Mammalian cell display with automated oligo design and library assembly allows for rapid residue level conformational epitope mapping

Precise epitope determination of therapeutic antibodies is of great value as it allows for further comprehension of mechanism of action, therapeutic responsiveness prediction, avoidance of unwanted cross reactivity, and vaccine design. The golden standard for discontinuous epitope determination is the laborious X-ray crystallography method. Here, we present a combinatorial method for rapid mapping of discontinuous epitopes by mammalian antigen display, eliminating the need for protein expression and purification. The method is facilitated by automated workflows and tailored software for antigen analysis and oligonucleotide design. These oligos are used in automated mutagenesis to generate an antigen receptor library displayed on mammalian cells for direct binding analysis by flow cytometry. Through automated analysis of 33930 primers an optimized single condition cloning reaction was defined allowing for mutation of all surface-exposed residues of the receptor binding domain of SARS-CoV-2. All variants were functionally expressed, and two reference binders validated the method. Furthermore, epitopes of three novel therapeutic antibodies were successfully determined followed by evaluation of binding also towards SARS-CoV-2 Omicron BA.2. We find the method to be highly relevant for rapid construction of antigen libraries and determination of antibody epitopes, especially for the development of therapeutic interventions against novel pathogens.

Selection, characterization and in vivo evaluation of novel CD44v6-targeting antibodies for targeted molecular radiotherapy

Molecular radiotherapy combines the advantages of systemic administration of highly specific antibodies or peptides and the localized potency of ionizing radiation. A potential target for molecular radiotherapy is the cell surface antigen CD44v6, which is overexpressed in numerous cancers, with limited expression in normal tissues. The aim of the present study was to generate and characterize a panel of human anti-CD44v6 antibodies and identify a suitable candidate for future use in molecular radiotherapy of CD44v6-expressing cancers. Binders were first isolated from large synthetic phage display libraries containing human scFv and Fab antibody fragments. The antibodies were extensively analyzed through in vitro investigations of binding kinetics, affinity, off-target binding, and cell binding. Lead candidates were further subjected to in vivo biodistribution studies in mice bearing anaplastic thyroid cancer xenografts that express high levels of CD44v6. Additionally, antigen-dependent tumor uptake of the lead candidate was verified in additional xenograft models with varying levels of target expression. Interestingly, although only small differences were observed among the top antibody candidates in vitro, significant differences in tumor uptake and retention were uncovered in in vivo experiments. A high-affinity anti-CD44v6 lead drug candidate was identified, mAb UU-40, which exhibited favorable target binding properties and in vivo distribution. In conclusion, a panel of human anti-CD44v6 antibodies was successfully generated and characterized in this study. Through comprehensive evaluation, mAb UU-40 was identified as a promising lead candidate for future molecular radiotherapy of CD44v6-expressing cancers due to its high affinity, excellent target binding properties, and desirable in vivo distribution characteristics.

Design, structure and plasma binding of ancestral β-CoV scaffold antigens

We report the application of ancestral sequence reconstruction on coronavirus spike protein, resulting in stable and highly soluble ancestral scaffold antigens (AnSAs). The AnSAs interact with plasma of patients recovered from COVID-19 but do not bind to the human angiotensin-converting enzyme 2 (ACE2) receptor. Cryo-EM analysis of the AnSAs yield high resolution structures (2.6-2.8 Å) indicating a closed pre-fusion conformation in which all three receptor-binding domains (RBDs) are facing downwards. The structures reveal an intricate hydrogen-bonding network mediated by well-resolved loops, both within and across monomers, tethering the N-terminal domain and RBD together. We show that AnSA-5 can induce and boost a broad-spectrum immune response against the wild-type RBD as well as circulating variants of concern in an immune organoid model derived from tonsils. Finally, we highlight how AnSAs are potent scaffolds by replacing the ancestral RBD with the wild-type sequence, which restores ACE2 binding and increases the interaction with convalescent plasma.

