. Exploration of the human pathophysiological response by variations in protein profiles in plasma presents an excellent opportunity to increase the understanding. This is ultimately required for better prediction, prevention and treatment of malaria, which is essential for ongoing elimination and eradication efforts.

Results

An affinity proteomics approach was used to analyse 541 paediatric plasma samples collected from community controls and patients with mild or severe malaria in Rwanda. Protein profiles were generated with an antibody-based suspension bead array containing 255 antibodies targetting 115 human proteins. Here, 57 proteins were identified with significantly altered levels (adjusted p-values < 0.001) in patients with malaria compared to controls. From these, the 27 most significant proteins (adjusted p-values < 10⁻¹⁴) were selected for a stringent analysis approach. Here, 24 proteins showed elevated levels in malaria patients and included proteins involved in acute inflammatory response as well as cell adhesion. The remaining three proteins, also implicated in immune regulation and cellular adhesivity, displayed lower abundance in malaria patients. In addition, 37 proteins (adjusted p-values < 0.05) were identified with increased levels in patients with severe compared to mild malaria. This set includes, proteins involved in tissue remodelling and erythrocyte membrane proteins. Collectively, this approach has been successfully used to identify proteins both with known and unknown association with different stages of malaria.

Conclusion

In this study, a high-throughput affinity proteomics approach was used to find protein profiles in plasma linked to P. falciparum infection and malaria disease progression. The proteins presented herein are mainly involved in inflammatory response, cellular adhesion and as constituents of erythrocyte membrane. These findings have a great potential to provide increased conceptual understanding of host-parasite interaction and malaria pathogenesis.

Electronic supplementary material

The online version of this article (10.1186/s12936-018-2576-y) contains supplementary material, which is available to authorized users.

Current applications of antibody microarrays

The concept of antibody microarrays is one of the most versatile approaches within multiplexed immunoassay technologies. These types of arrays have increasingly become an attractive tool for the exploratory detection and study of protein abundance, function, pathways, and potential drug targets. Due to the properties of the antibody microarrays and their potential use in basic research and clinical analytics, various types of antibody microarrays have already been developed. In spite of the growing number of studies utilizing this technique, few reviews about antibody microarray technology have been presented to reflect the quality and future uses of the generated data. In this review, we provide a summary of the recent applications of antibody microarray techniques in basic biology and clinical studies, providing insights into the current trends and future of protein analysis.

Neuroproteomic Profiling of Cerebrospinal Fluid (CSF) by Multiplexed Affinity Arrays

Protein profiling through affinity proteomic approaches represents a powerful strategy for the analysis of human body fluids. Cerebrospinal fluid (CSF), being the fluid proximal to the central nervous system, is commonly analyzed in the context of neurological diseases, and can offer novel insights into the physiological state of the brain. Ultimately, and by analyzing the presence of brain-derived proteins in larger sets of samples that represent different phenotypes, profiling of CSF may serve as an important source to discover and verify disease-associated markers. Here, we describe a multiplexed and flexible protein profiling approach using antibody-based assays on suspension bead arrays. Through streamlined sample processing, protein biotinylation, and single-binder assay readout, this method enables high-throughput neuroproteomic analysis of up to 384 proteins in 384 samples.

Affinity Proteomics Exploration of Melanoma Identifies Proteins in Serum with Associations to T-Stage and Recurrence

BACKGROUND

Blood-based proteomic profiling may aid and expand our understanding of diseases and their different phenotypes. The aim of the presented study was to profile serum samples from patients with malignant melanoma using affinity proteomic assays to describe proteins in the blood stream that are associated to stage or recurrence of melanoma.

MATERIAL AND METHODS

Multiplexed protein analysis was conducted using antibody suspension bead arrays. A total of 232 antibodies against 132 proteins were selected from (i) a screening with 4595 antibodies and 32 serum samples from melanoma patients and controls, (ii) antibodies used for immunohistochemistry, (iii) protein targets previously related with melanoma. The analysis was performed with 149 serum samples from patients with malignant melanoma. Antibody selectivity was then assessed by Western blot, immunocapture mass spectrometry, and epitope mapping. Lastly, indicative antibodies were applied for IHC analysis of melanoma tissues.

