TY - JOUR
AU1 - Sun, Ruping
AU2 - Hu, Zheng
AU3 - Sottoriva, Andrea
AU4 - Graham, Trevor A.
AU5 - Harpak, Arbel
AU6 - Ma, Zhicheng
AU7 - Fischer, Jared M.
AU8 - Shibata, Darryl
AU9 - Curtis, Christina
AB - Given the implications of tumor dynamics for precision medicine, there is a need to systematically characterize the mode of evolution across diverse solid tumor types. In particular, methods to infer the role of natural selection within established human tumors are lacking. By simulating spatial tumor growth under different evolutionary modes and examining patterns of between-region subclonal genetic divergence from multi-region sequencing (MRS) data, we demonstrate that it is feasible to distinguish tumors driven by strong positive subclonal selection from those evolving neutrally or under weak selection, as the latter fail to dramatically alter subclonal composition. We developed a classifier based on measures of between-region subclonal genetic divergence and projected patient data into model space, revealing different modes of evolution both within and between solid tumor types. Our findings have broad implications for how human tumors progress, accumulate intra-tumor heterogeneity, and ultimately how they may be more effectively treated.
TI - Between-Region Genetic Divergence Reflects the Mode and Tempo of Tumor Evolution
JF - Nature Genetics
DO - 10.1038/ng.3891
DA - 2017-06-05
UR - https://www.deepdyve.com/lp/pubmed-central/between-region-genetic-divergence-reflects-the-mode-and-tempo-of-tumor-29suYOZ7E1
SP - 1015
EP - 1024
VL - 49
IS - 7
DP - DeepDyve
ER -