Enhancing breast cancer outcomes with machine learning-driven glutamine metabolic reprogramming signature.

Journal: Frontiers in immunology
PMID: 38756785

Abstract

BACKGROUND: This study aims to identify precise biomarkers for breast cancer to improve patient outcomes, addressing the limitations of traditional staging in predicting treatment responses.

Authors

  • Xukui Li
    Research Laboratory Center, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
  • Xue Li
    Department of Clinical Research Center, Dazhou Central Hospital, Dazhou 635000, China.
  • Bin Yang
    School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, PR China. Electronic address: yangbin@dlut.edu.cn.
  • Songyang Sun
    Research Laboratory Center, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
  • Shu Wang
    Department of Radiology, Affiliated Hospital 6 of Nantong University, Yancheng Third People's Hospital, Yancheng, Jiangsu, China.
  • Fuxun Yu
    Research Laboratory Center, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
  • Tao Wang
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

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