Room: ePoster Forums
Purpose: Until recently, it was believed that a hallmark of typical cancer cells is unlimited replicative potential with the ability to regenerate tumors. In recent years, however, research revealed that only a small subpopulation of all cancer cells may be immortal. They are dubbed cancer stem cells (CSC) and have been identified in many different types of cancers. The remaining cancer cells (progenitor cells) possess a limited replicative ability before going into apoptosis. Previous computer simulation models suggested that a dynamic equilibrium exists between progenitor cells and CSCs within the tumor and is essential to the treatment outcome. Conventional radiobiological modelling does not take into account the existence of these two components in tumor population and may be one of the reasons for discrepancy between the predicted TCPs and clinical data. The purpose of this study is to investigate how the incorporation of CSC paradigm affects calculated TCP.
Methods: Cellular automata are increasingly used to simulate temporo-spatial tumor growth dynamics. In stochastic Monte Carlo models cell dynamics is governed by probability distributions of cell internal states coupled to a continuously changing local environment. An agent-based Monte Carlo model is used to simulate the tumor growth and the radiation damage. The TCP is calculated as the number of runs with resulting CSC kill divided by the total number of simulated histories.
Results: Multiparametric computer simulation studies show that TCP is dependent on internal cell kinetic parameters. When there are two categories of cancer cells (CSC and progenitor cells), the calculated TCP has lower value at the given dose level compared to that calculated using conventional models.
Conclusion: Incorporating the CSC hypothesis into the TCP modeling may notably modify the dose prescription as well as the concept of the expected TCP after the radiation treatments.