Identification of Novel Biomarkers for Behcet Disease Diagnosis Using Human Proteome Microarray Approach

Altered polyunsaturated fatty acids and oxylipins profile in Behçet's disease

BACKGROUND/AIMS

Behçet's disease (BD) is an autoinflammatory disease of unknown etiopathogenesis. Oxylipins i.e., prostaglandins, leukotrienes, lipoxins, resolvins, and protectins are bioactive polyunsaturated fatty acids (PUFAs) derivatives involved in inflammatory response induction and resolution. The study aimed to determine the profile of selected PUFAs and oxylipins and to define a lipidomic signature for BD.

METHODS

A case-control study was conducted involving thirty-five patients with BD and thirty-five age and sex-matched healthy individuals as a control group. Selected plasma PUFAs and oxylipins were analyzed using a targeted LC-MS/MS method.

RESULTS

The lipidomic profile was different between the two groups. BD patients showed higher levels of oxylipins deriving from either the n-6-arachidonic acid (i.e., prostaglandin D2, E2, F2α, and 6-keto-F1α, thromboxane B2, leukotriene B4, E4 and F4, and 6-epi and 15-epi-lipoxin A4) or n-3 PUFAs (i.e., 18-hydroxyeicosapentaenoic acid, 7,17-dihydroxy docosapentaenoic acid, protectin X, and resolvin D5), but decreased levels of both n-3 and n-6 PUFAs. Multivariate analyses selected the combination of four mediators, i.e., docosapentaenoic acid, prostaglandin E2, thromboxane B2, and lipoxin A4 as an accurate lipidomic signature for BD.

CONCLUSION

The profile of PUFAs/oxylipins is altered in BD patients, characterized by increased pro-inflammatory and pro-resolving oxylipins. The findings suggest that oxylipin metabolism might be involved in BD pathophysiology and may represent a therapeutic target for the disease. Further research is required to examine the role of lipid mediators in BD.

Screening of Cancer-Specific Biomarkers for Hepatitis B-Related Hepatocellular Carcinoma Based on a Proteome Microarray

Hepatocellular carcinoma (HCC) is associated with one of the highest mortality rates among cancers, rendering its early diagnosis clinically invaluable. Serum biomarkers, specifically alpha-fetoprotein (AFP), represent the most promising and widely used diagnostic biomarkers for HCC. However, its detection rate is low in the early stages of HCC progression, and distinguishing specific false positives for other liver-related diseases, such as cirrhosis and acute hepatitis, remains challenging. Therefore, this study was conducted to identify biomarkers for hepatitis B (HBV)-related liver diseases by screening differentially expressed autoantibodies against tumor-associated antigens (TAAbs). We designed a large-scale multistage investigation, encompassing initial screening, HCC-focused, and ELISA validation cohorts to identify potential TAAbs in HBV-related liver diseases, spanning from healthy control (HC) individuals to patients with chronic hepatitis B (CHB), hepatitis B-related cirrhosis (HBC), and HCC, using protein microarray technology. The differential biological characteristics of TAAbs were analyzed using bioinformatics analysis. Validation of tumor-specific biomarkers for HCC was performed using ELISA. In the screening cohort, 547 candidate TAAbs were identified in the HCC group compared to those in the HC group. In the HCC-focused cohort, 64, 61, and 65 candidate TAAbs were identified in the CHB, HBC, and HCC groups, respectively, compared to those in the HC group. Thirty-four proteins exhibited continuously elevated expression from HCs to patients with CHB, HBC, and HCC. Among these, nine were identified as cancer-specific proteins. In the validation cohort, UBE2Z, CNOT3, and EID3 were correlated with liver function indicators in patients with hepatitis B-related HCC. Overall, UBE2Z, CNOT3, and EID3 emerged as cancer-specific biomarkers for HBV-related liver disease, providing a scientific basis for clinical application.

PhIP-Seq: methods, applications and challenges

Phage-immunoprecipitation sequencing (PhIP-Seq) technology is an innovative, high-throughput antibody detection method. It enables comprehensive analysis of individual antibody profiles. This technology shows great potential, particularly in exploring disease mechanisms and immune responses. Currently, PhIP-Seq has been successfully applied in various fields, such as the exploration of biomarkers for autoimmune diseases, vaccine development, and allergen detection. A variety of bioinformatics tools have facilitated the development of this process. However, PhIP-Seq technology still faces many challenges and has room for improvement. Here, we review the methods, applications, and challenges of PhIP-Seq and discuss its future directions in immunological research and clinical applications. With continuous progress and optimization, PhIP-Seq is expected to play an even more important role in future biomedical research, providing new ideas and methods for disease prevention, diagnosis, and treatment.

Phage Immunoprecipitation and Sequencing-a Versatile Technique for Mapping the Antibody Reactome

Characterizing the antibody reactome for circulating antibodies provide insight into pathogen exposure, allergies, and autoimmune diseases. This is important for biomarker discovery, clinical diagnosis, and prognosis of disease progression, as well as population-level insights into the immune system. The emerging technology phage display immunoprecipitation and sequencing (PhIP-seq) is a high-throughput method for identifying antigens/epitopes of the antibody reactome. In PhIP-seq, libraries with sequences of defined lengths and overlapping segments are bioinformatically designed using naturally occurring proteins and cloned into phage genomes to be displayed on the surface. These libraries are used in immunoprecipitation experiments of circulating antibodies. This can be done with parallel samples from multiple sources, and the DNA inserts from the bound phages are barcoded and subjected to next-generation sequencing for hit determination. PhIP-seq is a powerful technique for characterizing the antibody reactome that has undergone rapid advances in recent years. In this review, we comprehensively describe the history of PhIP-seq and discuss recent advances in library design and applications.

An autoantibody profile identified by human genome-wide protein arrays in rheumatoid arthritis

Precise diagnostic biomarkers of anticitrullination protein antibody (ACPA)-negative and early-stage RA are still to be improved. We aimed to screen autoantibodies in ACPA-negative patients and evaluated their diagnostic performance. The human genome-wide protein arrays (HuProt arrays) were used to define specific autoantibodies from the sera of 182 RA patients and 261 disease and healthy controls. Statistical analysis was performed with SPSS 17.0. In Phase I study, 51 out of 19,275 recombinant proteins covering the whole human genome were selected. In Phase II validation study, anti-ANAPC15 (anaphase promoting complex subunit 15) exhibited 41.8% sensitivity and 91.5% specificity among total RA patients. There were five autoantibodies increased in ACPA-negative RA, including anti-ANAPC15, anti-LSP1, anti-APBB1, anti-parathymosin, and anti-UBL7. Anti-parathymosin showed the highest prevalence of 46.2% (p = 0.016) in ACPA-negative early stage (<2 years) RA. To further improve the diagnostic efficacy, a prediction model was constructed with 44 autoantibodies. With increased threshold for RA calling, the specificity of the model is 90.8%, while the sensitivity is 66.1% (87.8% in ACPA-positive RA and 23.8% in ACPA-negative RA) in independent testing patients. Therefore, HuProt arrays identified RA-associated autoantibodies that might become possible diagnostic markers, especially in early stage ACPA-negative RA.

A Glimpse into Humoral Response and Related Therapeutic Approaches of Takayasu's Arteritis

Takayasu's arteritis (TAK) manifests as an insidiously progressive and debilitating form of granulomatous inflammation including the aorta and its major branches. The precise etiology of TAK remains elusive, with current understanding suggesting an autoimmune origin primarily driven by T cells. Notably, a growing body of evidence bears testimony to the widespread effects of B cells on disease pathogenesis and progression. Distinct alterations in peripheral B cell subsets have been described in individuals with TAK. Advancements in technology have facilitated the identification of novel autoantibodies in TAK. Moreover, emerging data suggest that dysregulated signaling cascades downstream of B cell receptor families, including interactions with innate pattern recognition receptors such as toll-like receptors, as well as co-stimulatory molecules like CD40, CD80 and CD86, may result in the selection and proliferation of autoreactive B cell clones in TAK. Additionally, ectopic lymphoid neogenesis within the aortic wall of TAK patients exhibits functional characteristics. In recent decades, therapeutic interventions targeting B cells, notably utilizing the anti-CD20 monoclonal antibody rituximab, have demonstrated efficacy in TAK. Despite the importance of the humoral immune response, a systematic understanding of how autoreactive B cells contribute to the pathogenic process is still lacking. This review provides a comprehensive overview of the biological significance of B cell-mediated autoimmunity in TAK pathogenesis, as well as insights into therapeutic strategies targeting the humoral response. Furthermore, it examines the roles of T-helper and T follicular helper cells in humoral immunity and their potential contributions to disease mechanisms. We believe that further identification of the pathogenic role of autoimmune B cells and the underlying regulation system will lead to deeper personalized management of TAK patients. We believe that further elucidation of the pathogenic role of autoimmune B cells and the underlying regulatory mechanisms holds promise for the development of personalized approaches to managing TAK patients.

