Autoantibody Signatures Research Articles

Individual and stable autoantibody repertoires in healthy individuals

In the era towards precision medicine, we here present the individual specific autoantibody signatures of 193 healthy individuals. The self-reactive IgG signatures are stable over time in a way that each individual profile is recognized in longitudinal sampling. The IgG autoantibody reactivity towards an antigen array comprising 335 protein fragments, representing 204 human proteins with potential relevance to autoimmune disorders, was measured in longitudinal plasma samples from 193 healthy individuals. This analysis resulted in unique autoantibody barcodes for each individual that were maintained over one year’s time. The reactivity profiles, or signatures, are person specific in regards to the number of reactivities and antigen specificity. Two independent data sets were consistent in that each healthy individual displayed reactivity towards 0–16 antigens, with a median of six. Subsequently, four selected individuals were profiled on in-house produced high-density protein arrays containing 23,000 protein fragments representing 14,000 unique protein coding genes. Based on a unique, broad and deep longitudinal profiling of autoantibody reactivities, our results demonstrate a unique autoreactive profile in each analyzed healthy individual. The need and interest for broad-ranged and high-resolution molecular profiling of healthy individuals is rising. We have here generated and assessed an initial perspective on the global distribution of the self-reactive IgG repertoire in healthy individuals, by investigating 193 well-characterized healthy individuals.HighlightsA unique longitudinal profiling of autoantibody repertoires in healthy individualsAutoantibody profiles are highly individual and stable over timeAll individuals display IgG binding to human protein fragmentsThe specificity of disease associated autoantigens needs to be thoroughly characterizedThe identification of a small set of highly reactive autoantigensImportance of stringent antigen and sample specific cut-offs for defining reactivity

GPCR-specific autoantibody signatures are associated with physiological and pathological immune homeostasis

Autoantibodies have been associated with autoimmune diseases. However, studies have identified autoantibodies in healthy donors (HD) who do not develop autoimmune disorders. Here we provide evidence of a network of immunoglobulin G (IgG) autoantibodies targeting G protein-coupled receptors (GPCR) in HD compared to patients with systemic sclerosis, Alzheimer’s disease, and ovarian cancer. Sex, age and pathological conditions affect autoantibody correlation and hierarchical clustering signatures, yet many of the correlations are shared across all groups, indicating alterations to homeostasis. Furthermore, we identify relationships between autoantibodies targeting structurally and functionally related molecules, such as vascular, neuronal or chemokine receptors. Finally, autoantibodies targeting the endothelin receptor type A (EDNRA) exhibit chemotactic activity, as demonstrated by neutrophil migration toward HD-IgG in an EDNRA-dependent manner and in the direction of IgG from EDNRA-immunized mice. Our data characterizing the in vivo signatures of anti-GPCR autoantibodies thus suggest that they are a physiological part of the immune system.

Multiplexed Autoantibody Signature for Serological Detection of Canine Mammary Tumours

Spontaneously occurring canine mammary tumours (CMTs) are the most common neoplasms of female unspayed dogs and are of potential importance as models for human breast cancer as well. Mortality rates are thrice higher in dogs as compared to humans with breast cancer, which can partly be attributed to lack of diagnostic techniques for their early detection. Human breast cancer studies reveal role of autoantibodies in early cancer diagnosis and also the usefulness of autoantibody panels in increasing the sensitivity, as well as, specificity of diagnostic assays. Therefore, in this study, we took advantage of high-throughput Luminex technique for developing a multiplex assay to detect autoantibody signatures against 5 canine mammary tumour-associated autoantigens (TAAs). These TAAs were expressed separately as fusion proteins with halo tag at the N-terminus, which allows easy and specific covalent coupling with magnetic microspheres. The multiplex assay, comprising a panel of candidate autoantigens (TPI, PGAM1, MNSOD, CMYC & MUC1) was used for screening circulating autoantibodies in 125 dog sera samples, including 75 mammary tumour sera and 50 healthy dog sera. The area under curve (AUC) of the combined panel of biomarkers is 0.931 (p < 0.0001), which validates the discriminative potential of the panel in differentiating tumour patients from healthy controls. The assay could be conducted in 3hrs using only 1ul of serum sample and could detect clinical cases of canine mammary tumour with sensitivity and specificity of 78.6% and 90%, respectively. In this study, we report for the first time a multiplexed assay for detection of autoantibodies in canine tumours, utilizing luminex technology and halo-tag coupling strategy. Further to the best of our knowledge, autoantibodies to CMYC and MUC1 have been reported for the first time in canines in this study.

