Antibody-based proteomics and biomarker research - current status and limitations.

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DOI 10.1002/pmic.201300334

Proteomics 2014, 14, 774–783

REVIEW

Antibody-based proteomics and biomarker research—Current status and limitations Corinne Solier and Hanno Langen Translational Technologies and Bioinformatics, Pharma Research and Early Development, F. Hoffmann-La Roche AG, Basel, Switzerland

Antibody-based proteomics play a very important role in biomarker discovery and validation, facilitating the high-throughput evaluation of candidate markers. Most proteomics-driven discovery is nowadays based on the use of MS. MS has many advantages, including its suitability for hypothesis-free biomarker discovery, since information on protein content of a sample is not required prior to analysis. However, MS presents one main caveat which is the limited sensitivity in complex samples, especially for body fluids, where protein expression covers a huge dynamic range. Antibody-based technologies remain the main solution to address this challenge since they reach higher sensitivity. In this article, we review the benefits and limitations of antibody-based proteomics in preclinical and clinical biomarker research for discovery and validation in body fluids and tissue. The combination of antibodies and MS, utilizing the best of both worlds, opens new avenues in biomarker research.

Received: August 1, 2013 Revised: November 8, 2013 Accepted: December 16, 2013

Keywords: Antibodies / Biomedicine / Mass spectrometry / Protein arrays / SRM

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Introduction

Protein biomarkers can inform on biological processes and have therefore been a focus of interest in research in the pharmaceutical industry. They can provide key insights into the mechanisms of drugs, how they act on their targets, and what are their downstream effects. Protein biomarkers are used to identify drug toxicity in early development or to support dose range finding. According to the National Institute of Health, a biomarker is defined as “a characteristic used to measure and evaluate objectively normal biological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention” [1]. Therefore, biomarkers provide a tremendous opportunity to personalize medicine. Biomarkers can be used for early detection of disease, for example, cancer, and provide diagnostic, prognostic, and predictive information. They also

Correspondence: Dr. Hanno Langen, Translational Technologies and Bioinformatics, Pharma Research and Early Development, F. Hoffmann-La Roche Ltd., CH-4070 Basel, Switzerland E-mail: [email protected] Abbreviations: FDA, Federal Drug Administration; FFPE, formalin-fixed, paraffin embedded; IHC, immunohistochemistry; PEA, proximity extension assay; PR, progesterone receptor; RPPA, reverse-phase protein array

support assessment of risk and disease monitoring in highrisk populations. In addition, biomarkers can be applied to guide targeted therapy and be used in differential diagnosis. Finally, they can be used to monitor response to therapy. Proteins are studied in experiments that range from discovery proteomics to panels of preselected assays to verify proteomics discovery results. They can also be used to take forward hypotheses generated by a variety of—omics technologies, such as transcript profiling or next generation sequencing.

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General considerations and challenges

Biomarker research has raised interest due to the numerous publications identifying putative new plasma or serum protein markers for cancer and other diseases. In the last years, many studies on protein markers were published using sophisticated—omics approaches, but very little progress was made to translate these early discoveries into clinically useful applications improving diagnosis, therapeutic choices, and monitoring [2–11]. In fact, the overall rate of introduction of new protein biomarkers into clinical use has been static at approximately one to two per year for the past 15 years [12, 13]. Furthermore, despite significant technological developments, unbiased Proteomics have failed to translate

C 2014 The Authors. Proteomics published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Figure 1. Antibody-based technology landscape for biofluid biomarker research and respective platform functional sensitivities. Untargeted MS approaches have shown to achieve sensitivities in the range of microgram per milliliter to milligram per milliliter. SRM has improved sensitivity by two to three orders of magnitude, reaching sensitivities within the mid-nanogram per milliliter range in plasma. RPPAs display similar sensitivity, albeit with the drawback of lower specificity and multiplexing power. The use of antibodies for protein immunocapture prior to SRM analysis (e.g., stable isotope standard capture with antipeptide antibodies, MS immune assay) have pushed sensitivity down to the high picogram per milliliter range. Immunoassay platforms remain more sensitive, enabling detection of proteins in the picogram per milliliter range. Further technology developments are warranted to achieve sufficient sensitivity to measure low-abundant proteins, such as cytokines, present in the low and subpicogram per milliliter range in limited sample volumes, since the Singulex platform performs well in relatively high volumes of fluid (ca. 100 ␮L).

protein biomarkers into clinical use [14]. What are the challenges hampering protein biomarker research and how can we overcome them? (i) A robust technology for clinical samples testing must be available. Or it must be technically and economically feasible to develop an analytically reliable testing system [15] under a timeline consistent with a reasonable development effort, since many markers will fail during the process of demonstrating clinical utility. (ii) Measuring biomarker performance in generic terms, however, is not sufficient for demonstrating clinical utility [16]. The decision to use a biomarker in clinical practice should be based on supporting data, suggesting that it will bring value in clinical practice. Technological limitations [14] are mainly related to sensitivity, accuracy, and reproducibility. Also, limiting progress of biomarker research is the lack of well-established methods for validation of candidate biomarkers in large clinical sample sets [14]. The lack of a well-defined cohort of controls together with the huge biological variability among patients and preanalytical sample variability, as well as the broad dynamic range of proteins in the samples, makes it extremely difficult to derive clinically relevant data for prognosis, diagnosis, and response to therapy or toxicity [17].

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Dynamic range

One of the major technology challenges for protein biomarker discovery in plasma or serum is the extremely broad dynamic

range of protein expression that spans over ten orders of magnitude [18] (albumin is present at about 34–54 mg/mL, cytokines are typically present at the picogram per milliliter level). Putative new disease protein biomarkers, including peptides, produced by disease-targeted organs or tumors are likely to be present in biological fluids at extremely low concentrations. We therefore need to have access to technologies that are quantitative, highly sensitive, and reproducible as well as able to span the whole expression range in plasma or serum. However, convincing data for de novo discovery of low abundance, tumor-derived peptides, and proteins for diagnostic purposes using MS are currently lacking [19–21]. In Fig. 1, an estimate of the sensitivities of the different technologies used in protein biomarker discovery in plasma is given.