Clinical Significance of Uncommon, Non-Clinical, and Novel Autoantibodies

Autoantibodies are a common mark of autoimmune reaction and their identification in the patients' serum, cerebrospinal fluid, or tissues is generally believed to represent diagnostic or prognostic biomarkers of autoimmune diseases or autoinflammatory conditions. Traditionally, autoantibody testing is an important part of the clinical examination of suspected patients, and in the absence of reliable T cell tests, characterization of autoantibody responses might be suitable in finding causes of specific autoimmune responses, their strength, and sometimes commencement of autoimmune disease. Autoantibodies are also useful for prognostic stratification in clinically diverse groups of patients if checked repeatedly. Antibody discoveries are continuing, with important consequences for verifying autoimmune mechanisms, diagnostic feasibility, and clinical management. Adding newly identified autoantibody-autoantigen pairs to common clinical laboratory panels should help upgrade and harmonize the identification of systemic autoimmune rheumatic disorders and other autoimmune conditions. Herein, we aim to summarize our current knowledge of uncommon and novel autoantibodies in the context of discussing their validation, diagnostic practicability, and clinical relevance. The regular updates within the field are important and well justified.

Autoimmune diseases: targets, biology, and drug discovery

Autoimmune diseases (AIDs) arise from a breakdown in immunological self-tolerance, wherein the adaptive immune system mistakenly attacks healthy cells, tissues and organs. AIDs impose excessive treatment costs and currently rely on non-specific and universal immunosuppression, which only offer symptomatic relief without addressing the underlying causes. AIDs are driven by autoantigens, targeting the autoantigens holds great promise in transforming the treatment of these diseases. To achieve this goal, a comprehensive understanding of the pathogenic mechanisms underlying different AIDs and the identification of specific autoantigens are critical. In this review, we categorize AIDs based on their underlying causes and compile information on autoantigens implicated in each disease, providing a roadmap for the development of novel immunotherapy regimens. We will focus on type 1 diabetes (T1D), which is an autoimmune disease characterized by irreversible destruction of insulin-producing β cells in the Langerhans islets of the pancreas. We will discuss insulin as possible autoantigen of T1D and its role in T1D pathogenesis. Finally, we will review current treatments of TID and propose a potentially effective immunotherapy targeting autoantigens.

Proteome microarray identifies autoantibody biomarkers for diagnosis of hepatitis B-related hepatocellular carcinoma

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) has the highest mortality rate among malignant tumors worldwide. This study aimed to analyze the biological characteristics of serum proteins in hepatitis B (HBV)-related liver diseases, identify diagnostic biomarkers for HBV-infected HCC, and provide a scientific basis for its prevention and treatment.

MATERIALS AND METHODS

We used HuProt arrays to identify candidate biomarkers for HBV-related liver diseases and verified the differential biomarkers by using an HCC-focused array. The biological characteristics of serum proteins were analyzed via bioinformatics. Serum biomarkers levels were validated by ELISA.

RESULTS

We identified 547 differentially expressed proteins from HBV-infected HCC in a screening cohort. After analyzing the biological characteristics of serum proteins, we identified 10 potential differential autoantibodies against tumor-associated antigens (TAAbs) and a candidate biomarker panel (APEX2, RCSD1, and TP53) for the diagnosis of HBV-associated HCC with 61.9% sensitivity and 81.7% specificity in an HCC-focused array validation cohort. Finally, the protein levels and diagnostic capability of the biomarker panel were confirmed in a large-sample validation cohort, and this panel was found to be superior to alpha-fetoprotein, the standard hallmark for the diagnosis of HCC.

CONCLUSION

The APEX2, RCSD1, and TP53 biomarker panels could be used for the diagnosis of HBV-associated HCC, providing a scientific basis for clinical practice.

Discovery and characterization of cross-reactive intrahepatic antibodies in severe alcoholic hepatitis

The pathogenesis of antibodies in severe alcoholic hepatitis (SAH) remains unknown. We analyzed immunoglobulins (Ig) in explanted livers from SAH patients (n=45) undergoing liver transplantation and tissues from corresponding healthy donors (HD, n=10) and found massive deposition of IgG and IgA isotype antibodies associated with complement fragment C3d and C4d staining in ballooned hepatocytes in SAH livers. Ig extracted from SAH livers, but not patient serum exhibited hepatocyte killing efficacy. Employing human and Escherichia coli K12 proteome arrays, we profiled the antibodies extracted from explanted SAH, livers with other diseases, and HD livers. Compared with their counterparts extracted from livers with other diseases and HD, antibodies of IgG and IgA isotypes were highly accumulated in SAH and recognized a unique set of human proteins and E. coli antigens. Further, both Ig- and E. coli-captured Ig from SAH livers recognized common autoantigens enriched in several cellular components including cytosol and cytoplasm (IgG and IgA), nucleus, mitochondrion, and focal adhesion (IgG). Except IgM from primary biliary cholangitis livers, no common autoantigen was recognized by Ig- and E. coli-captured Ig from livers with other diseases. These findings demonstrate the presence of cross-reacting anti-bacterial IgG and IgA autoantibodies in SAH livers.

Behçet's syndrome: recent advances to aid diagnosis

Behçet's syndrome is a recurring inflammatory multiorgan disorder affecting the skin, mucosa, eyes, joints, stomach, and central nervous system. Behçet's syndrome epidemiology varies greatly among populations (0.64-420/100,000), and Behçet's syndrome has gained increasing international acclaim in the recent 50 years due to raising awareness of the syndrome, although it is rare in most population. In addition to the unclear etiology of the syndrome, the diagnosis of Behçet's syndrome is complicated by a vague clinical presentation, phenotypic heterogeneity and/or incomplete representation, and the lack of any specific laboratory, radiographic, or histological findings. There exists a dire need to elucidate factors that contribute to disease pathogenesis and/or are associated with clinical features of Behçet's syndrome and the classification of different forms of the syndrome. The identification of such molecular, cellular, and/or clinical factors are crucial for timely diagnosis and efficacious management of Behçet's syndrome. We discuss recent advances in the clinical diagnosis of Behçet's syndrome and related contributions of genetics, epigenetics, microbiome, inflammasomes, and autoantibodies to the improved diagnosis, management, and understanding of Behçet's syndrome.

Risk factors, clinical features and treatment of Behçet's disease uveitis

Behçet's disease is a systemic vasculitis frequently associated with intraocular inflammation. Recent findings identified independent clinical clusters in Behçet's disease, each involving distinct combinations of affected organs. Ocular Behçet's disease, mainly manifested as uveitis, is characterized as an independent cluster with a low likelihood of association with other system involvements, such as intestinal, cardiovascular, or central nervous system. A prevailing theory suggests that the pathogenesis of the disease is multifactorial, where a variety of genetic and infectious agents may interact with each other to cause the disease. Among sporadic cases, the human leukocyte antigen (HLA) genes, including HLA-B51, HLA-A26, HLA-B15, and HLA-B5701, have been found to be a key component conferring genetic susceptibility. Outside the HLA region, a set of susceptibility variants are identified, closely related to interleukin (IL)-23/IL-17 pathway, tumor necrosis factor (TNF) signaling, and pattern recognition receptor systems. Microbial infections, such as Streptococcus sanguinis, Mycobacterium tuberculosis, and Herpes simplex virus (HSV), are linked to play the triggering of disease in immunogenetically predisposed individuals. Clinically, due to the notable relapsing-remitting course of ocular Behçet's disease, the prevention of recurrent attack would be the primary treatment goal. Combination of corticosteroids and immunomodulatory drugs, such as anti-TNF agents, interferon, and conventional immunosuppressants (e.g. cyclosporine, azathioprine), have been the mainstream regimen for the disease. Future research may focus on comparing the effectiveness of immunomodulatory drugs and identifying the most suitable subgroups for a specific drug on the basis of the knowledge of the molecular heterogeneity of the disease.

