AAgAtlas 1.0: a human autoantigen database

abstract: Autoantibodies refer to antibodies that target self-antigens, which can play pivotal roles in maintaining homeostasis, distinguishing normal from tumor tissue and trigger autoimmune diseases. In the last three decades, tremendous efforts have been devoted to elucidate the generation, evolution and functions of autoantibodies, as well as their target autoantigens. However, reports of these countless previously identified autoantigens are randomly dispersed in the literature. Here, we constructed an AAgAtlas database 1.0 using text-mining and manual curation. We extracted 45 830 autoantigen-related abstracts and 94 313 sentences from PubMed using the keywords of either ‘autoantigen’ or ‘autoantibody’ or their lexical variants, which were further refined to 25 520 abstracts, 43 253 sentences and 3984 candidates by our bio-entity recognizer based on the Protein Ontology. Finally, we identified 1126 genes as human autoantigens and 1071 related human diseases, with which we constructed a human autoantigen database (AAgAtlas database 1.0). The database provides a user-friendly interface to conveniently browse, retrieve and download human autoantigens as well as their associated diseases. The database is freely accessible at http://biokb.ncpsb.org/aagatlas/. We believe this database will be a valuable resource to track and understand human autoantigens as well as to investigate their functions in basic and translational research.The final version of this article, as published in Nucleic Acids Research, can be viewed online at: https://academic.oup.com/nar/article/45/D1/D769/2290910/AAgAtlas-1-0-a-human-autoantigen-databas

Identification of Novel Native Autoantigens in Rheumatoid Arthritis

The majority of patients diagnosed with rheumatoid arthritis (RA) have developed autoantibodies against neoepitopes in proteins that have undergone post-translational modification, e.g., citrullination or carbamylation. There is growing evidence of their molecular relevance and their potential utility to improve diagnosis, patient stratification, and prognosis for precision medicine. Autoantibodies reacting to native proteins may also have a role in RA pathogenesis, however, their reactivity patterns remain much less studied. We hypothesized that a high-density protein array technology could shed light onto the normal and disease-related autoantibodies produced in healthy and RA patient subgroups. In an exploratory study, we investigated the global reactivity of autoantibodies in plasma pools from 15 anti-cyclic citrullinated peptide (CCP)-positive and 10 anti-CCP-negative RA patients and 10 healthy donors against more than 1600 native and unmodified human proteins using a high-density protein array. A total of 102 proteins recognized by IgG autoantibodies were identified, hereof 86 were recognized by antibodies from CCP-positive RA patients and 76 from anti-CCP-negative RA patients, but not by antibodies from healthy donors. Twenty-four of the identified autoantigens have previously been identified in synovial fluid. Multiple human proteins in their native conformation are recognized by autoantibodies from anti-CCP-positive as well as anti-CCP-negative RA patients

Detection of Antinuclear Antibodies Targeting Intracellular Signal Transduction, Metabolism, Apoptotic Processes and Cell Death in Critical COVID-19 Patients

Background and Objectives: The heterogeneity of the coronavirus disease of 2019 (COVID-19) lies within its diverse symptoms and severity, ranging from mild to lethal. Acute respiratory distress syndrome (ARDS) is a leading cause of mortality in COVID-19 patients, characterized by a hyper cytokine storm. Autoimmunity is proposed to occur as a result of COVID-19, given the high similarity of the immune responses observed in COVID-19 and autoimmune diseases. Here, we investigate the level of autoimmune antibodies in COVID-19 patients with different severities. Results: Initial screening for antinuclear antibodies (ANA) IgG using ELISA revealed that 1.58% (2/126) and 4% (5/126) of intensive care unit (ICU) COVID-19 cases expressed strong and moderate ANA levels, respectively. An additional sample was positive with immunofluorescence assays (IFA) screening. However, all the non-ICU cases (n=273) were ANA negative using both assays. Samples positive for ANA were further confirmed with large-scale autoantibody screening by phage immunoprecipitation-sequencing (PhIP-Seq). The majority of the ANA-positive samples showed "speckled" ANA pattern by microscopy and revealed autoantibody specificities that targeted proteins involved in intracellular signal transduction, metabolism, apoptotic processes, and cell death by PhIP-Seq; further denoting reactivity to nuclear and cytoplasmic antigens. Conclusion: Our results further support the notion of routine screening for autoimmune responses in COVID-19 patients, which might help improve disease prognosis and patient management. Further, results provide compelling evidence that ANA-positive individuals should be excluded from being donors for convalescent plasma therapy in the context of COVID-19.This study was supported by funds from QNRF, grant # NPRP11S-1212-170092

