Predictive modeling of therapy induced secondary thyroid malignancies in childhood cancer survivors. (24th July 2017) - Manem, Venkata S K; Kohandel, Mohammad; Hodgson, David C; Sivaloganathan, Siv
Abstract: Surgery, radiation therapy and chemotherapy are the primary modes of therapeutic intervention in current clinical practice. The price often paid for effective treatment is the development of a secondary malignancy several decades after successful treatment of the primary tumor, as a result of the mutagenic effects of the initial cancer treatments on normal cells. In this work, we employ a biologically motivated mathematical model to estimate the radiation and chemotherapy-induced relative risks of thyroid malignancies in four childhood cancer study survivors (CCSS) data sets. A sensitivity analysis is performed on various chemotherapy treatment variables to evaluate their impact on second cancer risks. Furthermore, the predictions of radiation and chemotherapy-induced relative risks of secondary thyroid malignancies using the mathematical model are compared against four clinical datasets from the CCSS cohort. Moreover, the extracted average value of growth rate of premalignant cells is 0.8175 (d −1 ) and the extracted chemotherapy-induced mutation rate is of the order of 10 −10 (per unit of chemotherapeutic dose). In addition, our model predictions of sequential therapy induced carcinogenic risks are in line with the clinical data in secondary thyroid cancers. Our in silico risk predictions can provide insight into the impact of therapy sequencing on secondary cancer risks, while at the same time eliminating the primary tumor. These findings might potentially guide clinicians in developing optimal treatment regimens that minimize secondary cancer risks.