Low level of Lck kinase in Th2 cells limits expression of CD4 co-receptor and S73 phosphorylation of transcription factor c-Jun

Shebzukhov, Yury; Stanislawiak, Silke; Bezhaeva, Taisiya; Nedospasov, Sergei A.; Kuprash, Dmitry V.

doi:10.1038/s41598-017-02553-y

Cited by 11 publications

(6 citation statements)

References 41 publications

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“…The Src-family tyrosine kinase Lck is associated with the CD4 and CD8 co-receptors. Lck expression is reduced in Th2 cells compared Th1 cells; Ectopic expression of Lck in Th2 cells led to increased expression of CD4 co-receptor and c-Jun phosphorylation at Serine 73 via concerted actions of JNK and ERK signaling [49], suggesting that Lck promotes Th1 polarization in part through a JNK-dependent process. JNK/c-Jun signaling is at least partly responsible for CD27-induced suppression of IL-17 and CCR6 expression and consequently reduced Th17 cell development and differentiation [50].…”

Section: Jnk Regulation Of Immune Responsesmentioning

confidence: 95%

“…Taken together, JNK mediates keratinocyte cell production and the release of chemokines and cytokines, leading to the recruitment of immune cells. These immune cells stimulate further dysregulation of skin cell proliferation and the continued amplification of the disease state [49,50,[69][70][71][72][73] (Figure 3).…”

Section: Jnk Regulation Of Barrier Protein Defectsmentioning

confidence: 99%

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The JNK Signaling Pathway in Inflammatory Skin Disorders and Cancer

Hammouda

Ford

Liu

et al. 2020

Cells

171

114

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The c-Jun N-terminal kinases (JNKs), with its members JNK1, JNK2, and JNK3, is a subfamily of (MAPK) mitogen-activated protein kinases. JNK signaling regulates a wide range of cellular processes, including cell proliferation, differentiation, survival, apoptosis, and inflammation. Dysregulation of JNK pathway is associated with a wide range of immune disorders and cancer. Our objective is to provide a review of JNK proteins and their upstream regulators and downstream effector molecules in common skin disorders, including psoriasis, dermal fibrosis, scleroderma, basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and melanoma.

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Section: Jnk Regulation Of Immune Responsesmentioning

confidence: 95%

Section: Jnk Regulation Of Barrier Protein Defectsmentioning

confidence: 99%

The JNK Signaling Pathway in Inflammatory Skin Disorders and Cancer

Hammouda

Ford

Liu

et al. 2020

Cells

171

114

View full text Add to dashboard Cite

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“…For the in vitro study, PBMCs from RA patients were collected after incubating with IgD and IgD-Fc-Ig for 48 h. Cells were lysed in lysis buffer supplemented with protease inhibitors and phosphatase inhibitors for 30 min on ice (24), whereas for the in vivo study, mice spleens were isolated from each group and homogenized in lysis buffer. Primary antibodies Lck (1:1,000), p-Lck (1:1,000), ZAP70 (1:1,000), p-ZAP70 (1:1,000), and βactin (1:1,000) were then incubated at 4 • C overnight, and a goat anti-rabbit secondary antibody (1:50,000) was incubated for 2 h at 37 • C. The membrane was scanned using GS-700 Imaging Densitometer.…”

Section: Western Blot Analysismentioning

confidence: 99%

Regulation of T Cell Activities in Rheumatoid Arthritis by the Novel Fusion Protein IgD-Fc-Ig

Zhang

Dong

et al. 2020

Front. Immunol.

