OncoNPC, a machine learning classifier developed to predict the primary origin of tumors, made confident predictions for over 40% of cancers of unknown primary (CUP) cases analyzed. Patients with CUP who had received site-specific treatments that retrospectively matched the OncoNPC predictions had better outcomes than patients who had been treated with discordant site-specific therapies. OncoNPC predictions doubled the number of patients with CUP who would be eligible for genomically guided therapies.
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References
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This is a summary of: Moon, I. et al. Machine learning for genetics-based classification and treatment response prediction in cancer of unknown primary. Nat. Med. https://doi.org/10.1038/s41591-023-02482-6 (2023).
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Machine learning for improved clinical management of cancers of unknown primary. Nat Med 29, 1920–1921 (2023). https://doi.org/10.1038/s41591-023-02501-6
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DOI: https://doi.org/10.1038/s41591-023-02501-6
