Interleukin 35 contributes to immunosuppression by regulating inflammatory cytokines and T cell populations in the acute phase of sepsis

2022 ◽  
pp. 108915
Author(s):  
Wu Dansen ◽  
Wang Liming ◽  
Hong Donghuang ◽  
Zheng Caifa ◽  
Zeng Yongping ◽  
...  
2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A52-A52
Author(s):  
Elen Torres ◽  
Stefani Spranger

BackgroundUnderstanding the interactions between tumor and immune cells is critical for improving current immunotherapies. Pre-clinical and clinical evidence has shown that failed T cell infiltration into lung cancer lesions might be associated with low responsiveness towards checkpoint blockade.1 For this reason, it is necessary to characterize not only the phenotype of T cells in tumor-bearing lungs but also their spatial location in the tumor microenvironment (TME). Multiplex immunofluorescence staining allows the simultaneous use of several cell markers to study the state and the spatial location of cell populations in the tissue of interest. Although this technique is usually applied to thin tissue sections (5 to 12 µm), the analysis of large tissue volumes may provide a better understanding of the spatial distribution of cells in relation to the TME. Here, we analyzed the number and spatial distribution of cytotoxic T cells and other immune cells in the TME of tumor-bearing lungs, using both 12 µm sections and whole-mount preparations imaged by confocal microscopy.MethodsLung tumors were induced in C57BL/6 mice by tail vein injection of a cancer cell line derived from KrasG12D/+ and Tp53-/- mice. Lung tissue with a diverse degree of T cell infiltration was collected after 21 days post tumor induction. Tissue was fixed in 4% PFA, followed by snap-frozen for sectioning. Whole-mount preparations were processed according to Weizhe Li et al. (2019) 2 for tissue clearing and multiplex volume imaging. T cells were labeled with CD8 and FOXP3 antibodies to identify cytotoxic or regulatory T cells, respectively. Tumor cells were labeled with a pan-Keratin antibody. Images were acquired using a Leica SP8 confocal microscope. FIJI3 and IMARIS were used for image processing.ResultsWe identified both cytotoxic and regulatory T cell populations in the TME using thin sections and whole-mount. However, using whole-mount after tissue clearing allowed us to better evaluate the spatial distribution of the T cell populations in relation to the tumor structure. Furthermore, tissue clearance facilitates the imaging of larger volumes using multiplex immunofluorescence.ConclusionsAnalysis of large lung tissue volumes provides a better understanding of the location of immune cell populations in relation to the TME and allows to study heterogeneous immune infiltration on a per-lesion base. This valuable information will improve the characterization of the TME and the definition of cancer-immune phenotypes in NSCLC.ReferencesTeng MW, et al., Classifying cancers based on T-cell infiltration and PD-L1. Cancer Res 2015;75(11): p. 2139–45.Li W, Germain RN, and Gerner MY. High-dimensional cell-level analysis of tissues with Ce3D multiplex volume imaging. Nat Protoc 2019;14(6): p. 1708–1733.Schindelin J, et al, Fiji: an open-source platform for biological-image analysis. Nat Methods 2012;9(7): p. 676–82.


2021 ◽  
Vol 27 (3) ◽  
pp. S74
Author(s):  
Pablo Domizi ◽  
Astraea Jager ◽  
Jolanda Sarno ◽  
Charles G. Mullighan ◽  
Stephan Grupp ◽  
...  

2008 ◽  
Vol 68 (8) ◽  
pp. 2961-2971 ◽  
Author(s):  
H. Singh ◽  
P. R. Manuri ◽  
S. Olivares ◽  
N. Dara ◽  
M. J. Dawson ◽  
...  

2021 ◽  
Vol 6 (3) ◽  
pp. 121
Author(s):  
Alison Luce-Fedrow ◽  
Suchismita Chattopadhyay ◽  
Teik-Chye Chan ◽  
Gregory Pearson ◽  
John B. Patton ◽  
...  