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Rheumatoid arthritis (RA) is an autoimmune disease characterized by chronic inflammation and T cell hyper-activation. Emerging evidence has shown that the stimulation of immunoglobulin D (IgD) induces T cell activation and may contribute to disease pathogenesis. In this study, the sIgD concentrations were positively associated with disease activity score in 28 joints (DAS28) and anti-cyclic citrullinated peptide (anti-CCP) in RA. We demonstrated that IgD-Fc-Ig (composed of human IgD Fc domain and IgG 1 Fc domain, obtained through prokaryotic protein expression and chromatography purification) effectively inhibited the activation and proliferation of T cells in healthy controls and PBMCs in RA patients stimulated by IgD, recovered the Th17/Treg cell subset balance, and downregulated p-Lck and p-ZAP70 expression. Moreover, in vivo, IgD-Fc-Ig decreased the swollen joint counts and arthritis indices in mice with collagen-induced arthritis (CIA), and ameliorated histopathological changes in joint and spleen tissue. It also downregulated thymocyte proliferation and reduced the percentage of helper T cells (Th) and CD154 + T cells, reversed the imbalance of Th1/Th2 and Th17/Treg cell subsets, reduced cytokine and chemokine levels, and inhibited p-Lck and p-ZAP70 expression. Our data suggest that IgD-Fc-Ig fusion protein regulates T cell activity in RA. These findings have potential implications for IgD-targeted strategies to treat IgD-associated RA.

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“…LCK exists in all normal T cells. In the cells, LCK is located in the plasma membrane and vesicles around the centrosome, which is related to the cytoplasmic tail of CD4 co-receptors on helper T cells and CD8 co-receptors on cytotoxic T cells, to help T-cell receptor (TCR) complexes signal and participate in the TCR-mediated T-cell activation ( Shebzukhov et al, 2017 ). Human somatic cell experiments showed that the inhibition of LCK expression led to the inhibition of the TCR pathway, thereby hindering the differentiation and development of T cells.…”

Section: Discussionmentioning

confidence: 99%

Identification of Important Modules and Biomarkers That Are Related to Immune Infiltration Cells in Severe Burns Based on Weighted Gene Co-Expression Network Analysis

Zhang

Lin³

et al. 2022

Front. Genet.

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Background: Immunosuppression is an important trigger for infection and a significant cause of death in patients with severe burns. Nevertheless, the prognostic value of immune-related genes remains unclear. This study aimed to identify the biomarkers related to immunosuppression in severe burns.Methods: The gene expression profile and clinical data of 185 burn and 75 healthy samples were obtained from the GEO database. Immune infiltration analysis and gene set variation analysis were utilized to identify the disorder of circulating immune cells. A weighted gene co-expression network analysis (WGCNA) was carried out to select immune-related gene modules. Enrichment analysis and protein–protein interaction (PPI) network were performed to select hub genes. Next, LASSO and logistic regression were utilized to construct the hazard regression model with a survival state. Finally, we investigated the correlation between high- and low-risk patients in total burn surface area (TBSA), age, and inhalation injury.Results: Gene set variation analysis (GSVA) and immune infiltration analysis showed that neutrophils increased and T cells decreased in severe burns. In WGCNA, four modular differently expressed in burns and controls were related to immune cells. Based on PPI and enrichment analysis, 210 immune-related genes were identified, mainly involved in T-cell inhibition and neutrophil activation. In LASSO and logistic regression, we screened out key genes, including LCK, SKAP1 and GZMB, and LY9. In the ROC analysis, the area under the curve (AUC) of key genes was 0.945, indicating that the key genes had excellent diagnostic value. Finally, we discovered that the key genes were related to T cells, and the regression model performed well when accompanied by TBSA and age.Conclusion: We identified LCK, SKAP1, GZMB, and LY9 as good prognostic biomarkers that may play a role in post-burn immunosuppression against T-cell dysfunction and as potential immunotherapeutic targets for transformed T-cell dysfunction.

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Low level of Lck kinase in Th2 cells limits expression of CD4 co-receptor and S73 phosphorylation of transcription factor c-Jun

Cited by 11 publications

References 41 publications

The JNK Signaling Pathway in Inflammatory Skin Disorders and Cancer

The JNK Signaling Pathway in Inflammatory Skin Disorders and Cancer

Regulation of T Cell Activities in Rheumatoid Arthritis by the Novel Fusion Protein IgD-Fc-Ig

Identification of Important Modules and Biomarkers That Are Related to Immune Infiltration Cells in Severe Burns Based on Weighted Gene Co-Expression Network Analysis

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