fetching data ...

OP0178 (2024)
IMAGING MASS CYTOMETRY-BASED CHARACTERIZATION OF FIBROBLASTS SUBSETS, THEIR NETWORKS AND SPATIAL MICROENVIRONMENT IN SYSTEMIC SCLEROSIS
Keywords: '-omics, Skin, Fibroblasts, Imaging
A. Rius Rigau1,2, M. Liang3,4,5, T. Filla4,5, V. Devakumar4,5, A. E. Matei4,5, A. H. Györfi4,5, G. Schett1,2, J. Distler4,5, Y. N. Li4,5
1Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and University Hospital Erlangen, Department of Internal Medicine 3, Rheumatology and Clinical Immunology, Erlangen, Germany
2FAU Erlangen-Nürnberg and University Hospital Erlangen, Deutsches Zentrum Immuntherapie (DZI), Erlangen, Germany
3Huashan Hospital, Fudan University, Department of Rheumatology, Shanghai, China
4University Hospital Düsseldorf, Hiller Research Center, Medical Faculty of Heinrich Heine University, Düsseldorf, Germany
5University Hospital Düsseldorf, Clinic for Rheumatology, Medical Faculty of Heinrich Heine University, Düsseldorf, Germany

Background: Systemic sclerosis (SSc) is an autoimmune disorder characterized by excessive extracellular matrix accumulation. Fibroblasts are the key players in the fibrotic tissue remodeling process. Several evidences have emerged supporting that fibroblasts are a heterogeneous group of cells with distinct phenotypes and functions. However, their spatial distribution, the organization of local niches and interactions between fibroblast are not known to date.


Objectives: Using Imaging Mass Cytometry (IMC) as spatial proteomics technique with subcellular resolution, we aimed to characterize fibroblasts compartments, subsets, as well as their interactions and spatial relationships in the skin of SSc patients and healthy controls.


Methods: We stained skin histology section from 12 SSc and 7 donors using a 36 metal-conjugated antibody cocktail and analyzed by an IMC device to generate highly multiplex images of the skin. We employed bioinformatics pipelines to deconvolute the stromal cells subsets, characterize their phenotype and their spatial relationships.


Results: We identified 13 different subsets of fibroblasts, including FAP high , ADRP + , myofibroblasts, S1PR + , Thy1 + ADAM high PU.1 high , Cdh11 + , PI16 + FAP + , PI16 + FAP - , PI16 + FAP + TFAM low , TFAM high , ADAM12 + Gli1 + , Thy1 + ADAM12 low and resting fibroblasts. The frequencies of myofibroblast, S1PR + , FAP high , Thy1 + ADAM high PU.1 high and ADAM12 + Gli1 + are significantly higher in SSc individuals compared to healthy controls, while the levels of PI16 + FAP + , Thy1 + ADAM low and TFAM high are significantly decreased in SSc. Based on the spatial relationship of the individual cell types, we identified distinct cellular neighborhood clusters. Three are of particular interest. In one of these clusters the number of fibroblasts increases in SSc with a predominance of S1PR + fibroblasts. Of note, the proportion of S1PR + fibroblasts is positively correlated with clinical parameters of fibrosis progression including the mRSS. This neighborhood of profibrotic S1PR + fibroblasts replaces another neighborhood of homeostatic fibroblasts, consisting in particular of resting fibroblasts and Thy1 + ADAM12 low cells. A third cellular neighborhood is located beneath the epithelial layer, in the papillary dermis. This neighborhood changes its cellular composition in SSc: in healthy controls, this neighborhood consist mainly of TFAM high fibroblasts with only few ADAM12 + Gli1 + fibroblasts, whereas in SSc the TFAM high population is decreased and ADAM12 + Gli1 + fibroblasts dominate.


Conclusion: We present the first spatial proteomics-based characterization of fibroblast compartments in SSc. We have identified the S1PR + fibroblasts as a novel profibrotic population in SSc. This subset is increased in SSc, resides in close vicinity with myofibroblasts, and correlates with the extent and progression of fibrosis. Future studies will unravel whether targeting these fibroblasts offers therapeutic potential.


REFERENCES: NIL.


Acknowledgements: NIL.


Disclosure of Interests: None declared.


DOI: 10.1136/annrheumdis-2024-eular.2974
Keywords: '-omics, Skin, Fibroblasts, Imaging
Citation: , volume 83, supplement 1, year 2024, page 47
Session: Basic Abstract Sessions: Pathophysiology in systemic sclerosis disease (Oral Abstract Presentations)