AI Article Synopsis

  • Immune checkpoint inhibitors (ICIs) are crucial immunotherapy drugs for cancer, but their increased use has led to a rise in immune-related adverse events (irAEs), impacting treatment effectiveness and patient survival.
  • Current tests can identify specific organ damage but struggle to differentiate irAEs from infections or other immune disorders, highlighting the need for reliable biomarkers for irAE prediction or diagnosis.
  • This review summarizes major irAEs, explores existing biomarker studies, and discusses advanced techniques like machine learning and gut microbiota profiling to find new biomarkers, while also explaining the mechanisms behind irAEs for better management strategies.

Article Abstract

Immune checkpoint inhibitors (ICIs) constitute a pivotal class of immunotherapeutic drugs in cancer treatment. However, their widespread clinical application has led to a notable surge in immune-related adverse events (irAEs), significantly affecting the efficacy and survival rates of patients undergoing ICI therapy. While conventional hematological and imaging tests are adept at detecting organ-specific toxicities, distinguishing adverse reactions from those induced by viruses, bacteria, or immune diseases remains a formidable challenge. Consequently, there exists an urgent imperative for reliable biomarkers capable of accurately predicting or diagnosing irAEs. Thus, a thorough review of existing studies on irAEs biomarkers is indispensable. Our review commences by providing a succinct overview of major irAEs, followed by a comprehensive summary of irAEs biomarkers across various dimensions. Furthermore, we delve into innovative methodologies such as machine learning, single-cell RNA sequencing, multiomics analysis, and gut microbiota profiling to identify novel, robust biomarkers that can facilitate precise irAEs diagnosis or prediction. Lastly, this review furnishes a concise exposition of irAEs mechanisms to augment understanding of irAEs prediction, diagnosis, and treatment strategies.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11346067PMC
http://dx.doi.org/10.5306/wjco.v15.i8.1002DOI Listing

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