High-throughput proteomics using antibody microarrays: an update

Comparative serum proteomic analysis of a selected protein panel in individuals with schizophrenia and bipolar disorder and the impact of genetic risk burden on serum proteomic profiles

The diagnostic criteria for schizophrenia (SCZ) and bipolar disorder (BD) are based on clinical assessments of symptoms. In this pilot study, we applied high-throughput antibody-based protein profiling to serum samples of healthy controls and individuals with SCZ and BD with the aim of identifying differentially expressed proteins in these disorders. Moreover, we explored the influence of polygenic burden for SCZ and BD on the serum levels of these proteins. Serum samples from 113 individuals with SCZ and 125 with BD from the PsyCourse Study and from 44 healthy controls were analyzed by using a set of 155 antibodies in an antibody-based assay targeting a selected panel of 95 proteins. For the cases, genotyping and imputation were conducted for DNA samples and SCZ and BD polygenic risk scores (PRS) were calculated. Univariate linear and logistic models were used for association analyses. The comparison between SCZ and BD revealed two serum proteins that were significantly elevated in BD after multiple testing adjustment: "complement C9" and "Interleukin 1 Receptor Accessory Protein". Moreover, the first principal component of variance in the proteomics dataset differed significantly between SCZ and BD. After multiple testing correction, SCZ-PRS, BD-PRS, and SCZ-vs-BD-PRS were not significantly associated with the levels of the individual proteins or the values of the proteome principal components indicating no detectable genetic effects. Overall, our findings contribute to the evidence suggesting that the analysis of circulating proteins could lead to the identification of distinctive biomarkers for SCZ and BD. Our investigation warrants replication in large-scale studies to confirm these findings.

Application of an antibody microarray for serum protein profiling of coronary artery stenosis

Protein expression profiling in the serum is used to identify novel biomarkers and investigate the signaling pathways in various diseases. The aim of the present study was to evaluate serum biomarkers associated with coronary artery stenosis resulting from atherosclerosis. The study included 4 groups of subjects: group A and B with and without coronary lesions, respectively, were selected from a previously reported cohort study on coronary atherosclerosis, control group C comprised of asymptomatic subjects and group D was used for independent validation of the microarray data by ELISA. Labeled serum proteins were profiled by an Explorer antibody array, which included 656 specific antibodies in two replicates (FullMoon Biosystems, USA). Cadherin-P, interleukin-5, glutathione S-transferase Mu, and neuronal nitric oxide synthase were sex-independently increased in Group A compared with those in group B. The microarray data on cadherin-P were externally validated in an independent group D using ELISA. Fibroblast growth factor-1, FGF-2, collagen II, granulocyte-macrophage colony-stimulating factor, IL-1 alpha, angiopoietin-2, granulocyte colony-stimulating factor, lymphocyte cell-specific protein tyrosine kinase, and IkappaB kinase b were increase in men in group A compared with group B. Cyclin-dependent kinase 1, DNA fragmentation factor subunit alpha DFF45/ICAD, adenovirus type 2 E1A, calponin, ADP-ribosylation factor-6, muscle-specific actin, thyroid hormone receptor alpha, and alpha-methylacyl-CoA racemase were specifically increased in women in Group A compared with group B. Alterations in the levels of specific proteins may point to the signaling pathways contributing to coronary atherosclerosis, and these proteins will be useful biomarkers for the progression of cardiovascular diseases.

Comparative Analysis of Skeleton Muscle Proteome Profile between Yak and Cattle Provides Insight into High-Altitude Adaptation

Background::

Mechanisms underlying yak adaptation to high-altitude environments have been investigated at the levels of morphology, anatomy, physiology, genome and transcriptome, but have not been explored at the proteome level.

Objective:

The protein profiles were compared between yak and cattle to explore molecular mechanisms underlying yak adaptation to high altitude conditions.

Methods:

In the present study, an antibody microarray chip was developed, which included 6,500 mouse monoclonal antibodies. Immunoprecipitation and mass spectrometry were performed on 12 selected antibodies which showed that the chip was highly specific. Using this chip, muscle tissue proteome was compared between yak and cattle, and 12 significantly Differentially Expressed Proteins (DEPs) between yak and cattle were identified. Their expression levels were validated using Western blot.

Results:

ompared with cattle, higher levels of Rieske Iron-Sulfur Protein (RISP), Cytochrome C oxidase subunit 4 isoform 1, mitochondrial (COX4I1), ATP synthase F1 subunit beta (ATP5F1B), Sarcoplasmic/ Endoplasmic Reticulum Calcium ATPase1 (SERCA1) and Adenosine Monophosphate Deaminase1 (AMPD1) in yak might improve oxygen utilization and energy metabolism. Pyruvate Dehydrogenase protein X component (PDHX) and Acetyltransferase component of pyruvate dehydrogenase complex (DLAT) showed higher expression levels and L-lactate dehydrogenase A chain (LDHA) showed lower expression level in yak, which might help yak reduce the accumulation of lactic acid. In addition, higher expression levels of Filamin C (FLNC) and low levels of AHNAK and Four and a half LIM domains 1 (FHL1) in yak might reduce the risks of pulmonary arteries vasoconstriction, remodeling and hypertension.