A diagnostic autoantibody signature for primary cutaneous melanoma.

Melanoma is an aggressive form of skin cancer that is curable by surgical excision in the majority of cases, if detected at an early stage. To improve early stage melanoma detection, the development of a highly sensitive diagnostic test is of utmost importance. Here we aimed to identify antibodies to a panel of tumour associated antigens that can differentiate primary melanoma patients and healthy individuals. A total of 245 sera from primary melanoma patients and healthy volunteers were screened against a high-throughput microarray platform containing 1627 functional proteins. Following rigorous statistical analysis, we identified a combination of 10 autoantibody biomarkers that, as a panel, displays a sensitivity of 79%, specificity of 84% and an AUC of 0.828 for primary melanoma detection. This melanoma autoantibody signature may prove valuable for the development of a diagnostic blood test for routine population screening that, when used in conjunction with current melanoma diagnostic techniques, could improve the early diagnosis of this malignancy and ultimately decrease the mortality rate of patients.

The Immunome of Colon Cancer: Functional In Silico Analysis of Antigenic Proteins Deduced from IgG Microarray Profiling

Characterization of the colon cancer immunome and its autoantibody signature from differentially-reactive antigens (DIRAGs) could provide insights into aberrant cellular mechanisms or enriched networks associated with diseases. The purpose of this study was to characterize the antibody profile of plasma samples from 32 colorectal cancer (CRC) patients and 32 controls using proteins isolated from 15,417 human cDNA expression clones on microarrays. 671 unique DIRAGs were identified and 632 were more highly reactive in CRC samples. Bioinformatics analyses reveal that compared to control samples, the immunoproteomic IgG profiling of CRC samples is mainly associated with cell death, survival, and proliferation pathways, especially proteins involved in EIF2 and mTOR signaling. Ribosomal proteins (e.g., RPL7, RPL22, and RPL27A) and CRC-related genes such as APC, AXIN1, E2F4, MSH2, PMS2, and TP53 were highly enriched. In addition, differential pathways were observed between the CRC and control samples. Furthermore, 103 DIRAGs were reported in the SEREX antigen database, demonstrating our ability to identify known and new reactive antigens. We also found an overlap of 7 antigens with 48 “CRC genes.” These data indicate that immunomics profiling on protein microarrays is able to reveal the complexity of immune responses in cancerous diseases and faithfully reflects the underlying pathology.

Novel autoantibody signatures in plasma exosomes as potential biomarkers for diagnostics and prognosis of non-small-cell lung cancer

Novel autoantibody signatures in plasma exosomes as potential biomarkers for diagnostics and prognosis of non-small-cell lung cancer

Estimating autoantibody signatures to detect autoimmune disease patient subsets.

Autoimmune diseases are characterized by highly specific immune responses against molecules in self-tissues. Different autoimmune diseases are characterized by distinct immune responses, making autoantibodies useful for diagnosis and prediction. In many diseases, the targets of autoantibodies are incompletely defined. Although the technologies for autoantibody discovery have advanced dramatically over the past decade, each of these techniques generates hundreds of possibilities, which are onerous and expensive to validate. We set out to establish a method to greatly simplify autoantibody discovery, using a pre-filtering step to define subgroups with similar specificities based on migration of radiolabeled, immunoprecipitated proteins on sodium dodecyl sulfate (SDS) gels and autoradiography [Gel Electrophoresis and band detection on Autoradiograms (GEA)]. Human recognition of patterns is not optimal when the patterns are complex or scattered across many samples. Multiple sources of errors-including irrelevant intensity differences and warping of gels-have challenged automation of pattern discovery from autoradiograms.In this article, we address these limitations using a Bayesian hierarchical model with shrinkage priors for pattern alignment and spatial dewarping. The Bayesian model combines information from multiple gel sets and corrects spatial warping for coherent estimation of autoantibody signatures defined by presence or absence of a grid of landmark proteins. We show the pre-processing creates more clearly separated clusters and improves the accuracy of autoantibody subset detection via hierarchical clustering. Finally, we demonstrate the utility of the proposed methods with GEA data from scleroderma patients.