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From discovery to validation technologies

Once a specific question has been identified, it is important to develop a scientific and technical approach to find biomarkers that addresses that question, for example, prognosis, pharmacodynamics, drug efficacy. This includes the consideration or assessment of already available sources of candidate biomarkers in the literature and pathway analysis as well as candidates identified via RNA profiling studies. In addition to public domain knowledge, experimental discovery studies can be designed to enrich the biomarker candidate list. The new technologies being used in research such as MS allow for the simultaneous thorough assessment of thousands of proteins and peptides without prior knowledge about their biological relevance in disease or drug mechanism.


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Beyond the protein coverage of technologies used for biomarker research, it is critical that the discovery platform is adequately validated, with measures in place to minimize the effects of artifacts and false discovery rates, in order to ensure adequate robustness and yield sufficiently promising candidates for the qualification (validation) step. Due to easy access to patient blood, protein biomarkers would ideally be discovered in plasma or serum. However, due to the high dilution of protein biomarkers released into the circulation from disease-targeted organs or tumors, the sensitivity required for the measurement of many relevant protein biomarkers in blood (serum or plasma) is extremely high. This constraint has hampered protein biomarker discovery in serum or plasma. Alternatively, biomarker discovery should be directly performed in tissue biopsies, where expression levels are highest and biomarkers should later be translated with higher sensitivity technologies in plasma as described in the following section. Several antibody-based technologies can be used for biomarker discovery and validation: one option is based on highly multiplexed protein immunoassays; another option on multiplexed SRM, an MS technology.

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Tissue versus biofluid biomarker discovery: Different needs, different technologies

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example, a discrepancy between the FDA and American Society of Clinical Oncology and College of American Pathologists guidelines for the immunohistochemical testing of HER2 leading to different false-negative rates has recently been debated [22], while several recent publications emphasized the importance of antibody screening, of the introduction of positive and negative cell-control reference material, of optimization and standardization of protocols, notably in the field of oncology [23,24]. Although IHC is well established for clinical diagnostics, efforts have focused on developing more sensitive methods allowing for tissue protein and pathway profiling that could open new avenues toward tissue biomarker discovery.

5.2 Needs for tissue biomarker research The main needs for tissue biomarker research are adequate sensitivity to detect low-abundant proteins, a good dynamic range, and proper spatial resolution to get information about expression in specific cell types or organelles. Ideally, options to multiplex ten to hundreds of different proteins are attractive, especially when exploring candidate biomarkers in the discovery phase. For discovery purposes, the development of biomarker assays should be cost-effective and fast.

5.3 What are the advantages of antibody-based technologies for tissue biomarker research?

5.1 Tissue biomarker discovery and validation Tissue biomarkers have been investigated to identify pathological cellular pathways, in particular in oncology. A classical method to discover tissue biomarkers and translate them into routine clinical practice is immunohistochemistry (IHC). This technique uses antibodies to measure levels of intracellular or membrane proteins from formalin-fixed, paraffin embedded (FFPE) tissue slices. Most commonly, IHC uses an enzyme-linked chromogenic substrate for detection and requires microscopic examination by trained professionals, which remains a time-consuming and subjective process producing a semiquantitative assessment. Standardization and automation of immunohistochemical data acquisition and analysis has therefore been a cornerstone for technological improvements in the last years. For example, Ventana received in 2011 Federal Drug Administration (FDA) clearance for its tyrosine kinase type cell surface receptor HER2 (4B5) image analysis and digital read applications that help ensure consistency and objectivity in HER2 data analysis. In addition, the FDA and American Society of Clinical Oncology and College of American Pathologists have issued guidelines to improve the accuracy of the testing of some diagnostic marker, including HER2, estrogen receptor, and progesterone receptor (PR). However, issues related to accuracy and comparability of results across different laboratories persist, leading to variable false-positive and false-negative rates. For

Reverse-phase protein arrays (RPPAs) have proven useful for efficient tissue protein quantification and characterization of distinct pathological signaling pathways [25–27]. This technique uses discrete amounts of whole protein lysates from a multitude of samples spotted onto slides. Protein quantitation is accomplished using protein-specific antibodies. This methodology has been shown to produce high-throughput protein profiles in a robust quantitative manner, providing an advantage over traditional methods, such as IHC [28, 29]. Since FFPE is the standard and most commonly adopted tissue fixation and storage method, several studies have aimed at demonstrating the performance of RPPA in FFPE tissues. We have shown that RPPA can successfully be applied to profile proteins extracted from FFPE tumors, by showing good concordance between the HER2 score obtained from IHC and RPPA in breast cancer samples and by identifying candidate markers of differentiation of adenocarcinoma and squamous cell carcinoma [30]. The applicability of RPPA to high-throughput FFPE tissue protein profiling was further demonstrated via a systematic comparison of RPPA data obtained from fresh frozen and FFPE preparations from diverse cell lines, xenografts, and breast cancer and renal tissues [31]. In addition, the investigators showed that RPPA-based measurements of PR in human breast tumors correlated significantly with the IHC-based clinical status (PR-positive or PR-negative), which together with Assadi



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Proteomics 2014, 14, 774–783 Table 1. The advantages and challenges of antibody-based technologies for tissue biomarker discovery

Advantages IHC

Sensitivity Spatial resolution at cellular level Established in clinical practice Works with FFPE tissue Automated systems Antibody- Multiplexing enriched Fast development time SRM Moderate development costs High specificity Isoforms can be distinguished Quantitative RPPA Works with FFPE tissue High multiplexing option Low sample consumption Semi-quantitative