The antigenic diversity of Orientia tsutsugamushi as well as the interstrain difference(s) associated with virulence in mice impose the necessity to dissect the host immune response. In this study we compared the host response in lethal and non-lethal murine models of O. tsutsugamushi infection using the two strains, Karp (New Guinea) and Woods (Australia). The models included the lethal model: Karp intraperitoneal (IP) challenge; and the nonlethal models: Karp intradermal (ID), Woods IP, and Woods ID challenges. We monitored bacterial trafficking to the liver, lung, spleen, kidney, heart, and blood, and seroconversion during the 21-day challenge. Bacterial trafficking to all organs was observed in both the lethal and nonlethal models of infection, with significant increases in average bacterial loads observed in the livers and hearts of the lethal model. Multicolor flow cytometry was utilized to analyze the CD4+ and CD8+ T cell populations and their intracellular production of the cytokines IFNγ, TNF, and IL2 (single, double, and triple combinations) associated with both the lethal and nonlethal murine models of infection. The lethal model was defined by a cytokine signature of double- (IFNγ-IL2) and triple-producing (IL2-TNF-IFNγ) CD4+ T-cell populations; no multifunctional signature was identified in the CD8+ T-cell populations associated with the lethal model. In the nonlethal model, the cytokine signature was predominated by CD4+ and CD8+ T-cell populations associated with single (IL2) and/or double (IL2-TNF) populations of producers. The cytokine signatures associated with our lethal model will become depletion targets in future experiments; those signatures associated with our nonlethal model are hypothesized to be related to the protective nature of the nonlethal challenges.


2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 45.2-45
Author(s):  
I. Heggli ◽  
R. Schüpbach ◽  
N. Herger ◽  
T. A. Schweizer ◽  
A. Juengel ◽  
...  

Background:Modic type 1 changes (MC1) are vertebral bone marrow (BM) edema that associate with non-specific low back pain (LBP). Two etiologies have been described. In the infectious etiology the anaerobic aerotolerant Cutibacterium acnes (C. acnes) invades damaged intervertebral discs (IVDs) resulting in disc infection and endplate damage, which leads to the evocation of an immune response. In the autoinflammatory etiology disc and endplate damage lead to the exposure of immune privileged disc cells and matrix to leukocytes, thereby evoking an immune response in the BM. Different etiologies require different treatment strategies. However, it is unknown if etiology-specific pathological mechanisms exist.Objectives:The aim of this study was to identify etiology-specific dysregulated pathways of MC1 and to perform in-depth analysis of immune cell populations of the autoinflammatory etiology.Methods:BM aspirates and biopsies were obtained from LBP patients with MC1 undergoing spinal fusion. Aspirates/biopsies were taken prior screw insertion through the pedicle screw trajectory. From each patient, a MC1 and an intra-patient control aspiration/biopsy from the adjacent vertebral level was taken. If C. acnes in IVDs adjacent to MC1 were detected by anaerobic bacterial culture, patients were assigned to the infectious, otherwise to the autoinflammatory etiology.Total RNA was isolated from aspirates and sequenced (Novaseq) (infectious n=3 + 3, autoinflammatory n=5 + 5). Genes were considered as differentially expressed (DEG) if p-value < 0.01 and log2fc > ± 0.5. Gene ontology (GO) enrichment was performed in R (GOseq), gene set enrichment analysis (GSEA) with GSEA software.Changes in cell populations of the autoinflammatory etiology were analyzed with single cell RNA sequencing (scRNAseq): Control and MC1 biopsies (n=1 + 1) were digested, CD45+CD66b- mononuclear cells isolated with fluorescence activated cell sorting (FACS), and 10000 cells were sequenced (10x Genomics). Seurat R toolkit was used for quality-control, clustering, and differential expression analysis.Transcriptomic changes (n=5 + 5) of CD45+CD66b+ neutrophils isolated with flow cytometry from aspirates were analyzed as for total bulk RNAseq. Neutrophil activation (n=3 + 3) was measured as CD66b+ expression with flow cytometry. CD66bhigh and CD66blow fractions in MC1 and control neutrophils were compared with paired t-test.Results:Comparing MC1 to control in total bulk RNAseq, 204 DEG in the autoinflammatory and 444 DEG in the infectious etiology were identified with only 67 shared genes (Fig. 1a). GO enrichment revealed “T-cell activation” (p = 2.50E-03) in the autoinflammatory and “complement activation, classical pathway” (p=1.1E-25) in the infectious etiology as top enriched upregulated biological processes (BP) (Fig 1b). ScRNAseq of autoinflammatory MC1 showed an overrepresentation of T-cells (p= 1.00E-34, OR=1.54) and myelocytes (neutrophil progenitor cells) (p=4.00E-05, OR=2.27) indicating an increased demand of these cells (Fig. 1c). Bulk RNAseq analysis of neutrophils from the autoinflammatory etiology revealed an activated, pro-inflammatory phenotype (Fig 1d), which was confirmed with more CD66bhigh neutrophils in MC1 (+11.13 ± 2.71%, p=0.02) (Fig. 1e).Figure 1.(a) Venn diagram of DEG from total bulk RNAseq (b) Top enriched upregulated BP of autoinflammatory (left) and infectious (right) etiology (c) Cell clustering of autoinflammatory MC1 BM (d) Enrichment of “inflammatory response” gene set in autoinflammatory MC1 neutrophils (e) Representative histogram of CD66b+ expression in MC1 and control neutrophils.Conclusion:Autoinflammatory and infectious etiologies of MC1 have different pathological mechanisms. T-cell and neutrophil activation seem to be important in the autoinflammatory etiology. This has clinical implication as it could be explored for diagnostic approaches to distinguish the two MC1 etiologies and supports developing targeted treatments for both etiologies.Disclosure of Interests:None declared