Identification of Anti-SNRPA as a Novel Serological Biomarker for Systemic Sclerosis Diagnosis

Systemic sclerosis (SSc) is a systemic autoimmune disorder that leads to vasculopathy and tissue fibrosis. A lack of reliable biomarkers has been a challenge for clinical diagnosis of the disease. We employed a protein array-based approach to identify and validate SSc-specific autoantibodies. Phase I involved profiled autoimmunity using human proteome microarray (HuProt arrays) with 90 serum samples: 40 patients with SSc, 30 patients diagnosed with autoimmune diseases, and 20 healthy subjects. In Phase II, we constructed a focused array with candidates identified antigens and used this to profile a much larger cohort comprised of serum samples. Finally, we used a western blot analysis to validate the serum of validated proteins with high signal values. Bioinformatics analysis allowed us to identify 113 candidate autoantigens that were significantly associated with SSc. This two-phase strategy allowed us to identify and validate anti-small nuclear ribonucleoprotein polypeptide A (SNRPA) as a novel SSc-specific serological biomarker. The observed positive rate of anti-SNRPA antibody in patients with SSc was 11.25%, which was significantly higher than that of any disease control group (3.33%) or healthy controls (1%). In conclusion, anti-SNRPA autoantibody serves as a novel biomarker for SSc diagnosis and may be promising for clinical applications.

Human antibody profiling technologies for autoimmune disease

Autoimmune diseases are caused by the break-down in self-tolerance mechanisms and can result in the generation of autoantibodies specific to human antigens. Human autoantigen profiling technologies such as solid surface arrays and display technologies are powerful high-throughput technologies utilised to discover and map novel autoantigens associated with disease. This review compares human autoantigen profiling technologies including the application of these approaches in chronic and post-infectious autoimmune disease. Each technology has advantages and limitations that should be considered when designing new projects to profile autoantibodies. Recent studies that have utilised these technologies across a range of diseases have highlighted marked heterogeneity in autoantibody specificity between individuals as a frequent feature. This individual heterogeneity suggests that epitope spreading maybe an important mechanism in the pathogenesis of autoimmune disease in general and likely contributes to inflammatory tissue damage and symptoms. Studies focused on identifying autoantibody biomarkers for diagnosis should use targeted data analysis to identify the rarer public epitopes and antigens, common between individuals. Thus, utilisation of human autoantigen profiling technology, combined with different analysis approaches, can illuminate both pathogenesis and biomarker discovery.

Serum Interleukin-36 α as a Candidate Biomarker to Distinguish Behçet's Syndrome and Psoriatic Arthritis

Behçet's syndrome (BS) is a rare systemic vasculitis characterized by different clinical manifestations. As no specific laboratory tests exist, the diagnosis relies on clinical criteria, and the differential diagnosis with other inflammatory diseases can be challenging. Indeed, in a relatively small proportion of patients, BS symptoms include only mucocutaneous, articular, gastrointestinal, and non-typical ocular manifestations, which are frequently found also in psoriatic arthritis (PsA). We investigate the ability of serum interleukin (IL)-36α-a pro-inflammatory cytokine involved in cutaneous and articular inflammatory diseases-to differentiate BS from PsA. A cross-sectional study was performed on 90 patients with BS, 80 with PsA and 80 healthy controls. Significantly lower IL-36α concentrations were found in patients with BS as compared to PsA, although in both groups IL-36α was significantly increased compared to healthy controls. An empirical cut-off of 420.6 pg/mL displayed a specificity of 0.93, with a sensitivity of 0.70 (AUC 0.82) in discriminating PsA from BS. This cut-off displayed a good diagnostic performance also in BS patients lacking highly specific BS manifestations. Our results indicate that IL-36α might be involved in the pathogenesis of both BS and PsA, and might be a candidate biomarker to support the differential diagnosis of BS.

Discovery and characterization of cross-reactive intrahepatic antibodies in severe alcoholic hepatitis

The pathogenesis of antibodies in severe alcoholic hepatitis (SAH) remains unknown. We sought to determine if there was antibody deposition in SAH livers and whether antibodies extracted from SAH livers were cross-reactive against both bacterial antigens and human proteins. We analyzed immunoglobulins (Ig) in explanted livers from SAH patients (n=45) undergoing liver transplantation and tissue from corresponding healthy donors (HD, n=10) and found massive deposition of IgG and IgA isotype antibodies associated with complement fragment C3d and C4d staining in ballooned hepatocytes in SAH livers. Ig extracted from SAH livers, but not patient serum exhibited hepatocyte killing efficacy in an antibody-dependent cell-mediated cytotoxicity (ADCC) assay. Employing human proteome arrays, we profiled the antibodies extracted from explanted SAH, alcoholic cirrhosis (AC), nonalcoholic steatohepatitis (NASH), primary biliary cholangitis (PBC), autoimmune hepatitis (AIH), hepatitis B virus (HBV), hepatitis C virus (HCV) and HD livers and found that antibodies of IgG and IgA isotypes were highly accumulated in SAH and recognized a unique set of human proteins as autoantigens. The use of an E. coli K12 proteome array revealed the presence of unique anti- E. coli antibodies in SAH, AC or PBC livers. Further, both Ig and E. coli captured Ig from SAH livers recognized common autoantigens enriched in several cellular components including cytosol and cytoplasm (IgG and IgA), nucleus, mitochondrion and focal adhesion (IgG). Except IgM from PBC livers, no common autoantigen was recognized by Ig and E. coli captured Ig from AC, HBV, HCV, NASH or AIH suggesting no cross-reacting anti- E. coli autoantibodies. The presence of cross-reacting anti-bacterial IgG and IgA autoantibodies in the liver may participate in the pathogenesis of SAH.

Finding the Needle in the Haystack: Serological and Urinary Biomarkers in Behçet's Disease: A Systematic Review

Urinary and serological markers play an essential role in the diagnostic process of autoimmune diseases. However, to date, specific and reliable biomarkers for diagnosing Behçet's disease (BD) are still lacking, negatively affecting the management of these patients. To analyze the currently available literature on serological and urinary BD biomarkers investigated in the last 25 years, we performed a systematic literature review using the Population, Intervention, Comparison, and Outcomes (PICO) strategy. One hundred eleven studies met the eligibility criteria (6301 BD patients, 5163 controls). Most of them were retrospective, while five (5%) were prospective. One hundred ten studies (99%) investigated serological biomarkers and only two (2%) focused on urinary biomarkers. One hundred three studies (93%) explored the diagnostic potential of the biomolecules, whereas sixty-two (56%) tested their effect on disease activity monitoring. Most articles reported an increase in inflammatory markers and pro-oxidant molecules, with a decrease in antioxidants. Promising results have been shown by the omics sciences, offering a more holistic approach. Despite the vast number of investigated markers, existing evidence indicates a persistent gap in BD diagnostic/prognostic indices. While new steps have been taken in the direction of pathogenesis and disease monitoring, international efforts for the search of a diagnostic marker for BD are still needed.

Identification of novel serological autoantibodies in Chinese prostate cancer patients using high-throughput protein arrays

Autoantibody (AAb) has a prominent role in prostate cancer (PCa), with few studies profiling the AAb landscape in Chinese patients. Therefore, the AAb landscape in Chinese patients was characterized using protein arrays. First, in the discovery phase, Huprot arrays outlined autoimmune profiles against ~ 21,888 proteins from 57 samples. In the verification phase, the PCa-focused arrays detected 25 AAbs selected from the discovery phase within 178 samples. Then, PCa was detected using a backpropagation artificial neural network (BPANN) model. In the validation phase, an enzyme-linked immunosorbent assay (ELISA) was used to validate four AAb biomarkers from 196 samples. Huprot arrays profiled distinct PCa, benign prostate diseases (BPD), and health AAb landscapes. PCa-focused array depicted that IFIT5 and CPOX AAbs could distinguish PCa from health with an area under curve (AUC) of 0.71 and 0.70, respectively. PAH and FCER2 AAbs had AUCs of 0.86 and 0.88 in discriminating PCa from BPD. Particularly, PAH AAb detected patients in the prostate-specific antigen (PSA) gray zone with an AUC of 0.86. Meanwhile, the BPANN model of 4-AAb (IFIT5, PAH, FCER2, CPOX) panel attained AUC of 0.83 among the two cohorts for detecting patients with gray-zone PSA. In the validation cohort, the IFIT5 AAb was upregulated in PCa compared to health (p < 0.001). Compared with BPD, PAH and FCER2 AAbs were significantly elevated in PCa (p = 0.012 and 0.039). We have demonstrated the first extensive profiling of autoantibodies in Chinese PCa patients, identifying novel diagnostic AAb biomarkers, especially for identification of gray-zone-PSA patients.