Challenges Multiplexing Absolute quantification (qualitative) Specificity

Sensitivity Relatively low throughput Complex sample preparation Peptidic specificity Spatial resolution High instrument costs Specificity Sensitivity Spatial resolution Tissue sample preparation

et al. [30] opens novel perspectives in the use of RPPA in clinical routine practice as a complementary approach to the well-established IHC methodology. SRM is a quantitative MS technology, measuring preselected peptide ions based on two mass parameters (parent peptide and a specific sequence fragment), providing a capability to accurately (CV 10%) quantify peptides [32, 33]. The main challenge is that, without further fractionation, for example, albumin depletion, this technology can only reach high nanogram per milliliter sensitivity level. Since the isotope standard is only added after the fractionation, the reproducibility is highly dependent on the good performance of the fractionation steps. SRM has been applied to the precise detection of cancer biomarkers (including HER2) in FFPE breast cancer tissues and renal cell carcinoma and results were compared to those obtained in frozen tissues [34]. Good reproducibility was shown in FFPE as compared to fresh frozen tissue, the data demonstrating that SRM analyses of HER2 are concordant with HER2 status as measured by IHC, but lower sensitivity of SRM detection was observed in FFPE tissues than in fresh frozen tissue. Recent advances in the SRM technology suggest that a combination of antibody capture with MS could potentially overcome performance limitation of MS alone. Data suggest that sensitivity combining peptide immunoaffinity enrichment with quantitative MS [35] achieves nanogram milliliter sensitivity limits from 10 ␮L of sample and picogram milliliter sensitivity limits from 1 mL of sample with good precision. In Table 1, we show the strengths and weaknesses of antibody-enriched SRM methods for tissue biomarker research.

5.4 Biofluid biomarker discovery and validation Blood-based biomarkers have attracted attention in light of the inaccessibility of disease-targeted organs for repeated tissue sampling. Accurate, sensitive, and reproducible methods may help identify diagnostic markers, markers predictive of disease progression, as well as markers predictive of response to therapy. Circulating biomarkers can be measured by a variety of assay formats. We review here some of the most popular platforms, highlighting their respective strengths and limitations. ELISAs are the gold standards in the clinical setting for the measurement of proteins. Many of the strategies to set up immunological prototype assays are explained elsewhere [36]. Polyclonal, affinity-absorbed polyclonal, or monoclonal antibodies can be applied. It is useful to characterize antibodies before setting up prototype assay formats. For instance, the specificity of antibodies can be characterized in Western blots utilizing lysates of different tissues. Furthermore, antibody binding constants can be characterized in reasonable binding kinetics experiments. In any case, the technical qualification of assays for the characterization of a biomarker or a combination of biomarkers in clinical validation experiments needs to be established. Typical immunoassay formats achieve sensitivity down to 10 fM.

5.5 Needs for biofluid biomarker research The main needs for fluid biomarker research are adequate sensitivity to detect low-abundant proteins and an excellent dynamic range. Ideally, options to multiplex ten to hundreds of different proteins are attractive, especially when exploring candidate biomarkers in the discovery phase. For discovery purposes, the development of biomarker assays should be cost-effective and fast.

5.6 What are the advantages of antibody-based technologies for biofluid biomarker research? The application of multiparametric immunoassay technology brings several advantages to the experimental setup, including the possibility to simultaneously detect multiple biomarkers in miniaturized assay procedures. This leads to a dramatic reduction of precious sample and reagent consumption. The utility, reliability, and reproducibility of common immunoassay multiplex kits have recently been reviewed [37]. Multiplex immunoassay formats include planar arrays, on which analyte-specific capture antibodies are immobilized at discreet locations of a solid-phase surface, and bead-based assays utilizing size and color-coded beads on which analytespecific capture antibodies are immobilized. In both formats, specific detection of the markers of interest is ensured by labeled detection antibodies. The dimensional constraints of



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Table 2. The advantages and challenges of antibody-based technologies for biofluid biomarker discovery

Advantages

Challenges

ELISA

Sensitivity Established in the clinic

Multiplex immunoassays

Low sample volume consumption Multiplexing

Antibody-enriched SRM

Multiplexing Fast development time Moderate development costs High specificity Isoforms can be distinguished Quantitative Lower cost for large-scale studies High multiplexing option Low sample consumption Works in all biofluids Ultra high sensitivity Established in the clinic Multiplexing Specificity

Multiplexing High development costs High sample volume consumption Sensitivity Specificity Robustness Complex assay validation Sensitivity Relatively low throughput Complex sample preparation Peptidic specificity High instrument costs

RPPA

ErennaTM (Singulex) PEA (Olink Bioscience)

a single well and the need for robotic tip clearance mean that multiplex immunoassays in planar format may be limited to less than 20 specific proteins [38], therefore, limiting the potential application of these planar formats to broad biomarker discovery campaigns. In contrast, multiplex bead-based immunoassays have been used successfully for biomarker discovery in a variety of matrices and diseases, including ovarian cancer, coronary artery disease, schizophrenia, diabetic macular edema [39–42]. However, despite demonstrated potential in biomarker research, evidence of the utility of multiplex platforms in clinical practice remains limited because of technical and developmental challenges. Because of the complexity of these assays, extensive validation is required for the multiplex protein test panels intended for use in clinical trials or for diagnostic applications. Technical and operational challenges of antibody-based multiplex platforms have been reviewed in detail elsewhere [43]. These include variable reproducibility when using bead-based formats due to insufficiently robust bead manufacturing, compromised functional assay sensitivity due to the constrained common assay protocol applied to all assays from a panel and specificity issues caused by cross-reactivities between detection antibodies and immobilized capture antibodies. The authors emphasize the need for the establishment of a globally accepted guidance defining technical performance validation criteria for multiplex assays to aid in the complex analytical validation of these types of assays. RPPAs enable large-scale sample screening for virtually all biological fluids (serum, urine, cerebrospinal fluid, or saliva). As reviewed in [37], there are many advantages of RPPA for high-throughput analysis: it is potentially much cheaper for large sample numbers than other immunoassay techniques and requires less sample and fewer reagents.

Specificity Sensitivity Semiquantitative High sample volume consumption Multiplexing Not established in the clinic

Nevertheless, the authors emphasize that the complexity of the immobilized sample is associated with absolute requirements for high specificity, validated antibodies, to avoid false-positive readouts. The limited availability of such specific antibodies is a clear drawback of the RPPA approach. Furthermore, the detection sensitivity for low-abundant proteins is limited by the complexity of the biological mixture.