2021 ◽  
pp. annrheumdis-2020-219335
Author(s):  
Emma Garcia-Melchor ◽  
Giacomo Cafaro ◽  
Lucy MacDonald ◽  
Lindsay A N Crowe ◽  
Shatakshi Sood ◽  
...  

ObjectivesIncreasing evidence suggests that inflammatory mechanisms play a key role in chronic tendon disease. After observing T cell signatures in human tendinopathy, we explored the interaction between T cells and tendon stromal cells or tenocytes to define their functional contribution to tissue remodelling and inflammation amplification and hence disease perpetuation.MethodsT cells were quantified and characterised in healthy and tendinopathic tissues by flow cytometry (FACS), imaging mass cytometry (IMC) and single cell RNA-seq. Tenocyte activation induced by conditioned media from primary damaged tendon or interleukin-1β was evaluated by qPCR. The role of tenocytes in regulating T cell migration was interrogated in a standard transwell membrane system. T cell activation (cell surface markers by FACS and cytokine release by ELISA) and changes in gene expression in tenocytes (qPCR) were assessed in cocultures of T cells and explanted tenocytes.ResultsSignificant quantitative differences were observed in healthy compared with tendinopathic tissues. IMC showed T cells in close proximity to tenocytes, suggesting tenocyte–T cell interactions. On activation, tenocytes upregulated inflammatory cytokines, chemokines and adhesion molecules implicated in T cell recruitment and activation. Conditioned media from activated tenocytes induced T cell migration and coculture of tenocytes with T cells resulted in reciprocal activation of T cells. In turn, these activated T cells upregulated production of inflammatory mediators in tenocytes, while increasing the pathogenic collagen 3/collagen 1 ratio.ConclusionsInteraction between T cells and tenocytes induces the expression of inflammatory cytokines/chemokines in tenocytes, alters collagen composition favouring collagen 3 and self-amplifies T cell activation via an auto-regulatory feedback loop. Selectively targeting this adaptive/stromal interface may provide novel translational strategies in the management of human tendon disorders.


2001 ◽  
Vol 25 (12) ◽  
pp. 1137-1142 ◽  
Author(s):  
Jiřı́ Schwarz ◽  
Zuzana Trnková ◽  
Renáta Bedrlı́ková ◽  
Adam Jirásek ◽  
Dana Žáková ◽  
...  

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