Background The ligand-activated transcription factor, AHR (aryl hydrocarbon receptor) is an important regulator of different biological process including angiogenesis, hematopoiesis, drug and lipid metabolism, cell motility, and immune modulation. AHR activating ligands are found in the environment (e.g., dioxin), but are also generated endogenously, for example by tryptophan catabolizing enzymes (e.g., IDO1, TDO2, IL4I1).1,2,3 AHR activation can lead to immunosuppression, thus limiting response to therapy. AHR activity is increased in cancer and efforts are ongoing to decipher the AHR-mediated immune modulation in the crosstalk between cancer and the tumor microenvironment. Methods By combining analysis of gene expression data from over 10,000 tumors in 32 different cancers and natural language processing we developed a pan-cancer AHR transcriptional gene signature (PAHR) that allows detecting the status of AHR activation in a cell and ligand independent manner. We built a plug & play pipeline using PAHR, which employs multiple machine learning methods for AHR target biomarker discovery. Results Using PAHR, we profiled transcriptomics and amino acid metabolic profiles of 32 different cancers that associate with the production of AHR activating ligands. Furthermore, we used PAHR to characterize AHR specific cancer subtypes showing various AHR-mediated immunosuppressive functions. In most cancers, the AHR cancer subtypes reflected worse overall survival outcome with increasing AHR activity. Functional characterization of bladder cancer AHR subtypes showed that AHR mediates different transcriptional programs leading to similar survival outcomes using different immunosuppressive modules. Some cancer subtypes showed better survival outcome associated with high AHR activity, indicating that AHR can play both tumor promoting and suppressive roles. Conclusions PAHR integrative analysis detects different patterns of AHR activities across cancers with significant induction of immunosuppression in cancers leading to the development of distinct patient strata on a pan-cancer level. We conclude that assessment of AHR-activity by way of PAHR presents as a new stratification strategy in immune oncology. PAHR will improve patient selection in clinical trials, and therapy selection of todays and future cancer immunotherapies to improve response to treatment for the individual patient. References Sadik A, Somarribas Patterson LF, Öztürk S, Mohapatra SR, …Trump S, Seiffert M, Opitz CA. IL4I1 Is a Metabolic Immune Checkpoint that Activates the AHR and Promotes Tumor Progression. Cell. 2020 Aug 17:S0092–8674(20)30946–6. Opitz CA, Litzenburger UM, …, Wick W, Platten M. An endogenous tumour-promoting ligand of the human aryl hydrocarbon receptor. Nature. 2011 Oct 5;478 (7368):197–203. Panitz V, Končarević S, Sadik , …Platten M, Wick W, Opitz CA. Tryptophan metabolism is inversely regulated in the tumor and blood of patients with glioblastoma. Theranostics. 2021 Sep 3;11(19):9217–9233. Ethics Approval Metastatic melanoma samples were obtained from the section of dermatooncology in the National Center for Tumor Diseases (NCT), Heidelberg, Germany, under the ethics board approval S-207/2005. Participants gave informed consent before taking part in the study.

Tryptophan (Trp)-catabolic enzymes (TCEs) produce metabolites that activate the aryl hydrocarbon receptor (AHR) and promote tumor progression and immunosuppression in glioblastoma. As therapies targeting TCEs or AHR become available, a better understanding of Trp metabolism is required. Methods: The combination of LC-MS/MS with chemical isobaric labeling enabled the simultaneous quantitative comparison of Trp and its amino group-bearing metabolites in multiple samples. We applied this method to the sera of a cohort of 43 recurrent glioblastoma patients and 43 age- and sex-matched healthy controls. Tumor volumes were measured in MRI data using an artificial neural network-based approach. MALDI MSI visualized Trp and its direct metabolite N-formylkynurenine (FK) in glioblastoma tissue. Analysis of scRNA-seq data was used to detect the presence of Trp metabolism and AHR activity in different cell types in glioblastoma. Results: Compared to healthy controls, glioblastoma patients showed decreased serum Trp levels. Surprisingly, the levels of Trp metabolites were also reduced. The decrease became smaller with more enzymatic steps between Trp and its metabolites, suggesting that Trp availability controls the levels of its systemic metabolites. High tumor volume associated with low systemic metabolite levels and low systemic kynurenine levels associated with worse overall survival. MALDI MSI demonstrated heterogeneity of Trp catabolism across glioblastoma tissues. Analysis of scRNA-seq data revealed that genes involved in Trp metabolism were expressed in almost all the cell types in glioblastoma and that most cell types, in particular macrophages and T cells, exhibited AHR activation. Moreover, high AHR activity associated with reduced overall survival in the glioblastoma TCGA dataset. Conclusion: The novel techniques we developed could support the identification of patients that may benefit from therapies targeting TCEs or AHR activation.