Complementarity-determining region clustering may cause CAR-T cell dysfunction

Chimeric antigen receptor (CAR)-T cell therapy is rapidly advancing as cancer treatment, however, designing an optimal CAR remains challenging. A single-chain variable fragment (scFv) is generally used as CAR targeting moiety, wherein the complementarity-determining regions (CDRs) define its specificity. We report here that the CDR loops can cause CAR clustering, leading to antigen-independent tonic signalling and subsequent CAR-T cell dysfunction. We show via CARs incorporating scFvs with identical framework and varying CDR sequences that CARs may cluster on the T cell surface, which leads to antigen-independent CAR-T cell activation, characterized by increased cell size and interferon (IFN)-γ secretion. This results in CAR-T cell exhaustion, activation-induced cell death and reduced responsiveness to target-antigen-expressing tumour cells. CDR mutagenesis confirms that the CAR-clustering is mediated by CDR-loops. In summary, antigen-independent tonic signalling can be induced by CDR-mediated CAR clustering, which could not be predicted from the scFv sequences, but could be tested for by evaluating the activity of unstimulated CAR-T cells.

Generation and Next-Generation Sequencing-Based Characterization of a Large Human Combinatorial Antibody Library

Antibody phage display is a key technology for the discovery and development of target-specific monoclonal antibodies (mAbs) for use in research, diagnostics, and therapy. The construction of a high-quality antibody library, with larger and more diverse antibody repertoires, is essential for the successful development of phage display-derived mAbs. In this study, a large human combinatorial single-chain variable fragment library (1.5 × 10¹¹ colonies) was constructed from Epstein-Barr virus-infected human peripheral blood mononuclear cells stimulated with a combination of two of the activators of human B cells, the Toll-like receptor 7/8 agonist R848 and interleukin-2. Next-generation sequencing analysis with approximately 1.9 × 10⁶ and 2.7 × 10⁶ full-length sequences of heavy chain variable (VH) and κ light chain variable (Vκ) domains, respectively, revealed that the library consists of unique VH (approximately 94%) and Vκ (approximately 91%) sequences with greater diversity than germline sequences. Lastly, multiple unique mAbs with high affinity and broad cross-species reactivity could be isolated from the library against two therapeutically relevant target antigens, validating the library quality. These findings suggest that the novel antibody library we have developed may be useful for the rapid development of target-specific phage display-derived recombinant human mAbs for use in therapeutic and diagnostic applications.

Spike-Dependent Opsonization Indicates Both Dose-Dependent Inhibition of Phagocytosis and That Non-Neutralizing Antibodies Can Confer Protection to SARS-CoV-2

Spike-specific antibodies are central to effective COVID19 immunity. Research efforts have focused on antibodies that neutralize the ACE2-Spike interaction but not on non-neutralizing antibodies. Antibody-dependent phagocytosis is an immune mechanism enhanced by opsonization, where typically, more bound antibodies trigger a stronger phagocyte response. Here, we show that Spike-specific antibodies, dependent on concentration, can either enhance or reduce Spike-bead phagocytosis by monocytes independently of the antibody neutralization potential. Surprisingly, we find that both convalescent patient plasma and patient-derived monoclonal antibodies lead to maximum opsonization already at low levels of bound antibodies and is reduced as antibody binding to Spike protein increases. Moreover, we show that this Spike-dependent modulation of opsonization correlate with the outcome in an experimental SARS-CoV-2 infection model. These results suggest that the levels of anti-Spike antibodies could influence monocyte-mediated immune functions and propose that non-neutralizing antibodies could confer protection to SARS-CoV-2 infection by mediating phagocytosis.

Facilitating Machine Learning-Guided Protein Engineering with Smart Library Design and Massively Parallel Assays

Protein design plays an important role in recent medical advances from antibody therapy to vaccine design. Typically, exhaustive mutational screens or directed evolution experiments are used for the identification of the best design or for improvements to the wild-type variant. Even with a high-throughput screening on pooled libraries and Next-Generation Sequencing to boost the scale of read-outs, surveying all the variants with combinatorial mutations for their empirical fitness scores is still of magnitudes beyond the capacity of existing experimental settings. To tackle this challenge, in-silico approaches using machine learning to predict the fitness of novel variants based on a subset of empirical measurements are now employed. These machine learning models turn out to be useful in many cases, with the premise that the experimentally determined fitness scores and the amino-acid descriptors of the models are informative. The machine learning models can guide the search for the highest fitness variants, resolve complex epistatic relationships, and highlight bio-physical rules for protein folding. Using machine learning-guided approaches, researchers can build more focused libraries, thus relieving themselves from labor-intensive screens and fast-tracking the optimization process. Here, we describe the current advances in massive-scale variant screens, and how machine learning and mutagenesis strategies can be integrated to accelerate protein engineering. More specifically, we examine strategies to make screens more economical, informative, and effective in discovery of useful variants.