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Recent highlights

6.1 Novel technological development to increase specificity and sensitivity of antibody-based proteomics Interrogating the plasma/serum proteome is one of the main targets for proteomics because of the accessibility of this fluid and because pathological proteins locally secreted by diseasetargeted organs are presumably present in blood circulation. However, many proteins that would be early markers of disease onset or predictive markers of disease resolution are likely to be present at low picogram per milliliter or even subpicogicogram per milliliter levels, which exceed the sensitivity capabilities of the common antibody-based proteomics technologies described above. Interestingly, baseline concentrations from plasma of normal human subjects for many cytokines have yet to be defined by current assay technologies. In addition, most proteins function with other molecular partners to regulate networks of pathophysiological signaling pathways in a concerted way. Therefore, proteomics technologies able to quantify multiple low-abundant proteins, without interference from other proteins that may be several orders of magnitude more abundant, are needed. This is particularly



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important for the assessment of low-abundant proteins as potential therapeutic targets in order to investigate target engagement and pharmacodynamics. A novel immunoassay technology supported by the ErennaTM Immunoassay System (Singulex, Alameda, CA, USA) utilizing single-photon fluorescence detection and paramagnetic microparticles has been shown to increase precision and sensitivity of immunoassays by up to three orders of magnitude [44]. This platform has been used for quantifying baseline concentration of cytokines in serum from healthy individuals with unprecedented functional sensitivities below 1 pg/ml (http://www.singulex.com/ documents/AACC2008Lu(final).pdf) [45]. We have investigated the performance of this platform for the measurement of serum and plasma IL-17A (data not shown), for which concentrations have previously been reported to be variable in healthy and rheumatoid arthritis patients [46]. We have confirmed the high sensitivity of this platform as we determined the lower limit of quantification to be 0.07 pg/ml in serum and plasma spiked with various concentrations of recombinant IL-17A protein. In addition, we measured IL-17A concentrations in a panel of 20 healthy and ten rheumatoid arthritis subjects and found that IL-17A concentrations were below 1 pg/ml, therefore below the lowest calibrator standard values of popular monoplex commercial ELISA kits. Furthermore, the performance of the IL-17A assay remained unaffected by high rheumatoid factor titers present in serum and plasma of rheumatoid patients, which can notoriously cause false positive results in immunoassays. The Singulex high-sensitivity cardiac troponin I assay has enabled important biomarker development in the cardiovascular arena as this assay detects troponin levels up to an order of magnitude lower that those detected by other “high sensitive” assays [47]. Several studies established the prognostic value of troponin I measured using the Singulex assay and revealed that this marker is associated with increased cardiovascular death in two independent studies when evaluated in a multiple biomarker analysis [48, 49]. Altogether, these results indicate that the Singulex platform achieves the performance standards required for the discovery of low-abundant biomarkers of clinical value, for accurate target characterization in human blood, and for clinical biomarker validation. Alternatively, this platform may be used to minimize sample consumption when measuring more abundant proteins, for example, in rodent samples, or when aiming at measuring several proteins in parallel monoplex assays. However, technical constraints inherent to the high sample volumes requirements, up to 100 ␮L of undiluted fluid, and the monoplex nature of the assays, can be prohibitive in early discovery projects requiring broad biomarker screening from limited sample volumes, or in preclinical animal studies, for example, in rodents. A highly sensitive detection immunoassay called digital ELISA (Quanterix Corporation, Cambridge, MA, USA) has recently been described [50–52]. This new technology is based on the detection of single enzyme-linked immunocomplexes

on beads that are sealed in arrays of femtoliter wells and has been shown to achieve subfemtomolar protein detection. This digital ELISA was shown to be typically 1000-fold more sensitive than conventional ELISA approaches [51, 52]. This method has been used to detect prostate-specific antigen with a robust limit of quantification 2 logs lower than current ultrasensitive third-generation prostate-specific antigen assays, translating into a functional sensitivity limit < 0.05 pg/ml [53]. Similarly, digital ELISA allowed quantitative measurements and monitoring of IL-6 and TNF-␣ cytokine concentrations in plasma of patients with Crohn’s disease under therapy [54]. In addition, it proved effective in the highly sensitive (limit of quantification 0.032 pg/ml) and precise quantification of amyloid ␤ 42 in serum from patients following cardiac arrest and resuscitation [55], and in highly sensitive detection of tau in plasma from Alzheimer’s disease patients [56]. Theoretical aspects explaining the femtogram per milliliter sensitivity of digital ELISA have been detailed in [50], highlighting the technical rationale for reduced background detection, improved specificity, and sensitivity. Interestingly, digital ELISA has recently been successfully used to simultaneously measure TNF-␣, IL-6, IL-1␣, and IL-1␤ in human plasma, reaching 200- to 1000-fold better sensitivity than current multiplexed immunoassays [57]. This publication shows the potential of this platform for the accurate, multiplexed measurement of subpicogram per milliliter markers in body fluids. In order to circumvent the lack of availability of high specificity antibodies covering the proteome and develop a wider range of high sensitivity multiplex immunoassays, Olink Bioscience (Uppsala, Sweden) have developed a nucleic acid proximity-based assay using antibodies, called proximity extension assay (PEA) [58]. Target-specific antibody pairs are linked to DNA strands that, upon simultaneous binding to the target analyte, create a real-time PCR amplicon in a proximity-dependent manner enabled by the action of a DNA polymerase. A PEA was set up for IL-8 and GDNF in a userfriendly, homogenous assay displaying femtomolar detection sensitivity, good recovery in human plasma, high specificity, and up to 5-log dynamic range in as little as 1 ␮L samples. The current assay menu offered by Olink Bioscience comprises a panel of 92 proteins that can all be measured from 1 ␮L of sample. This technology therefore offers several significant potential advantages addressing the main shortcomings of multiplex immunoassay platforms, including the very low sample consumption, high sensitivity, and specificity detection in a homogeneous reaction, which we believe warrant further attention and investigation. One of the future directions of SRM could be the combination of antibodies directed against PTMs and MS. Carr reports [59] an MS-based method for the integrated analysis of protein expression, phosphorylation, ubiquitination, and acetylation by serial enrichments of different PTMs with a set of different antibodies directed against phosphotyrosine sites, ubiquitination sites, or acetylation sites. This technology enabled Carr to perform quantitative analysis of nearly 8000 proteins