Background and Aims Systemic Lupus Erythematosus (SLE) is a complex, multifactorial autoimmune disease mediated by the deposition of immune complexes in tissues such as the kidney, skin and brain, with the ensuing inflammatory cascade driving progressive tissue damage and dysfunction. Mice lacking Lyn tyrosine kinase (Lyn mice) develop an autoimmune disease similar to SLE, driven by dysregulation of the immune system, immune complex deposition in tissue and systemic inflammation culminating in progressive glomerulonephritis. The gut microbiome has been shown to have an immunoregulatory effect on the development of autoimmune and inflammatory diseases, in large part due to the production of short chain fatty acids from the fermentation of dietary fibre. Methods To determine whether dietary fibre could moderate systemic autoimmune and inflammatory pathology, Lyn mice and control C57BL6/J mice were fed a high fibre diet (HFD) or a standard control diet from weaning until 42 weeks old. Results On the control diet, Lyn mice developed dysbiosis, lymphopenia, splenomegaly from enhanced splenic myelopoiesis, hyperactivation of immune cells, and pathogenic IgG antidsDNA autoantibodies that deposited in the kidney glomeruli leading to glomerulonephritis. These hallmarks of inflammation and autoimmune disease were significantly reduced in Lyn mice fed a HFD, indicating that dietary intervention is effective at dampening chronic systemic inflammation and glomerular pathology. Conclusions These findings highlights the contribution of diet and the gut microbiome in regulating systemic immune responses and controlling autoimmunity, inflammation, and preventing the progression of immunopathology and suggests that fibre supplementation may improve outcomes for those living with SLE or other chronic systemic inflammatory diseases.

Abstract Objective To assess the diagnostic potential of IgG antibodies to citrullinated and corresponding native autoantigens in early arthritis. Methods IgG autoantibodies to 390 distinct unmodified and corresponding in vitro citrullinated recombinant proteins were measured by a multiplex assay in baseline blood samples from a German multicenter national cohort of 411 early arthritis patients (56.5 ± 14.6 years, 62.8% female). The cohort was randomly split into a training cohort (n = 329, 28.6% ACPA positive) and a validation cohort (n = 82, 32.9% ACPA pos.). The diagnostic properties of candidate antibodies to predict a subsequent diagnosis of rheumatoid arthritis (RA) as opposed to a non-RA diagnosis were assessed by receiver operating characteristics analysis and generalized linear modeling (GLM) with Bonferroni correction in comparison to clinically determined IgM rheumatoid factor (RF) and citrullinated peptide antibody (ACPA) status. Results Of 411 patients, 309 (75.2%) were classified as RA. Detection rates of antibody responses to citrullinated and uncitrullinated forms of the proteins were weakly correlated (Spearman’s r = 0.13 (95% CI 0.029–0.22), p = 0.01). The concentration of 34 autoantibodies (32 to citrullinated and 2 to uncitrullinated antigens) was increased at least 2-fold in RA patients and further assessed. In the training cohort, a significant association of citrullinated “transformer 2 beta homolog” (cTRA2B)-IgG with RA was observed (OR 5.3 × 103, 95% CI 0.8 × 103–3.0 × 106, p = 0.047). Sensitivity and specificity of cTRA2B-IgG (51.0%/82.9%) were comparable to RF (30.8%/91.6%) or ACPA (32.1%/94.7%). Similar results were obtained in the validation cohort. The addition of cTRA2B-IgG to ACPA improved the diagnostic performance over ACPA alone (p = 0.026 by likelihood ratio test). Conclusions cTRA2B-IgG has the potential to improve RA diagnosis in conjunction with RF and ACPA in early arthritis.

