Machine learning-driven programmed cell death signature for prognosis and drug candidate discovery in diffuse large B-cell lymphoma: Multi-cohort study and experimental validation.

Journal: International immunopharmacology
Published Date:

Abstract

BACKGROUND: Relapse and drug resistance are major contributor to chemotherapy failure in diffuse large B-cell lymphoma (DLBCL). Programmed cell death (PCD), a key mechanism in tumor progression and resistance, has emerged as a promising biomarker for predicting prognosis and chemotherapy sensitivity in DLBCL.

Authors

  • Bin Luo
  • Le Yu
    Tobacco Research Institute, Chinese Academy of Agricultural Sciences, Qingdao, China.
  • Wei Zhang
    The First Affiliated Hospital of Nanchang University, Nanchang, China.
  • Jiawei Fan
    Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
  • Mengdi Wan
    School of Pharmacy, Faculty of Medicine, Macau University of Science and Technology, Macau 999078 (or Macau SAR), China.
  • Huangming Hong
    Department of Medical Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, No.55, Section South Renmin Road, Chengdu, China.
  • Yizhun Zhu
    School of Pharmacy, Faculty of Medicine, Macau University of Science and Technology, Macau 999078 (or Macau SAR), China; School of Pharmacy, Faculty of Medicine & Laboratory of Drug Discovery from Natural Resources and Industrialization, Macau University of Science and Technology, Macau 999078 (or Macau SAR), China.
  • Tongyu Lin
    Department of Medical Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, No.55, Section South Renmin Road, Chengdu, China; State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China. Electronic address: lintongyu@scszlyy.org.cn.

Keywords

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