RESULTS

Serum levels of regucalcin (RGN) and syntaxin 7 (STX7) were found to be lower in patients with both recurring tumors and a high Breslow's thickness (T-stage 3/4) compared to low thickness (T-stage 1/2) without disease recurrence. Serum levels of methylenetetrahydrofolate dehydrogenase 1-like (MTHFD1L) were instead elevated in sera of T3/4 patients with recurrence. The analysis of tissue sections with S100A6 and MTHFD1L showed positive staining in a majority of patients with melanoma, and S100A6 was significantly associated to T-stage.

CONCLUSIONS

Our findings provide a starting point to further study RGN, STX7, MTHFD1L and S100A6 in serum to elucidate their involvement in melanoma progression and to assess a possible contribution to support clinical indications.

PDGFB, a new candidate plasma biomarker for venous thromboembolism: results from the VEREMA affinity proteomics study

High-throughput affinity plasma proteomic profiling can identify candidate plasma biomarkers for VTE. Elevated plasma PDGFB levels are identified as associated with VTE in 2 independent case control studies.

Three-Dimensionally Functionalized Reverse Phase Glycoprotein Array for Cancer Biomarker Discovery and Validation

Glycoproteins have vast structural diversity that plays an important role in many biological processes and have great potential as disease biomarkers. Here, we report a novel functionalized reverse phase protein array (RPPA), termed polymer-based reverse phase glycoprotein array (polyGPA), to capture and profile glycoproteomes specifically, and validate glycoproteins. Nitrocellulose membrane functionalized with globular hydroxyaminodendrimers was used to covalently capture preoxidized glycans on glycoproteins from complex protein samples such as biofluids. The captured glycoproteins were subsequently detected using the same validated antibodies as in RPPA. We demonstrated the outstanding specificity, sensitivity, and quantitative capabilities of polyGPA by capturing and detecting purified as well as endogenous α-1-acid glycoprotein (AGP) in human plasma. We further applied quantitative N-glycoproteomics and the strategy to validate a panel of glycoproteins identified as potential biomarkers for bladder cancer by analyzing urine glycoproteins from bladder cancer patients or matched healthy individuals.

Protein profiling in serum after traumatic brain injury in rats reveals potential injury markers

INTRODUCTION

The serum proteome following traumatic brain injury (TBI) could provide information for outcome prediction and injury monitoring. The aim with this affinity proteomic study was to identify serum proteins over time and between normoxic and hypoxic conditions in focal TBI.

MATERIAL AND METHODS

Sprague Dawley rats (n=73) received a 3mm deep controlled cortical impact ("severe injury"). Following injury, the rats inhaled either a normoxic (22% O₂) or hypoxic (11% O₂) air mixture for 30min before resuscitation. The rats were sacrificed at day 1, 3, 7, 14 and 28 after trauma. A total of 204 antibodies targeting 143 unique proteins of interest in TBI research, were selected. The sample proteome was analyzed in a suspension bead array set-up. Comparative statistics and factor analysis were used to detect differences as well as variance in the data.

RESULTS

We found that complement factor 9 (C9), complement factor B (CFB) and aldolase c (ALDOC) were detected at higher levels the first days after trauma. In contrast, hypoxia inducing factor (HIF)1α, amyloid precursor protein (APP) and WBSCR17 increased over the subsequent weeks. S100A9 levels were higher in hypoxic-compared to normoxic rats, together with a majority of the analyzed proteins, albeit few reached statistical significance. The principal component analysis revealed a variance in the data, highlighting clusters of proteins.

CONCLUSIONS

Protein profiling of serum following TBI using an antibody based microarray revealed temporal changes of several proteins over an extended period of up to four weeks. Further studies are warranted to confirm our findings.

Multiplexed protein profiling by sequential affinity capture

Antibody microarrays enable parallelized and miniaturized analysis of clinical samples, and have proven to provide novel insights for the analysis of different proteomes. However, there are concerns that the performance of such direct labeling and single antibody assays are prone to off‐target binding due to the sample context. To improve selectivity and sensitivity while maintaining the possibility to conduct multiplexed protein profiling, we developed a multiplexed and semi‐automated sequential capture assay. This novel bead‐based procedure encompasses a first antigen capture, labeling of captured protein targets on magnetic particles, combinatorial target elution and a read‐out by a secondary capture bead array. We demonstrate in a proof‐of‐concept setting that target detection via two sequential affinity interactions reduced off‐target contribution, while lowered background and noise levels, improved correlation to clinical values compared to single binder assays. We also compared sensitivity levels with single binder and classical sandwich assays, explored the possibility for DNA‐based signal amplification, and demonstrate the applicability of the dual capture bead‐based antibody microarray for biomarker analysis. Hence, the described concept enhances the possibilities for antibody array assays to be utilized for protein profiling in body fluids and beyond.

