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REVIEW article

Front. Immunol.

Sec. Autoimmune and Autoinflammatory Disorders : Autoimmune Disorders

This article is part of the Research TopicNew Insights into Inflammation Driven Autoimmune Skin Disorders: Trends and ChallengesView all 27 articles

Mapping the Immune Landscape of Systemic Sclerosis: From Cellular Crosstalk to Precision Therapeutic Strategies The Immune Landscape of Systemic Sclerosis: From Pathogenic Mechanisms to Precision Therapeutic Breakthroughs

Provisionally accepted
  • Huashan Hospital, Fudan University, Shanghai, China

The final, formatted version of the article will be published soon.

Systemic sclerosis (SSc) is a chronic autoimmune disease characterized by immune dysregulation, microvascular damage, and multi-organ fibrosis. Recent breakthroughs in single-cell and spatial multi-omics technologies have profoundly revealed the high heterogeneity of the SSc immune microenvironment, including extensive aberrant activation of innate immunity (e.g., dendritic cells, macrophages, neutrophils) and adaptive immunity (T cells, B cells), and their interaction with fibroblasts and endothelial cells through an "immune-stromal-vascular" network that collectively drives the fibrotic process. These findings have advanced disease subtyping based on molecular features (e.g., inflammatory, fibrotic) and the development of precision therapeutic strategies. Emerging therapies targeting the IL-6 receptor (tocilizumab), B cells (rituximab, CAR-T), the JAK-STAT pathway (tofacitinib, baricitinib), and T-cell co-stimulation (abatacept) have shown potential to improve disease progression in clinical studies. However, heterogeneity in treatment response, difficulty in reversing fibrosis, and the lack of biomarkers remain current challenges. Future efforts require integrating multi-omics and artificial intelligence technologies to build dynamic predictive models, promoting multi-target combination and individualized therapies, ultimately aiming for early intervention and long-term remission in SSc. Systemic sclerosis (SSc) is a chronic autoimmune disease characterized by immune dysregulation, microvascular damage, and multi-organ fibrosis. Recent breakthroughs in single-cell and spatial multi-omics technologies have profoundly revealed the high heterogeneity of the SSc immune microenvironment, including extensive aberrant activation of innate immunity (e.g., dendritic cells, macrophages, neutrophils) and adaptive immunity (T cells, B cells), and their interaction with fibroblasts and endothelial cells through an "immune-stromal-vascular" network that collectively drives the fibrotic process. These findings have advanced disease subtyping based on molecular features (e.g., inflammatory, fibrotic) and the development of precision therapeutic strategies. Emerging therapies targeting the IL-6 receptor (tocilizumab), B cells (rituximab, belimumab,CAR-T), the JAK-STAT pathway (tofacitinib, baricitinib), and T-cell co-stimulation (abatacept) have shown potential to improve disease progression in clinical studies. However, heterogeneity in treatment response, difficulty in reversing fibrosis, and the lack of biomarkers remain current challenges. Future efforts require integrating multi-omics and artificial intelligence technologies to build dynamic predictive models, promoting multi-target combination and individualized therapies, ultimately aiming for early intervention and long-term remission in SSc.

Keywords: cellular crosstalk, Fibrosis, immune microenvironment, precision medicine, systemic sclerosis, targeted therapy, vasculopathy

Received: 25 Sep 2025; Accepted: 12 Feb 2026.

Copyright: © 2026 Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mengguo Liu

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