Integrated bioinformatic analysis and experimental validation for exploring the key immune checkpoint of COPD

•Bioinformatic analysis reveals that HAVCR2 expression is strongly correlated with CD8+ T cells in COPD.•Flow cytometry reveals high expression of Tim3 in lung CD8+ T cells of tobacco-exposed COPD mice.•Inhibiting or knocking out Tim3 promotes the expression of Tc1 cells in COPD mice while inhibitin...

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Veröffentlicht in:Gene 2024-11, Vol.927, p.148711, Article 148711
Hauptverfasser: Ke, Junyi, Huang, Shu, He, Zhixiong, Lei, Siyu, Lin, Shiya, Duan, Minchao
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He, Zhixiong
Lei, Siyu
Lin, Shiya
Duan, Minchao
description •Bioinformatic analysis reveals that HAVCR2 expression is strongly correlated with CD8+ T cells in COPD.•Flow cytometry reveals high expression of Tim3 in lung CD8+ T cells of tobacco-exposed COPD mice.•Inhibiting or knocking out Tim3 promotes the expression of Tc1 cells in COPD mice while inhibiting Tc17 cells.•Inhibiting Tim3 promotes effector memory CD8+ T cells while inhibiting central memory CD8+ T cells in COPD mice. There is growing evidence indicating immune inflammation is a key factor in the progression of chronic obstructive pulmonary disease (COPD). Immune checkpoints (ICs) are crucial targets for modulating the functional activation and differentiation of immune cells, particularly in relation to immune inflammation and the regulation of T cell activation and exhaustion. However, the precise mechanisms of ICs in COPD remain understood. COPD datasets were obtained from the Gene Expression Omnibus (GEO) and analyzed using GEO2R and Limma to identify differentially expressed genes. LASSO regression was then applied to screen ICs closely associated with COPD. Finally, target genes were selected based on gene expression profiles. Gene ontology (GO), immune infiltration analysis, and gene set enrichment analysis (GSEA) were utilized to assess the relationship between IC genes (ICGs) and immune cells. Subsequently, tobacco-exposed mice, anti-Tim3-treated mice, and HAVCR2-knockout mice were generated, with flow cytometry being used to confirm the results. Through the analysis of GSE38974 and LASSO regression, five ICGs were identified. Subsequent validation using GSE20257 and GSE76925 confirmed these findings. Gene expression profiling highlighted HAVCR2 as having the strongest correlation with COPD. Further investigation through immune infiltration analysis, GO, and GSEA indicated a link between HAVCR2 and CD8+ T cells in COPD. Flow cytometry experiments demonstrated high Tim3 expression in CD8+ T cells of mice exposed to tobacco, promoting Tc1 and inhibiting Tc17, thus affecting CD8+ Tem activation and CD8+ Tcm formation, leading to an immune imbalance within CD8+ T cells. Prolonged exposure to tobacco upregulates Tim3 in CD8+ T cells, triggering its regulatory effects on Tc1/Tc17. Knocking out HAVCR2 further upregulated the expression of CD8+ Tem while suppressing the expression of CD8+ Tcm, indicating that Tim3 plays a role in the activation and differentiation of CD8+ T cells in the context of tobacco exposure.
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There is growing evidence indicating immune inflammation is a key factor in the progression of chronic obstructive pulmonary disease (COPD). Immune checkpoints (ICs) are crucial targets for modulating the functional activation and differentiation of immune cells, particularly in relation to immune inflammation and the regulation of T cell activation and exhaustion. However, the precise mechanisms of ICs in COPD remain understood. COPD datasets were obtained from the Gene Expression Omnibus (GEO) and analyzed using GEO2R and Limma to identify differentially expressed genes. LASSO regression was then applied to screen ICs closely associated with COPD. Finally, target genes were selected based on gene expression profiles. Gene ontology (GO), immune infiltration analysis, and gene set enrichment analysis (GSEA) were utilized to assess the relationship between IC genes (ICGs) and immune cells. Subsequently, tobacco-exposed mice, anti-Tim3-treated mice, and HAVCR2-knockout mice were generated, with flow cytometry being used to confirm the results. Through the analysis of GSE38974 and LASSO regression, five ICGs were identified. Subsequent validation using GSE20257 and GSE76925 confirmed these findings. Gene expression profiling highlighted HAVCR2 as having the strongest correlation with COPD. Further investigation through immune infiltration analysis, GO, and GSEA indicated a link between HAVCR2 and CD8+ T cells in COPD. Flow cytometry experiments demonstrated high Tim3 expression in CD8+ T cells of mice exposed to tobacco, promoting Tc1 and inhibiting Tc17, thus affecting CD8+ Tem activation and CD8+ Tcm formation, leading to an immune imbalance within CD8+ T cells. Prolonged exposure to tobacco upregulates Tim3 in CD8+ T cells, triggering its regulatory effects on Tc1/Tc17. Knocking out HAVCR2 further upregulated the expression of CD8+ Tem while suppressing the expression of CD8+ Tcm, indicating that Tim3 plays a role in the activation and differentiation of CD8+ T cells in the context of tobacco exposure.