Background RA patients who are ACPA-positive (ACPA+) are known to have worse prognosis. Less is known regarding predictors of treatment outcomes in ACPA-negative (ACPA-) patients. Objectives We investigated whether autoantibodies captured on a custom array were associated with response to therapy in ACPA- RA patients. Methods RA patients were recruited to either the Biologics in RA Genetics and Genomics Study Syndicate (BRAGGSS, starting adalimumab, established disease) or the RA Medication Study (RAMS, starting methotrexate, early disease). Serum samples were collected at pre-treatment and 3/6 months in BRAGGSS/RAMS, respectively. Treatment groups were pooled for analysis. ACPA was measured using a commercially available ELISA (Axis-Shield Diagnostics Ltd, Dundee, UK). Pre-treatment RA and healthy blood donor control (HC) serum samples were incubated on a bead-based assay (Luminex FlexMap 3D) containing 376 human protein antigens associated with autoimmune disease (39 in citrullinated (cit) form) to detect autoantibodies. Median fluorescence intensity (MFI) values were calculated for each autoantibody for RA and HC, then normalised and log2-transformed. The 95th percentile for each autoantibody in HC was used to determine whether an RA sample was positive/negative for that autoantibody. Proteins with <10% frequency in RA patients were excluded from analysis. Linear regression was used to determine autoantibodies differing in MFI between RA and HC; p-values were adjusted using the Benjamini-Hochberg correction. Significant autoantibodies (adjusted p<0.05) were tested for associations with treatment outcomes in RA patients only using: (i) linear regression for improvement in DAS28; (ii) logistic regression for good/poor vs all EULAR response. All regression was adjusted for age, gender, disease duration and baseline DAS28. Subanalysis was carried out in a subset of ACPA-patients. Results 168 patients with RA were included in analysis (mean age 59.6 years, mean disease duration 14.3 years, 126 (75%) female patients, 90 (53.6%) ACPA+ patients). 34 autoantibodies were differentially expressed in RA patients, only one of which (TNF ligand superfamily member 13, TNFSF13) was lower than in HC. 29/34 autoantigens were in cit-form. In multivariate models of all differentially expressed autoantibodies, heterogeneous nuclear ribonucleoprotein A1 (HNRNPA1) was significantly associated with EULAR response (coefficient (coef) 0.7, 95% CI 0.1-1.3), and cit-vimentin (VIM) was significantly associated with poor EULAR response (ORadj 4.2, 95% CI 1.1-18.3) and reduced odds of good EULAR response (ORadj 0.2, 95% CI 0.1-0.8). ACPA remained the best predictor of treatment response. In a subanalysis of the 78 ACPA-patients, cit-cleavage and polyadenylation specificity factor subunit 6 (CPSF6) was significantly associated with worse DAS28 (coef (-1.8), 95% CI (-3.6)-(-0.1)). cit-DnaJ homolog subfamily B member 1 (DNAJB1) was significantly associated with DAS28 improvement (coef 2.2, 95% CI 0.6-3.8). No autoantibody was associated with EULAR response. Conclusion A subset of ACPA-patients have ACPA fine specificities not seen by a commercial assay. Larger ACPA profiling may provide additional information on treatment response. This requires validation with larger sample sizes and replication in an independent cohort. Reference [1] Ann Rheum Dis2013;72:844. 2. Arthritis Res Ther2016;18:235. Disclosure of Interests Stephanie Ling: None declared, Nisha Nair: None declared, Darren Plant: None declared, Hans-Dieter Zucht Employee of: Hans-Dieter Zucht is an employee of Protagen AG, Petra Budde Employee of: Petra Budde is an employee of Protagen AG, Peter Schulz-Knappe Shareholder of: Peter Schulz-Knappe is a shareholder of Protagen AG, Consultant for: Peter Schulz-Knappe is a consultant to Protagen AG, Employee of: Peter Schulz-Knappe was an employee of Protagen AG, MATURA Consortium: None declared, Anne Barton: None declared

