A systems-level machine learning approach uncovers therapeutic targets in clear cell renal cell carcinoma
Acknowledgements: This work was supported by the LifeArc grant (RG91966), the National Research Foundation of Korea grant funded by the Ministry of Science and ICT (RS-2025-18362970), a grant from the Korean ARPA-H Project through the Korea Health Industry Development Institute (KHIDI) funded by the Ministry of Health and Welfare (RS-2025-25456722), and the Brain Pool Plus Fellowship Program funded by the Ministry of Science and ICT (RS-2025-25427881). G.Y. was funded by Milner Therapeutics Institute and Cancer Research UK (CRUK). We would like to thank Professor Grant Stewart and Dr James Jones (Department of Surgery, University of Cambridge) for their guidance.
Authors
- Namshik Han
- Gehad Youssef
- Silas Ruhrberg Estévez
- Greta Baltusyte
Publication Details
- Journal
- Apollo (University of Cambridge)
- Published
- 2025-07-25
- Primary Topic
- Renal cell carcinoma treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- LifeArc
- Cancer Research UK
- National Research Foundation
- Korea Health Industry Development Institute
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea
- Advanced Research Projects Agency