Single-cell RNA sequencing and high-dimensional flow cytometry reveal distinct peripheral immune landscapes of type 1 autoimmune pancreatitis and pancreatic ductal adenocarcinoma.

BACKGROUND

Autoimmune pancreatitis (AIP) is a chronic pancreatic inflammatory disease that is often difficult to differentiate from pancreatic cancer. Some AIP patients may even progress into pancreatic ductal adenocarcinoma (PDAC). We sought to delineate the peripheral immunological landscape of AIP, identify its differences from PDAC and find novel biomarkers for disease differentiation.

METHODS

Single-cell RNA/BCR sequencing (scRNA/BCR-seq) was performed on peripheral blood mononuclear cells (PBMCs) from 10 type 1 AIP patients. Public PBMC sequencing data from 13 PDAC patients and 11 healthy volunteers were integrated in the analysis. Fourteen-colour flow cytometry was conducted in independent cohorts for validation.

RESULTS

The analyses revealed a significantly higher proportion of IgG4high-switched memory B cells in patients with AIP than in PDAC. These cells, characterised by high CD23 expression, exhibited enhanced antigen-presenting capacity and might differentiate into pancreatic plasma cells in AIP. Compared with PDAC, AIP was characterised by an increased frequency of T follicular helper (Tfh) cells with a more pronounced exhaustion-like phenotype. Coculture experiments demonstrated that IgG4high-switched memory B cells can promote Tfh cell differentiation through major histocompatibility complex-mediated antigen presentation. TREM2-up-regulated intermediate monocytes were also increased in AIP and showed greater potential to differentiate into macrophages. The Boruta algorithm identified proportional changes in these subsets as useful for disease differentiation, and these findings were validated by multi-colour flow cytometry. A nomogram was established, with an AUC of .94 in the internal cohort and .88 in the external cohort. As for prognostic prediction, the reduction rate of Tfh cells after steroid therapy was associated with relapse risk.

CONCLUSION

By integrating scRNA/BCR-seq and flow cytometry, we identified three novel immune cell subsets in PBMCs of AIP patients and confirmed their diagnostic and prognostic value. A flow cytometry-derived nomogram based on these subsets provides a novel tool for differentiating patients with AIP from those with PDAC.