OBJECTIVE:To investigate the role of epitope spreading in established systemic lupus erythematosus (SLE).METHODS:IgG autoantibody reactivity with 398 distinct recombinant proteins was measured over a period of 6 years in 69 SLE patients and compared to that in 45 controls. Changes in mean fluorescence intensity (MFI), number of autoantibodies to distinct antigens, and reactivity with distinct clones of established antigenic targets (e.g., U1 RNP, Sm, and ribosomal P) representing epitope fine mapping were assessed. Linear mixed modeling, adjusted with Bonferroni correction for age and sex, was applied.RESULTS:The total number of autoantibodies, mean MFI, and number of autoantibodies in epitope fine mapping were higher in SLE patients compared to controls (P < 0.0001). The total number of antibodies to distinct autoantigens remained stable over time, while the mean MFI decreased over time in SLE (P < 0.021). SLE patients showed variable recognition of epitopes in fine mapping over time. In particular, in SLE patients, more clones of the U1 RNP complex were recognized at the time of new organ involvement (+0.65) (P = 0.007). Mean MFI was higher in patients with lupus nephritis (P = 0.047). The time-averaged MFIs of 22 individual autoantibodies (including double-stranded DNA [dsDNA]) were higher, after Bonferroni correction, in SLE (P < 0.0001). The MFIs of dsDNA and histone cluster 2 H3c were associated with scores on the Systemic Lupus Activity Measure (P < 0.0001).CONCLUSION:Longitudinal surveillance of the IgG autoantibody repertoire in established SLE reveals evidence of sustained breadth of autoantibody repertoire without significant expansion. Associations of disease activity with dsDNA and with histone H3 autoantibodies were confirmed.

Seropositivity for anti-citrullinated peptide antibodies (ACPA) in patients with rheumatoid arthritis (RA), a chronic autoimmune arthritis, is associated with worse long-term disease outcomes. ACPA is ubiquitously tested in RA patients, but other autoantibodies exist (in both citrullinated and non-citrullinated form) which may provide additional information on RA subtypes and/or treatment response. We used a multiplex bead-based assay of 376 autoantibodies to test associations between these autoantibodies and treatment response in RA patients. Clusters of patients with similar autoantibody expression were defined and cluster membership was associated with treatment response. Thirty-four autoantibodies were differentially expressed in RA patients compared with healthy controls; citrullinated vimentin was associated with treatment response. A selection of citrullinated autoantibodies was found to be associated with treatment response in a subanalysis of ACPA-negative RA patients. Finer ACPA specificities in ACPA-negative RA patients may be predictive of treatment response and could represent a rich vein of future study.

Multiplex assays for autoantibodies have shown utility both in research towards understanding the basic biology of autoimmune disease, and as tools for clinical diagnosis. New label-free multiplex analysis methods have the potential to streamline both the process of assay development and assay workflow. We report fabrication and testing of a 5-plex autoantigen microarray using the Arrayed Imaging Reflectometry (AIR) platform. This label-free technology provides rapid, sensitive, and quantitative detection of an arbitrary number of analytes in a standard multiwell format. In this work, we demonstrate that AIR is able to detect antibodies to Ro60, La/SSB, Scl-70, BicD2, and Ro52 in single-donor human serum samples with multiplex results comparable to singleplex ELISA or Luminex assays.

Genetic Engineering & Biotechnology NewsVol. 38, No. 12 Translational MedicinePrevent Cancer Immunotherapy's Side EffectsProtagen Believes Immuno-Oncology Must Predict and Minimize Immune-Related Adverse EventsPeter K. Schulz-Knappe and Georg LautschamPeter K. Schulz-KnappePeter K. Schulz-Knappe, M.D., is chief scientific officer and Georg Lautscham, Ph.D. (E-mail Address: georg.lautscham@protagen.com) is chief business officer at Protagen. Website: www.protagen.com.Search for more papers by this author and Georg LautschamPeter K. Schulz-Knappe, M.D., is chief scientific officer and Georg Lautscham, Ph.D. (E-mail Address: georg.lautscham@protagen.com) is chief business officer at Protagen. Website: www.protagen.com.Search for more papers by this authorPublished Online:11 Jun 2018https://doi.org/10.1089/gen.38.12.12AboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetailsCited byA Novel Method for Controlled Gene Expression via Combined Bleomycin and Plasmid DNA Electrotransfer19 August 2019 | International Journal of Molecular Sciences, Vol. 20, No. 16 Volume 38Issue 12Jun 2018 InformationCopyright © GEN PublishingTo cite this article:Peter K. Schulz-Knappe and Georg Lautscham.Prevent Cancer Immunotherapy's Side Effects.Genetic Engineering & Biotechnology News.Jun 2018.28-29.http://doi.org/10.1089/gen.38.12.12Published in Volume: 38 Issue 12: June 11, 2018PDF download