Tracking the antibody immunome in sporadic colorectal cancer by using antigen self-assembled protein arrays

© 2021 by the authors.Sporadic Colorectal Cancer (sCRC) is the third leading cause of cancer death in the Western world, and the sCRC patients presenting with synchronic metastasis have the poorest prognosis. Genetic alterations accumulated in sCRC tumor cells translate into mutated proteins and/or abnormal protein expression levels, which contribute to the development of sCRC. Then, the tumor-associated proteins (TAAs) might induce the production of auto-antibodies (aAb) via humoral immune response. Here, Nucleic Acid Programmable Protein Arrays (NAPPArray) are employed to identify aAb in plasma samples from a set of 50 sCRC patients compared to seven healthy donors. Our goal was to establish a systematic workflow based on NAPPArray to define differential aAb profiles between healthy individuals and sCRC patients as well as between non-metastatic (n = 38) and metastatic (n = 12) sCRC, in order to gain insight into the role of the humoral immune system in controlling the development and progression of sCRC. Our results showed aAb profile based on 141 TAA including TAAs associated with biological cellular processes altered in genesis and progress of sCRC (e.g., FSCN1, VTI2 and RPS28) that discriminated healthy donors vs. sCRC patients. In addition, the potential capacity of discrimination (between non-metastatic vs. metastatic sCRC) of 7 TAAs (USP5, ML4, MARCKSL1, CKMT1B, HMOX2, VTI2, TP53) have been analyzed individually in an independent cohort of sCRC patients, where two of them (VTI2 and TP53) were validated (AUC ~75%). In turn, these findings provided novel insights into the immunome of sCRC, in combination with transcriptomics profiles and protein antigenicity characterizations, wich might lead to the identification of novel sCRC biomarkers that might be of clinical utility for early diagnosis of the tumor. These results explore the immunomic analysis as potent source for biomarkers with diagnostic and prognostic value in CRC. Additional prospective studies in larger series of patients are required to confirm the clinical utility of these novel sCRC immunomic biomarkers.We gratefully acknowledge financial support from the Spanish Health Institute Carlos III (ISCIII) for the grants: FIS PI14/01538, FIS PI17/01930 and CB16/12/00400. We also acknowledge Fondos FEDER (EU) “Una manera de hacer Europa” and Junta Castilla-León (COVID19 grant COV20EDU/00187). Fundación Solórzano FS/38-2017. The Proteomics Unit belongs to ProteoRed, PRB3-ISCIII, supported by grant PT17/0019/0023, of the PE I + D + I 2017-2020, funded by ISCIII and FEDER. CNPq-National Council for Scientific and Technological Development (Brazil) (306258/2019-6) and FAPERJ-Foundation for Research Support of Rio de Janeiro State for the financial support (E-26/201.670/2017 and 210.379/2018). M. González-González is supported by MINECOPTA2019-017870-I.A. Landeira-Viñuela is supported by VIII Centenario-USAL PhD Program. P.J.-V. is supported by JCYL PhD Program and scholarship JCYL-EDU/601/2020. P.D. and E.B. are supported by a JCYL-EDU/346/2013 Ph.D. scholarship

Identification of new candidate biomarkers for prostate cancer by affinity proteomics

