Signaling through stimulator of interferon genes (STING) leads to the production of type I interferons (IFN-Is) and inflammatory cytokines. A gain-of-function mutation in STING was identified in an autoinflammatory disease (STING-associated vasculopathy with onset in infancy; SAVI). The expression of cyclic GMP-AMP, DNA-activated cGAS-STING pathway, increased in a proportion of patients with SLE. The STING signaling pathway may be a candidate for targeted therapy in SLE. Here, we demonstrated that disruption of STING signaling ameliorated lupus development in Fcgr2b-deficient mice. Activation of STING promoted maturation of conventional dendritic cells and differentiation of plasmacytoid dendritic cells via LYN interaction and phosphorylation. The inhibition of LYN decreased the differentiation of STING-activated dendritic cells. Adoptive transfer of STING-activated bone marrow-derived dendritic cells into the FCGR2B and STING double-deficiency mice restored lupus phenotypes. These findings provide evidence that the inhibition of STING signaling may be a candidate targeted treatment for a subset of patients with SLE.

Background: Identification of universal biomarkers to predict systemic lupus erythematosus (SLE) flares is challenging due to the heterogeneity of the disease. Several biomarkers have been reported. However, the data of validated biomarkers to use as a predictor for lupus flares show variation. This study aimed to identify the biomarkers that are sensitive and specific to predict lupus flares. Methods: One hundred and twenty-four SLE patients enrolled in this study and were prospectively followed up. The evaluation of disease activity achieved by the SLE disease activity index (SLEDAI-2K) and clinical SLEDAI (modified SLEDAI). Patients with active SLE were categorized into renal or non-renal flares. Serum cytokines were measured by multiplex bead-based flow cytometry. The correlation and logistic regression analysis were performed. Results: Levels of IFN-α, MCP-1, IL-6, IL-8, and IL-18 significantly increased in active SLE and correlated with clinical SLEDAI. Complement C3 showed a weakly negative relationship with IFN-α and IL-18. IL-18 showed the highest positive likelihood ratios for active SLE. Multiple logistic regression analysis showed that IL-6, IL-8, and IL-18 significantly increased odds ratio (OR) for active SLE at baseline while complement C3 and IL-18 increased OR for active SLE at 12 weeks. IL-18 and IL-6 yielded higher sensitivity and specificity than anti-dsDNA and C3 to predict active renal and active non-renal, respectively. Conclusion: The heterogeneity of SLE pathogenesis leads to different signaling mechanisms and mediates through several cytokines. The monitoring of cytokines increases the sensitivity and specificity to determine SLE disease activity. IL-18 predicts the risk of active renal SLE while IL-6 and IL-8 predict the risk of active non-renal. The sensitivity and specificity of these cytokines are higher than the anti-dsDNA or C3. We propose to use the serum level of IL-18, IL-6, and IL-8 to monitor SLE disease activity in clinical practice.

Systemic Lupus Erythematosus (SLE) is an autoimmune disease resulting in autoantibody production, immune complex deposition, and complement activation. The standard biomarkers such as anti-dsDNA and complements (C3 and C4) do not always correlate with active clinical SLE. The heterogeneity of SLE patients may require additional biomarkers to designate disease activity. Ninety SLE patients participated in this study. Evaluation of disease activity was achieved with the Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) and modified SLEDAI-2K. The measured serum biomarkers were anti-dsDNA, C3, C4, ESR, interleukin-6 (IL-6), and circulating immune complexes (CIC). IL-6, ESR and CIC significantly increased in active clinical SLE. Complement, anti-dsDNA, ESR and CIC correlated with SLEDAI-2K while only anti-dsDNA, CIC, ESR and IL-6 correlated with modified SLEDAI-2K. A combination of biomarkers gave a higher odds ratio (OR) than any single biomarker. A combination of IL-6 or CIC exhibited the highest OR (OR = 7.27, 95%CI (1.99–26.63), p = 0.003) while either complement or anti-dsDNA showed a moderate odds ratio (OR = 3.14, 95%CI (1.16–8.48), p = 0.024) of predicting clinical active SLE. The combination of CIC and IL-6 strongly predicts active clinical SLE. CIC and IL-6 can be used in addition to standard biomarkers to determine SLE activity.

