Tumour auto-antibody screening: performance of protein microarrays using SEREX derived antigens

Patients with Systemic Juvenile Idiopathic Arthritis (SJIA) Show Differences in Autoantibody Signatures Based on Disease Activity

Systemic juvenile idiopathic arthritis (SJIA) is a severe rheumatic disease in children. It is a subgroup of juvenile idiopathic arthritis (JIA; MIM #604302), which is the most common rheumatic disease in children. The diagnosis of SJIA often comes with a significant delay, and the classification between autoinflammatory and autoimmune disease is still discussed. In this study, we analyzed the immunological responses of patients with SJIA, using human proteome arrays presenting immobilized recombinantly expressed human proteins, to analyze the involvement of autoantibodies in SJIA. Results from group comparisons show several differentially reactive antigens involved in inflammatory processes. Intriguingly, many of the identified antigens had a high reactivity against proteins involved in the NF-κB pathway, and it is also notable that many of the detected DIRAGs are described as dysregulated in rheumatoid arthritis. Our data highlight novel proteins and pathways potentially dysregulated in SJIA and offer a unique approach to unraveling the underlying disease pathogenesis in this chronic arthropathy.

Antibody Profiling and In Silico Functional Analysis of Differentially Reactive Antibody Signatures of Glioblastomas and Meningiomas

Studies on tumor-associated antigens in brain tumors are sparse. There is scope for enhancing our understanding of molecular pathology, in order to improve on existing forms, and discover new forms, of treatment, which could be particularly relevant to immuno-oncological strategies. To elucidate immunological differences, and to provide another level of biological information, we performed antibody profiling, based on a high-density protein array (containing 8173 human transcripts), using IgG isolated from the sera of n = 12 preoperative and n = 16 postoperative glioblastomas, n = 26 preoperative and n = 29 postoperative meningiomas, and n = 27 healthy, cancer-free controls. Differentially reactive antigens were compared to gene expression data from an alternate public GBM data set from OncoDB, and were analyzed using the Reactome pathway browser. Protein array analysis identified approximately 350-800 differentially reactive antigens, and revealed different antigen profiles in the glioblastomas and meningiomas, with approximately 20-30%-similar and 10-15%-similar antigens in preoperative and postoperative sera, respectively. Seroreactivity did not correlate with OncoDB-derived gene expression. Antigens in the preoperative glioblastoma sera were enriched for signaling pathways, such as signaling by Rho-GTPases, COPI-mediated anterograde transport and vesicle-mediated transport, while the infectious disease, SRP-dependent membrane targeting cotranslational proteins were enriched in the meningiomas. The pre-vs. postoperative seroreactivity in the glioblastomas was enriched for antigens, e.g., platelet degranulation and metabolism of lipid pathways; in the meningiomas, the antigens were enriched in infectious diseases, metabolism of amino acids and derivatives, and cell cycle. Antibody profiling in both tumor entities elucidated several hundred antigens and characteristic signaling pathways that may provide new insights into molecular pathology and may be of interest for the development of new treatment strategies.

Functional Analysis of Autoantibody Signatures in Rheumatoid Arthritis

For the identification of antigenic protein biomarkers for rheumatoid arthritis (RA), we conducted IgG profiling on high density protein microarrays. Plasma IgG of 96 human samples (healthy controls, osteoarthritis, seropositive and seronegative RA, n = 24 each) and time-series plasma of a pristane-induced arthritis (PIA) rat model (n = 24 total) were probed on AIT’s 16k protein microarray. To investigate the analogy of underlying disease pathways, differential reactivity analysis was conducted. A total of n = 602 differentially reactive antigens (DIRAGs) at a significance cutoff of p < 0.05 were identified between seropositive and seronegative RA for the human samples. Correlation with the clinical disease activity index revealed an inverse correlation of antibodies against self-proteins found in pathways relevant for antigen presentation and immune regulation. The PIA model showed n = 1291 significant DIRAGs within acute disease. Significant DIRAGs for (I) seropositive, (II) seronegative and (III) PIA were subjected to the Reactome pathway browser which also revealed pathways relevant for antigen presentation and immune regulation; of these, seven overlapping pathways had high significance. We therefore conclude that the PIA model reflects the biological similarities of the disease pathogenesis. Our data show that protein array analysis can elucidate biological differences and pathways relevant in disease as well be a useful additional layer of omics information.

