scholarly journals Calcium-dependent Activation of Interleukin-21 Gene Expression in T Cells

2005 ◽  
Vol 280 (26) ◽  
pp. 25291-25297 ◽  
Author(s):  
Hyoung-Pyo Kim ◽  
Lisa L. Korn ◽  
Ana M. Gamero ◽  
Warren J. Leonard
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Calcium Dependent ◽  
Interleukin 21

scholarly journals Aberrant expression of USF2 in refractory rheumatoid arthritis and its regulation of proinflammatory cytokines in Th17 cells

2020 ◽  
Vol 117 (48) ◽  
pp. 30639-30648
Author(s):  
Dan Hu ◽  
Emily C. Tjon ◽  
Karin M. Andersson ◽  
Gabriela M. Molica ◽  
Minh C. Pham ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gene Expression ◽  
T Cells ◽  
Transcription Factor ◽  
Proinflammatory Cytokines ◽  
Th17 Cells ◽  
Gene Set Enrichment Analysis ◽  
Aberrant Expression ◽  
Signature Genes ◽  
The Impact

IL-17–producing Th17 cells are implicated in the pathogenesis of rheumatoid arthritis (RA) and TNF-α, a proinflammatory cytokine in the rheumatoid joint, facilitates Th17 differentiation. Anti-TNF therapy ameliorates disease in many patients with rheumatoid arthritis (RA). However, a significant proportion of patients do not respond to this therapy. The impact of anti-TNF therapy on Th17 responses in RA is not well understood. We conducted high-throughput gene expression analysis of Th17-enriched CCR6+CXCR3−CD45RA−CD4+T (CCR6+T) cells isolated from anti-TNF–treated RA patients classified as responders or nonresponders to therapy. CCR6+T cells from responders and nonresponders had distinct gene expression profiles. Proinflammatory signaling was elevated in the CCR6+T cells of nonresponders, and pathogenic Th17 signature genes were up-regulated in these cells. Gene set enrichment analysis on these signature genes identified transcription factor USF2 as their upstream regulator, which was also increased in nonresponders. Importantly, short hairpin RNA targetingUSF2in pathogenic Th17 cells led to reduced expression of proinflammatory cytokines IL-17A, IFN-γ, IL-22, and granulocyte-macrophage colony-stimulating factor (GM-CSF) as well as transcription factor T-bet. Together, our results revealed inadequate suppression of Th17 responses by anti-TNF in nonresponders, and direct targeting of the USF2-signaling pathway may be a potential therapeutic approach in the anti-TNF refractory RA.

scholarly journals Gene expression profiling-based risk prediction and profiles of immune infiltration in diffuse large B-cell lymphoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Selin Merdan ◽  
Kritika Subramanian ◽  
Turgay Ayer ◽  
Johan Van Weyenbergh ◽  
Andres Chang ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
B Cell ◽  
Risk Prediction ◽  
Expression Profiling ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Gene Signatures ◽  
Large B Cell Lymphoma ◽  
Large B Cell

AbstractThe clinical risk stratification of diffuse large B-cell lymphoma (DLBCL) relies on the International Prognostic Index (IPI) for the identification of high-risk disease. Recent studies suggest that the immune microenvironment plays a role in treatment response prediction and survival in DLBCL. This study developed a risk prediction model and evaluated the model’s biological implications in association with the estimated profiles of immune infiltration. Gene-expression profiling of 718 patients with DLBCL was done, for which RNA sequencing data and clinical covariates were obtained from Reddy et al. (2017). Using unsupervised and supervised machine learning methods to identify survival-associated gene signatures, a multivariable model of survival was constructed. Tumor-infiltrating immune cell compositions were enumerated using CIBERSORT deconvolution analysis. A four gene-signature-based score was developed that separated patients into high- and low-risk groups. The combination of the gene-expression-based score with the IPI improved the discrimination on the validation and complete sets. The gene signatures were successfully validated with the deconvolution output. Correlating the deconvolution findings with the gene signatures and risk score, CD8+ T-cells and naïve CD4+ T-cells were associated with favorable prognosis. By analyzing the gene-expression data with a systematic approach, a risk prediction model that outperforms the existing risk assessment methods was developed and validated.