Conclusion:

Overall, the present study reported the differences in protein profile between yak and cattle, which might be helpful to further understand molecular mechanisms underlying yak adaptation to high altitude environments.

Aptamer-Based Proteomics Identifies Mortality-Associated Serum Biomarkers in Dialysis-Dependent AKI Patients

Introduction

Currently, no effective therapies exist to reduce the high mortality associated with dialysis-dependent acute kidney injury (AKI-D). Serum biomarkers may be useful in understanding the pathophysiological processes involved with AKI and the severity of injury, and point to novel therapeutic targets.

Methods

Study day 1 serum samples from 100 patients and day 8 samples from 107 patients enrolled in the Veteran’s Affairs/National Institutes of Health Acute Renal Failure Trial Network study were analyzed by the slow off-rate modified aptamers scan proteomic platform to profile 1305 proteins in each sample. Patients in each cohort were classified into tertiles based on baseline biomarker measurements. Cox regression analyses were performed to examine the relationships between serum levels of each biomarker and mortality.

Results

Changes in the serum levels of 54 proteins, 33 of which increased and 21 of which decreased, were detected when comparing samples of patients who died in the first 8 days versus patients who survived >8 days. Among the 33 proteins that increased, higher serum levels of fibroblast growth factor-23 (FGF23), tissue plasminogen activator (tPA), neutrophil collagenase (matrix metalloproteinase-8), and soluble urokinase plasminogen activator receptor, when stratified by tertiles, were associated with higher mortality. The association with mortality persisted for each of these proteins after adjusting for other potential risk factors, including age, sex, cardiovascular sequential organ failure assessment score, congestive heart failure, and presence of diabetes. Upper tertile levels of FGF23, tPA, and interleukin-6 on day 8 were associated with increased mortality; however, FGF23 barely lost significance after multivariable adjustment.

Conclusions

Our results underscore an emerging proteomics tool capable of identifying low-abundance serum proteins important not only in the pathogenesis of AKI-D, but which is also helpful in discriminating AKI-D patients with high mortality.

Direct labeling of serum proteins by fluorescent dye for antibody microarray

Analysis of serum proteome by antibody microarray is used to identify novel biomarkers and to study signaling pathways including protein phosphorylation and protein-protein interactions. Labeling of serum proteins is important for optimal performance of the antibody microarray. Proper choice of fluorescent label and optimal concentration of protein loaded on the microarray ensure good quality of imaging that can be reliably scanned and processed by the software. We have optimized direct serum protein labeling using fluorescent dye Arrayit Green 540 (Arrayit Corporation, USA) for antibody microarray. Optimized procedure produces high quality images that can be readily scanned and used for statistical analysis of protein composition of the serum.

Progress and prospects for the discovery of biomarkers for gastric cancer: a focus on proteomics

INTRODUCTION

Patient outcomes from gastric cancer vary due to the complexity of stomach carcinogenesis. Recent research using proteomic technologies has targeted components of all of these systems in order to develop biomarkers to aid the early diagnosis of gastric cancer and to assist in prognostic stratification. Areas covered: This review is comprised of evidence obtained from literature searches from PubMed. It covers the evidence of diagnostic, prognostic, and predictive biomarkers for gastric cancer using proteomic technologies, and provides up-to-date references. Expert commentary: The proteomic technologies have not only enabled the screening of a large number of samples, but also enabled the identification of diagnostic, prognostic and predictive biomarkers for gastric cancer. While major challenges still remain, to date, proteomic studies in gastric cancer have provided a wealth of information in revealing proteome alterations associated with the disease.

Advancing the global proteome survey platform by using an oriented single chain antibody fragment immobilization approach

Increasing the understanding of a proteome and how its protein composition is affected by for example different diseases, such as cancer, has the potential to improve strategies for early diagnosis and therapeutics. The Global Proteome Survey or GPS is a method that combines mass spectrometry and affinity enrichment with the use of antibodies. The technology enables profiling of complex proteomes in a species independent manner. The sensitivity of GPS, and other methods relying on affinity enrichment, is largely affected by the activity of the exploited affinity reagent. We here present an improvement of the GPS platform by utilizing an antibody immobilization approach which ensures a controlled immobilization process of the antibody to the magnetic bead support. More specifically, we make use of an antibody format that enables site-directed biotinylation and use this in combination with streptavidin coated magnetic beads. The performance of the expanded GPS platform was evaluated by profiling yeast proteome samples. We demonstrate that the oriented antibody immobilization strategy increases the ability of the GPS platform and results in larger fraction of functional antibodies. Additionally, we show that this new antibody format enabled in-solution capture, i.e. immobilization of the antibodies after sample incubation. A workflow has been established that permit the use of an oriented immobilization strategy for the GPS platform.

Evaluation of Solid Supports for Slide- and Well-Based Recombinant Antibody Microarrays

Antibody microarrays have emerged as an important tool within proteomics, enabling multiplexed protein expression profiling in both health and disease. The design and performance of antibody microarrays and how they are processed are dependent on several factors, of which the interplay between the antibodies and the solid surfaces plays a central role. In this study, we have taken on the first comprehensive view and evaluated the overall impact of solid surfaces on the recombinant antibody microarray design. The results clearly demonstrated the importance of the surface-antibody interaction and showed the effect of the solid supports on the printing process, the array format of planar arrays (slide- and well-based), the assay performance (spot features, reproducibility, specificity and sensitivity) and assay processing (degree of automation). In the end, two high-end recombinant antibody microarray technology platforms were designed, based on slide-based (black polymer) and well-based (clear polymer) arrays, paving the way for future large-scale protein expression profiling efforts.

