The use of genomic sequencing to predict the likelihood that gastric cancer patients will benefit from chemotherapy or from immunotherapy has been validated by findings in a study published Feb. 9 in Nature Communications.
Researchers developed a machine learning algorithm using genetic data from over 5,000 patients, and then developed a molecular signature consisting of 32 genes that could be used to guide patient care decisions.
"We were pleased that our 32-gene signature provided not only prognostic information, but also predicted patient benefit from chemotherapy and immunotherapy," stated Tae Hyun Hwang, PhD, the Florida Department of Health cancer chair at Mayo Clinic Cancer Center in Florida.
"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 stated.
Read the full study here.