Diagnostic value of anti-Kaiso autoantibody in axial spondyloarthritis

Objective

Axial spondyloarthritis (axSpA) is a chronic rheumatic disease predominantly characterized by inflammation and progressive structural damage. Patients are often diagnosed very late, which delays the optimal treatment period. Early diagnosis of axSpA, especially non-radiographic axSpA (nr-axSpA), remains a major challenge. This study aimed to investigate the diagnostic value of anti-Kaiso autoantibodies in axSpA and their correlation with clinical disease indicators.

Methods

Two pooled serum samples (seven patients with nr-axSpA and seven healthy controls) were profiled using HuProt arrays to investigate the diagnostic value of autoantibodies in nr-axSpA. Levels of anti-Kaiso autoantibodies in patients with axSpA and controls were determined using the Meso Scale Discovery assay system. Receiver operating characteristic curve analysis was performed to evaluate the diagnostic performance of anti-Kaiso autoantibodies in axSpA. Pearson's correlation was used to assess the correlation between anti-Kaiso autoantibodies and clinical parameters.

Results

Seven candidate autoantibodies were present in the serum of patients with nr-axSpA. The levels of anti-Kaiso autoantibodies were significantly higher in the nr-axSpA group than in the other groups. It can differentiate nr-axSpA from ankylosing spondylitis (AS), healthy controls, and rheumatoid arthritis. The level of early-stage AS among patients with nr-axSpA decreased when they progressed to the late stage. Of all patients with axSpA, serum anti-Kaiso autoantibody levels were positively correlated with the C-reactive protein level and the Bath Ankylosing Spondylitis Disease Activity Index score and negatively correlated with disease duration.

Conclusion

Anti-Kaiso autoantibody may be a valuable diagnostic biomarker for early-stage AS in the nr-axSpA period and may be a potential therapeutic target.

Development of a protein microarray for profiling circulating autoantibodies in human diseases

PURPOSE

To develop a robust microarray platform to detect thousands of serological autoantibodies (AAbs) simultaneously in different diseases.

EXPERIMENTAL DESIGN

An AAbMap microarray was prepared by printing a total of 4032 purified His-tagged human proteins and peptide probes on a chemically-modified slide. The sensitivity, dynamic range, and the inter- and intra-array reproducibility of the AAb microarray were then systematically tested and optimized. Finally, the large-scale profiling of AAbs in the serum of patients with different human diseases using the AAbMap microarray was demonstrated.

RESULTS

The dynamic range of antibody (Ab) detection was 2 to 3 orders of magnitude with the lowest limit of detection (LOD) of 68 pg/mL. The intra-array (r) correlation of duplicate spots was 1.00, whereas the inter-array correlations between different arrays and batches were 0.99 and 0.97 to 0.98, respectively. Notably, 132, 266, 171, and 84 AAbs were detected in pooled serum from healthy controls (HCs) or patients with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), or lung cancer (LC), respectively. These AAbs included antibodies that target well-known disease biomarkers, such as anti-cyclic citrullinated peptide, anti-ribonucleoprotein, and anti-nucleosome.

CONCLUSIONS AND CLINICAL RELEVANCE

We developed a microarray platform to measure thousands of serological AAbs simultaneously with high sensitivity and reproducibility. The array can help study autoimmunity and complement genomics, proteomics, and metabolomics data for systematic investigations of human diseases.

Current advances in antibody-based serum biomarker studies: From protein microarray to phage display

PURPOSE

This review aims to summarize the technological advances in the field of antibody-based biomarker studies by proteome microarray and phage display. In addition, the possible development directions of this field are also discussed.

EXPERIMENTAL DESIGN

We have focused on the antibody profiling by proteome microarray and phage display, including the technological advances, the tools/resources constructed, and the characteristics of both platforms.

RESULTS

With the help of tools/resources and technological advances in proteome microarray and phage display, the efficiency of profiling antibody-based biomarkers in serum samples has been greatly improved.

CONCLUSIONS

In the past few years, proteome microarray and phage display, especially the latter one, have already demonstrated their capacity and efficiency for biomarker identification. In the near future, we believe that more antibody-based biomarkers could be identified, and some of them could eventually be developed into real clinical applications.

Multiple rather than specific autoantibodies were identified in irritable bowel syndrome with HuProt™ proteome microarray

Immune activation and several autoantibodies might be involved in the pathophysiology of irritable bowel syndrome (IBS). We aimed to identify serum biomarkers for IBS by HuProt™ microarray. IBS patients met Rome III criteria were enrolled. Control groups included healthy controls (HCs) and disease controls (DCs). In stage I, we profiled sera from IBS and control groups with HuProt™ microarrays. Based on significant different proteins in stage I, IBS focused microarrays were constructed and validated in a larger cohort in stage II, then decision tree models were generated to establish a combination of biomarkers. In stage III, 4 purified proteins were verified by ELISA. Finally, we analyzed the correlation of autoantibodies with symptoms. In stage I, we identified 47 significant different proteins including 8 autoantibodies of IgG, 2 of IgA between IBS and HCs; 13 autoantibodies of IgG, 13 of IgA between IBS and DCs. In stage II, we found the positive rates of 14 IgG and IgA autoantibodies in IBS were significantly higher than HCs. Five autoantibodies of IgG and 7 IgA were comprehensively involved in differentiating IBS and HCs with the sensitivity and specificity to diagnose IBS as 40%–46.7% and 79.4%–86.3%. The median optical density value of ELAVL4 (IgG) and PIGP (IgA) were significantly higher in IBS than HCs. Parts of autoantibodies above were related to IBS symptoms. We found a combination of autoantibodies to differentiate IBS with HCs, but no specific autoantibodies could serve as serum biomarkers for IBS.

The learning curve of laparoscopic, robot-assisted and transanal total mesorectal excisions: a systematic review

BACKGROUND

The standard treatment of rectal carcinoma is surgical resection according to the total mesorectal excision principle, either by open, laparoscopic, robot-assisted or transanal technique. No clear consensus exists regarding the length of the learning curve for the minimal invasive techniques. This systematic review aims to provide an overview of the current literature regarding the learning curve of minimal invasive TME.

METHODS

A systematic literature search was performed. PubMed, Embase and Cochrane Library were searched for studies with the primary or secondary aim to assess the learning curve of either laparoscopic, robot-assisted or transanal TME for rectal cancer. The primary outcome was length of the learning curve per minimal invasive technique. Descriptive statistics were used to present results and the MINORS tool was used to assess risk of bias.

RESULTS

45 studies, with 7562 patients, were included in this systematic review. Length of the learning curve based on intraoperative complications, postoperative complications, pathological outcomes, or a composite endpoint using a risk-adjusted CUSUM analysis was 50 procedures for the laparoscopic technique, 32-75 procedures for the robot-assisted technique and 36-54 procedures for the transanal technique. Due to the low quality of studies and a high level of heterogeneity a meta-analysis could not be performed. Heterogeneity was caused by patient-related factors, surgeon-related factors and differences in statistical methods.

CONCLUSION

Current high-quality literature regarding length of the learning curve of minimal invasive TME techniques is scarce. Available literature suggests equal lengths of the learning curves of laparoscopic, robot-assisted and transanal TME. Well-designed studies, using adequate statistical methods are required to properly assess the learning curve, while taking into account patient-related and surgeon-related factors.

Predictive Factors of Severe Behçet's disease: A Longitudinal, Prospective Cohort Followed Between 1981-2020

INTRODUCTION

Behçet's disease (BD) is a systemic vasculitis of unknown cause. The spectrum of the disease ranges from mucocutaneous manifestations to other organ diseases with relevant morbidity. Associations between disease severity and male sex, earlier age at onset, and the presence of erythema nodosum have been described.

OBJECTIVES

To evaluate clinical factors associated with manifestations of severe disease in a single-center cohort.

METHODS

A longitudinal, prospective, unicentric cohort study with patients followed in a specialized outpatient clinic between 1981 and 2020. Severe BD was defined as a Krause total clinical severity score >4 points.

RESULTS

We included 243 patients, of whom 31% were male, with an average follow-up time of 14.6 years. Regarding organ manifestations, all patients had mucous manifestations (N=243, 100%), 133 (55%) skin, 104 (43%) joint, 71 (29%) ocular, 48 (20%) vascular, 47 (19%) neurological, 22 (9%) gastrointestinal and 1 (0.4%) cardiac involvement by BD. One hundred fifty-six (64%) patients were classified as having severe BD. Severe BD was more frequent in men (OR=2.004, p=0.024), increasing with age (OR=1.021 per year, p=0.037), in the presence of skin manifestations (OR=4.711, p<0.001), specifically erythema nodosum (OR=8.381, p<0.001), and pseudofolliculitis (OR=2.910, p<0.001). In the multivariate model, variables independently associated with severe BD were male gender (Adjusted OR=1.961, p=0.047), erythema nodosum (Adjusted OR=8.561, p<0.001) and pseudofolliculitis (Adjusted OR=2.372, p=0.007).

DISCUSSION

Male gender, erythema nodosum, and pseudofolliculitis were independently associated with severe BD forms and therefore should serve as warning signs to the clinician.

Evaluating the Immunopathogenesis of Diabetes After Acute Pancreatitis in the Diabetes RElated to Acute Pancreatitis and Its Mechanisms Study: From the Type 1 Diabetes in Acute Pancreatitis Consortium

ABSTRACT

The association between acute pancreatitis (AP) and diabetes mellitus (DM) has long been established, with the initial descriptions of AP patients presenting with DM after a bout of AP published in the 1940s and 50s. However, the potential mechanisms involved, particularly those components related to the immune system, have not been well defined. The Diabetes RElated to Acute pancreatitis and its Mechanisms (DREAM) study is a multicenter clinical study designed to understand the frequency and phenotype of DM developing after AP. This article describes one objective of the DREAM study: to determine the immunologic mechanisms of DM after AP, including the contribution of β-cell autoimmunity. This component of the study will assess the presence of islet autoimmunity, as well as the magnitude and kinetics of the innate and adaptive immune response at enrollment and during longitudinal follow-up after 1 or more episodes of AP. Finally, DREAM will evaluate the relationship between immune features, DM development, and pancreatitis etiology and severity.

The autoimmune signature of hyperinflammatory multisystem inflammatory syndrome in children

Multisystem inflammatory syndrome in children (MIS-C) manifests as a severe and uncontrolled inflammatory response with multiorgan involvement, occurring weeks after SARS-CoV-2 infection. Here, we utilized proteomics, RNA sequencing, autoantibody arrays, and B cell receptor (BCR) repertoire analysis to characterize MIS-C immunopathogenesis and identify factors contributing to severe manifestations and intensive care unit admission. Inflammation markers, humoral immune responses, neutrophil activation, and complement and coagulation pathways were highly enriched in MIS-C patient serum, with a more hyperinflammatory profile in severe than in mild MIS-C cases. We identified a strong autoimmune signature in MIS-C, with autoantibodies targeted to both ubiquitously expressed and tissue-specific antigens, suggesting autoantigen release and excessive antigenic drive may result from systemic tissue damage. We further identified a cluster of patients with enhanced neutrophil responses as well as high anti-Spike IgG and autoantibody titers. BCR sequencing of these patients identified a strong imprint of antigenic drive with substantial BCR sequence connectivity and usage of autoimmunity-associated immunoglobulin heavy chain variable region (IGHV) genes. This cluster was linked to a TRBV11-2 expanded T cell receptor (TCR) repertoire, consistent with previous studies indicating a superantigen-driven pathogenic process. Overall, we identify a combination of pathogenic pathways that culminate in MIS-C and may inform treatment.

Frenemies within: An Endocarditis Case in Behçet's Disease

A 57-year female patient diagnosed with Behçet's disease, on azathioprine, was noticed to have at a routine examination antinuclear and antiphospholipid antibodies. An overlapping lupus-like syndrome was diagnosed; hydroxychloroquine and aspirin were added. Three years later, the patient presented with dyspnea and sweating, with no fever. A cardiac bruit was noted; a giant vegetation was detected by echocardiography. Laboratory revealed severe thrombocytopenia, antiphospholipid antibodies and low complement. Blood cultures were positive for Abiotrophia defectiva serology and also revealed a chronic Coxiella burnetii infection. Antibiotic therapy, low-dose anticoagulation and control of the underlying disease mildly improved the platelet count, which fully recovered only after cardiac valve replacement. However, the Behçet's disease, initially quiescent, flared after the therapy of infections. We discuss potential links between Behçet's disease and the occurrence of antinuclear and antiphospholipid antibodies and Coxiella endocarditis in this setting. We also highlight the differences between the endocarditis in Behçet's disease, antiphospholipid syndrome, Coxiella burnetii and Abiotrophia defectiva infection, respectively. Intracellular infections may modify the presentation of autoimmune diseases. Confounding clinical features of Coxiella persistent infection and non-bacterial thrombotic endocarditis in Behçet's disease warrant further insight.

Microarray-based selection of a serum biomarker panel that can discriminate between latent and active pulmonary TB

Bacterial culture of M. tuberculosis (MTB), the causative agent of tuberculosis (TB), from clinical specimens is the gold standard for laboratory diagnosis of TB, but is slow and culture-negative TB cases are common. Alternative immune-based and molecular approaches have been developed, but cannot discriminate between active TB (ATB) and latent TB (LTBI). Here, to identify biomarkers that can discriminate between ATB and LTBI/healthy individuals (HC), we profiled 116 serum samples (HC, LTBI and ATB) using a protein microarray containing 257 MTB secreted proteins, identifying 23 antibodies against MTB antigens that were present at significantly higher levels in patients with ATB than in those with LTBI and HC (Fold change > 1.2; p < 0.05). A 4-protein biomarker panel (Rv0934, Rv3881c, Rv1860 and Rv1827), optimized using SAM and ROC analysis, had a sensitivity of 67.3% and specificity of 91.2% for distinguishing ATB from LTBI, and 71.2% sensitivity and 96.3% specificity for distinguishing ATB from HC. Validation of the four candidate biomarkers in ELISA assays using 440 serum samples gave consistent results. The promising sensitivity and specificity of this biomarker panel suggest it merits further investigation for its potential as a diagnostic for discriminating between latent and active TB.

Correlation of clinical signs and symptoms of Behçet's disease with platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR)

Behçet's disease (BD) is a chronic disorder that involves multiple organs and is pathologically considered as a form of vasculitis. The current study aims to assess the metric properties of platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) in assessing BD disease activity. Three-hundred-nineteen patients with BD were enrolled in this cross-sectional study. Demographic and epidemiological data, including IBDDAM, time since the onset, and medication and manifestation history were recorded. Complete blood counts (CBC), NLR, and PLR were assessed by analyzing blood samples. On the last visit, patients were assessed for active manifestations of disease. IBDDAM and ocular IBDAAM scores were calculated for activity of disease in each patient. Both PLR and NLR were higher in patients with active BD (Mann-Whitney U test, p-value < 0.05). Patients with active ocular manifestation had significantly higher NLR and PLR (Mann-Whitney U test, p-value < 0.05). These ratios, however, were not associated with other active BD manifestations. A value of NLR > 2.58 had 46% sensitivity and 85% specificity for the diagnosis of active ocular manifestations (AUC: 0.690). NLR had a significant, though, weak positive correlation with IBDDAM (Spearman's rho = 0.162; p-value < 0.05) and ocular IBDDAM (Spearman's rho = 0.159; p-value < 0.05). Active Behçet's presented with higher NLR and PLR ratios; however, there was only a modest correlation between NLR and BD activity (IBDDAM score). Also, NLR and PLR have significant relationship with ocular features of BD patients.

Predictive Factors of Severe Behçet's disease: A Longitudinal, Prospective Cohort Followed Between 1981-2020

INTRODUCTION

Behçet's disease (BD) is a systemic vasculitis of unknown cause. The spectrum of the disease ranges from mucocutaneous manifestations to other organ diseases with relevant morbidity. Associations between disease severity and male sex, earlier age at onset, and the presence of erythema nodosum have been described.

OBJECTIVES

To evaluate clinical factors associated with manifestations of severe disease in a single-center cohort.

METHODS

A longitudinal, prospective, unicentric cohort study with patients followed in a specialized outpatient clinic between 1981 and 2020. Severe BD was defined as a Krause total clinical severity score >4 points.

