Background: Rheumatoid arthritis (RA) is an inflammatory disease characterised by chronic synovial inflammation. Within the synovium, fibroblast-like synoviocytes (FLS) and activated immune cells contribute to the formation of the hyperplastic synovial membrane, a hallmark of RA, thereby driving bone and cartilage destruction [1]. The degree of immune cell infiltration varies among RA patients enabling classification into three distinct pathotypes (lympho-myeloid, diffuse-myeloid, pauci-immune). These pathotypes show an association with clinical parameters including response to treatment [2]. We have previously shown that synovial pathotype development is influenced by the synovial cytokine milieu with specific cytokines priming FLS to interact differently with immune cells [3]. The precise molecular mechanisms underlying FLS-immune cell interactions in the inflammatory synovial environment as well as their impact on immune cell activation and disease progression remain poorly understood.

Objectives: In this project, we aim to investigate how different inflammatory cytokines prime FLS-immune cell interactions and how these interactions may affect immune cell activation and synovial pathotype development. Given the clinical relevance of synovial pathotypes, we further aim to explore whether profiling these cell-cell interactions could serve as a biomarker for treatment response in RA.

Methods: Synovial tissues from RA patients were stained for markers of FLS (CD90) and immune cells (CD3, CD20, CD14, CD68) to study FLS-immune cell interactions using immunofluorescence (IF). To elucidate the mechanisms underlining FLS-immune cell interactions, human FLS were isolated and stimulated with different cytokines (IFNβ, IFNγ, IL1β, IL17, IL4, TGFβ, and TNFα) for 24hrs, followed by cytokine removal and the addition of autologous PBMCs. High-content fluorescence microscopy and bioinformatic analysis allowed visualisation and quantification of FLS-immune cell interactions. In addition, PBMCs were re-isolated for spectral cytometry and RNA sequencing (RNA-seq) to analyse activation states and transcriptional changes in monocytes, B-cells, memory CD4 T-cells, and memory CD8 T-cells. RNA-seq data were integrated with bulk [4] and single cell RNA-seq [5, 6] data from RA synovial biopsies. Bioinformatic tools, including CellChat, were employed to identify interaction modalities between FLS and immune cells.

Results: IF staining of RA synovial tissues identified distinct synovial niches where immune cell subsets localised to FLS-rich sub-synovial regions, suggesting robust FLS-immune cell interactions in the inflamed synovium of RA. Co-culture experiments with isolated FLS and autologous PBMCs revealed cell type-specific and cytokine-dependent interaction patterns, highlighting the critical role of the surrounding inflammatory milieu in shaping FLS-immune cell interactions. Cytokine-priming of FLS modulated the activation of immune cell subsets, with IFNγ potentiating and TGFβ repressing these interactions. RNA-seq analysis of FACS-purified monocytes post co-culture with FLS revealed significant transcriptomic changes, with IFNγ-primed FLS inducing a pro-inflammatory M1-like monocyte phenotype (“IFNγ-FLS monocytes” signature). Comparing this signature to synovial biopsy-derived inflammatory monocytes revealed a significant similarity in activated genes, including a specific enrichment in the M6 cluster of the AMP-RA2 dataset which is marked by elevated CXCL10 and STAT1 expression. Notably, the “IFNγ-FLS monocytes” signature was predominantly observed in synovial biopsies from RA patients of the lympho-myeloid pathotype, indicating that interactions with IFNγ-stimulated FLS not only contribute to the emergence of pro-inflammatory monocytes but also drive the development of this highly inflammatory synovial pathotype. Furthermore, CellChat analysis revealed several adhesion molecules likely driving monocyte activation by IFNγ-primed FLS.

Conclusion: This research underscores the critical role of FLS in orchestrating monocyte activation during synovitis. It also highlights the significant impact of the synovial cytokine environment, particularly IFNγ, on FLS-immune cell interactions that drive synovial pathotype progression.

REFERENCES: [1] Smolen JS, Aletaha D, McInnes IB. Rheumatoid arthritis. Lancet. 2016 Oct 22; 388(10055):2023-2038.

[2] Rivellese F, Surace AEA, Goldmann K, Sciacca E, Cubuk C, Giorli G, et al. Rituximab versus tocilizumab in rheumatoid arthritis: synovial biopsy-based biomarker analysis of the phase 4 R4RA randomized trial. Nat Med. 2022 Jun; 28(6):1256-1268.

[3] Kugler M, Dellinger M, Kartnig F, Muller L, Preglej T, Heinz LX, et al. Cytokine-directed cellular cross-talk imprints synovial pathotypes in rheumatoid arthritis. Ann Rheum Dis. 2023 Jun 21.

[4] Lewis MJ, Barnes MR, Blighe K, Goldmann K, Rana S, Hackney JA, et al. Molecular Portraits of Early Rheumatoid Arthritis Identify Clinical and Treatment Response Phenotypes. Cell Rep. 2019 Aug 27; 28(9):2455-2470 e2455.

[5] Zhang F, Wei K, Slowikowski K, Fonseka CY, Rao DA, Kelly S, et al. Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry. Nat Immunol. 2019 Jul; 20(7):928-942.

[6] Zhang F, Jonsson AH, Nathan A, Millard N, Curtis M, Xiao Q, et al. Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes. Nature. 2023 Nov; 623(7987):616-624.

Acknowledgements: NIL.

Disclosure of Interests: None declared.

© The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.