Simulating the Dynamic Intra-Tumor Heterogeneity and Therapeutic Responses

Simple Summary Various aspects of intra-tumor heterogeneity are key factors for improving clinical practice, but studies on them remain incomplete. Based on the clonal evolution theory, this study proposes a model to simulate the temporal variability of intra-tumor heterogeneity of cancer cell subpopulations. Multiple types of therapies are also incorporated in the model for the simulation of treatment responses at different time points. The simulation results in this study indicate the importance of the timing of therapy and the superiority of neoadjuvant therapy before surgery. The model is incorporated in a webserver for the convenience of understanding the roles of heterogeneity in cancer treatment response. A tumor is a complex tissue comprised of heterogeneous cell subpopulations which exhibit substantial diversity at morphological, genetic and epigenetic levels. Under the selective pressure of cancer therapies, a minor treatment-resistant subpopulation could survive and repopulate. Therefore, the intra-tumor heterogeneity is recognized as a major obstacle to effective treatment. In this paper, we propose a stochastic clonal expansion model to simulate the dynamic evolution of tumor subpopulations and the therapeutic effect at different times during tumor progression. The model is incorporated in the CES webserver, for the convenience of simulation according to initial user input. Based on this model, we investigate the influence of various factors on tumor progression and treatment consequences and present conclusions drawn from observations, highlighting the importance of treatment timing. The model provides an intuitive illustration to deepen the understanding of temporal intra-tumor heterogeneity dynamics and treatment responses, thus helping the improvement of personalized diagnostic and therapeutic strategies.