scholarly journals OP0021 IDENTIFICATION OF DIFFERENTIALLY EXPRESSED GENES IN EARLY RHEUMATOID ARTHRITIS PATIENTS RESPONDING TO TOCILIZUMAB

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 12.2-12
Author(s):  
I. Muller ◽  
M. Verhoeven ◽  
H. Gosselt ◽  
M. Lin ◽  
T. De Jong ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gene Expression ◽  
T Cells ◽  
Gene Ontology ◽  
Regulatory T Cells ◽  
Early Rheumatoid Arthritis ◽  
Whole Blood ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Double Blind

Background:Tocilizumab (TCZ) is a monoclonal antibody that binds to the interleukin 6 receptor (IL-6R), inhibiting IL-6R signal transduction to downstream inflammatory mediators. TCZ has shown to be effective as monotherapy in early rheumatoid arthritis (RA) patients (1). However, approximately one third of patients inadequately respond to therapy and the biological mechanisms underlying lack of efficacy for TCZ remain elusive (1). Here we report gene expression differences, in both whole blood and peripheral blood mononuclear cells (PBMC) RNA samples between early RA patients, categorized by clinical TCZ response (reaching DAS28 < 3.2 at 6 months). These findings could lead to identification of predictive biomarkers for TCZ response and improve RA treatment strategies.Objectives:To identify potential baseline gene expression markers for TCZ response in early RA patients using an RNA-sequencing approach.Methods:Two cohorts of RA patients were included and blood was collected at baseline, before initiating TCZ treatment (8 mg/kg every 4 weeks, intravenously). DAS28-ESR scores were calculated at baseline and clinical response to TCZ was defined as DAS28 < 3.2 at 6 months of treatment. In the first cohort (n=21 patients, previously treated with DMARDs), RNA-sequencing (RNA-seq) was performed on baseline whole blood PAXgene RNA (Illumina TruSeq mRNA Stranded) and differential gene expression (DGE) profiles were measured between responders (n=14) and non-responders (n=7). For external replication, in a second cohort (n=95 therapy-naïve patients receiving TCZ monotherapy), RNA-seq was conducted on baseline PBMC RNA (SMARTer Stranded Total RNA-Seq Kit, Takara Bio) from the 2-year, multicenter, double-blind, placebo-controlled, randomized U-Act-Early trial (ClinicalTrials.gov identifier: NCT01034137) and DGE was analyzed between 84 responders and 11 non-responders.Results:Whole blood DGE analysis showed two significantly higher expressed genes in TCZ non-responders (False Discovery Rate, FDR < 0.05): urotensin 2 (UTS2) and caveolin-1 (CAV1). Subsequent analysis of U-Act-Early PBMC DGE showed nine differentially expressed genes (FDR < 0.05) of which expression in clinical TCZ non-responders was significantly higher for eight genes (MTCOP12, ZNF774, UTS2, SLC4A1, FECH, IFIT1B, AHSP, and SPTB) and significantly lower for one gene (TND2P28M). Both analyses were corrected for baseline DAS28-ESR, age and gender. Expression of UTS2, with a proposed function in regulatory T-cells (2), was significantly higher in TCZ non-responders in both cohorts. Furthermore, gene ontology enrichment analysis revealed no distinct gene ontology or IL-6 related pathway(s) that were significantly different between TCZ-responders and non-responders.Conclusion:Several genes are differentially expressed at baseline between responders and non-responders to TCZ therapy at 6 months. Most notably, UTS2 expression is significantly higher in TCZ non-responders in both whole blood as well as PBMC cohorts. UTS2 could be a promising target for further analyses as a potential predictive biomarker for TCZ response in RA patients in combination with clinical parameters (3).References:[1]Bijlsma JWJ, Welsing PMJ, Woodworth TG, et al. Early rheumatoid arthritis treated with tocilizumab, methotrexate, or their combination (U-Act-Early): a multicentre, randomised, double-blind, double-dummy, strategy trial. Lancet. 2016;388(10042):343-55.[2]Bhairavabhotla R, Kim YC, Glass DD, et al. Transcriptome profiling of human FoxP3+ regulatory T cells. Human Immunology. 2016;77(2):201-13.[3]Gosselt HR, Verhoeven MMA, Bulatovic-Calasan M, et al. Complex machine-learning algorithms and multivariable logistic regression on par in the prediction of insufficient clinical response to methotrexate in rheumatoid arthritis. Journal of Personalized Medicine. 2021;11(1).Disclosure of Interests:None declared

