Deep learning based digital pathology for predicting treatment response to first-line PD-1 blockade in advanced gastric cancer.

Journal: Journal of translational medicine
Published Date: May 8, 2024

Abstract

BACKGROUND: Advanced unresectable gastric cancer (GC) patients were previously treated with chemotherapy alone as the first-line therapy. However, with the Food and Drug Administration's (FDA) 2022 approval of programmed cell death protein 1 (PD-1) inhibitor combined with chemotherapy as the first-li ne treatment for advanced unresectable GC, patients have significantly benefited. However, the significant costs and potential adverse effects necessitate precise patient selection. In recent years, the advent of deep learning (DL) has revolutionized the medical field, particularly in predicting tumor treatment responses. Our study utilizes DL to analyze pathological images, aiming to predict first-line PD-1 combined chemotherapy response for advanced-stage GC.

Authors

  • Yifan Liu
    College of Orthopedics and Traumatology, Henan University of Chinese Medicine, Zhengzhou, China.
  • Wei Chen
    Department of Urology, Zigong Fourth People's Hospital, Sichuan, China.
  • Ruiwen Ruan
    Department of Oncology, First Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi Province, China.
  • Zhimei Zhang
    Department of Pathology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Zhixiong Wang
    Department of Gastrointestinal Surgery, First Affiliated Hospital of Sun Yat-sen University, Zhongshan 2nd Street, No. 58, Guangzhou, 510080, 86, Guangdong, China.
  • Tianpei Guan
    Department of Gastrointestinal Surgery, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, Guangdong, China.
  • Qi Lin
    Shandong University, School of Mechanical, Electrical and Information Engineering, Weihai, 264209, China. Electronic address: 202100800115@mail.sdu.edu.cn.
  • Wei Tang
    Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Jun Deng
    Department of Therapeutic Radiology, Yale University, New Haven, CT, U.S.A.
  • Zhao Wang
    Department of Urology, Xiangya Hospital, Central South University, Changsha, China.
  • Guanghua Li
    Department of Gastrointestinal Surgery, First Affiliated Hospital of Sun Yat-sen University, Zhongshan 2nd Street, No. 58, Guangzhou, 510080, 86, Guangdong, China. ligh26@mail.sysu.edu.cn.

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