Deciphering Asthma Biomarkers with Protein Profiling Technology

Asthma is a chronic inflammatory disease of the airways, resulting in bronchial hyperresponsiveness with every allergen exposure. It is now clear that asthma is not a single disease, but rather a multifaceted syndrome that results from a variety of biologic mechanisms. Asthma is further problematic given that the disease consists of many variants, each with its own etiologic and pathophysiologic factors, including different cellular responses and inflammatory phenotypes. These facets make the rapid and accurate diagnosis (not to mention treatments) of asthma extremely difficult. Protein biomarkers can serve as powerful detection tools in both clinical and basic research applications. Recent endeavors from biomedical researchers have developed technical platforms, such as cytokine antibody arrays, that have been employed and used to further the global analysis of asthma biomarker studies. In this review, we discuss potential asthma biomarkers involved in the pathophysiologic process and eventual pathogenesis of asthma, how these biomarkers are being utilized, and how further testing methods might help improve the diagnosis and treatment strain that current asthma patients suffer.

Proteomics in gastric cancer research: Benefits and challenges

Among various cancers, gastric cancer (GC) exhibits relatively high morbidity and mortality rate worldwide. The lack of effective methods in early detection and diagnosis, and immediate therapies makes treating such disease a challenge for both clinicians and oncologists. Proteomics has emerged as a promising technology platform for rationally identifying biomarkers and novel therapeutic targets for GC, as well as discovering underlying mechanisms of carcinogenesis. Its application has greatly benefited mechanistic studies of this disease. This review will demonstrate the applications of proteomic technology in GC research. The advantages and shortcomings of this technology, as reflected by current studies, will also be discussed to improve and expand its application in the field of cancer research.

Antibody arrays in biomarker discovery

All of life is regulated by complex and organized chemical reactions that help dictate when to grow, to move, to reproduce, and to die. When these processes go awry, or are interrupted by pathological agents, diseases such as cancer, autoimmunity, or infections can result. Cytokines, chemokines, growth factors, adipokines, and other chemical moieties make up a vast subset of these chemical reactions that are altered in disease states, and monitoring changes in these molecules could provide for the identification of disease biomarkers. From the first identification of carcinoembryonic antigen, to the discovery of prostate-specific antigen, to numerous others described within, biomarkers of disease are detectable in a plethora of sample types. The growing number of biomarkers for infection, autoimmunity, and cancer allow for increasingly early detection, to identification of novel drug targets, to prognostic indicators of disease outcome. However, more and more studies are finding that a single cytokine or growth factor is insufficient as a true disease biomarker and that a more global perspective is needed to understand true disease biology. Such a broad view requires a multiplexed platform for chemical detection, and antibody arrays meet and exceed this need by performing this detection in a high-throughput fashion. Herein, we will discuss how antibody arrays have evolved, and how they have helped direct new drug target design, helped identify therapeutic disease markers, and helped in earlier disease detection. From asthma to renal disease, and neurological dysfunction to immunologic disorders, antibody arrays afford a bright future for new biomarkers discovery.

Preparation of molecularly imprinted polymers for the recognition of proteins via the generation of peptide-fragment binding sites by semi-covalent imprinting and enzymatic digestion

An acryloyl protein was copolymerized with a crosslinker, followed by enzymatic digestion, yielding protein imprinted polymers bearing peptide-fragment binding sites.

Antibody array in a multiwell plate format for the sensitive and multiplexed detection of important plant pathogens

The global seed market is considered to be an important industry with a total value of $10,543 million US dollars in 2012. Because plant pathogens such as bacteria and viruses cause a significant economic loss to both producers and exporters, the seed export industry urgently requires rapid, sensitive, and inexpensive testing for the pathogens to prevent disease spreading worldwide. This study developed an antibody array in a multiwell plate format to simultaneously detect four crucial plant pathogens, namely, a bacterial fruit blotch bacterium Acidovorax avenae subsp. citrulli (Aac), Chilli veinal mottle virus (ChiVMV, potyvirus), Watermelon silver mottle virus (WSMoV, tospovirus serogroup IV), and Melon yellow spot virus (MYSV, tospovirus). The capture antibodies specific to the pathogens were immobilized on each well at preassigned positions by an automatic microarrayer. The antibodies on the arrays specifically captured the corresponding pathogens present in the sample extracts. The presence of pathogens bound on the capture antibodies was subsequently detected by a cocktail of fluorescently conjugated secondary antibodies. The limits of detection of the developed antibody array for the detection of Aac, ChiVMV, WSMoV, and MYSV were 5 × 10(5) CFU/mL, 30 ng/mL, 1000 ng/mL, and 160 ng/mL, respectively, which were very similar to those of the conventional ELISA method. The antibody array in a multiwell plate format accurately detected plant pathogens in single and multiple detections. Moreover, this format enables easy handling of the assay at a higher speed of operation.