RESULTS

We included 243 patients, of whom 31% were male, with an average follow-up time of 14.6 years. Regarding organ manifestations, all patients had mucous manifestations (N=243, 100%), 133 (55%) skin, 104 (43%) joint, 71 (29%) ocular, 48 (20%) vascular, 47 (19%) neurological, 22 (9%) gastrointestinal and 1 (0.4%) cardiac involvement by BD. One hundred fifty-six (64%) patients were classified as having severe BD. Severe BD was more frequent in men (OR=2.004, p=0.024), increasing with age (OR=1.021 per year, p=0.037), in the presence of skin manifestations (OR=4.711, p<0.001), specifically erythema nodosum (OR=8.381, p<0.001), and pseudofolliculitis (OR=2.910, p<0.001). In the multivariate model, variables independently associated with severe BD were male gender (Adjusted OR=1.961, p=0.047), erythema nodosum (Adjusted OR=8.561, p<0.001) and pseudofolliculitis (Adjusted OR=2.372, p=0.007).

DISCUSSION

Male gender, erythema nodosum, and pseudofolliculitis were independently associated with severe BD forms and therefore should serve as warning signs to the clinician.

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.

The study of antiviral drugs targeting SARS-CoV-2 nucleocapsid and spike proteins through large-scale compound repurposing

Contributing to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) clinical treatment, a drug library encompassing approximately 3,142 clinical-stage or FDA-approved small molecules is profiled to identify the candidate therapeutic inhibitors targeting nucleocapsid protein (N) and spike protein (S) of SARS-CoV-2. 16 screened candidates with higher binding affinity are evaluated via virtual screening. Comparing to those under trial/temporarily used antivirus drugs (i.e., umifenovir, lopinavir), ceftriaxone, cefotaxime, and cefuroxime show higher binding affinities to the N-terminal domain of N protein (N-NTD), C-terminal domain of N protein (N-CTD), and receptor-binding domain of S protein (S-RBD). Cefotaxime and cefuroxime have high binding affinities towards S-RBD with angiotensin-converting enzyme 2 (ACE2) complex via influence the critical interface sites at the interface of S-RBD (Arg403, Tyr453, Trp495, Gly496, Phe497, Asn501and Tyr505) and ACE2 (Asn33, His34, Glu37, Asp38, Lys353, Ala386, Ala387, Gln388, Pro389, Phe390 and Arg393) complex.

Identification of Novel Serological Autoantibodies in Takayasu Arteritis Patients Using HuProt Arrays

To identify novel autoantibodies of Takayasu arteritis (TAK) using HuProt array-based approach, a two-phase approach was adopted. In Phase I, serum samples collected from 40 TAK patients, 15 autoimmune disease patients, and 20 healthy subjects were screened to identify TAK-specific autoantibodies using human protein (HuProt) arrays. In phase II, the identified candidate autoantibodies were validated with TAK-focused arrays using an additional cohort comprised of 109 TAK patients, 110 autoimmune disease patients, and 96 healthy subjects. Subsequently, the TAK-specific autoantibodies validated in phase II were further confirmed using western blot analysis. We identified and validated eight autoantibodies as potential TAK-specific diagnostic biomarkers, including anti-SPATA7, -QDPR, -SLC25A2, -PRH2, -DIXDC1, -IL17RB, -ZFAND4, and -NOLC1 antibodies, with AUC of 0.803, 0.801, 0.780, 0.696, 0.695, 0.678, 0.635, and 0.613, respectively. SPATA7 could distinguish TAK from healthy and disease controls with 73.4% sensitivity at 85.4% specificity, while QDPR showed 71.6% sensitivity at 86.4% specificity. SLC25A22 showed the highest sensitivity of 80.7%, but at lower specificity of 67.0%. In addition, PRH2, IL17RB, and NOLC1 showed good specificities of 88.3%, 85.9%, and 86.9%, respectively, but at lower sensitivities (<50%). Finally, DIXDC1 and ZFAND4 showed moderate performance as compared with the other autoantibodies. Using a decision tree model, we could reach a specificity of 94.2% with AUC of 0.843, a significantly improved performance as compared with that by each individual biomarker. The performances of three autoantibodies, namely anti-SPATA7, -QDPR, and -PRH2, were successfully confirmed with western blot analysis. Using this two-phase strategy, we identified and validated eight novel autoantibodies as TAK-specific biomarker candidates, three of which could be readily adopted in a clinical setting.

Protein Biomarkers in Uveitis

The diseases affecting the retina or uvea (iris, ciliary body, or choroid) generate changes in the biochemical or protein composition of ocular fluids/tissues due to disruption of blood-retinal barrier. Ocular infections and inflammations are sight-threatening diseases associated with various infectious and non-infectious etiologies. Several etiological entities cause uveitis, a complex intraocular inflammatory disease. These causes of uveitis differ in different populations due to geographical, racial, and socioeconomic variations. While clinical appearance is sufficiently diagnostic in many diseases, some of the uveitic entities manifest nonspecific or atypical clinical presentation. Identification of biomarkers in such diseases is an important aid in their diagnostic armamentarium. Different diseases and their different severity states release varying concentrations of proteins, which can serve as biomarkers. Proteomics is a high throughput technology and a powerful screening tool for serum biomarkers in various diseases that identifies proteins by mass spectrometry and helps to improve the understanding of pathogenesis of a disease. Proteins determine the biological state of a cell. Once identified as biomarkers, they serve as future diagnostic and pharmaceutical targets. With a potential to redirect the diagnosis of idiopathic uveitis, ocular proteomics provide a new insight into the pathophysiology and therapeutics of various ocular inflammatory diseases. Tears, aqueous and vitreous humor represent potential repositories for proteomic biomarkers discovery in uveitis. With an extensive proteomics work done on animal models of uveitis, various types of human uveitis are being subjected to proteome analysis for biomarker discovery in different ocular fluids (vitreous, aqueous, or tears).

Correlation of clinical signs and symptoms of Behçet's disease with mean platelet volume (MPV) and red cell distribution width (RDW)

Background

A strong correlation was previously found between mean platelet volume (MPV), red blood cell distribution width (RDW), and the severity of signs and symptoms in patients suffering from inflammatory and autoimmune diseases. The current study evaluated these correlations in patients with Behçet’s disease (BD) as well the relationship between MPV and RDW and disease activity score on the Iranian Behçet’s Disease Dynamic Activity Measurement (IBDDAM).

Methods

This cross-sectional study included 319 patients with BD for whom demographic and epidemiological data, IBDDAM scores, and duration of illness was recorded. Blood samples were then obtained and the relationships between their disease status and manifestations and their laboratory parameters were evaluated with statistical models to find possible correlations.

Results

Our analysis showed a significantly higher RDW in patients with BD who had ocular manifestations (p < 0.001) and oral aphthae (p = 0.004). Patients with active BD had higher RDW (p < 0.001) and MPV (p < 0.001) in comparison to those with currently inactive BD. Similarly, patients who had any type of ocular manifestation had higher RDW (p < 0.001) and MPV (p < 0.001). Regression analyses identified a statistically significant model for the effect of RDW and MPV in predicting active BD status (p < 0.001), as well as its significant relationship with active ocular manifestations (p < 0.001).

Conclusion

BD was found to be associated with an increase in MPV and RDW, particularly during active phases. RDW and MPV were also found to have predictive value for screening to detect BD activity and its ocular complications.

Discovery of new serum biomarker panels for systemic lupus erythematosus diagnosis

OBJECTIVE

Clinical diagnosis of SLE is currently challenging due to its heterogeneity. Many autoantibodies are associated with SLE and are considered potential diagnostic markers, but systematic screening and validation of such autoantibodies is lacking. This study aimed to systematically discover new autoantibodies that may be good biomarkers for use in SLE diagnosis.

METHODS

Sera from 15 SLE patients and 5 healthy volunteers were analysed using human proteome microarrays to identify candidate SLE-related autoantibodies. The results were validated by screening of sera from 107 SLE patients, 94 healthy volunteers and 60 disease controls using focussed arrays comprised of autoantigens corresponding to the identified candidate antibodies. Logistic regression was used to derive and validate autoantibody panels that can discriminate SLE disease. Extensive ELISA screening of sera from 294 SLE patients and 461 controls was performed to validate one of the newly discovered autoantibodies.

