Drug design, development and therapy · 2026
Metabolomics Reveals Potential Biomarkers for Early Detection of irAEs in ICI-Treated Patients.
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Fan Weibin, Ma Haoqun, Zhang Yue, Yin Weiming, Qian Chaojie, Zang Farong, Zhang Runcong, Lin Bin
Аннотация
PURPOSE: To identify predictive metabolic biomarkers for immune-related adverse events (irAEs) in cancer patients treated with immune checkpoint inhibitors (ICIs) using metabolomics, supporting early detection and intervention.
PATIENTS AND METHODS: Fifty-five ICI-treated cancer patients from Changxing People's Hospital were divided into irAEs-positive (34 cases) and irAEs-negative (21 cases) groups after 12-month follow-up. Pretreatment serum samples were analyzed by untargeted UPLC-MS metabolomics. PCA, OPLS-DA, and KEGG pathway enrichment were used to screen differential metabolites and key pathways.
RESULTS: Seventy significant differential metabolites (eg, ursodeoxycholic acid, uric acid) were identified. β-Alanine metabolism, pentose phosphate pathway, and coenzyme A biosynthesis were closely correlated with irAEs. Five metabolites showed AUC 0.7-0.9 with favorable predictive performance.
CONCLUSION: Metabolomics reveals specific metabolites and metabolic pathways linked to ICI-induced irAEs, providing potential biomarkers for early prediction and new insights into irAEs pathogenesis to optimize clinical management.
PATIENTS AND METHODS: Fifty-five ICI-treated cancer patients from Changxing People's Hospital were divided into irAEs-positive (34 cases) and irAEs-negative (21 cases) groups after 12-month follow-up. Pretreatment serum samples were analyzed by untargeted UPLC-MS metabolomics. PCA, OPLS-DA, and KEGG pathway enrichment were used to screen differential metabolites and key pathways.
RESULTS: Seventy significant differential metabolites (eg, ursodeoxycholic acid, uric acid) were identified. β-Alanine metabolism, pentose phosphate pathway, and coenzyme A biosynthesis were closely correlated with irAEs. Five metabolites showed AUC 0.7-0.9 with favorable predictive performance.
CONCLUSION: Metabolomics reveals specific metabolites and metabolic pathways linked to ICI-induced irAEs, providing potential biomarkers for early prediction and new insights into irAEs pathogenesis to optimize clinical management.