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Using protein interaction networks to assist in the grouping of tumour samples from somatic mutation data

In Nature Methods, an exciting development in large-scale tumour mutation analysis has been reported. Many large studies have analysed tumours to detect somatic mutations, aiming to identify characteristic patterns that are associated with, for example, tumour types and subtypes. Unfortunately, although there have been some notable successes, for many cancers these patterns have not been reproduced in other studies.

Now, a new approach is being used, which aims to find connections between genes that are mutated in tumour subtypes. The connections are identified by using computer algorithms such as STRING to search for protein-protein interactions. This permits the identification of genes which contain somatic mutations in a tumour subtype and that are linked by virtue of networks of interactions between their encoded proteins. This new approach has resulted in the identification of network-associated mutated genes and the assignment of tumour samples to identified subtypes that are reported to be biologically (and clinically) meaningful.
 


Fig. Network connections of mutated genes in human ovarian cancer. See Hofree et al. Nature Methods vol.10 no. 11 pages 1108-1115.

Network view of genes with high network-smoothed mutation scores in HumanNet ovarian cancer subtype 1 (relative to scores of other subtypes).
  

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