</description><identifier>ISSN: 0378-1119</identifier><identifier>ISSN: 1879-0038</identifier><identifier>EISSN: 1879-0038</identifier><identifier>DOI: 10.1016/j.gene.2024.148711</identifier><identifier>PMID: 38906393</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>CD8+T cell ; COPD ; Flow cytometry ; HAVCR2 ; Immune checkpoint ; TIM3</subject><ispartof>Gene, 2024-11, Vol.927, p.148711, Article 148711</ispartof><rights>2024 Elsevier B.V.</rights><rights>Copyright © 2024 Elsevier B.V. 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There is growing evidence indicating immune inflammation is a key factor in the progression of chronic obstructive pulmonary disease (COPD). Immune checkpoints (ICs) are crucial targets for modulating the functional activation and differentiation of immune cells, particularly in relation to immune inflammation and the regulation of T cell activation and exhaustion. However, the precise mechanisms of ICs in COPD remain understood. COPD datasets were obtained from the Gene Expression Omnibus (GEO) and analyzed using GEO2R and Limma to identify differentially expressed genes. LASSO regression was then applied to screen ICs closely associated with COPD. Finally, target genes were selected based on gene expression profiles. Gene ontology (GO), immune infiltration analysis, and gene set enrichment analysis (GSEA) were utilized to assess the relationship between IC genes (ICGs) and immune cells. Subsequently, tobacco-exposed mice, anti-Tim3-treated mice, and HAVCR2-knockout mice were generated, with flow cytometry being used to confirm the results. Through the analysis of GSE38974 and LASSO regression, five ICGs were identified. Subsequent validation using GSE20257 and GSE76925 confirmed these findings. Gene expression profiling highlighted HAVCR2 as having the strongest correlation with COPD. Further investigation through immune infiltration analysis, GO, and GSEA indicated a link between HAVCR2 and CD8+ T cells in COPD. Flow cytometry experiments demonstrated high Tim3 expression in CD8+ T cells of mice exposed to tobacco, promoting Tc1 and inhibiting Tc17, thus affecting CD8+ Tem activation and CD8+ Tcm formation, leading to an immune imbalance within CD8+ T cells. Prolonged exposure to tobacco upregulates Tim3 in CD8+ T cells, triggering its regulatory effects on Tc1/Tc17. 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There is growing evidence indicating immune inflammation is a key factor in the progression of chronic obstructive pulmonary disease (COPD). Immune checkpoints (ICs) are crucial targets for modulating the functional activation and differentiation of immune cells, particularly in relation to immune inflammation and the regulation of T cell activation and exhaustion. However, the precise mechanisms of ICs in COPD remain understood. COPD datasets were obtained from the Gene Expression Omnibus (GEO) and analyzed using GEO2R and Limma to identify differentially expressed genes. LASSO regression was then applied to screen ICs closely associated with COPD. Finally, target genes were selected based on gene expression profiles. Gene ontology (GO), immune infiltration analysis, and gene set enrichment analysis (GSEA) were utilized to assess the relationship between IC genes (ICGs) and immune cells. Subsequently, tobacco-exposed mice, anti-Tim3-treated mice, and HAVCR2-knockout mice were generated, with flow cytometry being used to confirm the results. Through the analysis of GSE38974 and LASSO regression, five ICGs were identified. Subsequent validation using GSE20257 and GSE76925 confirmed these findings. Gene expression profiling highlighted HAVCR2 as having the strongest correlation with COPD. Further investigation through immune infiltration analysis, GO, and GSEA indicated a link between HAVCR2 and CD8+ T cells in COPD. Flow cytometry experiments demonstrated high Tim3 expression in CD8+ T cells of mice exposed to tobacco, promoting Tc1 and inhibiting Tc17, thus affecting CD8+ Tem activation and CD8+ Tcm formation, leading to an immune imbalance within CD8+ T cells. Prolonged exposure to tobacco upregulates Tim3 in CD8+ T cells, triggering its regulatory effects on Tc1/Tc17. Knocking out HAVCR2 further upregulated the expression of CD8+ Tem while suppressing the expression of CD8+ Tcm, indicating that Tim3 plays a role in the activation and differentiation of CD8+ T cells in the context of tobacco exposure.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>38906393</pmid><doi>10.1016/j.gene.2024.148711</doi><orcidid>https://orcid.org/0009-0008-7533-2903</orcidid></addata></record>
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subjects CD8+T cell
COPD
Flow cytometry
HAVCR2
Immune checkpoint
TIM3
title Integrated bioinformatic analysis and experimental validation for exploring the key immune checkpoint of COPD
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