Williams, M. J. | Search bioRxiv

bioRxiv2018

Reply: Neutral tumor evolution?

Mutation, selection and neutral drift shape the cancer evolutionary process1. The role of selection has received particular interest, but inferring the presence and strength of selection during tumour growth remains challenging. Recently, we analysed the frequency distribution of subclonal mutations in many cancers and found that in approximately 30% of cases the observed distribution was entirely consistent with a simple model of neutral evolution2. Thus, we concluded that neutral evolution, perhaps surprisingly, provides an adequate explanation of the intra-tumour heterogeneity present in a significant proportion of cancers.\n\nTarabichi and colleagues [bioRxiv: 2017/06/30/158006] question the robustness of the method we presented in Williams et al. 20162 to identify neutral cancer evolution from variant allele frequency (VAF) distributions. Their critique has four main points that we addre ...

cancer biology↗

bioRxiv2016

Quantification of subclonal selection in cancer from bulk sequencing data

Recent studies have identified prevalent subclonal architectures within many cancer types. However, the temporal evolutionary dynamics that produce these subclonal architectures remain unknown. Here we measure evolutionary dynamics in primary human cancers using computational modelling of clonal selection applied to high throughput sequencing data. Our approach simultaneously determines the subclonal architecture of a tumour sample, and measures the mutation rate, the selective advantage, and the time of appearance of subclones. Simulations demonstrate the accuracy of the method, and revealed the degree to which evolutionary dynamics are recorded in the genome. Application of our method to high-depth sequencing data from gastric and lung cancers revealed that detectable subclones consistently emerged early during tumour growth and had considerably large fitness advantages (>20% growth advantage). Our quantitative platform provides new insight into the evolutionary history of cancers by facilitating the measurement of fundamental evolutionary parameters in individual patients.

cancer biology↗