1. Identification of neutral tumor evolution across cancer types
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Identification of neutral tumor evolution across cancer types
Marc J Williams,Benjamin Werner, Chris P Barnes, Trevor A Graham & Andrea Sottoriva

2. Interpreting genomic data of cancer evolution has always been difficult
Next generation sequencing of tumor samples
Provided the framework for power law distribution

3. New way to interpret cancer genomic data
Introduction
New way to interpret cancer genomic data
This resulted from neutral framework cancer sequencing
Allowed the measurement of in vivo mutation rates as well as the order and timing of mutations
Also allowed discrimination between functional and non- functional diversity within tumors

4. Barriers to tumor evolution research
Introduction
Barriers to tumor evolution research
Longitudinal measurements impractical
Lack of rigorous theoretical framework
Lack of a means of making predictions

5. Next generation sequencing
Results
Next generation sequencing
Under neutral growth, previously inaccessible parameters become measurable
-mutation rate
-mutational timeline

6. Next generation sequencing
Parameter free model was used and applied to a large preexisting cancer genomic set to determine which tumors were consistent with neutral growth

7. Figure 1: Neutral evolution is common in colon cancer and allows measurement of the mutation rate in each tumor.

12. In silico validation of the neutral model
A simulation of neutral growth produced next-generation sequencing data
This allowed the researchers to recover the mutation rate with validated predictions

13. Discussion
It was found that cancer growth was largely overpowered by neutral evolution in some cancers but not all
Non-neutral cancers had many different factors that played a key role in it’s evolution
The observation that cancer growth mainly displays a neutral evolutionary dynamic is shown across fourteen different types of cancer

14. References
Williams, Marc J., et al. “Identification of Neutral Tumor Evolution across Cancer Types.” Nature Genetics, no. 3, 2016, p EBSCOhost, doi: /ng.3489.
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