Cancer immunotherapy response prediction from multi-modal clinical and image data using semi-supervised deep learning.

Journal: Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Published Date: Jul 4, 2023

Abstract

BACKGROUND AND PURPOSE: Immunotherapy is a standard treatment for many tumor types. However, only a small proportion of patients derive clinical benefit and reliable predictive biomarkers of immunotherapy response are lacking. Although deep learning has made substantial progress in improving cancer detection and diagnosis, there is limited success on the prediction of treatment response. Here, we aim to predict immunotherapy response of gastric cancer patients using routinely available clinical and image data.

Authors

  • Xi Wang
    School of Information, Central University of Finance and Economics, Beijing, China.
  • Yuming Jiang
    Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Hao Chen
    The First School of Medicine, Wenzhou Medical University, Wenzhou, China.
  • Taojun Zhang
    Department of General Surgery & Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, China.
  • Zhen Han
    Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Chuanli Chen
    Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Qingyu Yuan
    Nanfang PET Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China.
  • Wenjun Xiong
    Department of Gastrointestinal Surgery, Guangdong Provincial Hospital of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
  • Wei Wang
    State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.
  • Guoxin Li
    Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China. gzliguoxin@163.com caishirong@yeah.net ehbhltj@hotmail.com keekee77@126.com.
  • Pheng-Ann Heng
  • Ruijiang Li
    Global Station for Quantum Medical Science and Engineering, Global Institution for Collaborative Research and Education (GI-CoRE), Proton Beam Therapy Center, North 14 West 5 Kita-ku, Sapporo, Hokkaido, 060-8648, Japan.

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