P3.13-020 A Pilot Study of the Autoantibodies to Tumor Antigens in Lung Cancer Using the EarlyCDT-Lung Test in Hong Kong

The EarlyCDT-Lung test detects autoantibodies to abnormal cell surface proteins in lung cancer patients. It has been studied in UK1 and USA2 in diagnosing lung cancer patients and has a sensitivity of up to 47%, specificity up to 90% and positive predictive value of 16%. It is a potential diagnostic test and when combines with radiological (Computed Tomography) test, the positive predictive value can be enhanced up to 72%3. We want to study the performance of the test in a predominantly Asian ethnic city. 1. Caroline J. Chapman et al. EarlyCDT®-Lung test: improved clinical utility through additional autoantibody assays. Tumor Biol. 2012; 33:1319–1326 2. JR Jett et al. Audit of the autoantibody test, EarlyCDT®-Lung, in 1600 patients: An evaluation of its performance in routine clinical practice. Lung Cancer 2014; 83:51–55 . 3. P Massion et al. Autoantibody Signature Enhances the Positive Predictive Power of Computed Tomography and Nodule-Based Risk Models for Detection of Lung Cancer Journal of Thoracic Oncology 2017; 12:578-584

Development of a multiplexed tumor-associated autoantibody-based blood test for the detection of colorectal cancer

BackgroundColorectal cancer (CRC) is one of the most common malignancies worldwide, and early diagnosis is vital to improving prognoses. We explored the diagnostic potential of a multiplex autoantibody panel as a biomarker for the detection of CRC by ELISA. MethodsIn total, 192 serum samples (92 CRC and 100 matched controls) were tested against a panel of 12 tumor-associated antigens (TAAs): RPH3AL, RPL36, SLP2, p53, survivin, ANAXA4, SEC61B, CCCAP, NYCO16, NMDAR, PLSCR1, and HDAC5. Individual and combined autoantibody signatures were examined. ResultsCompared to individual autoantibody markers, the combinations of TAAs provided better discrimination between tumorous and normal sera. The overall sensitivity of a selected panel of four antibodies (anti-SLP2, -p53, -SEC61B, and -PLSCR1) was 64.1%, with a specificity of 80% that increased to 83.7% when carcinoembryonic antigen (CEA) measurement was added. Furthermore, the sensitivity of the panel of four antibodies for early and advanced stages of CRC was 66.7% and 62%, increasing to 88.3% and 84%, respectively, when CEA was added. ConclusionsWe identified a panel of four antibodies as a promising diagnostic biomarker for the detection of CRC.

Risk assessment for high-grade prostate cancer using a novel cancer-specific biomarker assay derived from autoantibody signatures

Risk assessment for high-grade prostate cancer using a novel cancer-specific biomarker assay derived from autoantibody signatures

New developments in prostate cancer screening using a novel cancer-specific, non-PSA biomarker assay derived from autoantibody signatures

New developments in prostate cancer screening using a novel cancer-specific, non-PSA biomarker assay derived from autoantibody signatures

Improved risk assessment using a novel cancer-specific biomarker assay derived from autoantibody signatures for men with non-aggressive prostate cancer who are not receiving treatment

Improved risk assessment using a novel cancer-specific biomarker assay derived from autoantibody signatures for men with non-aggressive prostate cancer who are not receiving treatment

Serum Profiling for Identification of Autoantibody Signatures in Diseases Using Protein Microarrays.

