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• W4319868850 endingPage "100374" @default.
• W4319868850 startingPage "100374" @default.
• W4319868850 abstract "•ICIs may adversely cause AI.•Autoantibodies are promising candidate biomarkers for ICI-induced AI.•Upfront risk identification for ICI-induced AI may improve clinical management. Primary and secondary adrenal insufficiency (AI) are commonly known immune-related adverse events following treatment with immune checkpoint inhibitors (ICIs), and are clinically relevant due to their morbidity and potential mortality. For this reason, upfront identification of patients susceptible for ICI-induced AI could be a step in improving patient’s safety. Multiple studies have focused on the identification of novel biomarkers for ICI-induced AI, including autoantibodies, which may be involved in ICI-induced AI as a result of the T-cell-mediated activation of autoreactive B cells. This review highlights the currently described autoantibodies that may be involved in either primary [e.g. anti-21-hydroxylase, anti-17α-hydroxylase, anti-P450scc, anti-aromatic L-amino acid decarboxylase (AADC), anti-interferon (IFN)α and anti-IFNΩ] or secondary AI [e.g. anti-guanine nucleotide-binding protein G(olf) subunit alpha (GNAL), anti-integral membrane protein 2B (ITM2B), anti-zinc finger CCHC-type containing 8 (ZCCHC8), anti-pro-opiomelanocortin (POMC), anti-TPIT (corticotroph-specific transcription factor), anti-pituitary-specific transcriptional factor-1 (PIT-1) and others], and discusses the current evidence concerning their role as biomarker for ICI-induced AI. Standardized autoantibody measurements in patients (to be) treated with ICIs would be a clinically accessible and patient-friendly screening method to identify the patients at risk, and could change the management of ICI-induced AI. Primary and secondary adrenal insufficiency (AI) are commonly known immune-related adverse events following treatment with immune checkpoint inhibitors (ICIs), and are clinically relevant due to their morbidity and potential mortality. For this reason, upfront identification of patients susceptible for ICI-induced AI could be a step in improving patient’s safety. Multiple studies have focused on the identification of novel biomarkers for ICI-induced AI, including autoantibodies, which may be involved in ICI-induced AI as a result of the T-cell-mediated activation of autoreactive B cells. This review highlights the currently described autoantibodies that may be involved in either primary [e.g. anti-21-hydroxylase, anti-17α-hydroxylase, anti-P450scc, anti-aromatic L-amino acid decarboxylase (AADC), anti-interferon (IFN)α and anti-IFNΩ] or secondary AI [e.g. anti-guanine nucleotide-binding protein G(olf) subunit alpha (GNAL), anti-integral membrane protein 2B (ITM2B), anti-zinc finger CCHC-type containing 8 (ZCCHC8), anti-pro-opiomelanocortin (POMC), anti-TPIT (corticotroph-specific transcription factor), anti-pituitary-specific transcriptional factor-1 (PIT-1) and others], and discusses the current evidence concerning their role as biomarker for ICI-induced AI. Standardized autoantibody measurements in patients (to be) treated with ICIs would be a clinically accessible and patient-friendly screening method to identify the patients at risk, and could change the management of ICI-induced AI." @default.
• W4319868850 created "2023-02-11" @default.
• W4319868850 creator A5024621469 @default.
• W4319868850 creator A5029850163 @default.
• W4319868850 creator A5088390068 @default.
• W4319868850 date "2023-03-01" @default.
• W4319868850 modified "2023-10-17" @default.
• W4319868850 title "Autoantibodies involved in primary and secondary adrenal insufficiency following treatment with immune checkpoint inhibitors" @default.
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