Metabolomics Reveals Potential Biomarkers for Early Detection of irAEs in ICI-Treated Patients.

Authors

Weibin Fan, Haoqun Ma, Yue Zhang, Weiming Yin, Chaojie Qian, Farong Zang, Runcong Zhang, Bin Lin

Published in

Drug design, development and therapy. Volume 20. Pages 620321. Epub Jul 30, 2026.

Abstract

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.
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.
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.
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.

PMID:
42553638
Bibliographic data and abstract were imported from PubMed on 05 Aug 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.