Affinity proteomics discovers decreased levels of AMFR in plasma from Osteoporosis patients

PURPOSE

Affinity proteomic approaches by antibody bead arrays enable multiplexed analysis of proteins in body fluids. In the presented study, we investigated blood plasma within osteoporosis to discovery differential protein profiles and to propose novel biomarkers candidates for subsequent studies.

EXPERIMENTAL DESIGN

Starting with 4608 antibodies and plasma samples from 22 women for an untargeted screening, a set of 72 proteins were suggested for further analysis. Complementing these with targets from literature and other studies, a targeted bead array of 180 antibodies was built to profile for 92 proteins in plasma samples of 180 women from two independent population-based studies.

RESULTS

Differential profiles between osteoporosis patients and matched controls were discovered for 12 proteins in at least one of the two study sets. Among these targets, the levels of autocrine motility factor receptor (AMFR) were concordantly lower in plasma of female osteoporosis patients. Subsequently, verification of anti-AMFR antibody selectivity was conducted using high-density peptide and protein arrays, and Western blotting.

CONCLUSIONS AND CLINICAL RELEVANCE

Further validation in additional study sets will be needed to determine the clinical value of the observed decrease in AMFR plasma levels in osteoporosis patients, but AMFR may aid our understanding of disease mechanisms and could support existing tools for diagnosis and monitoring of patient mobility within osteoporosis.

Circulating carnosine dipeptidase 1 associates with weight loss and poor prognosis in gastrointestinal cancer

BACKGROUND

Cancer cachexia (CC) is linked to poor prognosis. Although the mechanisms promoting this condition are not known, several circulating proteins have been proposed to contribute. We analyzed the plasma proteome in cancer subjects in order to identify factors associated with cachexia.

DESIGN/SUBJECTS

Plasma was obtained from a screening cohort of 59 patients, newly diagnosed with suspected gastrointestinal cancer, with (n = 32) or without (n = 27) cachexia. Samples were subjected to proteomic profiling using 760 antibodies (targeting 698 individual proteins) from the Human Protein Atlas project. The main findings were validated in a cohort of 93 patients with verified and advanced pancreas cancer.

RESULTS

Only six proteins displayed differential plasma levels in the screening cohort. Among these, Carnosine Dipeptidase 1 (CNDP1) was confirmed by sandwich immunoassay to be lower in CC (p = 0.008). In both cohorts, low CNDP1 levels were associated with markers of poor prognosis including weight loss, malnutrition, lipid breakdown, low circulating albumin/IGF1 levels and poor quality of life. Eleven of the subjects in the discovery cohort were finally diagnosed with non-malignant disease but omitting these subjects from the analyses did not have any major influence on the results.

CONCLUSIONS

In gastrointestinal cancer, reduced plasma levels of CNDP1 associate with signs of catabolism and poor outcome. These results, together with recently published data demonstrating lower circulating CNDP1 in subjects with glioblastoma and metastatic prostate cancer, suggest that CNDP1 may constitute a marker of aggressive cancer and CC.

Mass spectrometry-based proteomic quest for diabetes biomarkers

Diabetes mellitus (DM) is a metabolic disorder characterized by chronic hyperglycemia, which affects hundreds of millions of individuals worldwide. Early diagnosis and complication prevention of DM are helpful for disease treatment. However, currently available DM diagnostic markers fail to achieve the goals. Identification of new diabetic biomarkers assisted by mass spectrometry (MS)-based proteomics may offer solution for the clinical challenges. Here, we review the current status of biomarker discovery in DM, and describe the pressure cycling technology (PCT)-Sequential Window Acquisition of all Theoretical fragment-ion (SWATH) workflow for sample-processing, biomarker discovery and validation, which may accelerate the current quest for DM biomarkers. This article is part of a Special Issue entitled: Medical Proteomics.