Protein microarrays are platforms for studying protein-protein interactions and identifying disease-related self-antigens/autoantigens, which elicit an immune response in a high-throughput format. Protein arrays have been extensively used over the past two decades for several clinical applications. By using this platform, serum containing autoantibodies against potential self-antigens can be screened on proteome-wide arrays, harboring a large repertoire of full-length human proteins. Identification of such autoantigens can help deducing early diagnostic, as well as, prognostic markers in case of malignancies, autoimmune disorders, and other systemic diseases. Here, we provide an overview of the protein microarray technology along with details of an established method to study autoantibody profiles from patient sera.

Phage Display Libraries in Sequelization of Autoantibody Signature Analyses in Cancer Immunomics

Phage Display Libraries in Sequelization of Autoantibody Signature Analyses in Cancer Immunomics

Multiparametric detection of autoantibodies in systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a heterogeneous disease with respect to disease manifestations, disease progression and treatment response. Therefore, strategies to identify biomarkers that help distinguishing SLE subgroups are a major focus of biomarker research. We reasoned that a multiparametric autoantibody profiling approach combined with data mining tools could be applied to identify SLE patient clusters. We used a bead-based array containing 86 antigens including diverse nuclear and immune defense pathway proteins. Sixty-four autoantibodies were significantly (p < 0.05) increased in SLE (n = 69) compared to healthy controls (HC, n = 59). Using binary cut-off thresholds (95% quantile of HC), hierarchical clustering of SLE patients yields five clusters, which differ qualitatively and in their total number of autoantibodies. In two patient clusters the overall accumulated autoantibody reactivity of all antigens tested was 31% and 48%, respectively. We observed a positive association between the autoantibody signature present in these two patient clusters and the clinical manifestation of glomerulonephritis (GLMN). In addition, groups of autoantibodies directed against distinct intracellular compartments and/or biological motifs characterize the different SLE subgroups. Our findings highlight the relevant potential of multiparametric autoantibody detection and may contribute to a deeper understanding of the clinical and serological diversity of SLE.

The prostate cancer immunome: In silico functional analysis of antigenic proteins from microarray profiling with IgG.

The study of the immunome of prostate cancer (PCa) and characterization of autoantibody signature from differentially reactive antigens can uncover disease stage proteins, reveal enriched networks and even expose aberrant cellular mechanisms during the disease process. By conducting plasma IgG profiling on protein microarrays presenting 5449 unique human proteins expressed in 15 417 E. coli human cDNA expression clones, we elucidated 471 (21 higher reactive in PCa) differentially reactive antigens in 50 PCa versus 49 patients with benign prostate hyperplasia (BPH) at initial diagnosis. Functional analyzes show that the immune-profile of PCa compared to BPH control samples is significantly enriched in features targeting Cellular assembly, Cell death and pathways involved in Cell cycle, translation, and assembly of proteins as EIF2 signaling, PCa related genes as AXIN1 and TP53, and ribosomal proteins (e.g. RPS10). An overlap of 61 (out of 471) DIRAGs with the published 1545 antigens from the SEREX database has been found, however those were higher reactive in BPH. Clinical relevance is shown when antibody-reactivities against eight proteins were significantly (p < 0.001) correlated with Gleason-score. Herewith we provide a biological and pathophysiological characterization of the immunological layer of cancerous (PCa) versus benign (BPH) disease, derived from antibody profiling on protein microarrays.

Abstract B05: Immunoproteomic profiling in African American men with prostate cancer: Evidence for an autoimmune response to glycolytic enzymes

