{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T15:32:42Z","timestamp":1787671962972,"version":"build-2736575974"},"reference-count":73,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T00:00:00Z","timestamp":1787616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cancers"],"abstract":"<jats:p>With immune checkpoint inhibitors becoming the mainstay of systemic therapy in both metastatic and early-stage settings across many cancer types, the management of immune-related adverse events has emerged as a central priority of modern oncological supportive care. These toxicities can substantially impair the quality of life of cancer patients, including those who achieve long-term survival. Consequently, there is a pressing need to develop reliable predictive biomarkers to better tailor immune checkpoint inhibitor treatment and optimize patient selection. This review summarizes several of the most promising predictive biomarkers currently under investigation, including genetic factors; peripheral blood parameters and their ratios; autoantibodies; cytokines and chemokines; cytomegalovirus serostatus; gut microbiome characteristics; body composition metrics; molecular imaging features; and tumour- and patient-related factors such as cancer type, gender, and physical activity. Because single biomarkers have limited predictive value, multi-omics prediction models and composite immune-cell scores are increasingly demonstrating greater potential. However, none of these candidate biomarkers have yet undergone sufficient validation to support their incorporation into routine clinical practice.<\/jats:p>","DOI":"10.3390\/cancers18172759","type":"journal-article","created":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T15:01:07Z","timestamp":1787670067000},"page":"2759","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Towards Predicting Immune-Related Adverse Events: Emerging Biomarkers in Patients Undergoing Immune Checkpoint Inhibitor Therapy"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6468-9906","authenticated-orcid":false,"given":"Ne\u017eka","family":"Hribernik","sequence":"first","affiliation":[{"name":"Department of Medical Oncology, Institute of Oncology Ljubljana, 1000 Ljubljana, Slovenia"},{"name":"Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martina","family":"Reber\u0161ek","sequence":"additional","affiliation":[{"name":"Department of Medical Oncology, Institute of Oncology Ljubljana, 1000 Ljubljana, Slovenia"},{"name":"Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2352","DOI":"10.1002\/ijc.35347","article-title":"How many people in the US are eligible for and respond to checkpoint inhibitors: An empirical analysis","volume":"156","author":"Haslam","year":"2025","journal-title":"Int. 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