Antibody array generation and use

Affinity proteomics, represented by antibody arrays, is a multiplex technology for high-throughput protein expression profiling of crude proteomes in a highly specific, sensitive, and miniaturized manner. The antibodies are individually deposited in an ordered pattern, an array, onto a solid support. Next, the sample is added, and any specifically bound proteins are detected and quantified using mainly fluorescence as the mode of detection. The binding pattern is then converted into a relative protein expression map, or protein atlas, delineating the composition of the sample at the molecular level. The technology provides unique opportunities for various applications, such as protein expression profiling, biomarker discovery, disease diagnostics, prognostics, evidence-based therapy selection, and disease monitoring. Here, we describe the generation and use of planar antibody arrays for serum protein profiling.

Recombinant antibody microarray for profiling the serum proteome of SLE

Systemic lupus erythematosus (SLE) is a severe autoimmune connective tissue disease. Our current knowledge about the serum proteome, or serum biomarker panels, reflecting disease and disease status is still very limited. Affinity proteomics, represented by recombinant antibody arrays, is a novel, multiplex technology for high-throughput protein expression profiling of crude serum proteomes in a highly specific, sensitive, and miniaturized manner. The antibodies are deposited one by one in an ordered pattern, an array, onto a solid support. Next, the sample is added, and any specifically bound proteins are detected and quantified. The binding pattern is then converted into a relative protein expression map, or protein map, deciphering the composition of the sample at the molecular level. The methodology provides unique opportunities for delineating serum biomarkers reflecting SLE, thus paving the way for improved diagnosis, classification, and prognosis.

The application of monoclonal antibodies in cancer diagnosis

Cancer becomes the second leading cause of death in the world. An effective strategy for early diagnosis of the disease is key to reduce the mortality and morbidity. Development of effective monoclonal antibody (mAb)-based assays or diagnostic imaging techniques for detection of antigens and small molecules that are released from cancerous cells will enhance modern diagnostic medicine of cancer significantly. Although mAb technology is still under development, recent advances in preparation of recombinant antigen and antibody engineering techniques have dramatically enhanced the applications of this technology in cancer diagnosis. Compared with other methods, mAb-based assays may provide spatial, temporal, accurate and quantitative measurement for diagnosis of the disease. This review summarizes the progress of the mAb-based assays in the field of molecular diagnosis of cancer.

Discovery of cancer biomarkers using antibody arrays

BACKGROUND

The cancer biomarkers field is being enriched by molecular profiling obtained by high-throughput approaches. In the context of other proteomic technologies, targeted antibody arrays are contributing strongly to the identification of protein cancer biomarker candidates.

OBJECTIVE

To describe innovative strategies multiplexing protein measurements of protein extracts of cultured cells, tissue and body fluids using antibody arrays that, combined with appropriate validation approaches, are enabling the discovery of cancer-associated biomarkers.

METHOD

The strategies and cancer biomarker candidates identified using antibody arrays reported so far that may assist in the diagnosis, surveillance and prognosis, and potentially for predictive and therapeutic purposes for patients affected with solid and hematological neoplasias.

RESULTS/CONCLUSION

Owing to their versatility, novel technological and experimental design implementations are broadening the applications of antibody arrays also for biomarker discovery. However, the cancer biomarker candidates delivered so far using this technology are still at an early developmental phase, requiring validation with many specimens focusing on specific clinical end points.

The current status of cancer biomarker research using tumour-associated antigens for minimal invasive and early cancer diagnostics

Tumour-associated antigens (TAA) can be detected prior to clinical diagnosis and thus would be ideal biomarkers for early detection of cancer using only a few microliters of a patient's serum. In this article we provide a summary of TAA screening and serum-profiling conducted for breast, prostate, lung and colon cancers. Different methodological approaches, including SEREX, SERPA, and phage display for TAA identification and TAA panels are summarised, and a revision of array based techniques is provided. The most promising studies performed on these cancers (performed with 80-400 serum samples, including controls) obtained sensitivities in a range of 44-95% and specificities of 80-100%. From the various studies reviewed, only one performed cross validation (AUC=0.71) in a prostate cancer study. Thus, albeit receiver operation characteristics are very promising, cross validation of most studies is still missing. Additionally, the concerted action of research groups for standardization of serum-TAA testing and cross validation is required. Along with today's technological options, the chances of establishing TAA biomarkers are now higher than ever before. This may also be true for confirmation and validation of already existing data, which is a prerequisite for implementation of TAA biomarkers into clinical diagnostics. This article is part of a Special Issue entitled: Integrated omics.

Identification of serum biomarker signatures associated with pancreatic cancer

Pancreatic cancer is an aggressive disease with poor prognosis, due, in part, to the lack of disease-specific biomarkers that could afford early and accurate diagnosis. With a recombinant antibody microarray platform, targeting mainly immunoregulatory proteins, we screened sera from 148 patients with pancreatic cancer, chronic pancreatitis, autoimmune pancreatitis (AIP), and healthy controls (N). Serum biomarker signatures were derived from training cohorts and the predictive power was evaluated using independent test cohorts. The results identified serum portraits distinguishing pancreatic cancer from N [receiver operating characteristics area under the curve (AUC) of 0.95], chronic pancreatitis (0.86), and AIP (0.99). Importantly, a 25-serum biomarker signature discriminating pancreatic cancer from the combined group of N, chronic pancreatitis, and AIP was determined. This signature exhibited a high diagnostic potential (AUC of 0.88). In summary, we present the first prevalidated, multiplexed serum biomarker signature for diagnosis of pancreatic cancer that may improve diagnosis and prevention in premalignant diseases and in screening of high-risk individuals.

