Identification of shared mechanisms and targets between immune checkpoint inhibitor-associated myocarditis and autoimmune myocarditis

Objective This study aimed to explore the shared mechanisms and targets between immune checkpoint inhibitor-associated myocarditis (ICIM) and autoimmune myocarditis. Methods Relevant data were retrieved from public datasets and Gene Expression Omnibus (GEO) database. Gene set enrichment analysis (GS...

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Main Authors: Kai Yang, Min Zhang, Dong Li, Yuandong Yu, Fengjun Cao, Guoxing Wan
Format: Article
Language:English
Published: SAGE Publishing 2024-12-01
Series:European Journal of Inflammation
Online Access:https://doi.org/10.1177/1721727X231223578
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author Kai Yang
Min Zhang
Dong Li
Yuandong Yu
Fengjun Cao
Guoxing Wan
author_facet Kai Yang
Min Zhang
Dong Li
Yuandong Yu
Fengjun Cao
Guoxing Wan
author_sort Kai Yang
collection DOAJ
description Objective This study aimed to explore the shared mechanisms and targets between immune checkpoint inhibitor-associated myocarditis (ICIM) and autoimmune myocarditis. Methods Relevant data were retrieved from public datasets and Gene Expression Omnibus (GEO) database. Gene set enrichment analysis (GSEA) of differentially expressed genes (DEGs) was used to identify significant shared signaling pathways between ICIM and non-ICI associated autoimmune myocarditis (NICIAM) represented by ICIM model and experimental autoimmune myocarditis (EAM) model, respectively. Cell type enrichment analysis and immune infiltration analysis by clusterProfiler and ImmuCellAI were performed to identify critical immune cell component involved in ICIM and NICIAM. Additionally, core shared genes across ICIM and NICIAM were identified and validated by various models and methods. Results Interferon-γ response, inflammatory response and allograft rejection signaling were identified as the shared signaling pathways associated with ICIM and NICIAM. Enrichment analysis of cell type supported an important role of increased infiltration of T cells and macrophages in both ICIM and NICIAM. However, the predominant increase of infiltrated T cells was CD4+ T cells in NICIAM, while that were CD8+ T cells in ICIM. Core shared genes Lck and Cd3d expression were found increased in both ICIM and NICIAM, and Lck inhibition was further identified and validated as potential therapeutic approach. Conclusions Our study initially established a comorbidity model to identify potential molecular mechanism including interferon-γ response, inflammatory response and allograft rejection signaling accounting for the concerns of myocarditis risk in patients with preexisting autoimmune disease (PAD) receiving ICI treatment, and supported the therapeutic potential of targeting Lck or Cd3d.
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spelling doaj.art-bf9e0e9a31de4cba862addcf26629a342024-01-12T22:04:00ZengSAGE PublishingEuropean Journal of Inflammation2058-73922024-12-012210.1177/1721727X231223578Identification of shared mechanisms and targets between immune checkpoint inhibitor-associated myocarditis and autoimmune myocarditisKai YangMin ZhangDong LiYuandong YuFengjun CaoGuoxing WanObjective This study aimed to explore the shared mechanisms and targets between immune checkpoint inhibitor-associated myocarditis (ICIM) and autoimmune myocarditis. Methods Relevant data were retrieved from public datasets and Gene Expression Omnibus (GEO) database. Gene set enrichment analysis (GSEA) of differentially expressed genes (DEGs) was used to identify significant shared signaling pathways between ICIM and non-ICI associated autoimmune myocarditis (NICIAM) represented by ICIM model and experimental autoimmune myocarditis (EAM) model, respectively. Cell type enrichment analysis and immune infiltration analysis by clusterProfiler and ImmuCellAI were performed to identify critical immune cell component involved in ICIM and NICIAM. Additionally, core shared genes across ICIM and NICIAM were identified and validated by various models and methods. Results Interferon-γ response, inflammatory response and allograft rejection signaling were identified as the shared signaling pathways associated with ICIM and NICIAM. Enrichment analysis of cell type supported an important role of increased infiltration of T cells and macrophages in both ICIM and NICIAM. However, the predominant increase of infiltrated T cells was CD4+ T cells in NICIAM, while that were CD8+ T cells in ICIM. Core shared genes Lck and Cd3d expression were found increased in both ICIM and NICIAM, and Lck inhibition was further identified and validated as potential therapeutic approach. Conclusions Our study initially established a comorbidity model to identify potential molecular mechanism including interferon-γ response, inflammatory response and allograft rejection signaling accounting for the concerns of myocarditis risk in patients with preexisting autoimmune disease (PAD) receiving ICI treatment, and supported the therapeutic potential of targeting Lck or Cd3d.https://doi.org/10.1177/1721727X231223578
spellingShingle Kai Yang
Min Zhang
Dong Li
Yuandong Yu
Fengjun Cao
Guoxing Wan
Identification of shared mechanisms and targets between immune checkpoint inhibitor-associated myocarditis and autoimmune myocarditis
European Journal of Inflammation
title Identification of shared mechanisms and targets between immune checkpoint inhibitor-associated myocarditis and autoimmune myocarditis
title_full Identification of shared mechanisms and targets between immune checkpoint inhibitor-associated myocarditis and autoimmune myocarditis
title_fullStr Identification of shared mechanisms and targets between immune checkpoint inhibitor-associated myocarditis and autoimmune myocarditis
title_full_unstemmed Identification of shared mechanisms and targets between immune checkpoint inhibitor-associated myocarditis and autoimmune myocarditis
title_short Identification of shared mechanisms and targets between immune checkpoint inhibitor-associated myocarditis and autoimmune myocarditis
title_sort identification of shared mechanisms and targets between immune checkpoint inhibitor associated myocarditis and autoimmune myocarditis
url https://doi.org/10.1177/1721727X231223578
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