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

Breast Cancer Immune Landscape: Interplay Between Systemic and Local Immunity

Breast cancer (BC) is one of the most common malignancies in women worldwide. Numerous studies in immuno-oncology and successful trials of immunotherapy have demonstrated the causal role of the immune system in cancer pathogenesis. The interaction between the tumor and the immune system is known to have a dual nature. Despite cytotoxic lymphocyte activity against transformed cells, a tumor can escape immune surveillance and leverage chronic inflammation to maintain its own development. Research on antitumor immunity primarily focuses on the role of the tumor microenvironment, whereas the systemic immune response beyond the tumor site is described less thoroughly. Here, a comprehensive review of the formation of the immune profile in breast cancer patients is offered. The interplay between systemic and local immune reactions as self-sustaining mechanism of tumor progression is described and the functional activity of the main cell populations related to innate and adaptive immunity is discussed. Additionally, the interaction between different functional levels of the immune system and their contribution to the development of the pro- or anti-tumor immune response in BC is highlighted. The presented data can potentially inform the development of new immunotherapy strategies in the treatment of patients with BC.

Autoantibody Diversity Is Augmented in Women with Breast Cancer and Is Related to the Stage of the Disease

Breast cancer (BC) is the most frequent malignant neoplasia and leading cause of cancer mortality for women. A timely diagnosis of BC is crucial to ensure the best chances of survival. Among the various screening tools for BC, antibodies directed towards self-antigens or tumor-associated antigens (autoantibodies) have emerged as an alternative to image-based screening modalities. However, little attention has been paid to the global diversity of autoantibodies. This work aimed to analyze the diversity of autoantibodies reactive to antigens expressed by the BC cell line T47D in the sera of Mexican women with BC, benign breast pathology (BBP), or without breast pathology (WBP). We found that the diversity of antibodies in the sera was higher in the BC and BBP groups than in the WBP group. Likewise, the diversity changed with the progression of BC. Our results show and measure the complexity of the antibody response in breast health and disease.

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.

Plasma cells are not restricted to the CD27+ phenotype: characterization of CD27-CD43+ antibody-secreting cells

Circulating antibody-secreting cells are present in the peripheral blood of healthy individuals reflecting the continued activity of the humoral immune system. Antibody-secreting cells typically express CD27. Here we describe and characterize a small population of antibody-secreting class switched CD19+CD43+ B cells that lack expression of CD27 in the peripheral blood of healthy subjects. In this study, we characterized CD27-CD43+ cells. We demonstrate that class-switched CD27-CD43+ B cells possess characteristics of conventional plasmablasts as they spontaneously secrete antibodies, are morphologically similar to antibody-secreting cells, show downregulation of B cell differentiation markers, and have a gene expression profile related to conventional plasmablasts. Despite these similarities, we observed differences in IgA and IgG subclass distribution, expression of homing markers, replication history, frequency of somatic hypermutation, immunoglobulin repertoire, gene expression related to Toll-like receptors, cytokines, and cytokine receptors, and antibody response to vaccination. Their frequency is altered in immune-mediated disorders.

Conclusion

we characterized CD27-CD43+ cells as antibody-secreting cells with differences in function and homing potential as compared to conventional CD27+ antibody-secreting cells.

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.

Systemic autoinflammatory diseases

Systemic autoinflammatory diseases (SAIDs) are a growing group of disorders caused by a dysregulation of the innate immune system leading to episodes of systemic inflammation. In 1997, MEFV was the first gene identified as disease causing for Familial Mediterranean Fever, the most common hereditary SAID. In most cases, autoinflammatory diseases have a strong genetic background with mutations in single genes. Since 1997 more than 30 new genes associated with autoinflammatory diseases have been identified, affecting different parts of the innate immune system. Nevertheless, for at least 40-60% of patients with phenotypes typical for SAIDs, a distinct diagnosis cannot be met, leading to undefined SAIDs (uSAIDs). However, SAIDs can also be of polygenic or multifactorial origin, with environmental influence modulating the phenotype. The implementation of a disease continuum model combining the adaptive and the innate immune system with autoinflammatory and autoimmune diseases shows the complexity of SAIDs and the importance of new methods to elucidate molecular changes and causative factors in SAIDs. Diagnosis is often based on clinical presentation and genetic testing. The timeline from onset to diagnosis takes up to 7.3 years, highlighting the indisputable need to identify new treatment and diagnostic targets. Recently, other factors are under investigation as additional contributors to the pathogenesis of SAIDs. This review gives an overview of pathogenesis and etiology of SAIDs, and summarizes recent diagnosis and treatment options.