Li, GuanghaoGuanghaoLiYang, ZuyuZuyuYangWu, DafeiDafeiWuLiu, SixueSixueLiuLi, XueningXueningLiLi, TaoTaoLiLi, YaweiYaweiLiLiang, LijiLijiLiangZou, WeilongWeilongZouWu, Chung-IChung-IWuWang, Hurng-YiHurng-YiWangLu, XuemeiXuemeiLu2021-12-242021-12-2420220737-40381537-1719https://scholars.lib.ntu.edu.tw/handle/123456789/590658Spatial genetic and phenotypic diversity within solid tumors has been well documented. Nevertheless, how this heterogeneity affects temporal dynamics of tumorigenesis has not been rigorously examined because solid tumors do not evolve as the standard population genetic model due to the spatial constraint. We therefore propose a neutral spatial (NS) model whereby the mutation accumulation increases toward the periphery; the genealogical relationship is spatially determined and the selection efficacy is blunted (due to kin competition). In this model, neutral mutations are accrued and spatially distributed in manners different from those of advantageous mutations. Importantly, the distinctions could be blurred in the conventional model. To test the NS model, we performed three-dimensional multiple micro-sampling of two hepatocellular carcinomas. Whole-genome sequencing (WGS) revealed a twofold increase in mutations going from the center to the periphery. The operation of natural selection can then be tested by examining the spatially-determined clonal relationships and the clonal sizes. Due to limited migration, only the expansion of highly advantageous clones can sweep through a large part of the tumor to reveal the selective advantages. Hence, even multi-regional sampling can only reveal a fraction of fitness differences in solid tumors. Our results suggest that the neutral spatial patterns are crucial for testing the influence of natural selection during tumorigenesis, especially for small solid tumors.enCancer Evolution; Intra-tumoral Heterogeneity; Natural Selection; Phenotypic Diversity; Tumor Spatial Growth Modelcancer evolution; intra-tumoral heterogeneity; natural selection; phenotypic diversity; tumor spatial growth model[SDGs]SDG3journal article10.1093/molbev/msab33534850073