Novel prognostic signature for hepatocellular carcinoma using a comprehensive machine learning framework to predict prognosis and guide treatment.

Journal: Frontiers in immunology
Published Date: Sep 24, 2024

Abstract

BACKGROUND: Hepatocellular carcinoma (HCC) is highly aggressive, with delayed diagnosis, poor prognosis, and a lack of comprehensive and accurate prognostic models to assist clinicians. This study aimed to construct an HCC prognosis-related gene signature (HPRGS) and explore its clinical application value.

Authors

  • Shengzhou Zheng
    Department of Emergency, Fujian Medical University Union Hospital, Fuzhou, China.
  • Zhixiong Su
    Department of Oncology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China.
  • Yufang He
    Department of Oncology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China.
  • Lijie You
    Department of Oncology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China.
  • Guifeng Zhang
  • Jingbo Chen
    School of Materials Science and Engineering, Henan Key Laboratory of Advanced Nylon Materials and Application, Henan Innovation Center for Functional Polymer Membrane Materials, Zhengzhou University, Zhengzhou, 450001, China. lsrzzdx@zzu.edu.cn.
  • Lihu Lu
    Department of Radiation Oncology, Fujian Medical University Union Hospital, Fuzhou, China.
  • Zhenhua Liu
    National R & D Center for Edible Fungus Processing Technology, Henan University, Kaifeng 475004, China.

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