B cell depletion reduces the number of autoreactive T helper cells and prevents glucose-6-phosphate isomerase-induced arthritis

GPI: An indicator for immune infiltrates and prognosis of human breast cancer from a comprehensive analysis

Glucose-6-phosphate isomerase (GPI) plays an important part in gluconeogenesis and glycolysis through the interconversion of d-glucose-6-phosphate and d-fructose-6-phosphate, and its clinical significance still remains unclear in breast cancer (BRCA). We analyzed the expressions of GPI in BRCA patients to determine prognostic values. Our results showed that the expression levels of GPI were upregulated in BRCA patients, and a high GPI expression is correlated with poor overall survival (OS) in BRCA. At the same time, a high GPI expression is correlated with poor clinicopathological characteristics, such as stage III, over 60 years old, N3, HER2 negative, and estrogen receptor (ER) positive. Further analysis of the influence of GPI on the prognosis of BRCA suggested that 50 genes and 10 proteins were positively correlated with GPI, and these genes and proteins were mainly involved in cell cycle signaling pathways. In addition, in this study, we observed that GPI was closely related to N ⁶-methyladenosine (m6A) RNA methylation modification and immune cell infiltration and ferroptosis-related gene expression in BRCA, and there was a difference in m6A RNA methylation alterations, immune cell infiltration, and ferroptosis-related gene expression between the high GPI expression group and the low GPI expression group. Finally, we found that GPI in BRCA had 2.6% gene alterations, and BRCA patients with gene alteration of GPI had a poor prognosis in disease-free survival (DFS). Altogether, our work strongly suggested that GPI may serve as a new prognostic biomarker for BRCA patients.

Revisit of autoimmunity to glucose-6-phosphate isomerase in experimental and rheumatoid arthritis

Rheumatoid arthritis (RA) is an inflammatory disorder characterized by synovial inflammation in multiple joints. Autoantibodies (Abs) are the hallmark of RA, and as disease-specific and diagnostic markers, rheumatoid factor and anti-citrullinated protein antibody (ACPA) are produced pre-clinically, but their pathogenic roles in RA remain elusive. In this review, we focus on one of the candidate autoantigens in RA; glucose-6-phosphate isomerase (GPI). The arthritogenic role of GPI has been confirmed in two different mouse models: the K/BxN- and GPI-induced arthritis models. Both anti-GPI Abs and citrullinated-GPI peptide Abs have been detected in human RA. Studies conducted in these rodent models have confirmed that the pathogenesis of arthritis involves the localization of autoantigens not only in the joints but also in the circulation. In this review, we revisit and summarize the arthritogenic relevance of GPI in animal RA models and in human RA, and extend the discussion to joint-specific inflammation.

Potential involvement of OX40 in the regulation of autoantibody sialylation in arthritis

OBJECTIVE

An increased proportion of circulating follicular helper T (Tfh) cells was reported in rheumatoid arthritis (RA), but it remains uncertain how Tfh cells affect antibody hyposialylation. We investigated the regulation of autoantibody hyposialylation by Tfh cells in RA using murine model.

METHODS

Behaviours of Tfh cells and their function on B cell promotion were analysed. Change of arthritogenicity and sialylation of autoantibodies during the course of arthritis was examined by mass spectrometry. Tfh-mediated regulation of hyposialylation was investigated, and the responsible cell surface molecule was specified both in vitro and in vivo. The relation between circulating Tfh cells and hyposialylation was analysed in patients with RA.

RESULTS

An increase in Tfh, particularly interleukin-17 producing Tfh (Tfh17) cells, at the onset of arthritis and their enhancement of autoantibody production were found. Autoantibodies at the onset phase demonstrated stronger inflammatory properties than those at the resolution phase, and mass spectrometric analysis revealed their difference in sialylation. In vitro coculture showed enhanced hyposialylation by the Tfh cells via OX40, which was highly expressed in the Tfh and Tfh17 cells. Blockade of OX40 prevented the development of arthritis with reduction in Tfh17 cells and recovery of autoantibody sialylation. Analysis of patients with RA showed abundance of OX40-overexpressing Tfh17 cells, and their proportion correlated negatively with the expression of α2,6-sialyltransferase 1, an enzyme responsible for sialylation.

CONCLUSIONS

OX40 expressed on Tfh cells can regulate autoantibody sialylation and play a crucial role in the development of autoimmune arthritis.