A Novel Method to Identify Autoantibodies against Putative Target Proteins in Serum from beta-Thalassemia Major: A Pilot Study

Abnormal immune reactivity in patients with beta-thalassemia (beta-thal) major can be associated with poor prognosis. Immunome protein-array analysis represents a powerful approach to identify novel biomarkers. The Sengenics Immunome Protein Array platform was used for high-throughput quantification of autoantibodies in 12 serum samples collected from nine beta-thal major patients and three non-thalassemia controls, which were run together with two pooled normal sera (Sengenics Internal QC samples). To obtain more accurate and reliable results, the evaluation of the biological relevance of the shortlisted biomarkers was analyzed using an Open Target Platform online database. Elevated autoantibodies directed against 23 autoantigens on the immunome array were identified and analyzed using a penetrance fold change-based bioinformatics method. Understanding the autoantibody profile of beta-thal major patients would help to further understand the pathogenesis of the disease. The identified autoantigens may serve as potential biomarkers for the prognosis of beta-thal major.

IgG based immunome analyses of breast cancer patients reveal underlying signaling pathways

Background: Breast cancer is the most frequent and one of the most fatal malignancies among women. Within the concept of personalized medicine, molecular characterization of tumors is usually performed by analyzing somatic mutations, RNA gene expression signatures or the proteome by mass-spectrometry. Alternatively, the immunological fingerprint of the patients can be analyzed by protein microarrays, which is able to provide another layer of molecular pathological information without invasive intervention.

Results: We have investigated the immune signature of breast cancer patients and compared them with healthy controls, using protein microarray-based IgG profiling. The identified differentially reactive antigens (n=517) were further evaluated by means of various pathway analysis tools. Our results indicate that the immune signature of breast cancer patients shows a clear distinction from healthy individuals characterized by differentially reactive antigens involved in known disease relevant signaling pathways, such as VEGF, AKT/PI3K/mTOR or c-KIT, which is in close agreement with the findings from RNA-based expression profiles.

Conclusion: Differential antigenic properties between breast cancer patients and healthy individual classes can be defined by serum-IgG profiling on protein microarrays. These immunome profiles provide an additional layer of molecular pathological information, which has the potential to refine and complete the systems biological map of neoplastic disease.

Autoantibodies as Potential Biomarkers in Breast Cancer

Breast cancer is a major cause of mortality in women; however, technologies for early stage screening and diagnosis (e.g., mammography and other imaging technologies) are not optimal for the accurate detection of cancer. This creates demand for a more effective diagnostic means to replace or be complementary to existing technologies for early discovery of breast cancer. Cancer neoantigens could reflect tumorigenesis, but they are hardly detectable at the early stage. Autoantibodies, however, are biologically amplified and hence may be measurable early on, making them promising biomarkers to discriminate breast cancer from healthy tissue accurately. In this review, we summarized the recent findings of breast cancer specific antigens and autoantibodies, which may be useful in early detection, disease stratification, and monitoring of treatment responses of breast cancer.