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and more than 20 000 phosphorylation, 15 000 ubiquitination, and 3000 acetylation sites per experiment. This strategy could be nicely combined with a multiplexed SRM strategy. Another area where the combination of MS with antibodies holds a big promise is single cell analysis using flow cytometry. Flow cytometry is commonly limited to the measurement of six to ten simultaneous parameters. In mass cytometry, transition element isotopes are used instead of fluorescence readout. These element isotopes are normally not found in biological systems and are used as chelated antibody tags in atomic mass spectrometric analysis. Recently Nolan [60] has published a research article where he simultaneously measured 34 cellular parameters on single cells to examine healthy human bone marrow. Single-cell unsupervised analysis was applied to create system-wide views of immune signaling in human hematopoiesis to enable mechanistic studies under various biological and chemical stimuli. The ability of this revolutionary technology to quantify 40 to 100 parameters simultaneously at the single-cell level makes it ideally suited for biomarker discovery, mode of action understanding, signaling pathway analysis, and compound differentiation. This becomes highly relevant in complex tissue samples composed of diverse cell types, such as solid tumors. With its superior multiplexing capabilities, mass cytometry is a promising technical platform to find and validate novel biomarker signatures at the single cell level.

6.2 Novel binding reagents: An alternative to antibodies in proteomics-based biomarker discovery? Strategies to overcome limitations of antibodies via the design of alternative binding proteins based on a variety of protein topologies have been reviewed elsewhere [61–64]. Besides engineered antibody fragments relying on conventional antibody binding structural properties (single-chain variable fragment, fragment antigen-binding fragment), affibodies have been described to be small engineered affinity proteins with proven potential for diagnostic and biotechnological applications [64]. Repeat proteins that contain consecutive copies of small (about 20–40 amino acid residues) structural units (repeats) forming a contiguous domain have also been developed as protein-binding alternatives to antibodies. For instance, designed ankyrin repeat proteins (DARPins) have been used to target a wide range of proteins with high picomolar affinity [61, 62]. Recently, a new attractive concept in protein recognition based on the conjugation of small organic molecules or short peptides to polypeptides was applied to design novel binders for several proteins [63]. These binders were subsequently used in pull down and ELISA-based tests in human serum, showing comparable selectivities to those of antibodies. Aptamers are single-stranded oligonucleotides that bind their target molecules with high affinity and specificity. Sometimes referred to as “chemical antibodies,” aptamers exhibit

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several significant advantages over antibodies for engineering and medical applications as reviewed in [65]. Significant advantages for diagnostic applications described in this publication include simple and cost-effective synthesis of aptamers, their high specificity that can be adjusted via sequence modifications, and their stability. Aptamers have therefore attracted significant interest for their use in protein detection assays as potential replacements of antibodies. For instance, aptamers have been described to successfully replace antibodies in Western blot [66,67], in dot blot [68], and flow cytometry applications (reviewed in [69]). Recently, several group groups have reported aptamer-based platforms with multiplexing capabilities [70–73]. SomaLogic, Inc., commercializes one of those aptamer microarrays based on proprietary SOMAmers (slow off-rate modified aptamers). SOMAmers are a new class of protein binding aptamers containing chemically modified nucleotides resulting in improved binding properties, optimized selection of SOMAmers with slow dissociation rates limiting nonspecific binding, an expanded range of possible targets for SELEX (systematic evolution of ligands by exponential enrichment) [72]. This microarray platform currently offers a menu of 1030 proteins, extending to subpicomolar detection limits and spans an average dynamic range of each analyte in the assay of >3 logs and an overall dynamic range of at least 7 logs [72]. This platform has been used in biomarker discovery campaigns across a variety of disease areas, including exploratory cardiovascular research [74], nonsmall-cell lung cancer [75], chronic kidney disease [76], and showed promise in cerebrospinal fluid proteomics [77]. These reports highlight the high potential of aptamers in proteomics applications for biomarker discovery.

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Concluding remarks and future trends

Technologies combining multiplexing, sensitivity, and specificity have represented the Holy Grail of biomarker research. Despite efforts to optimize specificity and sensitivity and enhance multiplexing power of antibody-based technologies in the recent years, the successful application of these technologies to biomarker discovery has remained limited by the lack of specificity of many antibodies which has resulted in unacceptable high rates of cross-reactivities and false discovery rates, as reviewed in [78]. Novel method developments relying on novel concepts on antibody functions have nevertheless led to significant improvement of the specificity and sensitivity, as illustrated by the antibody-enrichment SRM and PEA methods. In these techniques, antibodies are not utilized as the sole drivers of assay specificity, but as an additional proofreading step improving assay specificity [78]. Interestingly, the key technical component driving assay specificity in these two cases is the functional detection system, that is, the SRM analysis ensures specific detection of protein, whereas the PCR amplification of target-specific antibody pairs provides specific and sensitive target detection in the PEA method. Such novel concepts are



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attractive as the availability and development of specific antibodies for candidate biomarkers represent a hurdle impairing the development of assays covering the proteome. Significant progress has been made in the development of robust technologies to design novel protein-binding reagents and in their applications to proteomics. However, further developments are warranted to fulfill the needs for broad-scale proteome coverage complementing existing antibody resources, such as the Human Protein Atlas (http://www.proteinatlas.org/), currently covering over 15 000 protein coding genes. Another way to strengthen the degree of confidence in candidate biomarkers discovered using classic multiplex antibody-based immunoassay platforms is to integrate them into a system-wide approach, exploring signaling pathways using multiple technologies. For instance, less sensitive antibody-based methods, such as RPPA, that offer greater throughput and multiplexing power may be used for “-omic” integrated data analysis of large tissue or cell libraries in a system-based, pathway-oriented manner in order to unravel new biochemical linkages between RNA, DNA, protein expression, and PTMs under various stressors, for example, drug treatments. This concept was recently applied to the measurement of the phosphorylation state of 135 proteins in the National Cancer Institute’s NCI-60 cell line set using RPPA, the most molecularly profiled set of tumor cell lines in the world [79]. The signaling data were aggregated into biochemical modules of interconnected kinase substrates for key cancer signaling pathways, for example, serine/threonine kinase AKT, mammalian target of rapamycin, epidermal growth factor receptor (EGFR) for further correlation analysis with individual protein and phosphoprotein expression profiles, DNA mutations, transcriptional expression, microRNA, metabolomics, and drug sensitivities. These analyses generated reproducible pathway activation mappings. We believe that this approach systematically overlaying, integrating, and structuring functional pathway information gathered from multiple technologies, including proteomics, represents a powerful innovative platform for pathway analysis, biomarker discovery, and target identification. Specificity is not only a technological challenge but also a conceptual issue in biomarker research. An important aspect in the validation of biomarkers or targets discovered in such a heterogeneous source of proteins as blood is their adequate biological validation through the understanding of their exact role in relevant pathophysiological processes. In this respect, proteomics technologies enabling pathway analysis at a single-cell level, such as mass cytometry, bring great hope for future clinical applications. The authors have declared no conflict of interest.