Affinity proteomics reveals elevated muscle proteins in plasma of children with cerebral malaria

Systemic inflammation and sequestration of parasitized erythrocytes are central processes in the pathophysiology of severe Plasmodium falciparum childhood malaria. However, it is still not understood why some children are more at risks to develop malaria complications than others. To identify human proteins in plasma related to childhood malaria syndromes, multiplex antibody suspension bead arrays were employed. Out of the 1,015 proteins analyzed in plasma from more than 700 children, 41 differed between malaria infected children and community controls, whereas 13 discriminated uncomplicated malaria from severe malaria syndromes. Markers of oxidative stress were found related to severe malaria anemia while markers of endothelial activation, platelet adhesion and muscular damage were identified in relation to children with cerebral malaria. These findings suggest the presence of generalized vascular inflammation, vascular wall modulations, activation of endothelium and unbalanced glucose metabolism in severe malaria. The increased levels of specific muscle proteins in plasma implicate potential muscle damage and microvasculature lesions during the course of cerebral malaria.

Why do some malaria-infected children develop severe and lethal forms of the disease, while others only have mild forms? In order to try to find potential answers or clues to this question, we have here analyzed more than 1,000 different human proteins in the blood of more than 500 malaria-infected children from Ibadan in Nigeria, a holoendemic malaria region. We identified several proteins that were present at higher levels in the blood from the children that developed severe malaria in comparison to those that did not. Some of the most interesting identified proteins were muscle specific proteins, which indicate that damaged muscles could be a discriminatory pathologic event in cerebral malaria compared to other malaria cases. These findings will hopefully lead to an increased understanding of the disease and may contribute to the development of clinical algorithms that could predict which children are more at risks to severe malaria. This in turn will be of high value in the management of these children in already overloaded tertiary-care health facilities in urban large densely-populated sub-Saharan cities with holoendemic malaria such as in the case of Ibadan and Lagos.

The Use of Antibodies in Small-Molecule Drug Discovery

Antibodies are powerful research tools that can be used in many areas of biology to probe, measure, and perturb various biological structures. Successful drug discovery is dependent on the correct identification of a target implicated in disease, coupled with the successful selection, optimization, and development of a candidate drug. Because of their specific binding characteristics, with regard to specificity, affinity, and avidity, coupled with their amenability to protein engineering, antibodies have become a key tool in drug discovery, enabling the quantification, localization, and modulation of proteins of interest. This review summarizes the application of antibodies and other protein affinity reagents as specific research tools within the drug discovery process.

Colorectal cancer candidate biomarkers identified by tissue secretome proteome profiling

Colorectal cancer (CRC) is a major health problem. Biomarkers associated with molecular changes in cancer cells can aid early detection, diagnosis, prognosis, therapy selection, and disease monitoring. Tumor tissue secretomes are a rich source of candidate biomarkers. To identify CRC protein biomarkers, secretomes of four pairs of human CRC tissue and patient-matched normal colon tissue samples, and secretomes of five CRC cell lines were analyzed by GeLC-MS/MS. Subsequent data analysis was based on label-free spectral counting, Ingenuity Pathway Analysis, Secretome/SignalP, STRING and Cytoscape, resulting in 2703 protein identifications in the tissue secretomes, of which 409 proteins were significantly more present in CRC samples than in controls. Biomarker selection of 76 candidates was based on consistent and abundant over-representation in cancer- compared to control-secretomes, and presumed neoplastic origin. Overlap analysis with previously obtained datasets revealed 21 biomarkers suited for early detection of CRC. Immunohistochemistry confirmed overexpression in CRC of one candidate marker (MCM5). In conclusion, a human reference dataset of 76 candidate biomarkers was identified for which we illustrate that combination with existing pre-clinical datasets allows pre-selection of biomarkers for blood- or stool-based assays to support clinical management of CRC. Further dedicated validation studies are required to demonstrate their clinical applicability.

BIOLOGICAL SIGNIFICANCE

Tissue secretome proteomes are a rich source of candidate biomarkers. Several secretome proteome datasets have been obtained from pre-clinical in vitro and in vivo colorectal cancer (CRC) model systems, yielding promising CRC biomarkers obtained under well-defined experimentally controlled conditions. However, which of these biomarker proteins are actually secreted by human CRC samples was not known. To our knowledge, this is the first study that directly compares secretome proteomes from clinically relevant human CRC tissues to patient-matched normal colon tissues. We identified 76 human CRC protein biomarkers that may facilitate blood-based or stool-based assay development to support clinical management of CRC. Overlap analysis with datasets from well-defined pre-clinical studies helps to determine what clinical application suits these human CRC biomarkers best, i.e. early detection, diagnosis, prognosis, therapy selection, and/or disease monitoring of CRC. This is demonstrated for a CRC mouse model dataset, revealing 21 human CRC biomarkers suited for early detection of CRC.

