Microenvironment-Driven Mast Cell Plasticity: Insights From Cytokine-Activated Gene Signatures in Skin and Respiratory Diseases.

Microenvironment-Driven Mast Cell Plasticity: Insights From Cytokine-Activated Gene Signatures in Skin and Respiratory Diseases.

Publication date: Sep 10, 2025

Mast cells (MCs) rapidly adapt to the microenvironment due to the plethora of cytokine receptors expressed. Understanding microenvironment-primed immune responses is essential to elucidate the phenotypic/functional changes MCs undergo, and thus understand their contribution to diseases and predict the most effective therapeutic strategies. We exposed primary human MCs to cytokines mimicking a T1/pro-inflammatory (IFNγ), T2/allergic (IL-4 + IL-13), alarmin-rich (IL-33) and pro-fibrotic/pro-tolerogenic (TGFβ) microenvironment. We investigated MC surface receptor expression, activation, cytokine, histamine, and prostaglandin D2 release, and performed transcriptomics to define shared and unique genetic features. Using machine learning, we extracted minimal cytokine-activated signatures and performed gene set variation analysis (GSVA), single-cell clustering, and pseudotime analyses on tissue MCs from skin and respiratory diseases. MCs exposed in vitro to IFNγ acquire an antigen-presenting phenotype (HLA-DR+), increase IgE-mediated responses and histamine release, while TGFβ inhibits activation and boosts integrin αvβ3 expression. IL-33 primarily drives cytokine (GM-CSF, IL-5, IL-10, IL-13) and chemokine production (IL-8, MCP-1, MIP-1α) and facilitates mixed IgG-IgE responses. Among uniquely expressed genes, 245 were highly informative to discriminate cytokine-primed MCs. GSVA revealed MC IL-4 + IL-13 signatures enriched in atopic dermatitis and psoriasis, IFNγ in COVID-19 infection and cystic fibrosis, IL-33 in COVID-19 and chronic obstructive pulmonary disease (COPD) and TGFβ in pulmonary fibrosis (PF) and chronic rhinosinusitis. Furthermore, we detected positive IL-33/TGFβ priming in eosinophil-high COPD. Minimal cytokine-activated signatures identified disease-cytokine-specific MC clusters and pseudotime trajectories, suggesting involvement of MCs in fibrosis (COPD/PF), T1/alarmin-driven inflammation (COVID-19) and mixed T1/T2 inflammatory responses (AD/psoriasis). In conclusion, in cytokine-driven settings, MCs are phenotypically and functionally diverse. Thus, unique MC signatures will help to identify cytokine-primed MCs and predict the efficacy of anti-cytokine treatment in MC-driven diseases.

Concepts Keywords
Allergy artificial intelligence
Rhinosinusitis cytokines
Rich IFN
Transcriptomics IL‐33
IL‐4
machine learning
mast cells
omics
TGFβ
transcriptomics

Semantics

Type Source Name
disease IDO cell
disease MESH Respiratory Diseases
drug DRUGBANK Binetrakin
drug DRUGBANK Histamine
drug DRUGBANK Prostaglandin D2
pathway REACTOME Release
drug DRUGBANK Sargramostim
drug DRUGBANK Interleukin-10
disease MESH atopic dermatitis
disease MESH psoriasis
disease MESH COVID-19
disease MESH infection
disease MESH cystic fibrosis
disease MESH chronic obstructive pulmonary disease
disease MESH pulmonary fibrosis
disease MESH rhinosinusitis
disease MESH fibrosis
disease MESH inflammation
disease MESH Long Covid

Original Article

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