Chemically-blocked antibody microarray for multiplexed high-throughput profiling of specific protein glycosylation in complex samples

In this study, we describe an effective protocol for use in a multiplexed high-throughput antibody microarray with glycan binding protein detection that allows for the glycosylation profiling of specific proteins. Glycosylation of proteins is the most prevalent post-translational modification found on proteins, and leads diversified modifications of the physical, chemical, and biological properties of proteins. Because the glycosylation machinery is particularly susceptible to disease progression and malignant transformation, aberrant glycosylation has been recognized as early detection biomarkers for cancer and other diseases. However, current methods to study protein glycosylation typically are too complicated or expensive for use in most normal laboratory or clinical settings and a more practical method to study protein glycosylation is needed. The new protocol described in this study makes use of a chemically blocked antibody microarray with glycan-binding protein (GBP) detection and significantly reduces the time, cost, and lab equipment requirements needed to study protein glycosylation. In this method, multiple immobilized glycoprotein-specific antibodies are printed directly onto the microarray slides and the N-glycans on the antibodies are blocked. The blocked, immobilized glycoprotein-specific antibodies are able to capture and isolate glycoproteins from a complex sample that is applied directly onto the microarray slides. Glycan detection then can be performed by the application of biotinylated lectins and other GBPs to the microarray slide, while binding levels can be determined using Dylight 549-Streptavidin. Through the use of an antibody panel and probing with multiple biotinylated lectins, this method allows for an effective glycosylation profile of the different proteins found in a given human or animal sample to be developed.

Quantitative proteomics targeting classes of motif-containing peptides using immunoaffinity-based mass spectrometry

The development of high-performance technology platforms for generating detailed protein expression profiles, or protein atlases, is essential. Recently, we presented a novel platform that we termed global proteome survey, where we combined the best features of affinity proteomics and mass spectrometry, to probe any proteome in a species independent manner while still using a limited set of antibodies. We used so called context-independent-motif-specific antibodies, directed against short amino acid motifs. This enabled enrichment of motif-containing peptides from a digested proteome, which then were detected and identified by mass spectrometry. In this study, we have demonstrated the quantitative capability, reproducibility, sensitivity, and coverage of the global proteome survey technology by targeting stable isotope labeling with amino acids in cell culture-labeled yeast cultures cultivated in glucose or ethanol. The data showed that a wide range of motif-containing peptides (proteins) could be detected, identified, and quantified in a highly reproducible manner. On average, each of six different motif-specific antibodies was found to target about 75 different motif-containing proteins. Furthermore, peptides originating from proteins spanning in abundance from over a million down to less than 50 copies per cell, could be targeted. It is worth noting that a significant set of peptides previously not reported in the PeptideAtlas database was among the profiled targets. The quantitative data corroborated well with the corresponding data generated after conventional strong cation exchange fractionation of the same samples. Finally, several differentially expressed proteins, with both known and unknown functions, many relevant for the central carbon metabolism, could be detected in the glucose- versus ethanol-cultivated yeast. Taken together, the study demonstrated the potential of our immunoaffinity-based mass spectrometry platform for reproducible quantitative proteomics targeting classes of motif-containing peptides.

Reno: regularized non-parametric analysis of protein lysate array data

MOTIVATION

The reverse-phase protein lysate arrays have been used to quantify the relative expression levels of a protein in a number of cellular samples simultaneously. To avoid quantification bias due to mis-specification of commonly used parametric models, a nonparametric approach based on monotone response curves may be used. The existing methods, however, aggregate the protein concentration levels of replicates of each sample, and therefore fail to account for within-sample variability.

RESULTS

We propose a method of regularization on protein concentration estimation at the level of individual dilution series to account for within-sample or within-group variability. We use an efficient algorithm to optimize an approximate objective function, with a data-adaptive approach to choose the level of shrinkage. Simulation results show that the proposed method quantifies protein concentration levels well. We show through the analysis of protein lysate array data from cell lines of different cancer groups that accounting for within-sample variability leads to better statistical analysis.

AVAILABILITY

Code written in statistical programming language R is available at: http://odin.mdacc.tmc.edu/~jhhu/Reno

Antibody microarrays as tools for biomarker discovery

The cancer biomarkers field is being enriched by molecular profiling obtained by high-throughput approaches. Targeted antibody arrays are strongly contributing to the identification of protein cancer -biomarker candidates and functional proteomic analyses. Due to their versatility, novel technological and experimental design implementations are broadening the applications of antibody arrays. However, the cancer biomarker candidates delivered to date using this technology are still in their early developmental phase, requiring validation with high number of specimens focusing on specific clinical endpoints. Innovative strategies multiplexing protein measurements of protein extracts of cultured cells, tissue and body fluids using antibody arrays combined with appropriate validation approaches are enabling the -discovery of cancer-associated biomarkers. This review describes these strategies and cancer biomarker candidates reported to date that may assist in the diagnosis, surveillance, prognosis, and potentially for predictive and therapeutic purposes for patients affected with solid and hematological neoplasias.

