Immune profiling in orthopaedic diseases using mass cytometry

Aims: Musculoskeletal (MSK) diseases involve complex immune mechanisms. Conventional flow cytometry is restricted by spectral overlap, limiting multidimensional immune characterization. Mass cytometry by time-of-flight (CyTOF) can measure over 40 proteins per cell using metal-tagged antibodies and time-of-flight detection, providing deep immune phenotyping. The aim of this narrative review was to summarize the applications of CyTOF in the study of human orthopaedic and rheumatic diseases, highlight key immune findings including shared markers, and identify gaps to guide future research and panel standardization. Methods: A literature search of peer-reviewed studies published from 1 January 2014 to 31 December 2024 was conducted using PubMed, Scopus, and Web of Science. Search terms included "CyTOF" and "mass cytometry". Studies were included if CyTOF was applied to human MSK disorders with immune or inflammatory components and if the full text was available in English. Data extracted included disease type, sample source, computational pipeline, immune cell types analyzed, and main findings. Results: A total of 22 studies were included. Since some studies reported results for more than one disease, the total number of disease-specific entries was 26: rheumatoid arthritis (n = 13), osteoarthritis (n = 4), psoriatic arthritis (n = 3), juvenile idiopathic arthritis (n = 2), ankylosing spondylitis (n = 1), idiopathic inflammatory myopathies (n = 1), and post-surgical immune monitoring (n = 2). Human models were represented. CyTOF identified disease-specific immune cell subsets, cytokine profiles, and treatment-response signatures. No eligible studies addressed osteoporosis or osteonecrosis likely reflecting that these conditions would yield low immune-cell density and/or technical challenges in acquiring bone tissue. Eight recurrent markers emerged across diseases: program cell death protein 1 (PD-1), inducible T-cell costimulator (ICOS), CXC motif chemokine receptor (CXCR)5, CXCR4, phosphorylated signal transducer and activator of transcription 4 protein (pSTAT3), tumour necrosis factor receptor II (TNFRII), p16 inhibitor of cyclin-dependent kinase 4a (p16INK4a), and cluster of differentiation (CD)180, which reflect shared pathways of inflammation, senescence, and tissue damage. Conclusion: CyTOF enables high-dimensional immune profiling in MSK diseases, offering insights into pathogenesis, treatment response, and patient stratification. Broader application of this technology to underexplored conditions is warranted. A minimal eight-marker backbone may enhance panel harmonization and support future multicentre translational studies in orthopaedic immunology.