Bottom Line: An evolutionary model utilizing serial blood samples from patients with advanced colorectal cancer treated with anti-EGFR therapies in a phase II trial could predict personalized waiting time for progression.
Journal in Which the Study was Published: Cancer Discovery, a journal of the American Association for Cancer Research
Authors: Co-senior authors Andrea Sottoriva, PhD, MSc, Chris Rokos Fellow in Evolution and Cancer and team leader at The Institute of Cancer Research, London and Nicola Valeri, MD, PhD, team leader in Gastrointestinal Cancer Biology and Genomics at The Institute of Cancer Research, London, and consultant medical oncologist at The Royal Marsden NHS Foundation Trust
Background: “By combining frequent longitudinal sampling of cell-free DNA with mathematical modeling of tumor evolution, we were able to make statistical predictions of patients who were at risk of progression,” said Sottoriva. “We could also determine when a cancer was going to come back, on a patient-by-patient basis. This is the first time that quantitative forecasting of this sort has been successfully used in cancer.”
While clinicians often use tumor biopsies for cancer genotyping, many tumors have intratumor heterogeneity which can drive treatment resistance; therefore, multiple biopsies in time and space are needed to better
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