[SS22] Understanding complex dynamics of cancer progression and treatment response

[SS22-01] Mathematical model for evolution based cancer therapy

*Eunjung Kim¹ (1. Korea Institute of Science and Technology (Korea))

Keywords:

evolution based cancer therapy,acquired resistance,cancer cell plasticity,compartment model,agent based model

Recent preclinical and clinical studies have suggested that evolution-based cancer therapies exploiting intratumor competition can improve treatment outcomes. Various mathematical and computational models have been developed to explain the effectiveness of particular treatment strategies. However, this evolutionary approach often assumes only preexisting resistance, although acquired resistance and cancer phenotype plasticity can dramatically affect treatment outcomes. In this talk, I will present three different models for evolution-based therapy that consider acquired resistance. The first model is an agent-based model that investigates the role of spatial heterogeneity of such resistance on therapy outcome. The second model is a compartment model that can determine a patient-specific effective dose window when acquired resistance emerges. The last model investigates whether an evolutionary therapy that capitalizes on plasticity could delay resistance. In particular, we propose an evolutionary dose that can modulate the evolving competition among drug-sensitive, drug-resistant, and plastic cells.