Integrated multiomics analysis and machine learning refine molecular subtypes and prognosis for thyroid cancer.

Journal: Discover oncology
Published Date: Jun 23, 2025

Abstract

BACKGROUND: Thyroid cancer (THCA) exhibits high molecular heterogeneity, posing challenges for precise prognosis and personalized therapy. Most existing models rely on single-omics data and limited algorithms, reducing robustness and clinical value.

Authors

  • Peng Zhang
    Key Laboratory of Macromolecular Science of Shaanxi Province, School of Chemistry & Chemical Engineering, Shaanxi Normal University, Xi'an, Shaanxi 710062, China.
  • Meizhong Qin
    Department of Thyroid And Breast Surgery, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630, Guangdong Province, P.R. China.
  • Fen Li
    College of Information Science and Engineering, Hunan University, 2 Lushan S Rd, Yuelu District, 410086, Changsha, China.
  • Kunpeng Hu
    Department of Thyroid And Breast Surgery, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630, Guangdong Province, P.R. China. hukpeng@mail.sysu.edu.cn.
  • He Huang
  • Cuicui Li
    Department of Nephrology, the Fifth Affiliated Hospital of Guangzhou Medical University, 621 Gangwan Road, Huangpu District, Guangzhou, 510730, Guangdong Province, P.R. China. hnlicuicui@126.com.

Keywords

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