Trevor Graham

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  Patterns of clonal evolution in the human cancers
  Trevor Graham

  The process of clonal evolution underpins the maintenance of a normal healthy colon, and the “unwanted evolution� of mutant cells leads to the development of colon cancer. However, despite the central importance, a quantification of the parameters that define the clonal evolutionary process in human colon (and indeed all human tissues) has remained lacking. Our current understanding is derived from studies performed in model organisms, and it is uncertain if and how these insights apply to humans. I will describe how we coupled a novel “lineage tracing� strategy in human colon, that allows the fate of different clonal lineages to be visualised, with a reductionist mathematical analysis that allows us to infer the parameters governing clonal evolution in the human gut.

  
  

  Our analysis has shown that human intestinal stem cells evolve through a process of neutral drift, and that the neutrality of this process is disrupted by mutation to the APC gene that functions as a key tumour-suppressor in the colon. In the colon, cells are organized into millions of “crypts� – small tubular structures each housing a few thousand cells. Through our quantitative analysis of lineage-tracing data, we have been able to infer the number of functional stem cells per human crypt, and also how they behave over time. Further, our mathematical analysis reveals how often colon crypts divide, both in normal colon and in colon tumours. This parameterisation allows the age of colon tumours to be determined.

  
  

  Finally, we have coupled multi-region sampling of established colorectal cancers with whole-genome sequencing and other genomic analysis to infer how colorectal cancers evolve. Our results imply that clonal evolution is not a process of stepwise clonal sweeps as the “textbook� model implies.

  
  

  My particular excitement about this work is that it demonstrates how quantitative analysis of a static picture can resolve temporal dynamics. Application of these methods quantifies the dynamic process of clonal evolution that occurs in human tissues.

  
  
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  Quantifying intra-tumour heterogeneity as a prognostic marker
  Trevor Graham

  Carcinogenesis is an evolutionary process; establishing the prognosis for a cancer therefore requires predicting the future course of cancer evolution. The same is true in pre-cancerous conditions: the risk of developing cancer is determined by how the pre-cancerous lesion is evolving.

  
  

  The level of heterogeneity within a population measures the evolvability of the population: if there is no diversity natural selection cannot operate, whereas diverse populations are likely to contain well-adapted individuals that can prosper in changing environments. Consequently, quantification of within-tumour heterogeneity is likely to be a proxy-measure of the rate of the underlying evolutionary process that drives carcinogenesis, and so be an effective prognostic marker. In this talk, I will describe how we have measured within-tumour diversity, both genetically and phenotypically, to successfully determine prognosis in both established cancers and in premalignant lesions.

  
  

  In addition, I will describe how we begun to search for the most prognostic measures of intra-tumour heterogeneity by constructing simple computational models of cancer development, and using the models to perform an exhaustive search of possible heterogeneity measures.