Themis: advancing precision oncology through comprehensive molecular subtyping and optimization

Yue Xi, Kun Zheng, Fulan Deng, Yujun Liu, Hourong Sun, Yingxia Zheng, Henry H.Y. Tong, Yuan Ji, Yingchun Zhang, Wantao Chen, Yiming Zhang, Xin Zou, Jie Hao

Research output: Contribution to journalArticlepeer-review


Recent advances in tumor molecular subtyping have revolutionized precision oncology, offering novel avenues for patient-specific treatment strategies. However, a comprehensive and independent comparison of these subtyping methodologies remains unexplored. This study introduces 'Themis' (Tumor HEterogeneity analysis on Molecular subtypIng System), an evaluation platform that encapsulates a few representative tumor molecular subtyping methods, including Stemness, Anoikis, Metabolism, and pathway-based classifications, utilizing 38 test datasets curated from The Cancer Genome Atlas (TCGA) and significant studies. Our self-designed quantitative analysis uncovers the relative strengths, limitations, and applicability of each method in different clinical contexts. Crucially, Themis serves as a vital tool in identifying the most appropriate subtyping methods for specific clinical scenarios. It also guides fine-tuning existing subtyping methods to achieve more accurate phenotype-associated results. To demonstrate the practical utility, we apply Themis to a breast cancer dataset, showcasing its efficacy in selecting the most suitable subtyping methods for personalized medicine in various clinical scenarios. This study bridges a crucial gap in cancer research and lays a foundation for future advancements in individualized cancer therapy and patient management.

Original languageEnglish
JournalBriefings in Bioinformatics
Issue number4
Publication statusPublished - 1 Jul 2024


  • benchmark testing
  • bioinformatics
  • pan-cancer
  • tumor subtyping


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