RESULTS

A total of 31, 11 and 18 autoantibodies were identified to be expressed at significantly higher levels in the SLE group than in the healthy volunteers, disease controls and healthy volunteers plus disease control groups, respectively, with 25, 7 and 13 of these differentially expressed autoantibodies being previously unreported. Diagnostic panels comprising anti-RPLP2, anti-SNRPC and anti-PARP1, and anti-RPLP2, anti-PARP1, anti-MAK16 and anti- RPL7A were selected. Performance of the newly discovered anti-MAK16 autoantibody was confirmed by ELISA. Some associations were seen with clinical characteristics of SLE patients, such as disease activity with the level of anti-PARP1 and rash with the level of anti-RPLP2, anti-MAK16 and anti- RPL7A.

CONCLUSION

The combined autoantibody panels identified here show promise for the diagnosis of SLE and for differential diagnosis of other major rheumatic immune diseases.

Autoantibody signature in hepatocellular carcinoma using seromics

Background

Alpha-fetoprotein (AFP) is a widely used biomarker for hepatocellular carcinoma (HCC) early detection. However, low sensitivity and false negativity of AFP raise the requirement of more effective early diagnostic approaches for HCC.

Methods

We employed a three-phase strategy to identify serum autoantibody (AAb) signature for HCC early diagnosis using protein array-based approach. A total of 1253 serum samples from HCC, liver cirrhosis, and healthy controls were prospectively collected from three liver cancer centers in China. The Human Proteome Microarray, comprising 21,154 unique proteins, was first applied to identify AAb candidates in discovery phase (n = 100) and to further fabricate HCC-focused arrays. Then, an artificial neural network (ANN) model was used to discover AAbs for HCC detection in a test phase (n = 576) and a validation phase (n = 577), respectively.

Results

Using HCC-focused array, we identified and validated a novel 7-AAb panel containing CIAPIN1, EGFR, MAS1, SLC44A3, ASAH1, UBL7, and ZNF428 for effective HCC detection. The ANN model of this panel showed improvement of sensitivity (61.6–77.7%) compared to AFP (cutoff 400 ng/mL, 28.4–30.7%). Notably, it was able to detect AFP-negative HCC with AUC values of 0.841–0.948. For early-stage HCC (BCLC 0/A) detection, it outperformed AFP (cutoff 400 ng/mL) with approximately 10% increase in AUC.

Conclusions

The 7-AAb panel provides potentially clinical value for non-invasive early detection of HCC, and brings new clues on understanding the immune response against hepatocarcinogenesis.

Developments and Applications of Functional Protein Microarrays

Protein microarrays are crucial tools in the study of proteins in an unbiased, high-throughput manner, as they allow for characterization of up to thousands of individually purified proteins in parallel. The adaptability of this technology has enabled its use in a wide variety of applications, including the study of proteome-wide molecular interactions, analysis of post-translational modifications, identification of novel drug targets, and examination of pathogen-host interactions. In addition, the technology has also been shown to be useful in profiling antibody specificity, as well as in the discovery of novel biomarkers, especially for autoimmune diseases and cancers. In this review, we will summarize the developments that have been made in protein microarray technology in both in basic and translational research over the past decade. We will also introduce a novel membrane protein array, the GPCR-VirD array, and discuss the future directions of functional protein microarrays.

Integration of IgA and IgG Autoantigens Improves Performance of Biomarker Panels for Early Diagnosis of Lung Cancer

Lung cancer (LC) remains the leading cause of mortality from malignant tumors worldwide. In our previous study, we surveyed both IgG and IgM-bound serological biomarkers and validated a panel of IgG-bound autoantigens for early LC diagnosis with 50% sensitivity at 90% specificity. To further improve the performance of these serological biomarkers, we surveyed HuProt arrays, comprised of 20,240 human proteins, for IgA-bound autoantigens because IgAs are a major immunoglobulin isotype in the lung. Integrating with IgG-bound autoantigens, we discovered and validated a combined biomarker panel using ELISA-format tests. Specifically, in Phase I, we obtained IgA-based autoimmune profiles of 69 early stage LC patients, 30 healthy subjects and 25 patients with lung benign lesions (LBL) on HuProt arrays and identified 28 proteins as candidate autoantigens that were significantly associated with early stage LC. In Phase II, we re-purified the autoantigens and converted them into an ELISA-format testing to profile an additional large cohort, comprised of 136 early stage LC patients, 58 healthy individuals, and 29 LBL patients. Integration of IgG autoimmune profiles allowed us to identify and validate a biomarker panel of three IgA autoantigens (i.e. BCL7A, and TRIM33 and MTERF4) and three IgG autoantigens (i.e. CTAG1A, DDX4 and MAGEC2) for diagnosis of early stage LC with 73.5% sensitivity at >85% specificity. In Phase III, the performance of this biomarker panel was confirmed with an independent cohort, comprised of 88 early stage LC patients, 18 LBL patients, and 36 healthy subjects. Finally, a blind test on 178 serum samples was conducted to confirm the performance of the biomarker panel. In summary, this study demonstrates for the first time that an integrated panel of IgA/IgG autoantigens can serve as valuable biomarkers to further improve the performance of early diagnosis of LC.

FGA isoform as an indicator of targeted therapy for EGFR mutated lung adenocarcinoma

Epidermal growth factor receptor (EGFR) gene is frequently mutated in non-small cell lung cancer (NSCLC), which can be targeted by EGFR tyrosine kinase inhibitors (TKIs). It is hard, however, to monitor the performance of EGFR-TKI therapy dynamically. Therefore, therapeutic indicators are urgently needed. Novel antibody microarray, containing 41,472 antibodies, was used for comprehensive analyzing of serum samples from 9 normal subjects and 9 EGFR mutated lung adenocarcinoma patients at three EGFR-TKI treatment time points, including before treatment (Baseline), partial response (PR) during treatment, and disease progression (PD) after resistance. Through microarray data analysis, five candidate antibodies were screened out for confirmation in serum samples and the verified one was utilized for candidate protein identification through immunoprecipitation-mass spectrometry strategy. A novel protein, isoform 2 of fibrinogen alpha chain (FGA2), was revealed and verified in the discovery sample set. Its performance as therapy indicator was further evaluated in another pre-validation sample set (n = 60). Our data confirmed that serum FGA2 level was correlated with EGFR-TKI response (p < 0.05). The expression and secretion of FGA2 in hepatocytes were inhibited by EGFR-TKI, partially explaining the downregulation of FGA2 in serum. Our results demonstrate that FGA2 is an indicator of targeted therapy for EGFR mutated lung adenocarcinoma. KEY MESSAGES: Antibody microarray was coupled with mass spectrometry for proteomics research. FGA2 was discovered as an indicator of EGFR-TKI targeted therapy. FGA2's expression/secretion in hepatocytes was dramatically inhibited by EGFR-TKI.

Proteome microarray technology and application: higher, wider, and deeper

Introduction: Protein microarray is a powerful tool for both biological study and clinical research. The most useful features of protein microarrays are their miniaturized size (low reagent and sample consumption), high sensitivity and their capability for parallel/high-throughput analysis. The major focus of this review is functional proteome microarray. Areas covered: For proteome microarray, this review will discuss some recently constructed proteome microarrays and new concepts that have been used for constructing proteome microarrays and data interpretation in past few years, such as PAGES, M-NAPPA strategy, VirD technology, and the first protein microarray database. this review will summarize recent proteomic scale applications and address the limitations and future directions of proteome microarray technology. Expert opinion: Proteome microarray is a powerful tool for basic biological and clinical research. It is expected to see improvements in the currently used proteome microarrays and the construction of more proteome microarrays for other species by using traditional strategies or novel concepts. It is anticipated that the maximum number of features on a single microarray and the number of possible applications will be increased, and the information that can be obtained from proteome microarray experiments will more in-depth in the future.