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 potential serological prostate cancer biomarkers using CT100+ cancer antigen microarray platform in a multi-cultural South African cohort

There is a growing need for high throughput diagnostic tools for early diagnosis and treatment monitoring of prostate cancer (PCa) in Africa. The role of cancer-testis antigens (CTAs) in PCa in men of African descent is poorly researched. Hence, we aimed to elucidate the role of 123 Tumour Associated Antigens (TAAs) using antigen microarray platform in blood samples (N = 67) from a South African PCa, Benign prostatic hyperplasia (BPH) and disease control (DC) cohort. Linear (fold-over-cutoff) and differential expression quantitation of autoantibody signal intensities were performed. Molecular signatures of candidate PCa antigen biomarkers were identified and analyzed for ethnic group variation. Potential cancer diagnostic and immunotherapeutic inferences were drawn. We identified a total of 41 potential diagnostic/therapeutic antigen biomarkers for PCa. By linear quantitation, four antigens, GAGE1, ROPN1, SPANXA1 and PRKCZ were found to have higher autoantibody titres in PCa serum as compared with BPH where MAGEB1 and PRKCZ were highly expressed. Also, p53 S15A and p53 S46A were found highly expressed in the disease control group. Statistical analysis by differential expression revealed twenty-four antigens as upregulated in PCa samples, while 11 were downregulated in comparison to BPH and DC (FDR = 0.01). FGFR2, COL6A1and CALM1 were verifiable biomarkers of PCa analysis using urinary shotgun proteomics. Functional pathway annotation of identified biomarkers revealed similar enrichment both at genomic and proteomic level and ethnic variations were observed. Cancer antigen arrays are emerging useful in potential diagnostic and immunotherapeutic antigen biomarker discovery.

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.

Immune-Signatures for Lung Cancer Diagnostics: Evaluation of Protein Microarray Data Normalization Strategies

New minimal invasive diagnostic methods for early detection of lung cancer are urgently needed. It is known that the immune system responds to tumors with production of tumor-autoantibodies. Protein microarrays are a suitable highly multiplexed platform for identification of autoantibody signatures against tumor-associated antigens (TAA). These microarrays can be probed using 0.1 mg immunoglobulin G (IgG), purified from 10 µL of plasma. We used a microarray comprising recombinant proteins derived from 15,417 cDNA clones for the screening of 100 lung cancer samples, including 25 samples of each main histological entity of lung cancer, and 100 controls. Since this number of samples cannot be processed at once, the resulting data showed non-biological variances due to “batch effects”. Our aim was to evaluate quantile normalization, “distance-weighted discrimination” (DWD), and “ComBat” for their effectiveness in data pre-processing for elucidating diagnostic immune-signatures. “ComBat” data adjustment outperformed the other methods and allowed us to identify classifiers for all lung cancer cases versus controls and small-cell, squamous cell, large-cell, and adenocarcinoma of the lung with an accuracy of 85%, 94%, 96%, 92%, and 83% (sensitivity of 0.85, 0.92, 0.96, 0.88, 0.83; specificity of 0.85, 0.96, 0.96, 0.96, 0.83), respectively. These promising data would be the basis for further validation using targeted autoantibody tests.

The pre-analytical processing of blood samples for detecting biomarkers on protein microarrays

Specimen collection method and quality insurance are pivotal in biomarker discovery. Pre-analytical variables concerning blood collection and sample handling might affect analytical results and should be standardised prior application. In this study, we examine pre-analytical characteristics of blood samples using protein microarray. The influences of 1) standby times until centrifugation (1 h, 4 h, 24 h and 48 h), 2) four blood collection methods, and 3) IgG purified from those samples on differentially reactive antigens between samples ("DIRAGs") were investigated. Spearman correlation analyses of intra-individual arrays demonstrated remarkable differences (0.75-0.98 vs. 0.5-0.75) of antibody reactivities within and between serum and plasma samples. Class comparison showed that reactive antigen profiles were best preserved using IgG purified samples of serum tubes without separation gel as after 24h 83% of the 1h baseline DIRAGs were re-found. Testing dilution series with protein microarrays and Luminex xMap® Technology, we found linear correlations (R(2) = 0.94-0.99) between IgG concentration and read-out when using purified IgG instead of serum. Therefore, we highly recommend standardising pre-analytics and proposing the use of purified IgG for autoantibody immune-profiling with protein microarrays to reduce potential unspecific binding of matrix proteins abundant in serum and plasma samples.