Highly multiplexed antibody suspension bead arrays for plasma protein profiling

Alongside the increasing availability of affinity reagents, antibody microarrays have become a powerful tool to screen for target proteins in complex samples. Applying directly labeled samples onto arrays instead of using sandwich assays offers an approach to facilitate a systematic, high-throughput, and flexible exploration of protein profiles in body fluids such as serum or plasma. As an alternative to planar arrays, a system based on color-coded beads for the creation of antibody arrays in suspension has become available to offer a microtiter plate-based option for screening larger number of samples with variable sets of capture reagents. A procedure was established for analyzing biotinylated samples without the necessity to remove excess labeling substance. We have shown that this assay system allows detecting proteins down into lower pico-molar and higher pg/ml levels with dynamic ranges over three orders of magnitude. Presently, this workflow enables the profiling of 384 samples for up to 384 proteins per assay.

Cross-reactivity in antibody microarrays and multiplexed sandwich assays: shedding light on the dark side of multiplexing

Immunoassays are indispensable for research and clinical analysis, and following the emergence of the omics paradigm, multiplexing of immunoassays is more needed than ever. Cross-reactivity (CR) in multiplexed immunoassays has been unexpectedly difficult to mitigate, preventing scaling up of multiplexing, limiting assay performance, and resulting in inaccurate and even false results, and wrong conclusions. Here, we review CR and its consequences in single and dual antibody single-plex and multiplex assays. We establish a distinction between sample-driven and reagent-driven CR, and describe how it affects the performance of antibody microarrays. Next, we review and evaluate various platforms aimed at mitigating CR, including SOMAmers and protein fractionation-bead assays, as well as dual Ab methods including (i) conventional multiplex assays, (ii) proximity ligation assays, (iii) immuno-mass spectrometry, (iv) sequential multiplex analyte capture, (v) antibody colocalization microarrays and (vi) force discrimination assays.

Identification of candidate serum proteins for classifying well-differentiated small intestinal neuroendocrine tumors

BACKGROUND

Patients with well-differentiated small intestine neuroendocrine tumors (WD-SI-NETs) are most often diagnosed at a metastatic stage of disease, which reduces possibilities for a curative treatment. Thus new approaches for earlier detection and improved monitoring of the disease are required.

MATERIALS AND METHODS

Suspension bead arrays targeting 124 unique proteins with antibodies from the Human Protein Atlas were used to profile biotinylated serum samples. Discoveries from a cohort of 77 individuals were followed up in a cohort of 132 individuals both including healthy controls as well as patients with untreated primary WD-SI-NETs, lymph node metastases and liver metastases.

RESULTS

A set of 20 antibodies suggested promising proteins for further verification based on technically verified statistical significance. Proceeding, we assessed the classification performance in an independent cohort of patient serum, achieving, classification accuracy of up to 85% with different subsets of antibodies in respective pairwise group comparisons. The protein profiles of nine targets, namely IGFBP2, IGF1, SHKBP1, ETS1, IL1α, STX2, MAML3, EGR3 and XIAP were verified as significant contributors to tumor classification.

CONCLUSIONS

We propose new potential protein biomarker candidates for classifying WD-SI-NETs at different stage of disease. Further evaluation of these proteins in larger sample sets and with alternative approaches is needed in order to further improve our understanding of their functional relation to WD-SI-NETs and their eventual use in diagnostics.

Selectivity analysis of single binder assays used in plasma protein profiling

The increasing availability of antibodies toward human proteins enables broad explorations of the proteomic landscape in cells, tissues, and body fluids. This includes assays with antibody suspension bead arrays that generate protein profiles of plasma samples by flow cytometer analysis. However, antibody selectivity is context dependent so it is necessary to corroborate on-target detection over off-target binding. To address this, we describe a concept to directly verify interactions from antibody-coupled beads by analysis of their eluates by Western blots and MS. We demonstrate selective antibody binding in complex samples with antibodies toward a set of chosen proteins with different abundance in plasma and serum, and illustrate the need to adjust sample and bead concentrations accordingly. The presented approach will serve as an important tool for resolving differential protein profiles from antibody arrays within plasma biomarker discoveries.