Selection and structural characterization of anti-TREM2 scFvs that reduce levels of shed ectodomain

Mutations in TREM2, a receptor expressed by microglia in the brain, are associated with an increased risk of neurodegeneration, including Alzheimer's disease. Numerous studies support a role for TREM2 in sensing damaging stimuli and triggering signaling cascades necessary for neuroprotection. Despite its significant role, ligands and regulators of TREM2 activation, and the mechanisms governing TREM2-dependent responses and its cleavage from the membrane, remain poorly characterized. Here, we present phage display generated antibody single-chain variable fragments (scFvs) to human TREM2 immunoglobulin-like domain. Co-crystal structures revealed the binding of two scFvs to an epitope on the TREM2 domain distal to the putative ligand-binding site. Enhanced functional activity was observed for oligomeric scFv species, which inhibited the production of soluble TREM2 in a HEK293 cell model. We hope that detailed characterization of their epitopes and properties will facilitate the use of these renewable binders as structural and functional biology tools for TREM2 research.

Identification of a serum biomarker signature associated with metastatic prostate cancer

PURPOSE

Improved early diagnosis and determination of aggressiveness of prostate cancer (PC) is important to select suitable treatment options and to decrease over-treatment. The conventional marker is total prostate specific antigen (PSA) levels in blood, but lacks specificity and ability to accurately discriminate indolent from aggressive disease.

EXPERIMENTAL DESIGN

In this study, we sought to identify a serum biomarker signature associated with metastatic PC. We measured 157 analytes in 363 serum samples from healthy subjects, patients with non-metastatic PC and patients with metastatic PC, using a recombinant antibody microarray.

RESULTS

A signature consisting of 69 proteins differentiating metastatic PC patients from healthy controls was identified.

CONCLUSIONS AND CLINICAL RELEVANCE

The clinical value of this biomarker signature requires validation in larger independent patient cohorts before providing a new prospect for detection of metastatic PC.

Protein design and variant prediction using autoregressive generative models

The ability to design functional sequences and predict effects of variation is central to protein engineering and biotherapeutics. State-of-art computational methods rely on models that leverage evolutionary information but are inadequate for important applications where multiple sequence alignments are not robust. Such applications include the prediction of variant effects of indels, disordered proteins, and the design of proteins such as antibodies due to the highly variable complementarity determining regions. We introduce a deep generative model adapted from natural language processing for prediction and design of diverse functional sequences without the need for alignments. The model performs state-of-art prediction of missense and indel effects and we successfully design and test a diverse 105-nanobody library that shows better expression than a 1000-fold larger synthetic library. Our results demonstrate the power of the alignment-free autoregressive model in generalizing to regions of sequence space traditionally considered beyond the reach of prediction and design.

Fluorescence Signal Enhancement in Antibody Microarrays Using Lightguiding Nanowires

Fluorescence-based detection assays play an essential role in the life sciences and medicine. To offer better detection sensitivity and lower limits of detection (LOD), there is a growing need for novel platforms with an improved readout capacity. In this context, substrates containing semiconductor nanowires may offer significant advantages, due to their proven light-emission enhancing, waveguiding properties, and increased surface area. To demonstrate and evaluate the potential of such nanowires in the context of diagnostic assays, we have in this work adopted a well-established single-chain fragment antibody-based assay, based on a protocol previously designed for biomarker detection using planar microarrays, to freestanding, SiO₂-coated gallium phosphide nanowires. The assay was used for the detection of protein biomarkers in highly complex human serum at high dilution. The signal quality was quantified and compared with results obtained on conventional flat silicon and plastic substrates used in the established microarray applications. Our results show that using the nanowire-sensor platform in combination with conventional readout methods, improves the signal intensity, contrast, and signal-to-noise by more than one order of magnitude compared to flat surfaces. The results confirm the potential of lightguiding nanowires for signal enhancement and their capacity to improve the LOD of standard diagnostic assays.

Proteomic Data Analysis for Differential Profiling of the Autoimmune Diseases SLE, RA, SS, and ANCA-Associated Vasculitis

Early and correct diagnosis of inflammatory rheumatic diseases (IRD) poses a clinical challenge due to the multifaceted nature of symptoms, which also may change over time. The aim of this study was to perform protein expression profiling of four systemic IRDs, systemic lupus erythematosus (SLE), ANCA-associated systemic vasculitis (SV), rheumatoid arthritis (RA), and Sjögren’s syndrome (SS), and healthy controls to identify candidate biomarker signatures for differential classification. A total of 316 serum samples collected from patients with SLE, RA, SS, or SV and from healthy controls were analyzed using 394-plex recombinant antibody microarrays. Differential protein expression profiling was examined using Wilcoxon signed rank test, and condensed biomarker panels were identified using advanced bioinformatics and state-of-the art classification algorithms to pinpoint signatures reflecting each disease (raw data set available at https://figshare.com/s/3bd3848a28ef6e7ae9a9.). In this study, we were able to classify the included individual IRDs with high accuracy, as demonstrated by the ROC area under the curve (ROC AUC) values ranging between 0.96 and 0.80. In addition, the groups of IRDs could be separated from healthy controls at an ROC AUC value of 0.94. Disease-specific candidate biomarker signatures and general autoimmune signature were identified, including several deregulated analytes. This study supports the rationale of using multiplexed affinity-based technologies to reflect the biological complexity of autoimmune diseases. A multiplexed approach for decoding multifactorial complex diseases, such as autoimmune diseases, will play a significant role for future diagnostic purposes, essential to prevent severe organ- and tissue-related damage.

Immune-related protein signature in serum stratify relapsed mantle cell lymphoma patients based on risk

Background

Response to modern treatment strategies, which combine cytotoxic compounds with immune stimulatory agents and targeted treatment is highly variable among MCL patients. Thus, providing prognostic and predictive markers for risk adapted therapy is warranted and molecular information that can help in patient stratification is a necessity. In relapsed MCL, biopsies are rarely available and molecular information from tumor tissue is often lacking. Today, the main tool to access risk is the MCL international prognostic index (MIPI), which does not include detailed biological information of relevance for different treatment options. To enable continuous monitoring of patients, non-invasive companion diagnostic tools are needed which can further reduce cost and patient distress and enable efficient measurements of biological markers.

Methods

We have assessed if serum-based protein profiling can identify immune related proteins that stratify relapsed MCL patients based on risk. Overall, 371 scFv targeting 158 proteins were assessed using an antibody microarray platform. We profiled patients (n = 44) who had been treated within the MCL6-Philemon trial combining targeted and immune-modulatory treatment.

Results

The downstream processing led to the identification of the relapsed immune signature (RIS) consisting of 11 proteins with potential to stratify patients with long and short overall survival (OS). Moreover, in this population, MIPI alone failed to separate high, intermediate and low risk patients, but a combined index based on MIPI together with RIS, MIPI_ris, showed improved performance and significantly stratified all three risk groups based on OS.

Conclusions

Our results show that addition of biological parameters to previous prognostic indices improves patient stratification among patients treated with BTK inhibitor triplet combination, particularly, in the identification of an extreme high risk group.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-020-07678-4.

Generation and validation of recombinant antibodies to study human aminoacyl-tRNA synthetases

Aminoacyl-tRNA synthetases (aaRSs) have long been viewed as mere housekeeping proteins and have therefore often been overlooked in drug discovery. However, recent findings have revealed that many aaRSs have noncanonical functions, and several of the aaRSs have been linked to autoimmune diseases, cancer, and neurological disorders. Deciphering these roles has been challenging because of a lack of tools to enable their study. To help solve this problem, we have generated recombinant high-affinity antibodies for a collection of thirteen cytoplasmic and one mitochondrial aaRSs. Selected domains of these proteins were produced recombinantly in Escherichia coli and used as antigens in phage display selections using a synthetic human single-chain fragment variable library. All targets yielded large sets of antibody candidates that were validated through a panel of binding assays against the purified antigen. Furthermore, the top-performing binders were tested in immunoprecipitation followed by MS for their ability to capture the endogenous protein from mammalian cell lysates. For antibodies targeting individual members of the multi-tRNA synthetase complex, we were able to detect all members of the complex, co-immunoprecipitating with the target, in several cell types. The functionality of a subset of binders for each target was also confirmed using immunofluorescence. The sequences of these proteins have been deposited in publicly available databases and repositories. We anticipate that this open source resource, in the form of high-quality recombinant proteins and antibodies, will accelerate and empower future research of the role of aaRSs in health and disease.

