BACKGROUND. Checkpoint inhibitor–associated autoimmune diabetes mellitus (CIADM) is a rare but life-altering complication of immune checkpoint inhibitor (ICI) therapy. Biomarkers that predict type 1 diabetes (T1D) are unreliable for CIADM.
AIM. In the present study, we sought to identify biomarkers for the prediction of CIADM.
METHODS. From our prospective biobank, we identified 14 patients with CIADM who had metastatic melanoma treated with anti–programed antibody death 1 (anti–PD-1) with or without anti–cytotoxic T lymphocyte–associated antibody protein 4 (anti-CTLA4). Controls were selected from the same biobank, matched 2:1. Pretreatment, on-ICI, and post-CIADM serum and PBMCs were analyzed. Serum was analyzed for T1D autoantibodies, C-peptide, glucose, and cytokines. PBMCs were profiled using flow cytometry. Pancreatic volume was measured using CT volumetry.
RESULTS. Before treatment, patients with CIADM had smaller pancreatic volume (27% reduction, P = 0.044) and higher anti–glutamic acid decarboxylase autoantibody (anti-GAD) titers (median 2.9 vs. 0, P = 0.01). They had significantly higher baseline proportions of Th17 cells (P = 0.03), higher CD4+ central memory cells (P = 0.04), and lower naive CD4+ T cells (P= 0.01). With ICI treatment, greater declines in pancreatic volume were seen in patients with CIADM (P < 0.0001). Activated CD4+ T cell subsets increased significantly in CIADM and controls with immune-related adverse effects (IRAEs) but not in controls without IRAEs. Using only pretreatment results, we found that pancreatic volume, anti-GAD antibody titers, and the baseline immune flow profile were highly predictive of CIADM development, with an AUC of greater than 0.96.
CONCLUSIONS. People who develop CIADM are immunologically predisposed and have antecedent pancreatic and immunological changes that accurately predict disease with excellent sensitivity. These biomarkers could be used to guide ICI use, particularly when planning treatment for low-risk tumors.