In vivo activation of Treg cells with a CD28 superagonist prevents and ameliorates chronic destructive arthritis in mice

Although regulatory T (Treg) cells are necessary to prevent autoimmune diseases, including arthritis, whether Treg cells can ameliorate established inflammatory disease is controversial. Using the glucose-6-phosphate isomerase (G6PI)-induced arthritis model in mice, we aimed to determine the therapeutic efficacy of increasing Treg cell number and function during chronic destructive arthritis. Chronic destructive arthritis was induced by transient depletion of Treg cells prior to immunization with G6PI. At different time points after disease induction, mice were treated with a CD28 superagonistic antibody (CD28SA). CD28SA treatment during the induction phase of arthritis ameliorated the acute signs of arthritis and completely prevented the development of chronic destructive arthritis. CD28SA treatment of mice with fully developed arthritis induced a significant reduction in clinical and histological signs of arthritis. When given during the chronic destructive phase of arthritis, 56 days after disease induction, CD28SA treatment resulted in a modest reduction of clinical signs of arthritis and a reduction in histopathological signs of joint inflammation. Our data show that increasing the number and activation of Treg cells by a CD28SA is therapeutically effective in experimental arthritis.

Amelioration of experimental arthritis by stroke-induced immunosuppression is independent of Treg cell function

Objectives

Clinical evidence suggests that neurological lesions can protect from arthritis. Acute cerebral ischaemia induces severe immunosuppression, resulting in enhanced susceptibility to infections. We aimed to determine if stroke-induced immunosuppression can ameliorate arthritis and to delineate the immunological mechanisms involved.

Methods

Unilateral cerebral ischaemia was induced in mice by occlusion of one middle cerebral artery (MCAO) at different time points after induction of G6PI-induced arthritis in mice. Clinical and histological signs of arthritis were assessed. Regulatory T cells were specifically depleted by injection of diphtheria toxin into transgenic DEREG mice. Immunological correlates of MCAO were determined by flow cytometry and serological methods.

Results

MCAO reduced the clinical and histological signs of arthritis significantly. To be effective, stroke had to be induced during the induction phase or the early clinical stage of arthritis. MCAO induced a global loss of leucocytes. Despite the reduced absolute number of lymphocytes, the functional differentiation of T helper cells into Th1/17 cells and the production of autoantibodies were unimpaired. Depletion experiments showed that regulatory T cells were dispensable for the protective effect of MCAO.

Conclusions

MCAO ameliorates arthritis. The correlate of protection from arthritis is not the reduction of a particular pathogenic leucocyte subset or the preferential expansion or emergence of a protective cell population but the global reduction of leucocytes during arthritis.

B cells as effectors and regulators of sex-biased arthritis

B cells have been implicated both with pathogenic as well as protective capabilities in induction and regulation of autoimmune diseases. Rheumatoid arthritis (RA) is an autoimmune disease that occurs more often in women than men. A significant role of B cells as antibody producing and antigen-presenting cells has been demonstrated in RA. Predisposition to RA is associated with the presence of certain HLA class II alleles that share sequences with DRB1*0401. To determine the role of HLA genes and B cells in vivo, we have generated transgenic mice carrying HLA genes, DRB1*0401 and DQ8, known to be associated with susceptibility to RA. Humanized mice can be induced to develop arthritis that mimics human disease in clinical, histopathological and sex bias. Effect of hormones on immune cells and their function has been described in humans and mice and has been suggested to be the major reason for female bias of autoimmune diseases. An immune response to an antigen requires presentation by HLA molecules thus suggesting a critical role of MHC in combination with sex hormones in susceptibility to develop rheumatoid arthritis. Based on our observations, we hypothesize that modulation of B cells by estrogen, presentation of modified antigens by DR4 and production of antigen-specific B cell modulating cytokines leads to autoreactivity in females. These data suggest that considering patient's sex may be crucial in selecting the optimal treatment strategy. Humanized mice expressing RA susceptible and resistant haplotype provide a means to investigate mechanism sex-bias of arthritis and future strategies for therapy.

Multivariate analysis of flow cytometric data using decision trees

Characterization of the response of the host immune system is important in understanding the bidirectional interactions between the host and microbial pathogens. For research on the host site, flow cytometry has become one of the major tools in immunology. Advances in technology and reagents allow now the simultaneous assessment of multiple markers on a single cell level generating multidimensional data sets that require multivariate statistical analysis. We explored the explanatory power of the supervised machine learning method called "induction of decision trees" in flow cytometric data. In order to examine whether the production of a certain cytokine is depended on other cytokines, datasets from intracellular staining for six cytokines with complex patterns of co-expression were analyzed by induction of decision trees. After weighting the data according to their class probabilities, we created a total of 13,392 different decision trees for each given cytokine with different parameter settings. For a more realistic estimation of the decision trees' quality, we used stratified fivefold cross validation and chose the "best" tree according to a combination of different quality criteria. While some of the decision trees reflected previously known co-expression patterns, we found that the expression of some cytokines was not only dependent on the co-expression of others per se, but was also dependent on the intensity of expression. Thus, for the first time we successfully used induction of decision trees for the analysis of high dimensional flow cytometric data and demonstrated the feasibility of this method to reveal structural patterns in such data sets.