Using Machine Learning Algorithms to Predict Immunotherapy Response in Patients with Advanced Melanoma.

Journal: Clinical cancer research : an official journal of the American Association for Cancer Research
Published Date: Jan 1, 2021

Abstract

PURPOSE: Several biomarkers of response to immune checkpoint inhibitors (ICI) show potential but are not yet scalable to the clinic. We developed a pipeline that integrates deep learning on histology specimens with clinical data to predict ICI response in advanced melanoma.

Authors

  • Paul Johannet
    Department of Medicine, NYU Grossman School of Medicine, New York, NY, USA.
  • Nicolas Coudray
    Applied Bioinformatics Laboratories, NYU Grossman School of Medicine, New York, NY, USA. nicolas.coudray@nyulangone.org.
  • Douglas M Donnelly
    Ronald O. Perelman Department of Dermatology, NYU Grossman School of Medicine, New York, New York.
  • George Jour
    Ronald O. Perelman Department of Dermatology, NYU Grossman School of Medicine, New York, NY, USA. George.Jour@nyulangone.org.
  • Irineu Illa-Bochaca
    Ronald O. Perelman Department of Dermatology, NYU Grossman School of Medicine, New York, NY, USA.
  • Yuhe Xia
    Department of Population Health, NYU Grossman School of Medicine, New York, New York.
  • Douglas B Johnson
    Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA.
  • Lee Wheless
    Department of Dermatology, Vanderbilt University Medical Center, Nashville, TN, USA.
  • James R Patrinely
    Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
  • Sofia Nomikou
    Department of Pathology, NYU Grossman School of Medicine, New York, New York.
  • David L Rimm
    Department of Pathology, Yale University School of Medicine, New Haven, CT, USA.
  • Anna C Pavlick
    Perlmutter Cancer Center, NYU Langone Health, New York, New York.
  • Jeffrey S Weber
    Perlmutter Cancer Center, NYU Langone Health, New York, New York.
  • Judy Zhong
    Department of Population Health, NYU Grossman School of Medicine, 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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