Multi-omics analysis and experiments uncover the function of cancer stemness in ovarian cancer and establish a machine learning-based model for predicting immunotherapy responses
A strong relationship between cancer stemness and the response to immunotherapy has been identified in our study. This finding provides valuable insights for devising efficient strategies to address immune evasion by targeting the regulation of genes associated with cellular stemness.
Authors
- Yujie Zhai
- Xiaole Wang (ORCID: https://orcid.org/0000-0002-4404-2857)
- Jinbo Jian
- Zhibing Liu (ORCID: https://orcid.org/0000-0002-7429-6137)
- Yingjiang Xu (ORCID: https://orcid.org/0000-0001-6492-9132)
- Feng Wang (ORCID: https://orcid.org/0000-0002-4965-836X)
- Lei Han (ORCID: https://orcid.org/0000-0002-0707-5027)
- Xiaoyu Ji (ORCID: https://orcid.org/0000-0003-2524-8363)
- Xiuwen Wang (ORCID: https://orcid.org/0000-0001-6494-122X)
- Fangling Ning (ORCID: https://orcid.org/0000-0002-6697-2262)
Institutions
- Binzhou Medical University (CN)
- Shandong University of Aeronautics (CN)
- Fudan University (CN)
- Huashan Hospital (CN)
- Qilu Hospital of Shandong University (CN)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2024-12-11
- DOI
- https://doi.org/10.3389/fimmu.2024.1486652
- Citations
- 6
- Primary Topic
- Cancer Immunotherapy and Biomarkers
- Type
- article
- Field-Weighted Citation Impact
- 1.70
Funders
- National Natural Science Foundation of China
- Binzhou Medical University