SIGNIFICANCE

Although purified IgG cannot completely compensate the influence of pre-analytics, in highly parallel immune-profiling IgG enables reduction of unspecific effects, which occur when using serum or plasma for analysis on protein microarrays. Reproducibility problems due to pre-analytical processing of blood samples might explain discrepant results reported in various biomarker studies.

A microarray method for identifying tumor antigens by screening a tumor cDNA expression library against cancer sera

The immune system responds to tumor cells. The challenge has been how to effectively use these responses to treat or protect against cancer. Toward the goal of developing a cancer vaccine, we are pursuing methodologies for the discovery and testing of useful antigens. We present an array-based approach for discovering these B cell antigens by directly screening for specific host-sera reactivity to lysates from tumor-derived cDNA expression libraries. Several cancer-specific antigens were identified, and these are currently being validated as potential candidates.

Autoantibody against WD repeat domain 1 is a novel serological biomarker for screening of thyroid neoplasia

BACKGROUND

Thyroid nodules are common among adults, and accurate diagnosis is critical in for management decisions. Ultrasound and fine needle aspiration cytology are the most common methods to evaluate nodules, but they are not practical for screening large numbers of patients because of cost and time considerations.

OBJECTIVE

The aim of this study was to isolate an autoantibody to tumour antigen, WD repeat domain 1 (WDR1), and evaluate its diagnostic sensitivity and specificity for thyroid neoplasms.

PATIENTS AND METHODS

We investigated serological biomarkers in patients with thyroid carcinoma who had a poor prognosis. Using a serological analysis of recombinant cDNA expression cloning (SEREX) strategy, we isolated WDR1 and its specific autoantibody in the sera of patients with undifferentiated thyroid carcinoma (UTC). We examined using indirect ELISA, the titre of the anti-WDR1 antibody (AWA) in 54 study patients: 10 with UTC, 20 with papillary thyroid carcinoma (PTC), 17 with benign thyroid nodule (BTN), 7 with autoimmune thyroid disease (AITD), as well as 38 controls (N).

RESULTS

WDR1 was ubiquitously expressed in various types of thyroid tissues. However, the titre of AWA in UTC and PTC was significantly higher than that in BTN, AITD and N (P < 0·001). No significant correlation was observed between thyroid function, serum thyroglobulin and tumour diameter. The cut-off value estimated using ROC to differentiate malignancies from others was 0·95 (sensitivity 96·7%, specificity 91·9%, AUC 0·969, P < 0·001).

CONCLUSIONS

Anti-WDR1 antibody could be a novel approach for serological screening of PTC and UTC, and could be an efficient and inexpensive biomarker.

New targets for the immunotherapy of colon cancer-does reactive disease hold the answer?

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers in both men and women, posing a serious demographic and economic burden worldwide. In the United Kingdom, CRC affects 1 in every 20 people and it is often detected once well established and after it has spread beyond the bowel (Stage IIA-C and Stage IIIA-C). A diagnosis at such advanced stages is associated with poor treatment response and survival. However, studies have identified two sub-groups of post-treatment CRC patients--those with good outcome (reactive disease) and those with poor outcome (non-reactive disease). We aim to review the state-of-the-art for CRC with respect to the expression of cancer-testis antigens (CTAs) and their identification, evaluation and correlation with disease progression, treatment response and survival. We will also discuss the relationship between CTA expression and regulatory T-cell (Treg) activity to tumorigenesis and tumor immune evasion in CRC and how this could account for the clinical presentation of CRC. Understanding the molecular basis of reactive CRC may help us identify more potent novel immunotherapeutic targets to aid the effective treatment of this disease. In this review, based on our presentation at the 2012 International Society for the Cell and Gene Therapy of Cancer annual meeting, we will summarize some of the most current advances in CTA and CRC research and their influence on the development of novel immunotherapeutic approaches for this common and at times difficult to treat disease.