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References

[1] Atkinson, A. J., Colburn, W. A., DeGruttola, V. G., DeMets, D. L. et al., Biomarkers and surrogate endpoints: preferred def-

initions and conceptual framework. Clin. Pharmacol. Ther. 2001, 69, 89–95. [2] Au, J. S. K., Cho, W. C. S., Yip, T. T., Yip, C. et al., Deep proteome profiling of sera from never-smoked lung cancer patients. Biomed. Pharmacother. 2007, 61, 570–577. [3] Conrads, T. P., Hood, B. L., Petricoin, E. F., Liotto, L. A., Veenstra, T. D., Cancer proteomics: many technologies, one goal. Expert Rev. Proteomics 2005, 2, 693–703. [4] Dai, Y., Zhang, Y., Qiu, F., Li, Y. Y., Qiu, Z. Y., Analysis of differentially expressed proteome in urinary exosome from non-small cell lung cancer patients. Chinese J. Anal. Chem. 2010, 38, 325–331. [5] Ebert, M. P. A., Yu, J., Lordick, F., Rocken, C., Proteomics in gastrointestinal cancer. Ann. Oncol. 2006, 17, X253–X258. [6] Ikonomou, G., Samiotaki, M., Panayotou, G., Proteomic methodologies and their application in colorectal cancer research. Crit. Rev. Clin. Lab. Sci. 2009, 46, 319–342. [7] Li, H. Y., DeSouza, L. V., Ghanny, S., Li, W. et al., Identification of candidate biomarker proteins released by human endometrial and cervical cancer cells using two-dimensional liquid chromatography/tandem mass spectrometry. J. Proteome Res. 2007, 6, 2615–2622. [8] Lin, B. Y., White, J. T., Wu, J., Lele, S. et al., Deep depletion of abundant serum proteins reveals low-abundant proteins as potential biomarkers for human ovarian cancer. Proteome Clin. Appl. 2009, 3, 853–861. [9] Rangiah, K., Tippornwong, M., Sangar, V., Austin, D. et al., Differential secreted proteome approach in murine model for candidate biomarker discovery in colon cancer. J. Proteome Res. 2009, 8, 5153–5164. [10] Silberring, J., Ciborowski, P., Biomarker discovery and clinical proteomics. Trends Analyt. Chem. 2010, 29, 128–140. [11] van der Merwe, D. E., Oikonomopoulou, K., Marshall, J., Diamandis, E. P., Mass spectrometry: uncovering the cancer proteome for diagnostics. Adv. Cancer Res. 2007, 96, 23–50. [12] Anderson, N. L., The clinical plasma proteome: a survey of clinical assays for proteins in plasma and serum. Clin. Chem. 2010, 56, 177–185. [13] Hortin, G. L., Carr, S. A., Anderson, N. L., Introduction: advances in protein analysis for the clinical laboratory. Clin. Chem. 2010, 56, 149–151. [14] Kim, J. W., You, J., Protein target quantification decision tree. Int. J. Proteomics 2013, 2013, 701247. [15] Taube, S. E., Clark, G. M., Dancey, J. E., McShane, L. M. et al., A perspective on challenges and issues in biomarker development and drug and biomarker codevelopment. J. Natl. Cancer Inst. 2009, 101, 1453–1463. [16] Pletcher, M. J., Pignone, M., Evaluating the clinical utility of a biomarker: a review of methods for estimating health impact. Circulation 2011, 123, 1116–1124. [17] Rodriguez-Suarez, E., Whetton, A. D., The application of quantification techniques in proteomics for biomedical research. Mass Spectrom. Rev. 2013, 32, 1–26. [18] Anderson, N. L., Anderson, N. G., The human plasma proteome—history, character, and diagnostic prospects. Mol. Cell. Proteomics 2002, 1, 845–867.