OBJECTIVES:To identify predictors of remission and disease activity patterns in patients with rheumatoid arthritis (RA) using individual participant data (IPD) from clinical trials.METHODS:Phase II and III clinical trials completed between 2002 and 2012 were identified by systematic literature review and contact with UK market authorisation holders. Anonymised baseline and follow-up IPD from non-biological arms were amalgamated. Multiple imputation was used to handle missing outcome and covariate information. Random effects logistic regression was used to identify predictors of remission, measured by the Disease Activity Score 28 (DAS28) at 6 months. Novel latent class mixed models characterised DAS28 over time.RESULTS:IPD of 3290 participants from 18 trials were included. Of these participants, 92% received methotrexate (MTX). Remission rates were estimated at 8.4%(95%CI 7.4%to9.5%) overall, 17%(95%CI 14.8%to19.4%) for MTX-naïve patients with early RA and 3.2% (95% CI 2.4% to 4.3%) for those with prior MTX exposure at entry. In prior MTX-exposed patients, lower baseline DAS28 and MTX reinitiation were associated with remission. In MTX-naïve patients, being young, white, male, with better functional and mental health, lower baseline DAS28 and receiving concomitant glucocorticoids were associated with remission. Three DAS28 trajectory subpopulations were identified in MTX-naïve and MTX-exposed patients. A number of variables were associated with subpopulation membership and DAS28 levels within subpopulations.CONCLUSIONS:Predictors of remission differed between MTX-naïve and prior MTX-exposed patients at entry. Latent class mixed models supported differential non-biological therapy response, with three distinct trajectories observed in both MTX-naïve and MTX-exposed patients. Findings should be useful when designing future RA trials and interpreting results of biomarker studies.

Objective Diagnosis of SLE relies on the detection of autoantibodies. We aimed to assess the diagnostic potential of histone H4 and H2A variant antibodies in SLE. Methods IgG-autoantibodies to histones H4 (HIST1H4A), H2A type 2-A (HIST2H2AA3) and H2A type 2-C (HIST2H2AC) were measured along with a standard antibody (SA) set including SSA, SSB, Sm, U1-RNP and RPLP2 in a multiplex magnetic microsphere-based assay in 153 SLE patients [85% female, 41 (13.5) years] and 81 healthy controls [77% female, 43.3 (12.4) years]. Receiver operating characteristic analysis was performed to assess diagnostic performance of individual markers. Logistic regression analysis was performed on a random split of samples to determine the additional value of histone antibodies in comparison with SA by likelihood ratio test and determination of diagnostic accuracy in the remaining validation samples. Results Microsphere-based assay showed good interclass correlation (mean 0.85, range 0.73-0.99) and diagnostic performance in receiver operating characteristic analysis (area under the curve (AUC) range 84.8-93.2) compared with routine assay for SA parameters. HIST1H4A-IgG was the marker with the best individual diagnostic performance for SLE vs healthy (AUC 0.97, sensitivity 95% at 90% specificity). HIST1H4A-IgG was an independent significant predictor for the diagnosis of SLE in multivariate modelling (P < 0.0001), and significantly improved prediction of SLE over SA parameters alone (residual deviance 45.9 vs 97.1, P = 4.3 × 10-11). Diagnostic accuracy in the training and validation samples was 89 and 86% for SA, and 95 and 89% with the addition of HIST1H4A-IgG. Conclusion HIST1H4A-IgG antibodies improve diagnostic accuracy for SLE vs healthy.

Purpose Autoimmune diseases arise from an abnormal immune response of the body against self-proteins leading to tissue and organ damage. The excessive production of harmful autoantibodies (AAB) is a hallmark of autoimmune diseases including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), systemic sclerosis (SSc) and Sjogren’s syndrome (SjS). Also in cancer research, it has been recently shown that AABs are useful to characterise patients. The characterisation of patient subgroups by means of stratification is essential for the efficient development of therapies, but often difficult due to the lack of appropriate biomarkers. Personalised or precision medicine approaches rely on appropriate multivariate multiplexing technology and data analysis. AABs serve as diagnostic markers for various autoimmune diseases, but the co-occurrence of AABs has rarely been analysed and is difficult to comprehend. Detecting a broad set of AABs helps to investigate the similarity between patients. A multiplex signature enables clustering for the investigation of relationships and patterns, which can be related to relevant clinical variables. Methods Here, we illustrate Luminex bead-based AAB assays using a set of 96 biomarker targets and their utility to characterise SLE and SSc as well as cancer study groups. Data analysis is based on bi-clustering algorithms and a prevalence and signature analysis of the markers. Cluster analysis was also performed using transformed data sets (qualitative) to investigate and visualise characteristic marker prevalence and co-prevalence patterns. Results Based on the individual marker pattern, patients can often be stratified belonging to different study subgroups. For example, for SLE we show that different reactivity groups exist including patients with different disease activity scores and organ damage patterns. Conclusions We conclude that the approach of a comprehensive prevalence and signature analysis and a vivid data visualisation is useful for any multiplex omics assay.