274 Tumoral and peripheral immunophenotype of refractory vs relapse to PD-(L)1 blockade in patients with advanced non-small cell lung cancer

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A299-A299
Author(s):  
Maria Ascierto ◽  
Matthew Hellmann ◽  
Nathan Standifer ◽  
Song Wu ◽  
Han Si ◽  
...  
Keyword(s):  
Gene Expression ◽  
Informed Consent ◽  
Checkpoint Inhibitors ◽  
Patient Response ◽  
Calcium Dependent ◽  
Immune Exhaustion ◽  
Previously Treated ◽  
Expression Pathways ◽  
Relapsed Disease ◽  
Written Informed Consent

BackgroundDespite the encouraging successes of immune checkpoint inhibitors, many patients do not benefit and are either refractory or relapse. The mechanisms of refractory or relapsed disease following PD-(L)1 blockade are largely unknown. To identify characteristics associated with refractory or relapsed disease we explored the immune and genomic landscape of samples derived from NSCLC patients who previously received PD-(L)1 blockade and had blood and fresh tumor biopsies collected at the time of progression.MethodsPatient response categories were defined prospectively; ‘refractory’ defined as progression within 16 weeks of initiating PD-(L)1 and ‘relapse’ defined as initial clinical benefit (CR, PR, SD) followed by progression. RNAseq (n=52) and PD-L1 IHC (n=22) were performed on tumor tissue. Immune profiling of whole blood was assessed using flow cytometry or Biomark HD (Fluidigm) gene expression panel (n=54 and n=62, respectively). Differential gene expression was defined as unadjusted p<0.05 and fold-difference >1.5. Pathways analysis was conducted by David tool. Patient samples were collected during screening for clinical trial of second line immunotherapy. Written informed consent was obtained from the patients for publication of this abstract.ResultsIn patients with NSCLC previously treated with PD-(L)1 blockade, tumors of relapsed patients were characterized by increased expression of genes associated with interferon signaling (e.g. CXCL9, SPIC, IFNg), immune suppression (e.g. ARG1, TGFB), immune exhaustion (e.g. ADORA2A), and increased PD-L1 expression (by gene expression and IHC). Refractory disease was associated with increased cadherin signaling and calcium-dependent-cell-adhesion gene expression pathways. In the periphery, reduced quantities of B cells and activated (HLA-DR+ or CD38+) or proliferating (Ki67+) CD8+ T cells were observed in refractory patients.ConclusionsThe tumor and peripheral compartments of patients with NSCLC previously treated with PD-(L)1 blockade differ based on prior response. Relapsed patients tend to have signals of sturdy immune activation and chronic inflammation thus ultimately leading to immune exhaustion. These results may help inform rational therapeutic strategies to overcome resistance to PD-(L)1 blockade in NSCLC.Trial RegistrationNCT02000947Ethics ApprovalResearch on human samples here analyzed have been performed in accordance with the Declaration of Helsinki.ConsentWritten informed consent was obtained from the patient for publication of this abstract.

