Artificial Intelligence Algorithm Predicts Response to Immune Checkpoint Inhibitors.

Journal: Clinical cancer research : an official journal of the American Association for Cancer Research
Published Date: Jun 24, 2025

Abstract

PURPOSE: Cancer treatment has been revolutionized by the immune checkpoint inhibitors (ICIs). However, a subset of patients do not respond and/or experience significant adverse events. Attempts to integrate reliable biomarkers of ICI response as part of standard care have been hampered by limited generalizability. We previously reported our supervised machine learning (ML) model in a retrospective cohort of metastatic melanoma.

Authors

  • Faisal Fa'ak
    Washington University in St. Louis, St Louis, Missouri, United States.
  • Nicolas Coudray
    Applied Bioinformatics Laboratories, NYU Grossman School of Medicine, New York, NY, USA. nicolas.coudray@nyulangone.org.
  • George Jour
    Ronald O. Perelman Department of Dermatology, NYU Grossman School of Medicine, New York, NY, USA. George.Jour@nyulangone.org.
  • Milad Ibrahim
    New York University Langone Medical Center, New York, United States.
  • Irineu Illa-Bochaca
    Ronald O. Perelman Department of Dermatology, NYU Grossman School of Medicine, New York, NY, USA.
  • Shi Qiu
    Key Laboratory of Spectral Imaging Technology CAS, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China.
  • Adalberto Claudio Quiros
    School of Computing Science, University of Glasgow, Glasgow, Scotland, UK.
  • Ke Yuan
    Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong.
  • Douglas B Johnson
    Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA.
  • David L Rimm
    Department of Pathology, Yale University School of Medicine, New Haven, CT, USA.
  • Jeffrey S Weber
    Perlmutter Cancer Center, NYU Langone Health, New York, New York.
  • Aristotelis Tsirigos
    Department of Pathology, NYU School of Medicine, New York, NY 10016, USA; Laura and Isaac Perlmutter Cancer Center, NYU School of Medicine, New York, NY 10016, USA; Applied Bioinformatics Laboratories, NYU School of Medicine, New York, NY 10016, USA. Electronic address: aristotelis.tsirigos@nyulangone.org.
  • Iman Osman
    Departments of Dermatology, Medicine, and Urology, NYU School of Medicine, New York, New York.

Keywords

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