Advances like immunotherapy have improved treatment, but 20% to 40% of patients will experience a relapse after their first round of treatment. Current procedures for monitoring treatment response by imaging haven’t improved survival, and other approaches of deciding how best to treat patients involve invasive biopsies. But now a recent study led by Brian Chiu, PhD, a clinical cancer epidemiologist at the University of Chicago Medicine, shows how a simple blood test can better identify which patients are at risk for relapse.
The new test analyzes epigenetic signatures in circulating cell-free DNA, genetic fragments released by tumor cells into the blood. Chiu and his colleagues saw that certain epigenetic markers, or DNA modifications that can change how genes are expressed, are associated with higher risk of relapse or death from DLBCL after receiving treatment. That means a simple blood test, taken at the time of diagnosis, could help predict which patients may need more intensive treatment.
The prototype of this new technology was developed by co-senior author of the study, Chuan He, PhD, a chemical biologist at UChicago. Chiu, He and Wei Zhang, PhD, a cancer epidemiologist at Northwestern University and another co-senior author of the new study, worked together to develop the sensitive blood test for predicting clinical outcomes of lymphoma.
“Our findings, if validated in a larger independent patient population, could impact the cure rate for DLBCL,” Chiu said. “By identifying those patients who are at high-risk of treatment failure, we can see who may benefit from individualized clinical management or earlier treatment with novel or targeted therapies.”
The study, “Prognostic implications of 5-hydroxymethylcytosines from circulating cell-free DNA in diffuse large B-cell lymphoma,” was published in Blood Advances and supported by the National Institutes of Health, the National Institute on Minority Health and Health Disparities, the National Cancer Institute and the National Center for Advancing Translational Sciences.
Additional authors include Qiancheng You, Elizabeth Stepniak, Kangkang Yu, Girish Venkataraman and Sonali M. Smith from the University of Chicago; Zhou Zhang and Chang Zeng from Northwestern University; and Paige M. Bracci from the University of California San Diego.
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