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Machine learning–based transcriptomic signatures to predict treatment outcomes across targeted and immunotherapy regimens in renal cell carcinoma.

Year: 2026

Type: conference-abstract

Source: Journal of Clinical Oncology

DOI: 10.1200/jco.2026.44.16_suppl.4526

Authors: Peng Li, Zuhair Majeed, Semiha Ozgul, Mostafa I.H. Ali, Nancy Single, Daniel G. Stover, Mina S. Makary, Fuat Bicer, Amir Mortazavi, W. Kimryn Rathmell, Eric A. Singer, Khalid Niazi, Richard Cheng Han Wu, Merve Hasanov, Elshad Hasanov

Institutions: The Ohio State University Comprehensive Cancer Center – Arthur G. James Cancer Hospital and Richard J. Solove Research Institute, The Ohio State University, The Ohio State University Wexner Medical Center

Language: English

Topic: Renal cell carcinoma treatment

Subfield: Pulmonary and Respiratory Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: closed

OpenAlex ID: W7162551390

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