Deep learning analysis of histopathological images predicts immunotherapy prognosis and reveals tumour microenvironment features in non-small cell lung cancer.

Journal: British journal of cancer
PMID: 39455880

Abstract

BACKGROUND: Non-small cell lung cancer (NSCLC) is one of the leading causes of cancer mortality worldwide. Immune checkpoint inhibitors (ICIs) have emerged as a crucial treatment option for patients with advanced NSCLC. However, only a subset of patients experience clinical benefit from ICIs. Therefore, identifying biomarkers that can predict response to ICIs is imperative for optimising patient selection.

Authors

  • Youyu Wang
    Department of Thoracic Surgery, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
  • Xueming Ju
    Department of Ultrasound, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
  • Rong Hua
    Division of Esophageal Surgery, Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
  • Ji Chen
    Department of Population Health, New York University School of Medicine, New York, NY, United States.
  • Xiaoqin Dai
    Department of Traditional Chinese Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
  • Lunxu Liu
    Department of Thoracic surgery, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, Sichuan, 610041, China. lunxu_liu@aliyun.com.
  • Guifang Wang
    Department of Respiratory and Critical Care Medicine, Sixth People's Hospital of Chengdu, Chengdu, Sichuan, China. 403879096@qq.com.
  • Yifeng Bai
    Department of Oncology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China. baiyifeng@med.uestc.edu.cn.
  • Honglin Hu
  • Xiaohua Li
    Zuoshouyisheng Inc, Beijing, China.

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