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Multidimensional analysis reveals innate and adaptive immune features associated with toxicities in patients receiving checkpoint inhibitor therapy

ABSTRACT: Analysis of 162 patients revealed that individuals who developed clinically significant irAEs exhibited a baseline proinflammatory, autoimmune-like state characterized by a significantly higher abundance of CD57+ T and natural killer (NK) T cells, plasmablasts, proliferating and activated CXCR3+ lymphocytes, CD8+ effector and terminal effector memory T cells, along with reduced NK cells and elevated plasma ANA levels. In irAE cases, we identified distinct baseline proinflammatory gene signatures, including markedly higher expression of IL1B and CXCL8 in monocytes and CXCR3, TNF, and IFNG in T/NK cells. TNF signaling was the most enriched pathway, while immunosuppressive genes SIGLEC7 and CXCR4 were downregulated. Following ICI initiation, these patients exhibited an enhanced shift toward an activated and inflammatory immune phenotype, including monocyte reprogramming characterized by upregulation of IL18 and elevated gene expression levels of CXCL10. Conversely, post-treatment levels of CXCL8 were decreased in irAE patients. Notably, in patients who did not develop clinically significant irAE, we identified increased baseline abundance of a TGFBIhigh myeloid cluster enriched in immunosuppressive markers such as STAB1. In addition, patients without irAE exhibited upregulation of TNF and AIRE, accompanied by distinct myeloid protumorigenic reprogramming.

ORGANISM(S): Homo sapiens

PROVIDER: GSE249898 | GEO | 2025/10/28

REPOSITORIES: GEO

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Project description:Hayashi2013 - TNF-induced Signaling Dynamics Model (Model A) Tumor necrosis factor (TNF) plays a crucial role in inflammation and is associated with diseases such as rheumatoid arthritis and cancer. While TNF signaling pathways are well studied, targeted regulation of proinflammatory responses remains a challenge. In this study, Hayashi et al., (2013) developed a computational model to simulate TNF-induced activation of MAP kinase (p38), NF-κB, and proinflammatory gene expression in murine fibroblast cells. The model parameters were optimized to fit experimental data, ensuring accurate representation of TNF signaling dynamics. The simulations using in silico knockouts identified receptor-interacting protein 1 (RIP1) as a key regulator of TNF-driven proinflammatory responses. Experimental validation using Necrostatin-1, a RIP1 inhibitor, confirmed these predictions and demonstrated its potential as a therapeutic target for regulating proinflammatory mediators in TNF-driven diseases. This model is described in the article: Hayashi K, Piras V, Tabata S, Tomita M, Selvarajoo K. A systems biology approach to suppress TNF-induced proinflammatory gene expressions. Cell Commun Signal. 2013 Nov 7;11:84. doi: 10.1186/1478-811X-11-84. PMID: 24199619; PMCID: PMC3832246. Abstract: Background: Tumor necrosis factor (TNF) is a widely studied cytokine (ligand) that induces proinflammatory signaling and regulates myriad cellular processes. In major illnesses, such as rheumatoid arthritis and certain cancers, the expression of TNF is elevated. Despite much progress in the field, the targeted regulation of TNF response for therapeutic benefits remains suboptimal. Here, to effectively regulate the proinflammatory response induced by TNF, a systems biology approach was adopted. Results: We developed a computational model to investigate the temporal activations of MAP kinase (p38), nuclear factor (NF)-κB, and the kinetics of 3 groups of genes, defined by early, intermediate and late phases, in murine embryonic fibroblast (MEF) and 3T3 cells. To identify a crucial target that suppresses, and not abolishes, proinflammatory genes, the model was tested in several in silico knock out (KO) conditions. Among the candidate molecules tested, in silico RIP1 KO effectively regulated all groups of proinflammatory genes (early, middle and late). To validate this result, we experimentally inhibited TNF signaling in MEF and 3T3 cells with RIP1 inhibitor, Necrostatin-1 (Nec-1), and investigated 10 genes (Il6, Nfkbia, Jun, Tnfaip3, Ccl7, Vcam1, Cxcl10, Mmp3, Mmp13, Enpp2) belonging to the 3 major groups of upregulated genes. As predicted by the model, all measured genes were significantly impaired. Conclusions: Our results demonstrate that Nec-1 modulates TNF-induced proinflammatory response, and may potentially be used as a therapeutic target for inflammatory diseases such as rheumatoid arthritis and osteoarthritis. Figure 2B, obtained from the simulation of TNFR1 Model A, is highlighted here. This model was curated during the Hackathon hosted by BioMed X GmbH in 2024.

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Multidimensional analysis reveals innate and adaptive immune features associated with toxicities in patients receiving checkpoint inhibitor therapy

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