Integrating Bioinformatics and Machine Learning to Identify Glucose Metabolism-Related Biomarkers with Diagnostic and Prognostic Value for Patients with Kidney Renal Clear Cell Carcinoma.

Journal: Archivos espanoles de urologia
PMID: 40341002

Abstract

BACKGROUND: Glucose metabolism plays a critical role in the development and progression of kidney renal clear cell carcinoma (KIRC). This study aimed to identify glucose metabolism-related biomarkers (GRBs) and therapeutic targets for KIRC diagnosis and prognosis using bioinformatics and machine learning.

Authors

  • Haonan Zhao
    National Key Laboratory of Crop Genetic Improvement, College of Plant Science and Technology, Huazhong Agricultural University, No. 1 Shizishan Road, Hongshan District, Wuhan, Hubei 430070, China.
  • Zebin Shang
    School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, 301617 Tianjin, China.
  • Yujie Sun
    State Key Laboratory of Membrane Biology, Biodynamic Optical Imaging Center, School of Life Sciences, Peking University, Beijing, China.

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