Peripheral blood mononuclear cell proteome profile in Behçet's syndrome

Behçet's syndrome (BS) is a systemic inflammatory disorder with unknown etiology. Investigation of proteome profiles of disease specific cells facilitates our understanding of the processes and related molecular pathways, especially in disorders like BS with complex inheritance pattern and clinical heterogeneity. In the current study, we evaluated the peripheral blood mononuclear cells (PBMCs) proteome of 59 patients with BS (33 in active and 26 in inactive phases) and of 28 healthy controls using two-dimensional fluorescence difference gel electrophoresis (2D-DIGE). Differentially expressed protein spots with at least twofold and/or statistically significant change (p ≤ 0.05) between active BS vs inactive BS, and also active BS vs healthy controls were identified by mass spectrometry (MALDI-TOF/TOF). Bioinformatic analyses revealed 16 differentially expressed proteins (12 of them in active vs inactive BS comparison, whereas 11 of them for active BS vs healthy control comparison) belonging to glycolysis, cytoskeleton organization, protein folding, and regulation of blood coagulation pathways. Stathmin (active BS vs inactive BS; fourfold, active BS vs healthy control; 4.7-fold) and WD repeat-containing protein-1 (active BS vs inactive BS; 2.7-fold, active BS vs healthy control; 2.7-fold), which are cytoskeleton-related proteins, were found to be lower in active patients compared to inactive patients and healthy control. Decreased levels of calreticulin (active BS vs inactive BS; 1.29-fold) and heat shock 70 kDa protein 8 (active BS vs healthy control; 1.5-fold) which are involved in protein folding and endoplasmic reticulum (ER) stress process, were observed in patients with active phase of BS. Down-regulation of protein folding and ER stress process proteins in BS patients may further support the involvement of ER stress in BS.

AAgMarker 1.0: a resource of serological autoantigen biomarkers for clinical diagnosis and prognosis of various human diseases

Autoantibodies are produced to target an individual's own antigens (e.g. proteins). They can trigger autoimmune responses and inflammation, and thus, cause many types of diseases. Many high-throughput autoantibody profiling projects have been reported for unbiased identification of serological autoantigen-based biomarkers. However, a lack of centralized data portal for these published assays has been a major obstacle to further data mining and cross-evaluate the quality of these datasets generated from different diseases. Here, we introduce a user-friendly database, AAgMarker 1.0, which collects many published raw datasets obtained from serum profiling assays on the proteome microarrays, and provides a toolbox for mining these data. The current version of AAgMarker 1.0 contains 854 serum samples, involving 136 092 proteins. A total of 7803 (4470 non-redundant) candidate autoantigen biomarkers were identified and collected for 12 diseases, such as Alzheimer's disease, Bechet's disease and Parkinson's disease. Seven statistical parameters are introduced to quantitatively assess these biomarkers. Users can retrieve, analyse and compare the datasets through basic search, advanced search and browse. These biomarkers are also downloadable by disease terms. The AAgMarker 1.0 is now freely accessible at http://bioinfo.wilmer.jhu.edu/AAgMarker/. We believe this database will be a valuable resource for the community of both biomedical and clinical research.

Advances in the development of human protein microarrays

INTRODUCTION

High-content protein microarrays in principle enable the functional interrogation of the human proteome in a broad range of applications, including biomarker discovery, profiling of immune responses, identification of enzyme substrates, and quantifying protein-small molecule, protein-protein and protein-DNA/RNA interactions. As with other microarrays, the underlying proteomic platforms are under active technological development and a range of different protein microarrays are now commercially available. However, deciphering the differences between these platforms to identify the most suitable protein microarray for the specific research question is not always straightforward. Areas covered: This review provides an overview of the technological basis, applications and limitations of some of the most commonly used full-length, recombinant protein and protein fragment microarray platforms, including ProtoArray Human Protein Microarrays, HuProt Human Proteome Microarrays, Human Protein Atlas Protein Fragment Arrays, Nucleic Acid Programmable Arrays and Immunome Protein Arrays. Expert commentary: The choice of appropriate protein microarray platform depends on the specific biological application in hand, with both more focused, lower density and higher density arrays having distinct advantages. Full-length protein arrays offer advantages in biomarker discovery profiling applications, although care is required in ensuring that the protein production and array fabrication methodology is compatible with the required downstream functionality.

Multiplexed Biomarker Panels Discriminate Zika and Dengue Virus Infection in Humans

Zika virus (ZIKV) and dengue virus (DENV) are closely related flaviviruses that cause widespread, acute febrile illnesses, notably microcephaly for fetuses of infected pregnant women. Detecting the viral cause of these illnesses is paramount to determine risks to patients, counsel pregnant women, and help fight outbreaks. A combined diagnostic algorithm for ZIKV and DENV requires Reverse transcription polymerase chain reaction (RT-PCR) and IgM antibody detection. RT-PCR differentiates between DENV and ZIKV infections during the acute phases of infection, but differentiation based on IgM antibodies is currently nearly impossible in endemic areas. We have developed a ZIKV/DENV protein array and tested it with serum samples collected from ZIKV- and DENV-infected patients and healthy subjects in Puerto Rico. Our analyses reveal a biomarker panel that are capable of discriminating ZIKV and DENV infections with high accuracy, including Capsid protein from African ZIKV strain MR766, and other 5 pair of proteins (NS1, NS2A, NS3, NS4B and NS5) from ZIKV and DENV respectively. Both sensitivity and specificity of the test for ZIKV from DENV are around 90%. We propose that the ZIKV/DENV protein array will be used in future studies to discriminate patients infected with ZIKV from DENV.

Rare esophageal ulcers related to Behçet disease: A case report

RATIONALE

The fundamental pathogenesis of Behçet disease (BD) is still unclear and controversial. Many cases of oral aphthous ulcers and genital ulcers related to BD are reported; nevertheless, idiopathic giant esophageal ulcers related to BD are rare. A rare case for esophageal ulcers related to BD is presented.

PATIENT CONCERNS

In China, BD is represented with esophageal involvement which is called esophageal BD (EBD).

DIAGNOSES

A 56-year-old man diagnosed to the Gastroenterology Department of Integrated Traditional Chinese and Western Medicine Hospital, for multiple discrete, elliptical esophageal ulcers related to BD.

INTERVENTIONS

The esophageal ulcers were treated with corticosteroid treatment for 12 weeks.

OUTCOME

The esophageal ulcers were cured.

LESSONS

Our report might give further strength to avoiding the erroneous diagnosis or missed diagnosis for EBD, which is different from esophageal carcinoma, esophageal tuberculosis and esophageal Crohns disease.

Identification of Serological Biomarkers for Early Diagnosis of Lung Cancer Using a Protein Array-Based Approach

Lung cancer (LC) remains the leading cause of mortality from malignant tumors worldwide. Currently, a lack of serological biomarkers for early LC diagnosis is a major roadblock for early intervention and prevention of LC. To undertake this challenge, we employed a two-phase strategy to discover and validate a biomarker panel using a protein array-based approach. In Phase I, we obtained serological autoimmune profiles of 80 LC patients and 20 healthy subjects on HuProt arrays, and identified 170 candidate proteins significantly associated with LC. In Phase II, we constructed a LC focused array with the 170 proteins, and profiled a large cohort, comprised of 352 LC patients, 93 healthy individuals, and 101 patients with lung benign lesions (LBL). The comparison of autoimmune profiles between the early stage LC and the combined group of healthy and LBL allowed us to identify and validate a biomarker panel of p53, HRas, and ETHE1 for diagnosis of early stage LC with 50% sensitivity at >90% specificity. Finally, the performance of this biomarker panel was confirmed in ELISA tests. In summary, this study represents one of the most comprehensive proteome-wide surveys with one of the largest (i.e. 1,101 unique samples) and most diverse (i.e. nine disease groups) cohorts, resulting in a biomarker panel with good performance.

Analysis of Antineutrophil Cytoplasm Antibody from 118 730 Patients in Tertiary Hospitals in Jiangxi Province, China

BACKGROUND The discovery of antineutrophil cytoplasm antibody (ANCA) makes the early diagnosis of primary vasculitis possible, and also has important guiding significance for the diagnosis and treatment of secondary vasculitis. This study aimed to investigate the clinical significance of ANCA. MATERIAL AND METHODS ANCA was detected by indirect immunofluorescence assay (IIF), and anti-myeloperoxidase (MPO) antibody, and anti-proteinase 3 (PR3) antibody were detected by ELISA. The results were analyzed retrospectively. RESULTS Among 118 730 patients, a total of 5853 (4.93%) were positive for ANCA. In the positive cases, 3.98% were male and 6.33% were female, with significant differences (χ²=123.38, P<0.01). For ANCA, the department with the highest positive rate (15.06%) was the Department of Rheumatology, followed by 7.78% in the Department of Dermatology, 6.79% in the Department of Nephrology, and 5.72% in the Department of Traditional Chinese Medicine (TCM). Anti-PR3 and cANCA were highly specific in primary vasculitis (P<0.01). Anti-MPO and pANCA had high specificity for other autoimmune diseases (P<0.01). CONCLUSIONS ANCA has important guiding significance for vasculitis-related diseases. Therefore, it is important in the diagnosis and treatment of this disease and has value in clinical practice.