Indexed on: 20 Dec '18Published on: 20 Dec '18Published in: Cancer research
The evolution of cancer is inferred mainly from samples taken at discrete points that represent glimpses of the complete process. In this study, we present esiCancer as a cancer-evolution simulator. It uses a branching process, randomly applying events to a diploid oncogenome, altering probabilities of proliferation and death of the affected cells. Multiple events that occur over hundreds of generations lead to a gradual change in cell fitness and the establishment of a fast-growing population. esiCancer provides a platform to study the impact of several factors on tumor evolution, including dominance, fitness, event rate, and interactions among genes as well as factors affecting the tumor microenvironment. The output of esiCancer can be used to reconstruct clonal composition and Kaplan-Meier-like survival curves of multiple evolutionary stories. esiCancer is an open-source, standalone software to model evolutionary aspects of cancer biology. Copyright ©2018, American Association for Cancer Research.