Molecular biomarkers for the prognosis of breast cancer: role of amino acid metabolism genes.

Journal: Journal of physiology and biochemistry
Published Date: Jun 10, 2025

Abstract

The development of precise molecular biomarkers for breast cancer prognosis holds immense potential to improve treatment outcomes. This study aimed to investigate the role of amino acid metabolism genes as predictive markers for breast cancer prognosis and their association with the immune-tumour microenvironment. By employing advanced machine learning algorithms and bioinformatics analysis techniques, the impact of amino acid metabolism-related genes (AAMRGs) on the immune status and overall survival of patients with breast cancer was examined. An AAMRG-based risk model was established to assess the prognostic significance. Validated risk models (AIMP2, IYD, and QARS1) accurately predicted patient outcomes [1 y: 0.87 (0.96-0.78); 3 y: 0.82 (0.87-0.76); 5 y: 0.80 (0.86-0.75)]. Furthermore, this study revealed evidence suggesting that QARS1 may influence breast cancer cell proliferation through methionine metabolism. This analysis provides valuable insights into the mechanisms of breast cancer, emphasizing the significance of AAMRGs as prognostic biomarkers and potential therapeutic targets for optimizing personalized treatment strategies.

Authors

  • Yudong Zhou
    Department of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaan'xi Province, China.
  • Shibo Yu
    Department of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaan'xi Province, China.
  • Lizhe Zhu
    Department of Chemistry, The Hong Kong University of Science and Technology, Hong Kong, China. zhulizhe@cuhk.edu.cn.
  • Yalong Wang
    School of Medicine, Shaan'xi Province, Xi'an Jiaotong University, Xi'an, 710061, China.
  • Chenglong Duan
    Department of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaan'xi Province, China.
  • Danni Li
    Radiology Department, The People's Hospital of Lezhi, Ziyang, Sichuan, China.
  • Jinsui Du
    Department of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaan'xi Province, China.
  • Jiaqi Zhang
  • Jianing Zhang
    Faculty of Psychology, Tianjin Normal University, Tianjin, China.
  • Ruichao Ma
    Beijing university of post and telecommunication, Beijing, 100876, China.
  • Jianjun He
  • Yu Ren
    Department of Breast Surgery, School of Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China.
  • Bin Wang
    State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, China; New South Wales Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga 2650, Australia. Electronic address: bin.a.wang@dpi.nsw.gov.au.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals