Autoimmune profiling with protein microarrays in clinical applications

Endometrial cancer diagnostic and prognostic algorithms based on proteomics, metabolomics, and clinical data: a systematic review

Endometrial cancer is the most common gynaecological malignancy in developed countries. Over 382,000 new cases were diagnosed worldwide in 2018, and its incidence and mortality are constantly rising due to longer life expectancy and life style factors including obesity. Two major improvements are needed in the management of patients with endometrial cancer, i.e., the development of non/minimally invasive tools for diagnostics and prognostics, which are currently missing. Diagnostic tools are needed to manage the increasing number of women at risk of developing the disease. Prognostic tools are necessary to stratify patients according to their risk of recurrence pre-preoperatively, to advise and plan the most appropriate treatment and avoid over/under-treatment. Biomarkers derived from proteomics and metabolomics, especially when derived from non/minimally-invasively collected body fluids, can serve to develop such prognostic and diagnostic tools, and the purpose of the present review is to explore the current research in this topic. We first provide a brief description of the technologies, the computational pipelines for data analyses and then we provide a systematic review of all published studies using proteomics and/or metabolomics for diagnostic and prognostic biomarker discovery in endometrial cancer. Finally, conclusions and recommendations for future studies are also given.

Immunoglobulin profiling with large high-density peptide microarrays as screening method to detect candidate proteins for future biomarker detection in dogs with steroid-responsive meningitis-arteritis

Steroid responsive meningitis arteritis (SRMA) is an aberrant Th2-mediated systemic inflammatory disease in dogs. The etiopathogenesis still remains unclear as no triggering pathogen or autoantigen could be found so far.

HYPOTHESIS

Large high-density peptide microarrays are a suitable screening method to detect possible autoantigens which might be involved in the pathogenesis of SRMA.

METHODS

The IgA and IgG profile of pooled serum samples of 5 dogs with SRMA and 5 dogs with neck pain due to intervertebral disc herniation (IVDH) without ataxia or paresis were compared via commercially available high-density peptide microarrays (Discovery Microarray) containing 29,240 random linear peptides. Canine distemper virus nucleoprotein (CDVN) served as positive control as all dogs were vaccinated. Common motifs were compared to amino acid sequences of known proteins via databank search. One suitable protein was manually selected for further analysis with a smaller customized high-density peptide microarray.

RESULTS

Pooled serum of dogs with SRMA and IVDH showed different IgA and IgG responses on Discovery Microarray. Only top IgG responses of dogs with SRMA showed a common motif not related to the control protein CDVN. This common motif is part of the interleukin 1 receptor antagonist protein (IL1Ra). On IL1Ra, dogs with SRMA displayed IgA binding to an additional epitope, which dogs with IVDH did not show.

DISCUSSION

IL1Ra is an anti-inflammatory acute phase protein. Different immunoglobulin binding patterns on IL1Ra could be involved in the pathogenesis of SRMA and IL1Ra might be developed as future biomarker for SRMA.

Applications of Protein Microarrays in Biomarker Discovery for Autoimmune Diseases

Dysregulated autoantibodies and cytokines were deemed to provide important cues for potential illnesses, such as various carcinomas and autoimmune diseases. Increasing biotechnological approaches have been applied to screen and identify the specific alterations of these biomolecules as distinctive biomarkers in diseases, especially autoimmune diseases. As a versatile and robust platform, protein microarray technology allows researchers to easily profile dysregulated autoantibodies and cytokines associated with autoimmune diseases using various biological specimens, mainly serum samples. Here, we summarize the applications of protein microarrays in biomarker discovery for autoimmune diseases. In addition, the key issues in the process of using this approach are presented for improving future studies.

PAWER: protein array web exploreR

Background

Protein microarray is a well-established approach for characterizing activity levels of thousands of proteins in a parallel manner. Analysis of protein microarray data is complex and time-consuming, while existing solutions are either outdated or challenging to use without programming skills. The typical data analysis pipeline consists of a data preprocessing step, followed by differential expression analysis, which is then put into context via functional enrichment. Normally, biologists would need to assemble their own workflow by combining a set of unrelated tools to analyze experimental data. Provided that most of these tools are developed independently by various bioinformatics groups, making them work together could be a real challenge.

Results

Here we present PAWER, the online web tool dedicated solely to protein microarray analysis. PAWER enables biologists to carry out all the necessary analysis steps in one go. PAWER provides access to state-of-the-art computational methods through the user-friendly interface, resulting in publication-ready illustrations. We also provide an R package for more advanced use cases, such as bespoke analysis workflows.

Conclusions

PAWER is freely available at https://biit.cs.ut.ee/pawer.

Autoantibody Repertoire in APECED Patients Targets Two Distinct Subgroups of Proteins

High titer autoantibodies produced by B lymphocytes are clinically important features of many common autoimmune diseases. APECED patients with deficient autoimmune regulator (AIRE) gene collectively display a broad repertoire of high titer autoantibodies, including some which are pathognomonic for major autoimmune diseases. AIRE deficiency severely reduces thymic expression of gene-products ordinarily restricted to discrete peripheral tissues, and developing T cells reactive to those gene-products are not inactivated during their development. However, the extent of the autoantibody repertoire in APECED and its relation to thymic expression of self-antigens are unclear. We here undertook a broad protein array approach to assess autoantibody repertoire in APECED patients. Our results show that in addition to shared autoantigen reactivities, APECED patients display high inter-individual variation in their autoantigen profiles, which collectively are enriched in evolutionarily conserved, cytosolic and nuclear phosphoproteins. The APECED autoantigens have two major origins; proteins expressed in thymic medullary epithelial cells and proteins expressed in lymphoid cells. These findings support the hypothesis that specific protein properties strongly contribute to the etiology of B cell autoimmunity.

Infrared imaging of high density protein arrays

We propose in this paper that protein microarrays could be analysed by infrared imaging in place of enzymatic or fluorescence labelling.

Protein microarray-mediated detection of antienterovirus antibodies in serum

Objective

To utilize prokaryotic gene expression and protein microarray to develop and evaluate a sensitive, accurate protein microarray assay for detecting antienterovirus antibodies in serum samples from patients with hand, foot and mouth disease (HFMD). Enterovirus 71 (EV71) and coxsackievirus A16 (CA16), two common causative agents for HFMD, were used for assay development.

Methods

Serum was collected from patients with HFMD and healthy controls. EV71 and CA16 VP1 and VP3 genes were expressed in transfected Escherichia coli; the resultant VP1 and 3 proteins were used in a microarray assay for human serum EV71 and CA16 immunoglobulin (Ig) M and IgG. To validate the microarray assay, serum samples were tested for EV71 IgM using enzyme-linked immunosorbent assay (ELISA).

Results

Out of 50 patients with HFMD, EV71 IgM and CA16 IgM was detected in 80% and 44% of serum samples, respectively, using protein microarray, and EV71 IgM was detected in 78% of samples using ELISA. Protein microarray and ELISA showed 100% specificity for EV71-IgM detection.

Conclusion

The protein microarray assay developed in the present study shows potential as a sensitive technique for detecting EV71 IgM in serum samples from patients with HFMD.

Novel technologies and emerging biomarkers for personalized cancer immunotherapy

The culmination of over a century's work to understand the role of the immune system in tumor control has led to the recent advances in cancer immunotherapies that have resulted in durable clinical responses in patients with a variety of malignancies. Cancer immunotherapies are rapidly changing traditional treatment paradigms and expanding the therapeutic landscape for cancer patients. However, despite the current success of these therapies, not all patients respond to immunotherapy and even those that do often experience toxicities. Thus, there is a growing need to identify predictive and prognostic biomarkers that enhance our understanding of the mechanisms underlying the complex interactions between the immune system and cancer. Therefore, the Society for Immunotherapy of Cancer (SITC) reconvened an Immune Biomarkers Task Force to review state of the art technologies, identify current hurdlers, and make recommendations for the field. As a product of this task force, Working Group 2 (WG2), consisting of international experts from academia and industry, assembled to identify and discuss promising technologies for biomarker discovery and validation. Thus, this WG2 consensus paper will focus on the current status of emerging biomarkers for immune checkpoint blockade therapy and discuss novel technologies as well as high dimensional data analysis platforms that will be pivotal for future biomarker research. In addition, this paper will include a brief overview of the current challenges with recommendations for future biomarker discovery.

Novel technologies and emerging biomarkers for personalized cancer immunotherapy

The culmination of over a century’s work to understand the role of the immune system in tumor control has led to the recent advances in cancer immunotherapies that have resulted in durable clinical responses in patients with a variety of malignancies. Cancer immunotherapies are rapidly changing traditional treatment paradigms and expanding the therapeutic landscape for cancer patients. However, despite the current success of these therapies, not all patients respond to immunotherapy and even those that do often experience toxicities. Thus, there is a growing need to identify predictive and prognostic biomarkers that enhance our understanding of the mechanisms underlying the complex interactions between the immune system and cancer. Therefore, the Society for Immunotherapy of Cancer (SITC) reconvened an Immune Biomarkers Task Force to review state of the art technologies, identify current hurdlers, and make recommendations for the field. As a product of this task force, Working Group 2 (WG2), consisting of international experts from academia and industry, assembled to identify and discuss promising technologies for biomarker discovery and validation. Thus, this WG2 consensus paper will focus on the current status of emerging biomarkers for immune checkpoint blockade therapy and discuss novel technologies as well as high dimensional data analysis platforms that will be pivotal for future biomarker research. In addition, this paper will include a brief overview of the current challenges with recommendations for future biomarker discovery.

Epitope Mapping Using Peptide Microarray in Autoantibody Profiling

The use of peptide microarrays for epitope mapping of autoantibodies greatly facilitates the early diagnosis of allergic, cytotoxin-associated diseases and especially inflammatory diseases. A common approach to create the microarrays utilizes nitrocellulose-coated glass slides for peptide probe binding, which is based on surface adsorption. Advantages of this method include excellent peptide binding capacity and long-term stability. To ensure equal accessibility to all antibodies on the peptide microarray during epitope mapping, all probes are immobilized in a random manner, thus avoiding concentration-dependent effects on signal intensity.In this chapter, we provide a step-by-step protocol on how to construct the peptide microarrays and perform epitope mapping of autoantibodies using them. Finally we present a comparative approach for the evaluation of the data.

Primary Central Nervous System (CNS) Lymphoma B Cell Receptors Recognize CNS Proteins

Primary lymphoma of the CNS (PCNSL) is a diffuse large B cell lymphoma confined to the CNS. To elucidate its peculiar organ tropism, we generated recombinant Abs (recAbs) identical to the BCR of 23 PCNSLs from immunocompetent patients. Although none of the recAbs showed self-reactivity upon testing with common autoantigens, they recognized 1547 proteins present on a large-scale protein microarray, indicating polyreactivity. Interestingly, proteins (GRINL1A, centaurin-α, BAIAP2) recognized by the recAbs are physiologically expressed by CNS neurons. Furthermore, 87% (20/23) of the recAbs, including all Abs derived from IGHV4-34 using PCNSL, recognized galectin-3, which was upregulated on microglia/macrophages, astrocytes, and cerebral endothelial cells upon CNS invasion by PCNSL. Thus, PCNSL Ig may recognize CNS proteins as self-Ags. Their interaction may contribute to BCR signaling with sustained NF-κB activation and, ultimately, may foster tumor cell proliferation and survival. These data may also explain, at least in part, the affinity of PCNSL cells for the CNS.

Glycoprofiling as a novel tool in serological assays of systemic sclerosis: a comparative study with three bioanalytical methods

Systemic sclerosis (SSc) is an autoimmune disease seriously affecting patient's quality of life. The heterogeneity of the disease also means that identification and subsequent validation of biomarkers of the disease is quite challenging. A fully validated single biomarker for diagnosis, prognosis, disease activity and assessment of response to therapy is not yet available. The main aim of this study was to apply an alternative assay protocol to the immunoassay-based analysis of this disease by employment of sialic acid recognizing lectin Sambucus nigra agglutinin (SNA) to glycoprofile serum samples. To our best knowledge this is the first study describing direct lectin-based glycoprofiling of serum SSc samples. Three different analytical methods for glycoprofiling of serum samples relying on application of lectins are compared here from a bioanalytical point of view including traditional ELISA-like lectin-based method (ELLA), novel fluorescent lectin microarrays and ultrasensitive impedimetric lectin biosensors. Results obtained by all three bioanalytical methods consistently showed differences in the level of sialic acid present on glycoproteins, when serum from healthy people was compared to the one from patients having SSc. Thus, analysis of sialic acid content in human serum could be of a diagnostic value for future detection of SSc, but further work is needed to enhance selectivity of assays for example by glycoprofiling of a fraction of human serum enriched in antibodies for individual diagnostics.