Multiplex profiling of serum proteins in solution using barcoded antibody fragments and next generation sequencing

The composition of serum proteins is reflecting the current health status and can, with the right tools, be used to detect early signs of disease, such as an emerging cancer. An earlier diagnosis of cancer would greatly increase the chance of an improved outcome for the patients. However, there is still an unmet need for proficient tools to decipher the information in the blood proteome, which calls for further technological development. Here, we present a proof-of-concept study that demonstrates an alternative approach for multiplexed protein profiling of serum samples in solution, using DNA barcoded scFv antibody fragments and next generation sequencing. The outcome shows high accuracy when discriminating samples derived from pancreatic cancer patients and healthy controls and represents a scalable alternative for serum analysis.

Brofelth, Ekstrand et al use DNA barcoded scFv antibody fragments and next generation sequencing for multiplex profiling of proteins in serum from pancreatic cancer patients with high accuracy. This approach can potentially be used in high throughput precision diagnosis.

Advances in the Production and Batch Reformatting of Phage Antibody Libraries

Phage display antibody libraries have proven an invaluable resource for the isolation of diagnostic and potentially therapeutic antibodies, the latter usually being antibody fragments converted into IgG formats. Recent advances in the production of highly diverse and functional antibody libraries are considered here, including for Fabs, scFvs and nanobodies. These advances include codon optimisation during generation of CDR diversity, improved display levels using novel signal sequences, molecular chaperones and isomerases and the use of highly stable scaffolds with relatively high expression levels. In addition, novel strategies for the batch reformatting of scFv and Fab phagemid libraries, derived from phage panning, into IgG formats are described. These strategies allow the screening of antibodies in the end-use format, facilitating more efficient selection of potential therapeutics.

SAMURAI (Solid-phase Assisted Mutagenesis by Uracil Restriction for Accurate Integration) for antibody affinity maturation and paratope mapping

Mutagenesis libraries are essential for combinatorial protein engineering. Despite improvements in gene synthesis and directed mutagenesis, current methodologies still have limitations regarding the synthesis of complete antibody single-chain variable fragment (scFv) genes and simultaneous diversification of all six CDRs. Here, we describe the generation of mutagenesis libraries for antibody affinity maturation using a cell-free solid-phase technique for annealing of single-strand mutagenic oligonucleotides. The procedure consists of PCR-based incorporation of uracil into a wild-type template, bead-based capture, elution of single-strand DNA, and in vitro uracil excision enzyme based degradation of the template DNA. Our approach enabled rapid (8 hours) mutagenesis and automated cloning of 50 position-specific alanine mutants for mapping of a scFv antibody paratope. We further exemplify our method by generating affinity maturation libraries with diversity introduced in critical, nonessential, or all CDR positions randomly. Assessment with Illumina deep sequencing showed less than 1% wild-type in two libraries and the ability to diversify all CDR positions simultaneously. Selections of the libraries with bacterial display and deep sequencing evaluation of the selection output showed that diversity introduced in non-essential positions allowed for a more effective enrichment of improved binders compared to the other two diversification strategies.

