Interpretable Machine Learning Algorithms Identify Inetetamab-Mediated Metabolic Signatures and Biomarkers in Treating Breast Cancer.

Journal: Journal of clinical laboratory analysis
PMID: 39569974

Abstract

BACKGROUND: HER2-positive breast cancer (BC), a highly aggressive malignancy, has been treated with the targeted therapy inetetamab for metastatic cases. Inetetamab (Cipterbin) is a recently approved targeted therapy for HER2-positive metastatic BC, significantly prolonging patients' survival. Currently, there is no established biomarker to reliably predict or assess the therapeutic efficacy of inetetamab in BC patients.

Authors

  • Ning Xie
  • Dehua Liao
    Department of Pharmacy, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital, Changsha, Hunan, China.
  • Binliang Liu
    Department of Breast Cancer Medical Oncology, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital, Changsha, Hunan, China.
  • Jiwen Zhang
    b Key Laboratory of Botanical Pesticide R&D in Shaanxi Province , Northwest A&F University , Yangling , People's Republic of China.
  • Liping Liu
    Department of Computer Sciences, Tufts University, Medford, MA.
  • Gang Huang
    School of Health, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China.
  • Quchang Ouyang
    Department of Breast Cancer Medical Oncology, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital, Changsha, Hunan, China.

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