Background: Checkpoint inhibition is an effective treatment in patients with metastatic melanoma (MM). T cell activation can induce tumor rejection but also possibly severe autoimmune side effects (irAE). Autoantibody biomarkers from serum have potential to predict irAEs such as an ipilimumab-induced colitis. Methods: We use a cancer immunotherapy array consisting of 850 human protein antigens from 4 classes: 1. Tumor-associated antigens (TAA), 2. cancer pathway proteins, 3. autoimmune antigens, 4. cytokines/interleukins. Protein antigens were covalently coupled to magnetic beads and serum AABs were analyzed by Luminex FlexMap 3D. First, we screened pre-immunotherapy sera from 142 patients with MM (Heidelberg Cohort: 82 Ipilimumab (Ipi) treated; 11 Ipi/Nivolumab (Nivo); 40 Pembrolizumab (Pembro), 119 healthy controls (HC)). In this cohort, 41.5% (n = 59) experienced irAEs of any grade and 7% (n = 10) had colitis of grade 3 or 4. In a second study, 200 MM patients from 5 European sites (53 Ipi/Nivo; 111 Pembro, 100 HC) were analyzed. 25.6% (n = 42) had grade 3 or 4 irAEs, 12.8% (n = 21) had diarrhea or colitis of any grade and 9.8% (n = 16) had grade 3 or 4 colitis. Results: 40 different AABs were significantly more prevalent in MM compared to HC including NY-ESO1, NY-ESO 2 and other TAAs, cytokines, and nuclear proteins. Significant correlations of AABs were seen in Ipi-treated patients who experienced irAEs, both in mono- but also in combination therapy, allowing to dichotomize MM in risk groups. Also different sets of AABs were seen in Pembro-treated patients with irAEs. The protein antigens represent a variety of biological processes: they are involved in melanoma progression including transcription factors or components of the E3 ubiquitin ligase complex, cytokeratins, and proteins involved in cell adhesion. Conclusions: In MM, screening of AABs prior to start of Checkpoint inhibition holds potential to predict risk for irAEs such as colitis. As irAEs are especially frequent in Ipi-based treatment regimes, AABs presented here may serve as useful biomarkers for a risk-based treatment decision. Legal entity responsible for the study: Jessica C. Hassel and Protagen AG. Funding: Protagen AG. Disclosure: J.C. Hassel: Consulting role: Merck, Amgen; Honoraria: Bristol-Myers Squibb, Merck, Novartis, Roche and Pfizer; Science projects support: BMS. J. Mangana: Temporary advisory relationship and receives travel support: MSD, Merck. C. Pföhler: Consulting role: Merck Serono, Novartis, Roche, Amgen, BMS; Honoraria: Merck Serono, Novartis, Roche, Amgen, BMS. B. Weide: Consulting role: Curevac, Philogen, BMS; Honoraria: MSD, BMS, Roche, Amgen, Philogen; Science projects support: BMS, Philogen. L. Hakim-Meibodi: Travel grants: BMS. F. Meier: Honoraria: Roche, BMS, GSK, Novartis, MSD; Travel support: Roche, BMS; Research funding: Wyeth/Pfizer, Merck-Serono, Novartis. H.-D. Zucht, P. Budde; M. Tuschen: Employee: Protagen AG. P. Schulz-Knappe: Board member and chair holder: Protagen AG. All other authors have declared no conflicts of interest.