Although the enhanced responses against serum cell-free DNA (cfDNA) in cases of sepsis—a life-threatening organ dysfunction due to systemic infection—are understood, the influence of the cytosolic DNA receptor cGAS (cyclic guanosine monophosphate–adenosine monophosphate (GMP–AMP) synthase) on sepsis is still unclear. Here, experiments on cGAS deficient (cGAS^-/-) mice were conducted using cecal ligation and puncture (CLP) and lipopolysaccharide (LPS) injection sepsis models and macrophages. Severity of CLP in cGAS^-/- mice was less severe than in wildtype (WT) mice, as indicated by mortality, serum LPS, cfDNA, leukopenia, cytokines (TNF-α, IL-6 and IL-10), organ histology (lung, liver and kidney) and spleen apoptosis. With the LPS injection model, serum cytokines in cGAS^-/- mice were lower than in WT mice, despite the similar serum cfDNA level. Likewise, in LPS-activated WT macrophages, the expression of several mitochondria-associated genes (as revealed by RNA sequencing analysis) and a profound reduction in mitochondrial parameters, including maximal respiration (determined by extracellular flux analysis), DNA (mtDNA) and mitochondrial abundance (revealed by fluorescent staining), were demonstrated. These data implied the impact of cfDNA resulting from LPS-induced cell injury. In parallel, an additive effect of bacterial DNA on LPS, seen in comparison with LPS alone, was demonstrated in WT macrophages, but not in cGAS^-/- cells, as indicated by supernatant cytokines (TNF-α and IL-6), M1 proinflammatory polarization (iNOS and IL-1β), cGAS, IFN-γ and supernatant cyclic GMP–AMP (cGAMP). In conclusion, cGAS activation by cfDNA from hosts (especially mtDNA) and bacteria was found to induce an additive proinflammatory effect on LPS-activated macrophages which was perhaps responsible for the more pronounced sepsis hyperinflammation observed in WT mice compared with the cGAS^-/- group.

Although the impacts of Saccharomyces cerevisiae on cancers are mentioned, data on its use in mice with cyclic GMP-AMP synthase deficiency (cGAS-/-) are even rarer. Here, 12 weeks of oral administration of S. cerevisiae protected cGAS-/- mice from azoxymethane (AOM)-induced colon cancers, partly through dysbiosis attenuation (fecal microbiome analysis). In parallel, a daily intralesional injection of a whole glucan particle (WGP; the beta-glucan extracted from S. cerevisiae) attenuated the growth of subcutaneous tumor using MC38 (murine colon cancer cell line) in cGAS-/- mice. Interestingly, the incubation of fluorescent-stained MC38 with several subtypes of macrophages, including M1 (using Lipopolysaccharide; LPS), M2 (IL-4), and tumor-associated macrophages (TAM; using MC38 supernatant activation), could not further reduce the tumor burdens (fluorescent intensity) compared with M0 (control culture media). However, WGP enhanced tumoricidal activities (fluorescent intensity), the genes of M1 pro-inflammatory macrophage polarization (IL-1β and iNOS), and Dectin-1 expression and increased cell energy status (extracellular flux analysis) in M0, M2, and TAM. In M1, WGP could not increase tumoricidal activities, Dectin-1, and glycolysis activity, despite the upregulated IL-1β. In conclusion, S. cerevisiae inhibited the growth of colon cancers through dysbiosis attenuation and macrophage energy activation, partly through Dectin-1 stimulation. Our data support the use of S. cerevisiae for colon cancer protection.

The prognosis of severe lupus nephritis (LN) is very different among individual patients. None of the current biomarkers can be used to predict the development of refractory LN. Because kidney histology is the gold standard for diagnosing LN, the authors hypothesize that molecular signatures detected in kidney biopsy tissue may have predictive value in determining the therapeutic response. Sixty-seven patients with biopsy-proven severely active LN by International Society of Nephrology/Renal Pathology Society (ISN/RPS) classification III/IV were recruited. Twenty-three kidney tissue samples were used for RNA microarray analysis, while the remaining 44 samples were used for validation by real-time polymerase chain reaction (PCR) gene expression analysis. From hundreds of differential gene expressions in refractory LN, 12 candidates were selected for validation based on gene expression levels as well as relevant functions. The candidate biomarkers were members of the innate immune response molecules, adhesion molecules, calcium-binding receptors, and paracellular tight junction proteins. S100A8, ANXA13, CLDN19 and FAM46B were identified as the best kidney biomarkers for refractory LN, and COL8A1 was identified as the best marker for early loss of kidney function. These new molecular markers can be used to predict refractory LN and may eventually lead to novel molecular targets for therapy.