Detecting Cancer Genes with Sequencing Studies

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Detecting Cancer Genes with Sequencing Studies

• Chris Greenman, Cancer Genome Project, Andy
  Futreal, Mike Stratton and Douglas F. Easton

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The Problem
BRAF 1500 (Somatic) Mutations V600E Exons 11 15
Binding Domain
518 KINASES 210 Cancers 921 Point Mutations 219
Silent Mostly Distinct
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Pattern of Mutations

• Is there enrichment for non-silent mutations?
• Which genes?

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Modelling Mutations
Silent mutations mutation type k, sample
c Non-silent mutations gene g Silent base
pairs, Non-silent base pairs, Mutation
probability per base.
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Mixture Model
gt1 Diversifying 1 Neutral lt1 Purifying
- Selection Pressure -
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Results

• Fit with EM algorithm

• Two groups best fit
• Neutral and Positive Group
• q 0.24 126 genes
• Which genes?

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Gene Ranking
Bayes Law
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Conclusions

• Silent mutations allow detection of selection
• Cancer contains multitude of low frequency
  variants
• 126 genes implicated

BRAF
KINASES
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References
http//www.sanger.ac.uk/genetics/CGP/ Yang, Z.,
S. Ro and B. Rannala, Likelihood models of
somatic mutation and codon substitution in cancer
genes, Genetics, 165 695705 (2003). Chris
Greenman, Richard Wooster, P. Andrew Futreal,
Michael R. Stratton and Douglas F. Easton,
Statistical Analysis of Pathogenicity of Somatic
Mutations in Cancer, Genetics, 173(4) 21872198
(2006). Chris Greenman, Philip Stephens,
Raffaella Smith, et al., Patterns of somatic
mutation in human cancer genomes , Nature 446,
153-158 (2007).