Machine Learning Diagnostic Model for Hepatocellular Carcinoma Based on Liquid-Liquid Phase Separation and Ferroptosis-Related Genes.

Journal: The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology
PMID: 39635757

Abstract

BACKGROUND/AIMS: Hepatocellular carcinoma (HCC) represents a primary liver malignancy with a multifaceted molecular landscape. The interplay between liquid-liquid phase separation (LLPS) and ferroptosis-a regulated form of cell death-has garnered interest in tumorigenesis. However, the precise role of LLPS and ferroptosis-related genes in HCC progression and prognosis remains obscure. Unraveling this connection could pave the way for innovative diagnosis and therapeutic strategies.

Authors

  • Wenchao Chen
    School of Pharmacy, Hangzhou Normal University, Hangzhou 311121, PR China.
  • Ting Zhu
  • Xiaofan Pu
    Department of General Surgery, Zhejiang University School of Medicine, Sir Run Run Shaw Hospital, Hangzhou, China.
  • Linlin Zhao
    Mathematical Modelling of Biological Systems, Heinrich-Heine University, Düsseldorf, Germany.
  • Senhao Zhou
    Department of Otolaryngology Head and Neck Surgery, Zhejiang University School of Medicine, Sir Run Run Shaw Hospital, Hangzhou, China.
  • Xin Zhong
    Pancreatic Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China.
  • Suihan Wang
    Department of General Surgery, Zhejiang University School of Medicine, Sir Run Run Shaw Hospital, Hangzhou, China.
  • Tianyu Lin
    Department of General Surgery, Zhejiang University School of Medicine, Sir Run Run Shaw Hospital, Hangzhou, China.

Keywords

External Resources

Popular Topics
Recent Journals