Prostate cancer (PCA) is a complex malignancy that needs to be more thoroughly studied and understood at a molecular level to fill the current knowledge gap, and optimize diagnosis and to treatment. Prostate specific antigen (PSA) showed to be not specific for PCA, therefore a demand for novel specific biomarkers exists. The aim of our work was to identify new specific candidate biomarkers for PCA in tissue and plasma samples by means of affinity proteomics approaches such as reverse phase protein array and antigen arrays. Tissue samples are an invaluable source of biomarkers for cancer, but very limited in amount and requiring invasive procedures for collection. Still, they allow to directly profiling the molecular status of tumor itself. Beside tissue, a screening procedure on biological fluid such as plasma would be highly desirable, thanks to the less invasiveness and low-costs of samples collection. Among the biomarkers detectable in plasma are the autoantibodies. The first part of this thesis summarizes the current status of PCA epidemiology, treatment, and biomarkers research. Beside this, an overview of the affinity proteomics platforms available for biomarkers research, and the critical variables to consider in the biomarkers validation process are presented. The second part of the thesis reports the main results of two original studies where the author of the thesis is the main contributor. Paper I is based on the profiling of PCA tissue samples using RPPA. Our results indicate the feasibility of combining laser capture microdissection (LCM) and RPPA for evaluating the molecular architecture and cross-talking of epithelial and stromal compartments. Paper II is based on profiling the autoimmune response to PCA patients, comparing early and late stage of the disease. The authors identified and characterized the IgG reactivity toward a novel epitope for the candidate biomarker prostein. The data presented in this thesis provide two robust frameworks based on affinity proteomics platforms applied for protein profiling in tissue, and autoantibodies profiling in plasma in the context of PCA biomarkers discovery.Co-supervisors: Peter Nilsson (Biotechnology Department, KTH-Royal Institute of Technology, Stockholm, Sweden), Mariaelena Pierobon (Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA, USA)openDottorato di ricerca in Medicina cellulare e molecolareopenPin, Elis

In-depth serum proteomics reveals biomarkers of psoriasis severity and response to traditional Chinese medicine

Serum and plasma contain abundant biological information that reflect the body’s physiological and pathological conditions and are therefore a valuable sample type for disease biomarkers. However, comprehensive profiling of the serological proteome is challenging due to the wide range of protein concentrations in serum. Methods: To address this challenge, we developed a novel in-depth serum proteomics platform capable of analyzing the serum proteome across ~10 orders or magnitude by combining data obtained from Data Independent Acquisition Mass Spectrometry (DIA-MS) and customizable antibody microarrays. Results: Using psoriasis as a proof-of-concept disease model, we screened 50 serum proteomes from healthy controls and psoriasis patients before and after treatment with traditional Chinese medicine (YinXieLing) on our in-depth serum proteomics platform. We identified 106 differentially-expressed proteins in psoriasis patients involved in psoriasis-relevant biological processes, such as blood coagulation, inflammation, apoptosis and angiogenesis signaling pathways. In addition, unbiased clustering and principle component analysis revealed 58 proteins discriminating healthy volunteers from psoriasis patients and 12 proteins distinguishing responders from non-responders to YinXieLing. To further demonstrate the clinical utility of our platform, we performed correlation analyses between serum proteomes and psoriasis activity and found a positive association between the psoriasis area and severity index (PASI) score with three serum proteins (PI3, CCL22, IL-12B). Conclusion: Taken together, these results demonstrate the clinical utility of our in-depth serum proteomics platform to identify specific diagnostic and predictive biomarkers of psoriasis and other immune-mediated diseases

Restoring the Immunity in the Tumor Microenvironment: Insights into Immunogenic Cell Death in Onco-Therapies.

[EN]Immunogenic cell death (ICD) elicited by cancer therapy reshapes the tumor immune microenvironment. A long-term adaptative immune response can be initiated by modulating cell death by therapeutic approaches. Here, the major hallmarks of ICD, endoplasmic reticulum (ER) stress, and damage-associated molecular patterns (DAMPs) are correlated with ICD inducers used in clinical practice to enhance antitumoral activity by suppressing tumor immune evasion. Approaches to monitoring the ICD triggered by antitumoral therapeutics in the tumor microenvironment (TME) and novel perspective in this immune system strategy are also reviewed to give an overview of the relevance of ICD in cancer treatment