Mutational Interactions Define Novel Cancer Subgroups

Kuipers, Jack and Thurnherr, Thomas and Moffa, Giusi and Suter, Polina and Behr, Jonas and Goosen, Ryan and Christofori, Gerhard and Beerenwinkel, Niko. (2018) Mutational Interactions Define Novel Cancer Subgroups. Nature Communications, 9. p. 4353.

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Official URL: https://edoc.unibas.ch/81032/

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Large-scale genomic data highlight the complexity and diversity of the molecular changes that drive cancer progression. Statistical analysis of cancer data from different tissues can guide drug repositioning as well as the design of targeted treatments. Here, we develop an improved Bayesian network model for tumour mutational profiles and apply it to 8198 patient samples across 22 cancer types from TCGA. For each cancer type, we identify the interactions between mutated genes, capturing signatures beyond mere mutational frequencies. When comparing mutation networks, we find genes which interact both within and across cancer types. To detach cancer classification from the tissue type we perform de novo clustering of the pancancer mutational profiles based on the Bayesian network models. We find 22 novel clusters which significantly improve survival prediction beyond clinical information. The models highlight key gene interactions for each cluster potentially allowing genomic stratification for clinical trials and identifying drug targets.
Faculties and Departments:05 Faculty of Science > Departement Mathematik und Informatik > Mathematik > Statistik (Moffa)
UniBasel Contributors:Moffa, Giusi
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Nature Publishing Group
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:13 Apr 2021 13:49
Deposited On:13 Apr 2021 13:49

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