Mass cytometry is a cutting-edge high-dimensional technology for profiling marker expression at the single-cell level, advancing clinical research in immune monitoring. Nevertheless, the vast data generated by cytometry by time-of-flight (CyTOF) poses a significant analytical challenge. To address this, we describe ImmCellTyper (https://github.com/JingAnyaSun/ImmCellTyper), a novel toolkit for CyTOF data analysis. This framework incorporates BinaryClust, an in-house developed semi-supervised clustering tool that automatically identifies main cell types. BinaryClust outperforms existing clustering tools in accuracy and speed, as shown in benchmarks with two datasets of approximately 4 million cells, matching the precision of manual gating by human experts. Furthermore, ImmCellTyper offers various visualisation and analytical tools, spanning from quality control to differential analysis, tailored to users’ specific needs for a comprehensive CyTOF data analysis solution. The workflow includes five key steps: (1) batch effect evaluation and correction, (2) data quality control and pre-processing, (3) main cell lineage characterisation and quantification, (4) in-depth investigation of specific cell types; and (5) differential analysis of cell abundance and functional marker expression across study groups. Overall, ImmCellTyper combines expert biological knowledge in a semi-supervised approach to accurately deconvolute well-defined main cell lineages, while maintaining the potential of unsupervised methods to discover novel cell subsets, thus facilitating high-dimensional immune profiling.

miRNAs constitute fine-tuners of gene expression and are implicated in a variety of diseases spanning from inflammation to cancer. miRNA expression is deregulated in rheumatoid arthritis (RA); however, their specific role in key arthritogenic cells such as the synovial fibroblast (SF) remains elusive. Previous studies have shown that Mir221/222 expression is upregulated in RA SFs. Here, we demonstrate that TNF and IL-1β but not IFN-γ activated Mir221/222 gene expression in murine SFs. SF-specific overexpression of Mir221/222 in huTNFtg mice led to further expansion of SFs and disease exacerbation, while its total ablation led to reduced SF expansion and attenuated disease. Mir221/222 overexpression altered the SF transcriptional profile igniting pathways involved in cell cycle and ECM (extracellular matrix) regulation. Validation of targets of Mir221/222 revealed cell cycle inhibitors Cdkn1b and Cdkn1c, as well as the epigenetic regulator Smarca1. Single-cell ATAC-seq data analysis revealed increased Mir221/222 gene activity in pathogenic SF subclusters and transcriptional regulation by Rela, Relb, Junb, Bach1, and Nfe2l2. Our results establish an SF-specific pathogenic role of Mir221/222 in arthritis and suggest that its therapeutic targeting in specific subpopulations could lead to novel fibroblast-targeted therapies.