A Human IgE Antibody Binding Site on Der p 2 for the Design of a Recombinant Allergen for Immunotherapy

Der p 2 is one of the most important allergens from the house dust mite Dermatophagoides pteronyssinus Identification of human IgE Ab binding epitopes can be used for rational design of allergens with reduced IgE reactivity for therapy. Antigenic analysis of Der p 2 was performed by site-directed mutagenesis based on the x-ray crystal structure of the allergen in complex with a Fab from the murine IgG mAb 7A1 that binds an epitope overlapping with human IgE binding sites. Conformational changes upon Ab binding were confirmed by nuclear magnetic resonance using a 7A1-single-chain variable fragment. In addition, a human IgE Ab construct that interferes with mAb 7A1 binding was isolated from a combinatorial phage-display library constructed from a mite-allergic patient and expressed as two recombinant forms (single-chain Fab in Pichia pastoris and Fab in Escherichia coli). These two IgE Ab constructs and the mAb 7A1 failed to recognize two Der p 2 epitope double mutants designed to abolish the allergen-Ab interaction while preserving the fold necessary to bind Abs at other sites of the allergen surface. A 10-100-fold reduction in binding of IgE from allergic subjects to the mutants additionally showed that the residues mutated were involved in IgE Ab binding. In summary, mutagenesis of a Der p 2 epitope defined by x-ray crystallography revealed an IgE Ab binding site that will be considered for the design of hypoallergens for immunotherapy.

Circulating Levels of Interferon Regulatory Factor-5 Associates With Subgroups of Systemic Lupus Erythematosus Patients

Systemic Lupus Erythematosus (SLE) is a heterogeneous autoimmune disease, which currently lacks specific diagnostic biomarkers. The diversity within the patients obstructs clinical trials but may also reflect differences in underlying pathogenesis. Our objective was to obtain protein profiles to identify potential general biomarkers of SLE and to determine molecular subgroups within SLE for patient stratification. Plasma samples from a cross-sectional study of well-characterized SLE patients (n = 379) and matched population controls (n = 316) were analyzed by antibody suspension bead array targeting 281 proteins. To investigate the differences between SLE and controls, Mann–Whitney U-test with Bonferroni correction, generalized linear modeling and receiver operating characteristics (ROC) analysis were performed. K-means clustering was used to identify molecular SLE subgroups. We identified Interferon regulating factor 5 (IRF5), solute carrier family 22 member 2 (SLC22A2) and S100 calcium binding protein A12 (S100A12) as the three proteins with the largest fold change between SLE patients and controls (SLE/Control = 1.4, 1.4, and 1.2 respectively). The lowest p-values comparing SLE patients and controls were obtained for S100A12, Matrix metalloproteinase-1 (MMP1) and SLC22A2 (p_adjusted = 3 × 10⁻⁹, 3 × 10⁻⁶, and 5 × 10⁻⁶ respectively). In a set of 15 potential biomarkers differentiating SLE patients and controls, two of the proteins were transcription factors, i.e., IRF5 and SAM pointed domain containing ETS transcription factor (SPDEF). IRF5 was up-regulated while SPDEF was found to be down-regulated in SLE patients. Unsupervised clustering of all investigated proteins identified three molecular subgroups among SLE patients, characterized by (1) high levels of rheumatoid factor-IgM, (2) low IRF5, and (3) high IRF5. IRF5 expressing microparticles were analyzed by flow cytometry in a subset of patients to confirm the presence of IRF5 in plasma and detection of extracellular IRF5 was further confirmed by immunoprecipitation-mass spectrometry (IP-MS). Interestingly IRF5, a known genetic risk factor for SLE, was detected extracellularly and suggested by unsupervised clustering analysis to differentiate between SLE subgroups. Our results imply a set of circulating molecules as markers of possible pathogenic importance in SLE. We believe that these findings could be of relevance for understanding the pathogenesis and diversity of SLE, as well as for selection of patients in clinical trials.

Critical reagent screening and characterization: benefits and approaches for protein biomarker assays by hybrid LC–MS

In recent years, hybrid ligand-binding assays (LBAs)/LC–MS assays have been increasingly used for quantitation of protein biomarkers in biological matrices. However, unlike in LBAs where the importance of critical reagent screening and characterization is well understood and widely reported, benefits of well-characterized hybrid LC–MS assay reagents are frequently underestimated. Two groups of analyte-specific reagents, binding reagents and assay calibrators, are considered the critical reagents for biomarker assays. In this article, we summarize the similarities and differences of critical reagents used in LBAs and hybrid LC–MS assays, overview the benefits and approaches of critical reagent screening, characterization, antibody conjugation and discuss bioanalytical considerations in hybrid LC–MS assay development for robust measurements of protein biomarkers in biological matrices.