782


[19] Diamandis, E. P., Peptidomics for cancer diagnosis: present and future. J. Proteome Res. 2006, 5, 2079–2082. [20] Diamandis, E. P., Point—proteomic patterns in biological fluids: do they represent the future of cancer diagnostics? Clin. Chem. 2003, 49, 1272–1275. [21] Rose, K., Bougueleret, L., Baussant, T., Bohm, G. et al., Industrial-scale proteomics: from liters of plasma to chemically synthesized proteins. Proteomics 2004, 4, 2125–2150. [22] Perez, E. A., Dueck, A. C., McCullough, A. E., Reinholz, M. M. et al., Predictability of adjuvant trastuzumab benefit in N9831 patients using the ASCO/CAP HER2-positivity criteria. J. Natl. Cancer Inst. 2012, 104, 159–162. [23] Roge, R., Nielsen, S., Vyberg, M., Carb-3 is the superior anti-CD15 monoclonal antibody for immunohistochemistry. Appl. Immunohistochem. Mol. Morphol. 2013. [24] Cole, K. D., He, H. J., Wang, L., Breast cancer biomarker measurements and standards. Proteomics Clin. Appl. 2013, 7, 17–29. [25] Malinowsky, K., Wolff, C., Ergin, B., Berg, D., Becker, K. F., Deciphering signaling pathways in clinical tissues for personalized medicine using protein microarrays. J. Cell. Physiol. 2010, 225, 364–370. [26] Wilson, B., Liotta, L. A., Petricoin, E., 3rd, Monitoring proteins and protein networks using reverse phase protein arrays. Dis. Markers 2010, 28, 225–232. [27] Voshol, H., Ehrat, M., Traenkle, J., Bertrand, E., van Oostrum, J., Antibody-based proteomics: analysis of signaling networks using reverse protein arrays. FEBS. J. 2009, 276, 6871–6879. [28] Spurrier, B., Honkanen, P., Holway, A., Kumamoto, K. et al., Protein and lysate array technologies in cancer research. Biotechnol. Adv. 2008, 26, 361–369. [29] Speer, R., Wulfkuhle, J., Espina, V., Aurajo, R. et al., Development of reverse phase protein microarrays for clinical applications and patient-tailored therapy. Cancer Genomics Proteomics 2007, 4, 157–164. [30] Assadi, M., Lamerz, J., Jarutat, T., Farfsing, A. et al., Multiple protein analysis of FFPE tissue samples with reverse-phase protein arrays. Mol. Cell. Proteomics 2013. [31] Guo, H., Liu, W., Ju, Z., Tamboli, P. et al., An efficient procedure for protein extraction from formalin-fixed, paraffinembedded tissues for reverse phase protein arrays. Proteome Sci. 2012, 10, 56. [32] Hunter, C., Becker, G., Breite, A., Anderson, L., Developing peptide MRM-based assays for cardiovascular biomarker proteins in plasma using a hybrid triple quadrupole linear ion trap mass spectrometer. Mol. Cell. Proteomics 2005, 4, S217–S217. [33] Addona, T. A., Abbatiello, S. E., Schilling, B., Skates, S. J. et al., Multi-site assessment of the precision and reproducibility of multiple reaction monitoring-based measurements of proteins in plasma (vol 27, pg 633, 2009). Nat. Biotechnol. 2009, 27, 864–864. [34] Sprung, R. W., Martinez, M. A., Carpenter, K. L., Ham, A. J. et al., Precision of multiple reaction monitoring mass spectrometry analysis of formalin-fixed, paraffin-embedded tissue. J. Proteome Res. 2012.

Proteomics 2014, 14, 774–783 [35] Whiteaker, J. R., Zhao, L., Anderson, L., Paulovich, A. G., An automated and multiplexed method for high throughput peptide immunoaffinity enrichment and multiple reaction monitoring mass spectrometry-based quantification of protein biomarkers. Mol. Cell. Proteomics 2010, 9, 184–196. [36] Diamandis, E. P., Automation of molecular diagnostics. Clin. Chem. 1996, 42, 7–8. [37] Surnametighe, G., Surnamenegm, G., Surnametodd, G., Surnamefairclough, G., Utility, reliability and reproducibility of immunoassay multiplex kits. Methods 2013, 61, 23–29. [38] Tighe, G., Negm, G., Todd, G., Fairclough, G., Utility, reliability and reproducibility of immunoassay multiplex kits. Methods 2013, 61, 23–29. [39] Bertenshaw, G. P., Yip, P., Seshaiah, P., Zhao, J. et al., Multianalyte profiling of serum antigens and autoimmune and infectious disease molecules to identify biomarkers dysregulated in epithelial ovarian cancer. Cancer Epidemiol. Biomarkers Prev. 2008, 17, 2872–2881. [40] Gurbel, P. A., Kreutz, R. P., Bliden, K. P., DiChiara, J., Tantry, U. S., Biomarker analysis by fluorokine multianalyte profiling distinguishes patients requiring intervention from patients with long-term quiescent coronary artery disease: a potential approach to identify atherosclerotic disease progression. Am. Heart J. 2008, 155, 56–61. [41] Izmailov, R., Guest, P. C., Bahn, S., Schwarz, E., Algorithm development for diagnostic biomarker assays. Int. Rev. Neurobiol. 2011, 101, 279–298. [42] Jonas, J. B., Jonas, R. A., Neumaier, M., Findeisen, P., Cytokine concentration in aqueous humor of eyes with diabetic macular edema. Retina 2012, 32, 2150–2157. [43] Ellington, A. A., Kullo, I. J., Bailey, K. R., Klee, G. G., Antibodybased protein multiplex platforms: technical and operational challenges. Clin. Chem. 2010, 56, 186–193. [44] Todd, J., Freese, B., Lu, A., Held, D. et al., Ultrasensitive flowbased immunoassays using single-molecule counting. Clin. Chem. 2007, 53, 1990–1995. [45] St Ledger, K., Agee, S. J., Kasaian, M. T., Forlow, S. B. et al., Analytical validation of a highly sensitive microparticlebased immunoassay for the quantitation of IL-13 in human serum using the Erenna immunoassay system. J. Immunol. Methods 2009, 350, 161–170. [46] DeForge, L. E., Loyet, K. M., Delarosa, D., Chinn, J. et al., Evaluation of heterophilic antibody blocking agents in reducing false positive interference in immunoassays for IL-17AA, IL17FF, and IL-17AF. J. Immunol. Methods 2010, 362, 70–81. [47] Hochholzer, W., Morrow, D. A., Giugliano, R. P., Novel biomarkers in cardiovascular disease: update 2010. Am. Heart. J. 2010, 160, 583–594. [48] Wang, T. J., Wollert, K. C., Larson, M. G., Coglianese, E. et al., Prognostic utility of novel biomarkers of cardiovascular stress: the Framingham heart study. Circulation 2012, 126, 1596–1604. [49] Apple, F. S., Steffen, L. M., Pearce, L. A., Murakami, M. M., Luepker, R. V., Increased cardiac troponin I as measured by a high-sensitivity assay is associated with high odds of cardiovascular death: the Minnesota heart survey. Clin. Chem. 2012, 58, 930–935.



783

Proteomics 2014, 14, 774–783

agnostic and biotechnological applications. FEBS Lett. 2010, 584, 2670–2680.

[50] Chang, L., Rissin, D. M., Fournier, D. R., Piech, T. et al., Single molecule enzyme-linked immunosorbent assays: theoretical considerations. J. Immunol. Methods 2012, 378, 102–115.

[65] Banerjee, J., Nilsen-Hamilton, M., Aptamers: multifunctional molecules for biomedical research. J. Mol. Med. (Berl.) 2013.