scholarly journals POS0859 DEEP PHENOTYPING OF DERMATOMYOSITIS BASED ON LIPID FERROPTOSIS-RELATED GENES BY MACHINE LEARNING

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 684.1-684
Author(s):  
J. Q. Zhang ◽  
S. X. Zhang ◽  
R. Zhao ◽  
J. Qiao ◽  
M. T. Qiu ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Expression Profiles ◽  
Inflammatory Myopathy ◽  
Shanxi Province ◽  
Survival Prediction ◽  
Training Set ◽  
Redox Biology ◽  
Score Model ◽  
Validation Set

Background:Dermatomyositis (DM) is an idiopathic inflammatory myopathy with heterogeneous clinical manifestation that raise challenges regarding diagnosis and therapy1. Ferroptosis is a newly discovered form of regulated cell death that is the nexus between metabolism, redox biology, and rheumatic immune diseases2. However, how ferroptosis maintains the balance of lymphocyte T cells and affect disease activity in DM is unclear.Objectives:To investigate an ferroptosis-related multiple gene expression signature for classification by assessing the global gene expression profile, and calculate the lymphocyte T cells status in the different subsets.Methods:Gene expression profiles of skeletal muscle from DM samples were acquired from GEO database. GSE143323 (30 patients and 20 HCs) was selected as the training set. The GSE3307 contained 21 DM patients and was selected as the validation set. The 60 ferroptosis genes were obtained from previous literature3. The intersection of the global gene and ferroptosis genes was considered the set of significant G-Ferroptosis genes for further analysis. The “NMF” (R-package) was applied as an unsupervised clustering method for sample classification by using G-Ferroptosis genes expression microarray data from the training datasets. An ferroptosis score model was constructed. The performance of the ferroptosis genes-based risk score model constructed by the DM training set was validated in the batch-1 and batch-2 DM sets. Normalized ferroptosis genes training data was used to compare the ssGSEA scores of gene sets between the high risk and low risk group. The statistical software package R (version 4.0.3) was used for all analyses. P value < 0.05 were considered statistically significant.Results:We selected 54 significant G-Ferroptosis genes for further analysis in training set. There were 2 distinct subtypes (high-ferroptosis-score groups and low-ferroptosis-score groups) identified in G-Ferroptosis genes cohort which were also identified in validation datasets (Fig.1A, C, D). Metallothionein 1G (MT1G) was a characteristic gene of low-ferroptosis-score group. The characteristic genes of high-ferroptosis-score group were acyl-CoA synthetase family member 2(ACSF2) and aconitase 1(ACO1) (Fig.1B). Patients in high-ferroptosis-score group had a lower level of Tregs compared with that of low-ferroptosis-score patients in both training and validation set (P <0.05, Fig.1E).Conclusion:The biological process of ferroptosis is associated with the lever of Tregs, suggesting the process of ferroptosis may be involved in the disease progression of DM. Identificating ferroptosis-related features for DM might provide a new idea for clinical treatment.References:[1]DeWane ME, Waldman R, Lu J. Dermatomyositis: Clinical features and pathogenesis. Journal of the American Academy of Dermatology 2020;82(2):267-81. doi: 10.1016/j.jaad.2019.06.1309 [published Online First: 2019/07/08].[2]Liang C, Zhang X, Yang M, et al. Recent Progress in Ferroptosis Inducers for Cancer Therapy. Advanced materials (Deerfield Beach, Fla) 2019;31(51):e1904197. doi: 10.1002/adma.201904197 [published Online First: 2019/10/09].[3]Liang JY, Wang DS, Lin HC, et al. A Novel Ferroptosis-related Gene Signature for Overall Survival Prediction in Patients with Hepatocellular Carcinoma. International journal of biological sciences 2020;16(13):2430-41. doi: 10.7150/ijbs.45050 [published Online First: 2020/08/08].Acknowledgements:This project was supported by National Science Foundation of China (82001740).Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

Sign in / Sign up

Export Citation Format

Share Document