Nature Reviews Rheumatology 14, 53–60 (2018) In the version of this article originally published, the name of one of the authors, Peter Schulz-Knappe, was incorrectly given as Peter Schulze-Knappe. In addition, Mark Coles and James Butler were erroneously omitted from the list of members of the RA-MAP Consortium.

e15141 Background: Immune reactions in cancer involve cellular and humoral response and defense mechanisms. For example, therapies which target CTLA-4 and PD-1/PD-L1 pathways have led to significant improvements in patient care. Cancer therapy is emerging as a personalized approach requiring dedicated biomarkers and targets in immunology. Autoantibody profiling can provide such biomarker information of the immunological potency of a patient prior and during therapy to predict or monitor immune related adverse events or treatment efficacy. We present a technology for network analysis of cancer patient autoantibody reactivity connecting autoantibody patterns with clinical and demographic data. Methods: We constructed a Cancer Immunotherapy Array to perform large-scale multiplex profiling of patient autoantibody responses using antigen-coated Luminex beads. Run in MTPs, the array permits quantification of autoantibody reactivity in serum samples against > 900 human protein antigens. Bayesian network analysis is computed to investigate pairwise relationships of autoantibodies and clinical data, which is visualized as networks. Results: > 2,500 serum samples from diverse cancers and autoimmune diseases (RA, SLE, Sjogren) and HC were screened. In cancer, formation of autoantibodies is mainly directed against hypermutated proteins, surface proteins and cytokines, with roles in cancer progression, survival, and immune related adverse events. In contrast, classical autoimmune diseases show autoantibodies directed against nuclear proteins, structural complexes, such as ribosomes and DNA binding proteins. Autoantibody markers found in cancer can have diagnostic value, especially when used as multimarker panels. More important, investigation of autoantibody markers reveal networks suggesting that autoantibodies are involved in regulation of physiological reactions during cancer progression. Conclusions: Autoantibody profiling will broaden our understanding of the mechanisms of host defense, targeted therapies and may guide the prediction of novel targets in cancer.

Background Recent FDA-approved checkpoint inhibitors targeting the cytotoxic T-lymphocyte–associated antigen 4 (CTLA-4) and programmed death 1 (PD-1)/PD-L1 pathway represent milestones in the field of cancer immunotherapy. In general, cancer immunotherapy works only in a subset of patients, but some patients experience prolonged responses. Cancer immunotherapy can cause severe immune-related adverse events (irAE) in patients, who are increasingly seen by rheumatologists. We propose that that autoantibody profiling will reveal novel B-cell associated mechanisms of therapy response and side effects. This may yield minimally-invasive biomarkers to identify patients at risk to develop iRAE and monitor cancer patients over the course of their life under immunotherapy Objectives We have developed a novel Cancer Immunotherapy Array, which includes a combination of antigens important in autoimmune diseases, anti-tumour immunity, and oncogenes and tested the array in patient sera from a diverse set of cancer immunotherapy trials. Methods The Cancer Immunotherapy Array consists of a bead-based multiplex array using minimal patient serum samples incubated with antigen-coated, color-coded Luminex beads. Run in microtiter plate format, the Array permits quantification of the autoantibody reactivity in thousands of serum samples towards approximately 900 human protein antigens in each sample. Magnetic beads are employed to enable automated pipetting and washing steps.1 We selected human protein antigens from groups A) tumor-associated antigens (TAA), B) autoimmune disease antigens, C) cytokines, and D) cancer signalling pathway proteins Results In total, over 2000 serum samples from diverse cancer indications plus hundreds of samples from autoimmune diseases such as RA, SLE, Sjogren’s disease and healthy controls were screened with the Cancer Immunotherapy Array. As key findings we report autoantibody panels which can differentiate patients with irAEs and those without irAEs. Also, but less prominent, individual autoantibodies are associated with overall survival. Autoantibodies that target antigens involved in cancer signalling pathways are associated with irAEs. Also, patients with increased levels of a distinct autoantibody against an inflammatory cytokine do not develop irAEs across multiple tumours. Conclusions The Cancer Immunotherapy Array is a high throughput array suitable for the analysis of thousands of cancer patient serum samples. Its first application presents novel autoantibody signatures for therapy-related toxicities (irAEs) as well as response. These signatures have the potential to serve as useful tools that will broaden our understanding of the mechanisms of therapy response and irAE occurrence. Reference [1] Budde P, et al. Lupus. 2016;25:812–22. Disclosure of Interest P. Schulz-Knappe Shareholder of: Protagen AG, P. Budde Employee of: Protagen AG, H.-D. Zucht Employee of: Protagen AG, S. Konings Employee of: Protagen AG, L. Steeg Employee of: Protagen AG, E. Friedrich Employee of: Protagen AG, C. Gutjahr Employee of: Protagen AG, R. Steil Employee of: Protagen AG, S. Bhandari Employee of: Protagen AG, M. Tuschen Employee of: Protagen AG