Machine learning analysis of oxidative stress-related phenotypes for specific gene screening in ovarian cancer.

Journal: Environmental toxicology
PMID: 39162393

Abstract

BACKGROUND: Oxidative stress serves a crucial role in tumor development. However, the relationship between ovarian cancer and oxidative stress remains unknown. We aimed to create an oxidative stress-related prognostic signature to enhance the prognosis prediction of CC patients using bioinformatics.

Authors

  • Chenxiang Pan
    Department of Women's Oncology, Shuangyu Campus, Wenzhou Central Hospital, Wenzhou, Zhejiang, China.
  • Chunyu Pan
    Department of Women's Oncology, Shuangyu Campus, Wenzhou Central Hospital, Wenzhou, Zhejiang, China.
  • Lili Chen
    School of Mechatronics & Vehicle Engineering, Chongqing Jiaotong University, Chongqing 400074, China; School of Chongqing Key Laboratory of Urban Rail Transit Vehicle System Integration and Control, Chongqing Jiaotong University, Chongqing 400074, China.
  • Aidi Lin
    Department of Women's Oncology, Shuangyu Campus, Wenzhou Central Hospital, Wenzhou, Zhejiang, China.

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