Advances in human proteomics at high scale with the SOMAscan proteomics platform

In 1997, while still working at NeXstar Pharmaceuticals, several of us made a proteomic bet. We thought then, and continue to think, that proteomics offers a chance to identify disease-specific biomarkers and improve healthcare. However, interrogating proteins turned out to be a much harder problem than interrogating nucleic acids. Consequently, the 'omics' revolution has been fueled largely by genomics. High-scale proteomics promises to transform medicine with personalized diagnostics, prevention, and treatment. We have now reached into the human proteome to quantify more than 1000 proteins in any human matrix - serum, plasma, CSF, BAL, and also tissue extracts - with our new SOMAmer-based proteomics platform. The surprising and pleasant news is that we have made unbiased protein biomarker discovery a routine and fast exercise. The downstream implications of the platform are substantial.

Radiation-induced biomarkers for the detection and assessment of absorbed radiation doses

Radiation incident involving living organisms is an uncommon but a very serious situation. The first step in medical management including triage is high-throughput assessment of the radiation dose received. Radiation exposure levels can be assessed from viability of cells, cellular organelles such as chromosome and different intermediate metabolites. Oxidative damages by ionizing radiation result in carcinogenesis, lowering of the immune response and, ultimately, damage to the hematopoietic system, gastrointestinal system and central nervous system. Biodosimetry is based on the measurement of the radiation-induced changes, which can correlate them with the absorbed dose. Radiation biomarkers such as chromosome aberration are most widely used. Serum enzymes such as serum amylase and diamine oxidase are the most promising biodosimeters. The level of gene expression and protein are also good biomarkers of radiation.

Quantitative performance of antibody array technology in a prenatal screening setting

BACKGROUND

Antibody microarrays (Ab-array) represent a new, innovative proteomics platform for high-throughput protein expression profiling in body fluids. Because they allow for multiplexed measurements in small sample volumes, Ab-arrays are an interesting alternative to conventional indirect sandwich immunoassay (ELISA or DELFIA) tests in clinical or population screening if sets of markers are to be analyzed simultaneously. However, to allow implementation of Ab-arrays in clinical or population screening programs, it is of vital importance to establish that this method is both sensitive and quantitative.

METHODS

This study developed and optimized a duplex Ab-array for pregnancy-associated plasma protein A (PAPP-A) and human chorion gonadotropin (fβ-hCG), two serum biomarkers currently analyzed by conventional biochemical techniques in prenatal screening. Serum samples from pregnant women, representing the dynamic range of both markers, were analyzed on Ab-arrays, and validated to the, in prenatal screening routinely applied, AutoDelfia system.

RESULTS

Two different array hybridization conditions were tested, i.e., direct and indirect labeling, of which the indirect method displayed a sensitive and quantitative performance and a low intra- and inter-assay variation.

CONCLUSIONS

Taken together, these findings indicate that Ab-array technology is a promising alternative for ELISA or DELFIA in population screening programs, allowing future quantitative analysis of multiple biomarkers simultaneously in small volumes of serum.

Molecular serum portraits in patients with primary breast cancer predict the development of distant metastases

The risk of distant recurrence in breast cancer patients is difficult to assess with current clinical and histopathological parameters, and no validated serum biomarkers currently exist. Using a recently developed recombinant antibody microarray platform containing 135 antibodies against 65 mainly immunoregulatory proteins, we screened 240 sera from 64 patients with primary breast cancer. This unique longitudinal sample material was collected from each patient between 0 and 36 mo after the primary operation. The velocity for each serum protein was determined by comparing the samples collected at the primary operation and then 3-6 mo later. A 21-protein signature was identified, using leave-one-out cross-validation together with a backward elimination strategy in a training cohort. This signature was tested and evaluated subsequently in an independent test cohort (prevalidation). The risk of developing distant recurrence after primary operation could be assessed for each patient, using her molecular portraits. The results from this prevalidation study showed that patients could be classified into high- versus low-risk groups for developing metastatic breast cancer with a receiver operating characteristic area under the curve of 0.85. This risk assessment was not dependent on the type of adjuvant therapy received by the patients. Even more importantly, we demonstrated that this protein signature provided an added value compared with conventional clinical parameters. Consequently, we present here a candidate serum biomarker signature able to classify patients with primary breast cancer according to their risk of developing distant recurrence, with an accuracy outperforming current procedures.

Proteomic analysis and discovery using affinity proteomics and mass spectrometry

Antibody-based microarrays are a rapidly evolving affinity-proteomic methodology that recently has shown great promise in clinical applications. The resolution of these proteomic analyses is, however, directly related to the number of data-points, i.e. antibodies, included on the array. Currently, this is a key bottleneck because of limited availability of numerous highly characterized antibodies. Here, we present a conceptually new method, denoted global proteome survey, opening up the possibility to probe any proteome in a species-independent manner while still using a limited set of antibodies. We use context-independent-motif-specific antibodies directed against short amino acid motifs, where each motif is present in up to a few hundred different proteins. First, the digested proteome is exposed to these antibodies, whereby motif-containing peptides are enriched, which then are detected and identified by mass spectrometry. In this study, we profiled extracts from human colon tissue, yeast cells lysate, and mouse liver tissue to demonstrate proof-of-concept.

