Big data analysis and machine learning of the role of cuproptosis-related long non-coding RNAs (CuLncs) in the prognosis and immune landscape of ovarian cancer.

Journal: Frontiers in immunology
PMID: 40070821

Abstract

BACKGROUND: Ovarian cancer (OC) is a severe malignant tumor with a significant threat to women's health, characterized by a high mortality rate and poor prognosis despite conventional treatments such as cytoreductive surgery and platinum-based chemotherapy. Cuproptosis, a novel form of cell death triggered by copper ion accumulation, has shown potential in cancer therapy, particularly through the involvement of CuLncs. This study aims to identify risk signatures associated with CuLncs in OC, construct a prognostic model, and explore potential therapeutic drugs and the impact of CuLncs on OC cell behavior.

Authors

  • Mingqin Kuang
    Gynecology and Oncology Department of Ganzhou Cancer Hospital, Ganzhou, Jiangxi, China.
  • Yueyang Liu
    Department of Gynecology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
  • Hongxi Chen
    Department of Gynecology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
  • Guandi Chen
    Department of Gynecology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
  • Tian Gao
    IBM Research, Yorktown Heights, NY, USA.
  • Keli You
    Department of Gynecology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.

Keywords

External Resources

Popular Topics
Recent Journals