Inflamed immune phenotype predicts favorable clinical outcomes of immune checkpoint inhibitor therapy across multiple cancer types.

Journal: Journal for immunotherapy of cancer
Published Date:

Abstract

BACKGROUND: The inflamed immune phenotype (IIP), defined by enrichment of tumor-infiltrating lymphocytes (TILs) within intratumoral areas, is a promising tumor-agnostic biomarker of response to immune checkpoint inhibitor (ICI) therapy. However, it is challenging to define the IIP in an objective and reproducible manner during manual histopathologic examination. Here, we investigate artificial intelligence (AI)-based immune phenotypes capable of predicting ICI clinical outcomes in multiple solid tumor types.

Authors

  • Jeanne Shen
    Center for Artificial Intelligence in Medicine and Imaging, Stanford University, 1701 Page Mill Road, Palo Alto, CA, 94304, USA. jeannes@stanford.edu.
  • Yoon-La Choi
    Department of Pathology and Translational Genomics, Sungkyunkwan University School of Medicine, Suwon, Korea (the Republic of).
  • Taebum Lee
    Department of Pathology, Chonnam National University Medical School, Gwangju, Korea (the Republic of).
  • Hyojin Kim
    Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, Livermore, CA, United States.
  • Young Kwang Chae
    Department of Hematology and Oncology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
  • Ben W Dulken
    Department of Pathology, Stanford University School of Medicine, Stanford, California, USA.
  • Stephanie Bogdan
    Center for Artificial Intelligence in Medicine & Imaging, Stanford University, Stanford, California, USA.
  • Maggie Huang
    UCLA Health, University of California, Los Angeles, Los Angeles, California, USA.
  • George A Fisher
    Department of Medicine (Oncology), Stanford University School of Medicine, Stanford, California.
  • Sehhoon Park
    Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea (the Republic of).
  • Se-Hoon Lee
    Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea (the Republic of).
  • Jun-Eul Hwang
    Department of Internal Medicine, Chonnam National University Medical School, Gwangju, Korea (the Republic of).
  • Jin-Haeng Chung
    Department of Pathology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Korea (the Republic of).
  • Leeseul Kim
    Department of Internal Medicine, AMITA Health Saint Francis Hospital, Evanston, IL, USA.
  • Heon Song
    Lunit, Seoul, Korea (the Republic of).
  • Sérgio Pereira
    CMEMS-UMinho Research Unit, University of Minho, Guimarães, Portugal; Centro Algoritmi, University of Minho, Braga, Portugal. Electronic address: id5692@alunos.uminho.pt.
  • Seunghwan Shin
    Lunit, Seoul, Korea (the Republic of).
  • Yoojoo Lim
    Lunit, Seoul, Korea (the Republic of).
  • Chang Ho Ahn
    Lunit, Seoul, Korea (the Republic of).
  • Seulki Kim
    Department of Pediatrics, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • Chiyoon Oum
    Lunit, Seoul, Korea (the Republic of).
  • Sukjun Kim
    Lunit, Seoul, Korea (the Republic of).
  • Gahee Park
    Lunit, Seoul, Korea (the Republic of).
  • Sanghoon Song
    Lunit, Seoul, Korea (the Republic of).
  • Wonkyung Jung
    School of Nursing, University of Washington, Seattle, Washington, USA.
  • Seokhwi Kim
    Department of Pathology, Ajou University School of Medicine, Suwon, Korea (the Republic of).
  • Yung-Jue Bang
    Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea (the Republic of).
  • Tony S K Mok
    Department of Clinical Oncology, The Chinese University of Hong Kong, Prince of Wales Hospital, 30-32 Ngan Shing Street, Sha Tin, New Territories, Hong Kong, China. Electronic address: tony@clo.cuhk.edu.hk.
  • Siraj M Ali
    Lunit, Seoul, Korea (the Republic of).
  • Chan-Young Ock
    Lunit, Seoul, Korea (the Republic of) jeannes@stanford.edu ock.chanyoung@lunit.io.