Matrix stiffness regulates profibrotic fibroblast differentiation and fibrotic niche activation in systemic sclerosis.

Objectives: Fibrosis progression in systemic sclerosis (SSc) has been attributed to matrix stiffness. Despite extensive research on fibroblast heterogeneity and subset imbalances in fibrotic disorders, the interplay between biomechanical cues and fibroblast dynamics remains largely unexplored. Here, we investigate how matrix stiffness alters fibroblast transcriptional state and influences lineage specification in fibrotic skin.

Methods: We employed a collagen I-based 3-dimensional culture system to expose fibroblasts to varying levels of matrix stiffness, followed by RNA sequencing to identify stiffness-responsive gene expression signature. We integrated single-cell RNA sequencing data from SSc and healthy skin samples to identify fibroblast subsets associated with this signature. Spatial transcriptomic analyses were performed to localise these fibroblasts and their associations with the fibrotic niche.

Results: Fibroblasts subjected to increased matrix stiffness exhibited a distinct transcriptional signature, amplified in SSc patients and enriched in PI16⁺ progenitor-like cells within the SFRP2⁺ fibrotic compartment. Further analysis indicated that PI16⁺ fibroblasts are predisposed to SFRP2⁺COMP⁺ PU.1⁺ myofibroblasts differentiation, whereas blocking mechanotransduction by focal adhesion kinase inhibition disrupts this process, suggesting that matrix stiffness is a key driver of this lineage transition. Spatial mapping revealed colocalisation of the PI16⁺ and COMP⁺ subsets in extracellular matrix-dense regions, highlighting the functional relevance of this relationship in fibrotic progression.

Conclusions: Our findings suggest that increased matrix stiffness promotes fibroblast precursor differentiation into SFRP2⁺ COMP⁺ PU.1⁺ myofibroblasts, thereby sustaining the vicious cycle of persistent fibrosis in absence of inflammatory triggers. These insights reveal new aspects of fibrosis pathogenesis and highlight biomechanical signals as therapeutic targets in SSc.