Personalized treatment decision-making using a machine learning-derived lactylation signature for breast cancer prognosis.

Journal: Frontiers in immunology
Published Date: May 8, 2025

Abstract

BACKGROUND: Breast cancer is a heterogeneous malignancy with complex molecular characteristics, making accurate prognostication and treatment stratification particularly challenging. Emerging evidence suggests that lactylation, a novel post-translational modification, plays a crucial role in tumor progression and immune modulation.

Authors

  • Simin Min
    Clinical Research Center, Suzhou Hospital of Anhui Medical University, Suzhou, Anhui, China.
  • Xiaonan Zhang
    Department of Natural Language Processcing, Baidu International Technology (Shenzhen) Co., Ltd, Shenzhen 518000, China.
  • Yuling Liu
    State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi'an University of Technology, Xi'an, 710048, China. Electronic address: lyl29992359@163.com.
  • Weiqiang Wang
    Department of General Practice, Suzhou Hospital of Anhui Medical University, Suzhou, Anhui, China.
  • Jingwen Guan
    Department of Pathology, Suzhou Hospital of Anhui Medical University, Suzhou, Anhui, China.
  • Yuyan Chen
    Department of Urinary Surgery, Jinjiang Municipal Hospital, Quanzhou, China.
  • Meng Sun
    Department of Gynecology, The Second People's Hospital of Shenzhen, Shenzhen, China.
  • Ziheng Wang
  • Tao Wang
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Keywords

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