Antibodies on demand: a fast method for the production of human scFvs with minimal amounts of antigen

BACKGROUND

Antibodies constitute a powerful tool to study protein function, protein localization and protein-protein interactions, as well as for diagnostic and therapeutic purposes. High-throughput antibody development requires faster methodologies with lower antigen consumption.

RESULTS

Here, we describe a novel methodology to select human monoclonal recombinant antibodies by combining in vitro protein expression, phage display antibody libraries and antibody microarrays. The application of this combination of methodologies permitted us to generate human single-chain variable fragments (scFvs) against two proteins: green fluorescent protein (GFP) and thioredoxin (Trx) in a short time, using as low as 5 μg of purified protein. These scFvs showed specific reactivity against their respective targets and worked well by ELISA and western blot. The scFvs were able to recognise as low as 31 ng of protein of their respective targets by western blot.

CONCLUSION

This work describes a novel and miniaturized methodology to obtain human monoclonal recombinant antibodies against any target in a shorter time than other methodologies using only 5 μg of protein. The protocol could be easily adapted to a high-throughput procedure for antibody production.

High-content affinity-based proteomics: unlocking protein biomarker discovery

Single protein biomarkers measured with antibody-based affinity assays are the basis of molecular diagnostics in clinical practice today. There is great hope in discovering new protein biomarkers and combinations of protein biomarkers for advancing medicine through monitoring health, diagnosing disease, guiding treatment, and developing new therapeutics. The goal of high-content proteomics is to unlock protein biomarker discovery by measuring many (thousands) or all (∼23,000) proteins in the human proteome in an unbiased, data-driven approach. High-content proteomics has proven technically difficult due to the diversity of proteins, the complexity of relevant biological samples, such as blood and tissue, and large concentration ranges (in the order of 10(12) in blood). Mass spectrometry and affinity methods based on antibodies have dominated approaches to high-content proteomics. For technical reasons, neither has achieved adequate simultaneous performance and high-content. Here we review antibody-based protein measurement, multiplexed antibody-based protein measurement, and limitations of antibodies for high-content proteomics due to their inherent cross-reactivity. Finally, we review a new affinity-based proteomic technology developed from the ground up to solve the problem of high content with high sensitivity and specificity. Based on a new generation of slow off-rate modified aptamers (SOMAmers), this technology is unlocking biomarker discovery.

Proteomic technologies for the identification of disease biomarkers in serum: advances and challenges ahead

Serum is an ideal biological sample that contains an archive of information due to the presence of a variety of proteins released by diseased tissue, and serum proteomics has gained considerable interest for the disease biomarker discovery. Easy accessibility and rapid protein changes in response to disease pathogenesis makes serum an attractive sample for clinical research. Despite these advantages, the analysis of serum proteome is very challenging due to the wide dynamic range of proteins, difficulty in finding low-abundance target analytes due to the presence of high-abundance serum proteins, high levels of salts and other interfering compounds, variations among individuals and paucity of reproducibility. Sample preparation introduces pre-analytical variations and poses major challenges to analyze the serum proteome. The label-free detection techniques such as surface plasmon resonance, microcantilever, few nanotechniques and different resonators are rapidly emerging for the analysis of serum proteome and they have exhibited potential to overcome few limitations of the conventional techniques. In this article, we will discuss the current status of serum proteome analysis for the biomarker discovery and address key technological advancements, with a focus on challenges and amenable solutions.

Serum protein profiling of systemic lupus erythematosus and systemic sclerosis using recombinant antibody microarrays

Systemic lupus erythematosus (SLE) and systemic sclerosis (SSc) are two severe autoimmune connective tissue diseases. The fundamental knowledge about their etiology is limited and the conditions display complex pathogenesis, multifaceted presentations, and unpredictable courses. Despite significant efforts, the lack of fully validated biomarkers enabling diagnosis, classification, and monitoring of disease activity represents significant unmet clinical needs. In this discovery study, we have for the first time used recombinant antibody microarrays for miniaturized, multiplexed serum protein profiling of SLE and SSc, targeting mainly immunoregulatory proteins. The data showed that several candidate SLE-associated multiplexed serum biomarker signatures were delineated, reflecting disease (diagnosis), disease severity (phenotypic subsets), and disease activity. Selected differentially expressed markers were validated using orthogonal assays and a second, independent patient cohort. Further, biomarker signatures differentiating SLE versus SSc were demonstrated, and the observed differences increased with severity of SLE. In contrast, the data showed that the serum profiles of SSc versus healthy controls were more similar. Hence, we have shown that affinity proteomics could be used to de-convolute crude, nonfractionated serum proteomes, extracting molecular portraits of SLE and SSc, further enhancing our fundamental understanding of these complex autoimmune conditions.

Robust protein profiling with complex antibody microarrays in a dual-colour mode

Antibody microarrays are a multiplexing technique for the analyses of hundreds of different analytes in parallel from small sample volumes of few microlitres only. With sensitivities in the picomolar to femtomolar range, they are gaining importance in proteomic analyses. These sensitivities can be obtained for complex protein samples without any pre-fractionation or signal amplification. Also, no expensive or elaborate protein depletion steps are needed. As with custom DNA-microarrays, the implementation of a dual-colour assay adds to assay robustness and reproducibility and was therefore a focus of our technical implementation. In order to perform antibody microarray experiments for large sets of samples and analytes in a robust manner, it was essential to optimise the experimental layout, the protein extraction, labelling and incubation as well as data processing steps. Here, we present our current protocol, which is used for the simultaneous analysis of the abundance of more than 800 proteins in plasma, urine, and tissue samples.

