Machine learning-based detoxification enzymes-related genes prognosis model in breast cancer: immune landscape and clinical significance.

Journal: Discover oncology
Published Date: Jun 23, 2025

Abstract

BACKGROUND: Breast cancer is one of the most common malignant tumors, threatening women's health and life globally. Despite significant treatment advances, its prognosis still faces great challenges. With the rapid development of molecular biology and genomics, the role of detoxification enzymes in breast cancer occurrence, development, and prognosis has gained increasing attention. This paper aims to establish a prognostic model based on detoxification enzymes-related genes to predict breast cancer patient survival.

Authors

  • Jingdi Zhang
    School of Pharmacy, Hengyang Medical College, University of South China, Hengyang, China.
  • Wendi Zhan
    School of Pharmacy, Hengyang Medical College, University of South China, Hengyang, China.
  • Haihong Hu
    Mid-Atlantic Permanente Medical Group PC, Kaiser Permanente Mid-Atlantic States, Rockville, MD.
  • Hongxia Zhu
    School of Pharmacy, Hengyang Medical College, University of South China, Hengyang, China.
  • Bo Hao
  • Siyu Wang
    School of Nursing, Chengdu University of Traditional Chinese Medicine, Sichuan, Chengdu, 610075, China. Electronic address: 919008390@qq.com.
  • Zhuo Li
    Biostatistics Unit, Mayo Clinic, Jacksonville, FL, United States.
  • Zhiming Zhang
    Shenzhen Prevention and Treatment Center for Occupational Diseases, Shenzhen 518020, China.
  • Taolan Zhang
    Department of Pharmacy, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, China.

Keywords

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