Researchers from Denmark and Germany have trained a computer model on prostate cancer patient data to predict disease progression.
The model's dataset was culled from about 300 patients who had undergone complete genome sequencing; the focus on early-onset prostate cancer revealed a mutational mechanism involving an enzyme called APOBEC, which may help induce initial mutations in the disease.
The researchers also used the model to demonstrate that a putative novel oncogene in prostate cancer, ESRP1, may be used as a potential biomarker to detect whether the disease will be aggressive in a specific patient. This finding was validated on a cohort of 12,000 other patients with the same type of cancer.
The model is being deployed at a German clinic, and the team said full implementation should take two to three years, after which it may be rolled out to hospitals in other countries.
From University of Copenhagen
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