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Modeling Organ Specific Mechanistic Interactions Between Radiation and Chemotherapy

V Manem

V Manem*, C Grassberger , H Paganetti , Massachusetts General Hospital, Boston, MA


TH-AB-304-10 (Thursday, July 16, 2015) 7:30 AM - 9:30 AM Room: 304

Purpose: Investigate the mechanistic interactions between radiation therapy and chemotherapy for lung, breast and thyroid in the context of secondary malignancies, and derive the parameters needed to build a predictive model from clinical data of Hodgkin’s Lymphoma (HL) patients.

Methods: A biologically motivated mathematical framework, widely known as the initiation-inactivation-proliferation formalism, that describes the competition between cell kill and mutation induction, has been used to quantify the interaction between radiation and chemotherapy. HL data from studies including >17’000 patients, including the Childhood Cancer Survivors Study (CCSS), has been used to derive the parameters in the mathematical framework.

Results: The underlying mathematical framework provides a quantitative measure to examine the interaction between radiation therapy and chemotherapy. The relative proliferation rate of initiated cells in thyroid, breast and lung was found to be 0.63, 076 and 0.96 respectively. We also extracted chemotherapy induced mutation rates and found that it varies by orders of magnitude for these three organs, from 10e-9 to 10e-12. More importantly, the excess relative risk (ERR) of secondary thyroid cancer predicted by the model was approximately 3 times lower then the ERR rates in the literature, suggesting a synergistic interaction between radiation and chemotherapy. For breast and lung tissue on the other hand, the model correctly predicted the ERR values after combination therapy found in the literature. This demonstrates that in these organs secondary cancer induction from radiation and chemotherapy merely add up.

Conclusion: This study enhances the understanding of secondary malignancy induction due to concurrent therapy protocols, and could serve as a tool to design efficient therapeutic strategies for childhood cancers that minimize secondary cancer induction.

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