[51] Rissin, D. M., Fournier, D. R., Piech, T., Kan, C. W. et al., Simultaneous detection of single molecules and singulated ensembles of molecules enables immunoassays with broad dynamic range. Anal. Chem. 2011, 83, 2279–2285.

[66] Shin, S., Kim, I. H., Kang, W., Yang, J. K., Hah, S. S., An alternative to Western blot analysis using RNA aptamerfunctionalized quantum dots. Bioorg. Med. Chem. Lett. 2010, 20, 3322–3325.

[52] Rissin, D. M., Kan, C. W., Campbell, T. G., Howes, S. C. et al., Single-molecule enzyme-linked immunosorbent assay detects serum proteins at subfemtomolar concentrations. Nat. Biotechnol. 2010, 28, 595–599.

[67] Tombelli, S., Mascini, M., Aptamers as molecular tools for bioanalytical methods. Curr. Opin. Mol. Ther. 2009, 11, 179–188.

[53] Wilson, D. H., Hanlon, D. W., Provuncher, G. K., Chang, L. et al., Fifth-generation digital immunoassay for prostatespecific antigen by single molecule array technology. Clin. Chem. 2011, 57, 1712–1721. [54] Song, L., Hanlon, D. W., Chang, L., Provuncher, G. K. et al., Single molecule measurements of tumor necrosis factor alpha and interleukin-6 in the plasma of patients with Crohn’s disease. J. Immunol. Methods 2011, 372, 177–186. [55] Zetterberg, H., Mortberg, E., Song, L., Chang, L. et al., Hypoxia due to cardiac arrest induces a time-dependent increase in serum amyloid beta levels in humans. PLoS One 2011, 6, e28263. [56] Zetterberg, H., Wilson, D., Andreasson, U., Minthon, L. et al., Plasma tau levels in Alzheimer’s disease. Alzheimers Res. Ther. 2013, 5, 9. [57] Rissin, D. M., Kan, C. W., Song, L., Rivnak, A. J. et al., Multiplexed single molecule immunoassays. Lab. Chip 2013, 13, 2902–2911. [58] Lundberg, M., Eriksson, A., Tran, B., Assarsson, E., Fredriksson, S., Homogeneous antibody-based proximity extension assays provide sensitive and specific detection of lowabundant proteins in human blood. Nucleic Acids Res. 2011, 39, e102. [59] Mertins, P., Qiao, J. W., Patel, J., Udeshi, N. D. et al., Integrated proteomic analysis of post-translational modifications by serial enrichment. Nat. Methods 2013, 10, 634–637. [60] Bendall, S. C., Simonds, E. F., Qiu, P., Amir el, A. D. et al., Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science 2011, 332, 687–696. [61] Binz, H. K., Amstutz, P., Pluckthun, A., Engineering novel binding proteins from nonimmunoglobulin domains. Nat. Biotechnol. 2005, 23, 1257–1268. [62] Stoevesandt, O., Taussig, M. J., Affinity proteomics: the role of specific binding reagents in human proteome analysis. Expert Rev. Proteomics 2012, 9, 401–414. [63] Baltzer, L., Crossing borders to bind proteins—a new concept in protein recognition based on the conjugation of small organic molecules or short peptides to polypeptides from a designed set. Anal. Bioanal. Chem. 2011, 400, 1653–1664. [64] Lofblom, J., Feldwisch, J., Tolmachev, V., Carlsson, J. et al., Affibody molecules: engineered proteins for therapeutic, di-

[68] Zhu, J., Li, T., Hu, J., Wang, E., A novel dot-blot DNAzymelinked aptamer assay for protein detection. Anal. Bioanal. Chem. 2010, 397, 2923–2927. [69] Meyer, M., Scheper, T., Walter, J. G., Aptamers: versatile probes for flow cytometry. Appl. Microbiol. Biotechnol. 2013, 97, 7097–7109. [70] Ostroff, R. M., Bigbee, W. L., Franklin, W., Gold, L. et al., Unlocking biomarker discovery: large scale application of aptamer proteomic technology for early detection of lung cancer. PLoS One 2010, 5, e15003. [71] Wang, H., Yang, X., Bowick, G. C., Herzog, N. K. et al., Identification of proteins bound to a thioaptamer probe on a proteomics array. Biochem. Biophys. Res. Commun. 2006, 347, 586–593. [72] Mehan, M. R., Ostroff, R., Wilcox, S. K., Steele, F. et al., Highly multiplexed proteomic platform for biomarker discovery, diagnostics, and therapeutics. Adv. Exp. Med. Biol. 2013, 735, 283–300. [73] Berezovski, M. V., Lechmann, M., Musheev, M. U., Mak, T. W., Krylov, S. N., Aptamer-facilitated biomarker discovery (AptaBiD). J. Am. Chem. Soc. 2008, 130, 9137–9143. [74] Loffredo, F. S., Steinhauser, M. L., Jay, S. M., Gannon, J. et al., Growth differentiation factor 11 is a circulating factor that reverses age-related cardiac hypertrophy. Cell 2013, 153, 828–839. [75] Mehan, M. R., Ayers, D., Thirstrup, D., Xiong, W. et al., Protein signature of lung cancer tissues. PLoS One 2012, 7, e35157. [76] Gold, L., Ayers, D., Bertino, J., Bock, C. et al., Aptamer-based multiplexed proteomic technology for biomarker discovery. PLoS One 2010, 5, e15004. [77] Baird, G. S., Nelson, S. K., Keeney, T. R., Stewart, A. et al., Age-dependent changes in the cerebrospinal fluid proteome by slow off-rate modified aptamer array. Am. J. Pathol. 2012, 180, 446–456. [78] Wilson, R., Sensitivity and specificity: twin goals of proteomics assays. Can they be combined? Expert. Rev. Proteomics 2013, 10, 135–149. [79] Federici, G., Gao, X., Slawek, J., Arodz, T. et al., Systems analysis of the NCI-60 cancer cell lines by alignment of protein pathway activation modules with “-OMIC” data fields and therapeutic response signatures. Mol. Cancer Res. 2013, 11, 676–685.



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