Prediction of tumor control probability in prostate cancer radiotherapy using a biophysical model incorporating cancer stem cell and hypoxia

Saga, Ryo*; Iwamori, Kenta*; Matsuya, Yusuke; Hosokawa, Yoichiro*

Computers in Biology and Medicine, 211, p.111743_1 - 111743_10, 2026/07

https://doi.org/10.1016/j.compbiomed.2026.111743

This study developed a biophysical model that integrates the characteristics of cancer stem cells (CSCs), including the side population (SP), and the oxygen enhancement effect (OER) to more accurately predict radiotherapy outcomes in prostate cancer. SP and main population (MP) cells were isolated from the DU145 prostate cancer cell line, and DNA double-strand breaks and survival were evaluated under both normoxic and hypoxic conditions (0.1% O). The obtained data were analyzed using the IMK model incorporating MP, SP, and oxygen concentration, and the predictions were compared with clinical tumor control probability (TCP) under various fractionation regimens (2, 3, and 7 Gy/Fx). As a result, the in vitro and clinical data were well reproduced by considering the MP/SP fraction, a population-independent OER, and the intratumoral hypoxic volume. Furthermore, the initial yield of DSBs was identified as a key determinant of radiosensitivity depending on cell characteristics and oxygen levels. The developed model is expected to contribute to the optimization of prostate cancer radiotherapy, including dose escalation to hypoxic tumor regions.