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Pancreatic volume and immunological biomarkers predict checkpoint inhibitor-associated autoimmune diabetes in humans.

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NIAID Data Ecosystem2026-05-10 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP657290
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Background: Checkpoint inhibitor-associated autoimmune diabetes (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 To identify biomarkers for prediction of CIADM. Methods: From our prospective biobank, 14 CIADM patients who had metastatic melanoma treated with anti-PD-1±anti CTLA4 were identified. Controls were selected from the same biobank, matched 2:1. Pre-treatment, on-ICI and post-CIADM serum and peripheral blood mononuclear cells (PBMCs) were analysed. Serum was analysed for T1D autoantibodies, C-peptide, glucose and cytokines. PBMCs were profiled using flow cytometry. Pancreatic volume was measured using CT volumetry. Results: Before treatment, CIADM patients had smaller pancreatic volume (27% reduction, p=0.044) and higher anti-GAD antibody titres (median 2.9 versus 0, p=0.01). They had significantly higher baseline proportions of Th17 helper cells (p=0.03), higher CD4+ central memory cells (p=0.04) and lower naïve CD4+ cells (p=0.01). With ICI treatment, greater declines in pancreatic volume were seen in CIADM patients (p<0.0001). Activated CD4+ subsets increased significantly in CIADM and controls with immune-related adverse effects (IRAE) but not controls without IRAE. Using only pre-treatment results, pancreatic volume, anti-GAD antibody titre and baseline immune flow profile were highly predictive of CIADM development, with an area under the curve (AUC) of >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 tumours. Overall design: Fourteen deidentified patients with checkpoint inhibitor (CI)-associated autoimmune diabetes (CIADM) and 28 deidentified treated controls that had longitudinal biospecimens were identified from the prospectively collected Melanoma Institute of Australia medical record database and biospecimen bank.The diagnosis of CIADM was based on new onset diabetes (HbA1c = 6.5% and/or blood glucose = 11mmol/L) in the setting of CI therapy, with evidence of insulin deficiency (either presence of diabetic ketoacidosis or low C-peptide = 0.4nmol/L with elevated glucose). No patients had previous diabetes. Two controls were selected for each CIADM patient, matched as closely as possibly for age (±5 years), gender, type of immune checkpoint inhibitor therapy (single agent anti-PD1 versus combined anti-CTLA4 plus anti-PD1), time on therapy, treatment response and concurrent other immune related adverse effects. Control patients had prospectively collected pre-CI and on-CI FACS sorted CD8 positive periperal blood mononuclear cells (PBMCs) (~3 months after treatment initiation) samples analysed by RNA-seq. CIADM patients similarly had pre-CI and on-treatment PBMCs collected at approximately 3 months. CIADM patients additionally had samples collected approximately 3 months after CIADM diagnosis. Note: for RNA-seq some timepoints have one control case where the second had poor sequence quality.
创建时间:
2025-12-27
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