Abstract Prostate cancer (PCa) is the most frequently diagnosed cancer and the second leading cause of cancer-related male deaths in the U.S. This cancer is more aggressive in African American (AA) men, who are twice as likely to die from the disease when compared to other racial groups. Despite these racial disparities in PCa mortality, studies on PCa biology and biomarker discovery include mostly patients from European American (EA) backgrounds. There is a critical need to find minimally invasive PCa biomarkers that could aid in diagnosis and prognosis, especially in high risk populations like AA men. Immunoseroproteomics offers a minimally invasive approach to detect early malignant processes that trigger production of autoantibodies to tumor-associated antigens (TAA). These antibodies serve as “sensors” of tumorigenic events and can be assessed as potential biomarkers relevant to tumor biology. In this study we used this approach to interrogate anti-TAA autoantibody signatures in AA and EA men with PCa and explored racial differences in tumor immunobiology that could underlie PCa mortality disparities. We used serum samples from AA (n=59) and EA (n=50) men with PCa to probe one- and two-dimensional Western blots (WB) of protein lysates from aggressive PCa cell lines. AA PCa patient sera showed stronger immunoreactivity to proteins in PC3 cell lysates compared to the EA sera, with a 50 kD protein band frequently targeted by autoantibodies in several AA PCa sera. Serological proteomic analysis (SERPA) with mass spectrometry showed that these AA PCa autoantibodies recognized alpha-enolase (ENO1), known to be important in tumor formation, expansion, and glucose metabolism. In addition, several other glycolytic enzymes important for tumor proliferation were also identified as candidate prostate TAA, including GAPDH, phosphoglycerate kinase, and lactate dehydrogenase. These have been validated in other studies as overexpressed in PCa. The ENO1 autoantibody frequency, measured by ELISA in sera from 400 racially diverse men with and without PCa, was four-fold higher in PCa compared to non-PCa patients. Interestingly, although sera from AA men with PCa had stronger WB reactivity to ENO1 present in PC3 lysates compared to EA men, and the ENO1 autoantibodies were initially discovered in eight AA PCa sera but only in two EA sera, the anti-ENO1 autoantibody frequency measured by ELISA, which used E. coli-purified recombinant human ENO1 as a substrate, was higher in the EA PCa cohort. In addition, several anti-ENO1 positive sera from AA men with PCa showed increased immunoreactivity to this protein in the PCa cell lines LNCaP, MDA-PC2b, PC3, and DU145, but not against the purified ENO1 used in ELISA. The opposite was true in the EA PCa cohort, where strong reactivity against the purified ENO1 did not correlate with an equally strong immunoreactivity against the cellular ENO1. The EA PCa sera did not recognize the pattern of ENO1 expression observed with the AA sera in the same panel of prostate cell lines. These differences of immunoreactivity between AA and EA sera against PC3-ENO1 vs bacterially purified human ENO1 suggest that select AA sera may predominantly recognize ENO1 epitopes not displayed in the purified protein. A recent study found higher frequency of autoantibodies to phosphorylated ENO1 in pancreatic cancer sera compared to normal patient sera. Our own proteomic comparison of PC3-ENO1 and recombinant ENO1 yielded differences in phosphorylated, acetylated, and methylated amino acids. Taken together, these data suggest the anti-ENO1 autoantibodies from AA men with PCa target a modified form of ENO1 that may not be strongly recognized by EA men with PCa. These discrepancies point to racial differences in the immune response to prostate tumors. Citation Format: Tino Wilson Sanchez, Jitian Li, Liping Dai, Saied Mirshahidi, Guangyu Zhang, Nathan Wall, Colwick Wilson, Susanne Montgomery, Jianying Zhang, Carlos Casiano. Immunoproteomic profiling in African American men with prostate cancer: Evidence for an autoimmune response to glycolytic enzymes. [abstract]. In: Proceedings of the Eighth AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 13-16, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2016;25(3 Suppl):Abstract nr B05.

A systematic review of serum autoantibodies as biomarkers for pancreatic cancer detection.

Pancreatic cancer is a leading cause of cancer-related deaths in the western world. Patients with pancreatic cancer have poor prognosis, partly due to difficulties in detecting it at early stages. While different markers have been associated with pancreatic cancer, many of them show suboptimal sensitivity and specificity. Serum autoantibodies against tumor-associated antigens have recently emerged as early stage biomarkers for different types of cancers. Given the urgent need for early and reliable biomarkers for pancreatic cancer, we undertook a systematic review of the published literature to identify primary articles that evaluated serum autoantibodies in pancreatic cancer detection by searching PubMed and ISI Web of Knowledge. Two reviewers extracted data on study characteristics and results independently. Overall, 31 studies evaluating 124 individual serum autoantibodies in pancreatic cancer detection met the inclusion criteria. In general, single autoantibody markers showed relatively low sensitivities at high specificity. A combination of markers, either multiple serum autoantibodies or serum autoantibodies combined with tumor-associated markers, led to a better diagnostic performance. However, most of the analyzed autoantibodies have only been reported in single studies and therefore need to be independently validated. We conclude that serum autoantibodies might present an option as biomarkers for early detection of pancreatic cancer, but more work is needed to identify and validate autoantibody signatures that are associated with early stage pancreatic cancer.