Antibody-based profiling of cerebrospinal fluid within multiple sclerosis

Antibody suspension bead arrays have proven to enable multiplexed and high-throughput protein profiling in unfractionated plasma and serum samples through a direct labeling approach. We here describe the development and application of an assay for protein profiling of cerebrospinal fluid (CSF). While setting up the assay, systematic intensity differences between sample groups were observed that reflected inherent sample specific total protein amounts. Supplementing the labeling reaction with BSA and IgG diminished these differences without impairing the apparent sensitivity of the assay. We also assessed the effects of heat treatment on the analysis of CSF proteins and applied the assay to profile 43 selected proteins by 101 antibodies in 339 CSF samples from a multiple sclerosis (MS) cohort. Two proteins, GAP43 and SERPINA3 were found to have a discriminating potential with altered intensity levels between sample groups. GAP43 was detected at significantly lower levels in secondary progressive MS compared to early stages of MS and the control group of other neurological diseases. SERPINA3 instead was detected at higher levels in all MS patients compared to controls. The developed assay procedure now offers new possibilities for broad-scale protein profiling of CSF within neurological disorders.

Profiling post-centrifugation delay of serum and plasma with antibody bead arrays

Several biobanking initiatives have emerged to create extensive collections of specimen for biomedical studies and various analytical platforms. An affinity proteomic analysis with antibody suspension bead arrays was conducted to investigate the influence of the pre-analytical time and temperature conditions on blood derived samples. Serum and EDTA plasma prepared from 16 individuals was centrifuged and aliquots were kept either at 4°C or in ambient temperature for 1h and up to 36h prior to first storage. Multiplexed protein profiles of post-centrifugation delay were generated in 384 biotinylated samples using 373 antibodies that targeted 343 unique proteins. Very few profiles were observed as significantly altered by the studied temperature and time intervals. Single binder and sandwich assays revealed decreasing levels of caldesmon 1 (CALD1) related to EDTA standard tubes and prolonged post-centrifugation delay of 36h. Indications from changes in CALD1 levels require further confirmation in independent material, but the current data suggests that samples should preferentially be frozen during the day of collection when to be profiled with antibody arrays selected for this study.

BIOLOGICAL SIGNIFICANCE

Affinity-based profiling of serum and plasma by microarray assays can provide unique opportunities for the discovery of biomarkers. It is though often not known how differences in sample handling after collection influence the downstream analysis. By profiling three types of blood preparations for alterations in protein profiles with respect to time and temperature post centrifugation, we addressed an important component in the analysis and of such specimen. We believe that this analysis adds valuable information to be considered when biobanking blood derived samples. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics.

The role of proteomics in prostate cancer research: biomarker discovery and validation

PURPOSE

Prostate Cancer (PCa) represents the second most frequent type of tumor in men worldwide. Incidence increases with patient age and represents the most important risk factor. PCa is mostly characterized by indolence, however in a small percentage of cases (3%) the disease progresses to a metastatic state. To date, the most important issue concerning PCa research is the difficulty in distinguishing indolent from aggressive disease. This problem frequently results in low-grade PCa patient overtreatment and, in parallel; an effective treatment for distant and aggressive disease is not yet available.

RESULT

Proteomics represents a promising approach for the discovery of new biomarkers able to improve the management of PCa patients. Markers more specific and sensitive than PSA are needed for PCa diagnosis, prognosis and response to treatment. Moreover, proteomics could represent an important tool to identify new molecular targets for PCa tailored therapy. Several possible PCa biomarkers sources, each with advantages and limitations, are under investigation, including tissues, urine, serum, plasma and prostatic fluids. Innovative high-throughput proteomic platforms are now identifying and quantifying new specific and sensitive biomarkers for PCa detection, stratification and treatment. Nevertheless, many putative biomarkers are still far from being applied in clinical practice.

CONCLUSIONS

This review aims to discuss the recent advances in PCa proteomics, emphasizing biomarker discovery and their application to clinical utility for diagnosis and patient stratification.

