Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in precision medicine.

Journal: Frontiers in immunology
Published Date: May 27, 2025

Abstract

BACKGROUND: Breast cancer (BC) remains a leading cause of cancer-related mortality among women worldwide. Natural killer (NK) cells play a crucial role in the innate immune system and exhibit significant anti-tumor activity. However, the role of NK cell-related genes (NRGs) in BC diagnosis and prognosis remains underexplored. With the advent of machine learning (ML) techniques, predictive modeling based on NRGs may offer a new avenue for precision oncology.

Authors

  • Yutong Fang
    The Breast Center, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, 515041, People's Republic of China.
  • Rongji Zheng
    Department of Breast Surgery, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China.
  • Yefeng Xiao
    Department of Breast Surgery, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China.
  • Qunchen Zhang
    Department of Breast, Jiangmen Central Hospital, Jiangmen, Guangdong, 529030, People's Republic of China. qczhang2014@163.com.
  • Junpeng Liu
    Department of Urology, The Second Affiliated Hospital of Shantou University, Medical College, Shantou, Guangdong, China.
  • Jundong Wu

Keywords

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