Abstract 3591: A new method to infer clonal sequences and phylogenies from personal tumor genome profiles

Tumor progression involves the evolution of clonal cell populations that mutate and spread in the body. Genetic profiling has revealed the presence of extensive variation in tumor samples from individual patients. However, a tumor sample for genetic profiling is mixture of different clonal cell populations and needs to be decomposed into clonal sequences to infer the evolutionary history of the tumor. Therefore, we have developed a new method, CloneFinder, and show that the clone sequences present in each tumor sample can be accurately inferred from the analysis of multiple tumor sample profiles with our new CloneFinder method. CloneFinder is unique in its use of molecular evolutionary principles to deduce clone sequences at a single-nucleotide resolution along with their frequencies in each sample. It performs better than existing methods, which we found to produce incorrect numbers of clones, clone sequence errors, errors in clonal phylogenies, and biased estimates of cancerous cells in tumors. Application of CloneFinder to a large number of empirical datasets revealed that both early and recently evolved tumors contain ancestral clones at high frequencies. Therefore, our new method provides new insights into the clonal structure of tumors and their evolution within a personal life time. Citation Format: Sayaka Miura, Karen Gomez, Oscar Murillo, Sudhir Kumar. A new method to infer clonal sequences and phylogenies from personal tumor genome profiles [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3591. doi:10.1158/1538-7445.AM2017-3591