Tae Hyun Hwang, PhD, Florida Department of Health cancer chair at Mayo Clinic Cancer Center, and his team created a machine-learning algorithm using more than 5,000 patients’ genetic data. The team made a molecular signature with 32 genes to guide patient care options, according to a Feb. 14 news release.
The majority of patients with gastric cancer are treated with chemotherapy or immunotherapy. The model could allow doctors to determine which treatment option would work best for a patient based on genetics.
“We were pleased that our 32-gene signature provided not only prognostic information but also predicted patient benefit from chemotherapy and immunotherapy,” Dr. Hwang said. “In particular, we were surprised that the 32-gene signature we identified was able to predict a patient’s response to immunotherapy because identifying reliable biomarkers for immunotherapy response in patients with gastric cancer has been a challenge for the field.”
Dr. Hwang also said the model could help identify patients who would be less likely to benefit from chemotherapy and immunotherapy, which would help them avoid unnecessary side effects.
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