Advancing the immunoaffinity platform AFFIRM to targeted measurements of proteins in serum in the pg/ml range

There is a great need for targeted protein assays with the capacity of sensitive measurements in complex samples such as plasma or serum, not the least for clinical purposes. Proteomics keeps generating hundreds of biomarker candidates that need to be transferred towards true clinical application through targeted verification studies and towards clinically applicable analysis formats. The immunoaffinity assay AFFIRM (AFFInity sRM) combines the sensitivity of recombinant single chain antibodies (scFv) for targeted protein enrichment with a specific mass spectrometry readout through selected reaction monitoring (SRM) in an automated workflow. Here we demonstrate a 100 times improved detection capacity of the assay down to pg/ml range through the use of oriented antibody immobilization to magnetic beads. This was achieved using biotin-tagged scFv coupled to streptavidin coated magnetic beads, or utilizing the FLAG tag for coupling to anti-FLAG antibody coated magnetic beads. An improved multiplexing capacity with an 11-plex setup was also demonstrated compared to a previous 3-plex setup, which is of great importance for the analysis of panels of biomarker targets.

Tumor tissue protein signatures reflect histological grade of breast cancer

Histological grade is one of the most commonly used prognostic factors for patients diagnosed with breast cancer. However, conventional grading has proven technically challenging, and up to 60% of the tumors are classified as histological grade 2, which represents a heterogeneous cohort less informative for clinical decision making. In an attempt to study and extend the molecular puzzle of histologically graded breast cancer, we have in this pilot project searched for additional protein biomarkers in a new space of the proteome. To this end, we have for the first time performed protein expression profiling of breast cancer tumor tissue, using recombinant antibody microarrays, targeting mainly immunoregulatory proteins. Thus, we have explored the immune system as a disease-specific sensor (clinical immunoproteomics). Uniquely, the results showed that several biologically relevant proteins reflecting histological grade could be delineated. In more detail, the tentative biomarker panels could be used to i) build a candidate model classifying grade 1 vs. grade 3 tumors, ii) demonstrate the molecular heterogeneity among grade 2 tumors, and iii) potentially re-classify several of the grade 2 tumors to more like grade 1 or grade 3 tumors. This could, in the long-term run, lead to improved prognosis, by which the patients could benefit from improved tailored care.

Institutional profile: the national Swedish academic drug discovery & development platform at SciLifeLab

The Science for Life Laboratory Drug Discovery and Development Platform (SciLifeLab DDD) was established in Stockholm and Uppsala, Sweden, in 2014. It is one of ten platforms of the Swedish national SciLifeLab which support projects run by Swedish academic researchers with large-scale technologies for molecular biosciences with a focus on health and environment. SciLifeLab was created by the coordinated effort of four universities in Stockholm and Uppsala: Stockholm University, Karolinska Institutet, KTH Royal Institute of Technology and Uppsala University, and has recently expanded to other Swedish university locations. The primary goal of the SciLifeLab DDD is to support selected academic discovery and development research projects with tools and resources to discover novel lead therapeutics, either molecules or human antibodies. Intellectual property developed with the help of SciLifeLab DDD is wholly owned by the academic research group. The bulk of SciLifeLab DDD's research and service activities are funded from the Swedish state, with only consumables paid by the academic research group through individual grants.

Plasma protein profiling in a stage defined pancreatic cancer cohort - Implications for early diagnosis

Pancreatic ductal adenocarcinoma (PDAC) is a disease where detection preceding clinical symptoms significantly increases the life expectancy of patients. In this study, a recombinant antibody microarray platform was used to analyze 213 Chinese plasma samples from PDAC patients and normal control (NC) individuals. The cohort was stratified according to disease stage, i.e. resectable disease (stage I/II), locally advanced (stage III) and metastatic disease (stage IV). Support vector machine analysis showed that all PDAC stages could be discriminated from controls and that the accuracy increased with disease progression, from stage I to IV. Patients with stage I/II PDAC could be discriminated from NC with high accuracy based on a plasma protein signature, indicating a possibility for early diagnosis and increased detection rate of surgically resectable tumors.