Multi-omics and single-cell approaches reveal molecular subtypes and key cell interactions in hepatocellular carcinoma
Finally, we employed machine learning methods to construct a prognostic model for HCC patients and identified novel potential compounds for high risk patients. In summary, our novel multi-omics classification of HCC provides valuable insights into tumor heterogeneity and prognosis, offering potential clinical applications for precision oncology.
Authors
- Yizheng Zhang (ORCID: https://orcid.org/0009-0003-4891-950X)
- Mingyuan Luan (ORCID: https://orcid.org/0000-0003-3666-2113)
- Xueqing Zou (ORCID: https://orcid.org/0000-0003-1143-1028)
- Yongmei Wang (ORCID: https://orcid.org/0000-0002-7418-9489)
Institutions
- Qingdao University (CN)
- Affiliated Hospital of Qingdao University (CN)
Publication Details
- Journal
- Frontiers in Pharmacology
- Published
- 2025-05-22
- DOI
- https://doi.org/10.3389/fphar.2025.1605162
- Citations
- 4
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 3.22
Funders
- National Natural Science Foundation of China