Recombinant antibodies for the generation of antibody arrays

Affinity proteomics, mainly represented by antibody microarrays, has in recent years been established as a powerful tool for high-throughput (disease) proteomics. The technology can be used to generate detailed protein expression profiles, or protein maps, of focused set of proteins in crude proteomes and potentially even high-resolution portraits of entire proteomes. The technology provides unique opportunities, for example biomarker discovery, disease diagnostics, patient stratification and monitoring of disease, and taking the next steps toward personalized medicine. However, the process of designing high-performing, high-density antibody micro- and nanoarrays has proven to be challenging, requiring truly cross-disciplinary efforts to be adopted. In this mini-review, we address one of these key technological issues, namely, the choice of probe format, and focus on the use of recombinant antibodies vs. polyclonal and monoclonal antibodies for the generation of antibody arrays.

Aptamer-based multiplexed proteomic technology for biomarker discovery

BACKGROUND

The interrogation of proteomes ("proteomics") in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine.

METHODOLOGY/PRINCIPAL FINDINGS

We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (~100 fM-1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states.

CONCLUSIONS/SIGNIFICANCE

We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.

Assessment and optimisation of normalisation methods for dual-colour antibody microarrays

Background

Recent advances in antibody microarray technology have made it possible to measure the expression of hundreds of proteins simultaneously in a competitive dual-colour approach similar to dual-colour gene expression microarrays. Thus, the established normalisation methods for gene expression microarrays, e.g. loess regression, can in principle be applied to protein microarrays. However, the typical assumptions of such normalisation methods might be violated due to a bias in the selection of the proteins to be measured. Due to high costs and limited availability of high quality antibodies, the current arrays usually focus on a high proportion of regulated targets. Housekeeping features could be used to circumvent this problem, but they are typically underrepresented on protein arrays. Therefore, it might be beneficial to select invariant features among the features already represented on available arrays for normalisation by a dedicated selection algorithm.

Results

We compare the performance of several normalisation methods that have been established for dual-colour gene expression microarrays. The focus is on an invariant selection algorithm, for which effective improvements are proposed. In a simulation study the performances of the different normalisation methods are compared with respect to their impact on the ability to correctly detect differentially expressed features. Furthermore, we apply the different normalisation methods to a pancreatic cancer data set to assess the impact on the classification power.

Conclusions

The simulation study and the data application demonstrate the superior performance of the improved invariant selection algorithms in comparison to other normalisation methods, especially in situations where the assumptions of the usual global loess normalisation are violated.

NanoProbeArrays for the analysis of ultra-low-volume protein samples using piezoelectric liquid dispensing technology

Antibody microarrays are gaining popularity as a high-throughput technology to investigate the proteome. However, protein extracts from most body fluid or biopsy samples are available in very small volumes and are often unsuitable for large-scale antibody microarray studies. To demonstrate the potential for protein analysis with as little as a few nanoliters of sample, we have developed a new technology called NanoProbeArrays based on piezoelectric liquid dispensing for non-contact printing and probing of antibody arrays. Instead of flooding the protein sample on the antibody microarray surface, as in conventional microarray screening, a piezoelectric inkjet printer is used to dispense nanoliters of fluorescently labeled proteins over the antibody spots on the array. The ability of NanoProbeArrays to precisely identify and reliably distinguish between test proteins from different sources, without any loss of sensitivity and specificity as compared with conventional antibody microarrays, is illustrated here. The utility of NanoProbeArrays for biomarker identification in a complex biological sample was tested by detecting the cytokine interleukin-4 in serum. The significant reduction in volume of sample during NanoProbeArray analysis, as compared with conventional antibody microarrays, offers new opportunities for basic and applied proteomic research.

Proteomics of industrial fungi: trends and insights for biotechnology

Filamentous fungi are widely known for their industrial applications, namely, the production of food-processing enzymes and metabolites such as antibiotics and organic acids. In the past decade, the full genome sequencing of filamentous fungi increased the potential to predict encoded proteins enormously, namely, hydrolytic enzymes or proteins involved in the biosynthesis of metabolites of interest. The integration of genome sequence information with possible phenotypes requires, however, the knowledge of all the proteins in the cell in a system-wise manner, given by proteomics. This review summarises the progress of proteomics and its importance for the study of biotechnological processes in filamentous fungi. A major step forward in proteomics was to couple protein separation with high-resolution mass spectrometry, allowing accurate protein quantification. Despite the fact that most fungal proteomic studies have been focused on proteins from mycelial extracts, many proteins are related to processes which are compartmentalised in the fungal cell, e.g. β-lactam antibiotic production in the microbody. For the study of such processes, a targeted approach is required, e.g. by organelle proteomics. Typical workflows for sample preparation in fungal organelle proteomics are discussed, including homogenisation and sub-cellular fractionation. Finally, examples are presented of fungal organelle proteomic studies, which have enlarged the knowledge on areas of interest to biotechnology, such as protein secretion, energy production or antibiotic biosynthesis.