Antibodies for profiling the human proteome-The Human Protein Atlas as a resource for cancer research

In this review, we present an update on the progress of the Human Protein Atlas, with an emphasis on strategies for validating immunohistochemistry-based protein expression patterns and on the possibilities to extend the map of protein expression patterns for cancer research projects. The objectives underlying the Human Protein Atlas include (i) the generation of validated antibodies toward a major isoform of all proteins encoded by the human genome, (ii) creating an information database of protein expression patterns in normal human tissues, in cells, and in cancer, and (iii) utilizing generated antibodies and protein expression data as tools to identify clinically useful biomarkers. The success of such an effort is dependent on the validity of antibodies as specific binders of intended targets in applications used to map protein expression patterns. The development of strategies to support specific target binding is crucial and remains a challenge as a large fraction of proteins encoded by the human genome is poorly characterized, including the approximately one-third of all proteins lacking evidence of existence. Conceivable methods for validation include the use of paired antibodies, i.e. two independent antibodies targeting different and nonoverlapping epitopes on the same protein as well as comparative analysis of mRNA expression patterns with corresponding proteins.

Targeted proteome investigation via selected reaction monitoring mass spectrometry

Due to the enormous complexity of proteomes which constitute the entirety of protein species expressed by a certain cell or tissue, proteome-wide studies performed in discovery mode are still limited in their ability to reproducibly identify and quantify all proteins present in complex biological samples. Therefore, the targeted analysis of informative subsets of the proteome has been beneficial to generate reproducible data sets across multiple samples. Here we review the repertoire of antibody- and mass spectrometry (MS) -based analytical tools which is currently available for the directed analysis of predefined sets of proteins. The topics of emphasis for this review are Selected Reaction Monitoring (SRM) mass spectrometry, emerging tools to control error rates in targeted proteomic experiments, and some representative examples of applications. The ability to cost- and time-efficiently generate specific and quantitative assays for large numbers of proteins and posttranslational modifications has the potential to greatly expand the range of targeted proteomic coverage in biological studies. This article is part of a Special Section entitled: Understanding genome regulation and genetic diversity by mass spectrometry.

Opportunities for sensitive plasma proteome analysis

Despite great interest, investments, and efforts, the ongoing search for plasma protein biomarkers for disease so far has come up surprisingly empty-handed. Although discovery programs have revealed large numbers of biomarker candidates, the clinical utility has been validated for only a very small number of these. While this disappointing state of affairs may suggest that plasma protein biomarkers have little more to offer for diagnostics, we take the perspective that experimental conditions might not have been optimal and that analyses will be required that offer far greater sensitivity than currently available, in terms of numbers of molecules needed for unambiguous detection. Accordingly, techniques are needed to search deep and wide for protein biomarker candidates. The requirements and feasibility of such assays will be discussed.

Multiplexed immuno-precipitation with 1725 commercially available antibodies to cellular proteins

Antibody array analysis of complex samples requires capture reagents with exceptional specificity. The frequency of antibodies with label-based detection may be as low as 5%. Here, however, we show that as many as 25% of commercially available antibodies are useful when biotinylated cellular proteins are fractionated by size exclusion chromatography (SEC) first. A microsphere multiplex with 1725 antibodies to cellular proteins was added to 24 SEC fractions, labelled with streptavidin and analyzed by flow cytometry (microsphere-based affinity proteomics, MAP) The SEC-MAP approach resolved different targets captured by each antibody as reactivity peaks across the separation range of the SEC column (10-670kDa). Complex reactivity profiles demonstrated that most antibodies bound more than one target. However, specific binding was readily detected as reactivity peaks common for different antibodies to the same protein. We optimized sample preparation and found that amine-reactive biotin rarely inhibited antibody binding when the biotin to lysine ratio was kept below 1:1 during labelling. Moreover, several epitopes that were inaccessible to antibodies in native proteins were unmasked after heat denaturation with 0.1% of SDS. The SEC-MAP format should allow researchers to build multiplexed assays with antibodies purchased for use in e.g. Western blotting.

The Human Protein Atlas as a proteomic resource for biomarker discovery

The analysis of tissue-specific expression at both the gene and protein levels is vital for understanding human biology and disease. Antibody-based proteomics provides a strategy for the systematic generation of antibodies against all human proteins to combine with protein profiling in tissues and cells using tissue microarrays, immunohistochemistry and immunofluorescence. The Human Protein Atlas project was launched in 2003 with the aim of creating a map of protein expression patterns in normal cells, tissues and cancer. At present, 11,200 unique proteins corresponding to over 50% of all human protein-encoding genes have been analysed. All protein expression data, including underlying high-resolution images, are published on the free and publically available Human Protein Atlas portal (http://www.proteinatlas.org). This database provides an important source of information for numerous biomedical research projects, including biomarker discovery efforts. Moreover, the global analysis of how our genome is expressed at the protein level has provided basic knowledge on the ubiquitous expression of a large proportion of our proteins and revealed the paucity of cell- and tissue-type-specific proteins.