Autoantibody signatures defined by serological proteome analysis in sera from patients with cholangiocarcinoma.

BackgroundThe challenging diagnosis and poor prognosis of cholangiocarcinoma require the determination of biomarkers. Autoantibodies could be used in the clinic as diagnostic markers for the early detection of tumours. By proteomic approaches, several autoantibodies were proposed as potential markers. We tried in this study, to perform a serological proteome analysis, using various antigenic substrates, including tumours and human liver.MethodsSera from patients (n = 13) and healthy donors (n = 10) were probed on immunoblots performed using 2-dimensionally separated proteins from cholangiocarcinoma cell lines (CCLP1 and CCSW1), from the liver of healthy subject and interestingly, from tumour and adjacent non-tumour liver tissues from five patients with cholangiocarcinoma and tested with their corresponding serum. Spots of interest were identified using mass spectrometry and classified according gene ontology analysis.ResultsA comparison of the whole immunoblotting patterns given by cholangiocarcinoma sera against those obtained with normal control sera enabled the definition of 862 spots. Forty-five different proteins were further analysed, corresponding to (1) spots stained with more than four of 13 (30 %) sera tested with the CCLP1 or the CCSW1 cell line and with the normal liver, and (2) to spots immunoreactive with at least two of the five sera probed with their tumour and non-tumour counter-part of cholangiocarcinoma. Immunoreactive proteins with catalytic activity as molecular function were detected at rates of 93 and 64 % in liver from healthy subjects or cholangiocarcinoma non-tumour tissues respectively, compared to 43, 33, 33 % in tumour tissues, or CCSW1 and CCLP1 cell lines. A second pattern was represented by structural proteins with rates of 7 and 7 % in normal liver or non-tumour tissues compared to 14, 33 and 67 % in tumour tissue, CCSW1 or CCLP1 cell lines. Proteins with a binding function were detected at rates of 7 % in non-tumour tissue and 14 % in tumour tissue. Using the extracted tumour tissue, serotransferrin was targeted by all cholangiocarcinoma-related sera.ConclusionsImmunological patterns depended on the type of antigen substrate used; i.e. tumour versus non tumour specimens. Nevertheless, a combination of multiple autoantibodies tested with the most appropriate substrate might be more sensitive and specific for the diagnosis of cholangiocarcinoma.Electronic supplementary materialThe online version of this article (doi:10.1186/s12967-015-0751-2) contains supplementary material, which is available to authorized users.

Autoantibody Profiling of Glioma Serum Samples to Identify Biomarkers Using Human Proteome Arrays.

The heterogeneity and poor prognosis associated with gliomas, makes biomarker identification imperative. Here, we report autoantibody signatures across various grades of glioma serum samples and sub-categories of glioblastoma multiforme using Human Proteome chips containing ~17000 full-length human proteins. The deduced sets of classifier proteins helped to distinguish Grade II, III and IV samples from the healthy subjects with 88, 89 and 94% sensitivity and 87, 100 and 73% specificity, respectively. Proteins namely, SNX1, EYA1, PQBP1 and IGHG1 showed dysregulation across various grades. Sub-classes of GBM, based on its proximity to the sub-ventricular zone, have been reported to have different prognostic outcomes. To this end, we identified dysregulation of NEDD9, a protein involved in cell migration, with probable prognostic potential. Another subcategory of patients where the IDH1 gene is mutated, are known to have better prognosis as compared to patients carrying the wild type gene. On a comparison of these two cohorts, we found STUB1 and YWHAH proteins dysregulated in Grade II glioma patients. In addition to common pathways associated with tumourigenesis, we found enrichment of immunoregulatory and cytoskeletal remodelling pathways, emphasizing the need to explore biochemical alterations arising due to autoimmune responses in glioma.