Abstract A084: Personalized prediction of radiation sensitivity

Abstract

Abstract Purpose/Objective: Patients of different races with similar cancers are often treated with radiation according to safety criteria largely collected from patients of European origin. However, even among those patients, toxicities are not predictable. Patients of African origin appear to have more severe skin radiation reactions, particularly Black women with breast cancer, than other populations. We have developed a technique using circulating cell-free DNA (cfDNA) that appears to predict toxicity in patients with otherwise similar radiation dosimetry, allowing for early intervention to prevent side effects (marketed as RadToxTM, DiaCarta, Inc.). Methods: Pre-clinical studies were performed in mice with white (BALB/c), brown (C3H/HeJ), or black (C57BL/6) fur. Radiation was delivered to the hind limb, and the skin reaction was evaluated. Blood was collected to evaluate changes in cfDNA as compared to severity of cutaneous toxicity. A phase I/II clinical study (n=54) was also performed to determine if plasma cfDNA measured early in a radiotherapy course can predict the subset of patients who experience grade 2 or higher radiotoxicity. Results: The most severe toxicity was seen in the C57BL/6 mice, and at similar doses the increase in cfDNA was higher than in the other two strains. Fifty-four patients were evaluable for the clinical study. Radiation significantly increased cfDNA on all days following the first radiation session. Acute maximum GI toxicity score, but not acute GU toxicity, was significantly correlated with cfDNA levels obtained on days 1, 2, 3, 4, and 5 of radiotherapy (p<0.005). Conclusions: Plasma cfDNA levels predicted the mouse strain that experienced more severe toxicity, and in a small study detected acute bowel toxicity. A larger study is needed to confirm the results and the value of the test for identifying patients who need special interventions to reduce toxicity. Further testing of this hypothesis is under evaluation in an NCI-funded multi-institutional study. Citation Format: Natalie Lockney, Steven G Swarts, Jennifer Li, Christopher Morris, Randal Henderson, Steven B Zhang, Zhenhuan Zhang, Sadasivan Vidyasagar, Reshu Gupta, Katherine Casey-Sawicki, Robert Zlotecki, Paul Okunieff. Personalized prediction of radiation sensitivity [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr A084.