Classification of protein profiles from antibody microarrays using heat and detergent treatment

Antibody microarrays offer new opportunities for exploring the proteome and to identify biomarker candidates in human serum and plasma. Here, we have investigated the effect of heat and detergents on an antibody-based suspension bead array (SBA) assay using polyclonal antibodies and biotinylated plasma samples. With protein profiles from more than 2300 antibodies generated in 384-plex antibody SBAs, three major classes of heat and detergent susceptibility could be described. The results show that washing of the beads with SDS (rather than Tween) after target binding lowered intensity levels of basically all profiles and that about 50% of the profiles appeared to be lowered to a similar extent by heating of the sample. About 33% of the profiles appeared to be insensitive to heat treatment while another 17% showed a positive influence of heat to yield elevated profiles. The results suggest that the classification of antibodies is driven by the molecular properties of the antibody-antigen interaction and can generally not be predicted based on protein class or Western blot data. The experimental scheme presented here can be used to systematically categorize antibodies and thereby combine antibodies with similar properties into targeted arrays for analysis of plasma and serum.

Generation of monospecific antibodies based on affinity capture of polyclonal antibodies

A method is described to generate and validate antibodies based on mapping the linear epitopes of a polyclonal antibody followed by sequential epitope-specific capture using synthetic peptides. Polyclonal antibodies directed towards four proteins RBM3, SATB2, ANLN, and CNDP1, potentially involved in human cancers, were selected and antibodies to several non-overlapping epitopes were generated and subsequently validated by Western blot, immunohistochemistry, and immunofluorescence. For all four proteins, a dramatic difference in functionality could be observed for these monospecific antibodies directed to the different epitopes. In each case, at least one antibody was obtained with full functionality across all applications, while other epitope-specific fractions showed no or little functionality. These results present a path forward to use the mapped binding sites of polyclonal antibodies to generate epitope-specific antibodies, providing an attractive approach for large-scale efforts to characterize the human proteome by antibodies.

ProteinSeq: high-performance proteomic analyses by proximity ligation and next generation sequencing

Despite intense interest, methods that provide enhanced sensitivity and specificity in parallel measurements of candidate protein biomarkers in numerous samples have been lacking. We present herein a multiplex proximity ligation assay with readout via realtime PCR or DNA sequencing (ProteinSeq). We demonstrate improved sensitivity over conventional sandwich assays for simultaneous analysis of sets of 35 proteins in 5 µl of blood plasma. Importantly, we observe a minimal tendency to increased background with multiplexing, compared to a sandwich assay, suggesting that higher levels of multiplexing are possible. We used ProteinSeq to analyze proteins in plasma samples from cardiovascular disease (CVD) patient cohorts and matched controls. Three proteins, namely P-selectin, Cystatin-B and Kallikrein-6, were identified as putative diagnostic biomarkers for CVD. The latter two have not been previously reported in the literature and their potential roles must be validated in larger patient cohorts. We conclude that ProteinSeq is promising for screening large numbers of proteins and samples while the technology can provide a much-needed platform for validation of diagnostic markers in biobank samples and in clinical use.

Antibody array analysis of labelled proteomes: how should we control specificity?

Researchers who use protein binders in multiplexed assays can be divided into two camps. One believes that arrays with proteome-wide coverage will become a reality once we have developed binders for all proteins. The sceptics claim that detection with immobilized protein binders and sample labelling will not provide the required specificity. In this article, we review the evidence showing that antibody array analysis of labelled samples can provide meaningful data and discuss the issues raised by the sceptics. We argue that direct the evidence for monospecificity has yet to be published. This will require assays designed to resolve the proteins captured by each binder. One option is to combine array measurement with protein separation. We have developed an assay where labelled sample proteins are separated by size exclusion chromatography (SEC) before contact with microsphere-based arrays (Size-MAP; size exclusion chromatography-resolved microsphere-based affinity proteomics). The effect is an 'antibody array Western blot' where reactivity of immobilized binders is resolved against the size of the proteins in the sample. We show that Size-MAP is useful to discriminate monospecific- and polyreactive antibodies and for automatic detection of reacting with the same target. The possibility to test specificity directly in array-based measurement should be useful to select the best binders and to determine whether the DNA microarray for the proteome is a realistic goal or not.