Abstract 49: Genomic analysis and simulation for understanding heterogenous cancer evolution

Abstract

Abstract Cancer results from accumulation of mutations in the genome and evolutionary selection for growth advantage. In the evolutionary process, it is assumed that multiple clones appear, and this phenomenon called intratumor heterogeneity could cause therapeutic failures by fostering evolutionary adaptation. To study intratumor heterogeneity in colorectal cancer, we performed whole exome sequencing of samples from multiple regions within a single tumor. our genomic analysis revealed high intratumor heterogeneity; however, principles underlying it remained unclear. To explore the principles , we built a cellular automaton model, termed the BEP model, which can reproduce the branching cancer evolution in silico. We then extensively searched for conditions leading to high intratumor heterogeneity as observed in the experimental data, by performing simulations with various parameter settings on a supercomputer. The simulation result suggests that a high mutation rate leads to high intratumor heterogeneity, which is generated by neutral evolution. Collectively, this study provides provide novel insights into heterogenous cancer evolution. Citation Format: Atsushi Niida, Ryutaro Uchi, Yusuke Takahashi, Koshi Mimori, Satoru Miyano. Genomic analysis and simulation for understanding heterogenous cancer evolution. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Integrating Clinical Genomics and Cancer Therapy; Jun 13-16, 2015; Salt Lake City, UT. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(1_Suppl):Abstract nr 49.